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Sample records for biomarkers predicting stroke

  1. BRAIN NATRIURETIC PEPTIDE (BNP: BIOMARKER FOR RISK STRATIFICATION AND FUNCTIONAL RECOVERY PREDICTION IN ISCHEMIC STROKE

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    STANESCU Ioana

    2015-02-01

    Full Text Available Functional outcome after cardiovascular and cerebrovascular events is traditionally predicted using demographic and clinical variables like age, gender, blood pressure, cholesterol levels, diabetes status, smoking habits or pre-existing morbidity. Identification of new variables will improve the risk stratification of specific categories of patients. Numerous blood-based biomarkers associated with increased cardiovascular risk have been identified; some of them even predict cardiovascular events. Investigators have tried to produce prediction models by incorporating traditional risk factors and biomarkers. (1. Widely-available, rapidly processed and less expensive biomarkers could be used in the future to guide management of complex cerebrovascular patients in order to maximize their recovery (2 Recently, studies have demonstrated that biomarkers can predict not only the risk for a specific clinical event, but also the risk of death of vascular cause and the functional outcome after cardiovascular or cerebrovascular events. Early prediction of fatal outcome after stroke may improve therapeutic strategies (such as the use of more aggressive treatments or inclusion of patients in clinical trials and guide decision-making processes in order to maximize patient’s chances for survival and recovery. (3 Long term functional outcome after stroke is one of the most difficult variables to predict. Elevated serum levels of brain natriuretic peptide (BNP are powerful predictor of outcomes in patients with cardiovascular disease (heart failure, atrial fibrillation. Potential role of BNP in predicting atrial fibrillation occurrence, cardio-embolic stroke and post-stroke mortality have been proved in many studies. However, data concerning the potential role of BNP in predicting short term and long term functional outcomes after stroke remain controversial.

  2. Prominent deep medullary veins: a predictive biomarker for stroke risk from transient ischemic attack?

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    Duan, Yang; Xu, Zhihua; Li, Hongyi; Cai, Xiaonan; Chang, Cancan; Yang, Benqiang

    2018-05-01

    Background Deep medullary veins (DMVs) are a biomarker of severity and prognosis in patients with acute cerebral infarction. However, their clinical significance remains unclear in patients with transient ischemic attack (TIA). Purpose To determine whether prominent deep medullary veins (PDMVs) are a predictive biomarker for stroke risk after TIA. Material and Methods Clinical and imaging data of 49 patients with TIA and 49 sex- and age-matched controls were studied. PDMVs were defined as DMVs with a score of 3 (TDMVs) or asymmetric DMVs (ADMVs), and the relationship between PDMVs and clinical features was analyzed. The DMV score based on susceptibility weighted imaging (SWI) ranged from 0 (not visible) to 3 (very prominent) and was calculated for both hemispheres separately. A different score in each hemisphere was defined as ADMVs and an equal score was defined as symmetric DMVs. The asymmetry and score of DMVs were compared between the two groups and with respect to the time from TIA onset to imaging analysis. Results Agreement between neuroradiologists for the DMV asymmetry/score on SWI was excellent. The frequency of ADMVs and TDMVs was significantly higher in patients with TIA than controls ( P  0.05); PDMVs were not correlated with age, blood pressure, or diabetes. However, PDMVs were associated with the ABCD2 score (≥4), clinical symptoms, and duration of TIA (≥10 min). Conclusion Prominent deep medullary veins is a predictive biomarker for the risk of stroke in many patients having suffered from TIA.

  3. The Reliability and Predictive Ability of a Biomarker of Oxidative DNA Damage on Functional Outcomes after Stroke Rehabilitation

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    Hsieh, Yu-Wei; Lin, Keh-Chung; Korivi, Mallikarjuna; Lee, Tsong-Hai; Wu, Ching-Yi; Wu, Kuen-Yuh

    2014-01-01

    We evaluated the reliability of 8-hydroxy-2′-deoxyguanosine (8-OHdG), and determined its ability to predict functional outcomes in stroke survivors. The rehabilitation effect on 8-OHdG and functional outcomes were also assessed. Sixty-one stroke patients received a 4-week rehabilitation. Urinary 8-OHdG levels were determined by liquid chromatography–tandem mass spectrometry. The test-retest reliability of 8-OHdG was good (interclass correlation coefficient = 0.76). Upper-limb motor function and muscle power determined by the Fugl-Meyer Assessment (FMA) and Medical Research Council (MRC) scales before rehabilitation showed significant negative correlation with 8-OHdG (r = −0.38, r = −0.30; p rehabilitation, we found a fair and significant correlation between 8-OHdG and FMA (r = −0.34) and 8-OHdG and pain (r = 0.26, p rehabilitation. The exploratory study findings conclude that 8-OHdG is a reliable and promising biomarker of oxidative stress and could be a valid predictor of functional outcomes in patients. Monitoring of behavioral indicators along with biomarkers may have crucial benefits in translational stroke research. PMID:24743892

  4. The Reliability and Predictive Ability of a Biomarker of Oxidative DNA Damage on Functional Outcomes after Stroke Rehabilitation

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    Yu-Wei Hsieh

    2014-04-01

    Full Text Available We evaluated the reliability of 8-hydroxy-2'-deoxyguanosine (8-OHdG, and determined its ability to predict functional outcomes in stroke survivors. The rehabilitation effect on 8-OHdG and functional outcomes were also assessed. Sixty-one stroke patients received a 4-week rehabilitation. Urinary 8-OHdG levels were determined by liquid chromatography–tandem mass spectrometry. The test-retest reliability of 8-OHdG was good (interclass correlation coefficient = 0.76. Upper-limb motor function and muscle power determined by the Fugl-Meyer Assessment (FMA and Medical Research Council (MRC scales before rehabilitation showed significant negative correlation with 8-OHdG (r = −0.38, r = −0.30; p < 0.05. After rehabilitation, we found a fair and significant correlation between 8-OHdG and FMA (r = −0.34 and 8-OHdG and pain (r = 0.26, p < 0.05. Baseline 8-OHdG was significantly correlated with post-treatment FMA, MRC, and pain scores (r = −0.34, −0.31, and 0.25; p < 0.05, indicating its ability to predict functional outcomes. 8-OHdG levels were significantly decreased, and functional outcomes were improved after rehabilitation. The exploratory study findings conclude that 8-OHdG is a reliable and promising biomarker of oxidative stress and could be a valid predictor of functional outcomes in patients. Monitoring of behavioral indicators along with biomarkers may have crucial benefits in translational stroke research.

  5. Pathophysiology and Biomarkers in Acute Ischemic Stroke – A Review

    African Journals Online (AJOL)

    The pathophysiology of ischemic stroke is complex, and majorly involves excitotoxicity, oxidative stress, inflammation, blood-brain barrier dysfunction, apoptosis, etc. Several of the biomarkers are related to these pathophysiologic mechanisms and they may have applications in stroke prediction, diagnosis, assessment, ...

  6. [Neuroimaging and Blood Biomarkers in Functional Prognosis after Stroke].

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    Branco, João Paulo; Costa, Joana Santos; Sargento-Freitas, João; Oliveira, Sandra; Mendes, Bruno; Laíns, Jorge; Pinheiro, João

    2016-11-01

    Stroke remains one of the leading causes of morbidity and mortality around the world and it is associated with an important long-term functional disability. Some neuroimaging resources and certain peripheral blood or cerebrospinal fluid proteins can give important information about etiology, therapeutic approach, follow-up and functional prognosis in acute ischemic stroke patients. However, among the scientific community, there is currently more interest in the stroke vital prognosis over the functional prognosis. Predicting the functional prognosis during acute phase would allow more objective rehabilitation programs and better management of the available resources. The aim of this work is to review the potential role of acute phase neuroimaging and blood biomarkers as functional recovery predictors after ischemic stroke. Review of the literature published between 2005 and 2015, in English, using the terms "ischemic stroke", "neuroimaging" e "blood biomarkers". We included nine studies, based on abstract reading. Computerized tomography, transcranial doppler ultrasound and diffuse magnetic resonance imaging show potential predictive value, based on the blood flow study and the evaluation of stroke's volume and localization, especially when combined with the National Institutes of Health Stroke Scale. Several biomarkers have been studied as diagnostic, risk stratification and prognostic tools, namely the S100 calcium binding protein B, C-reactive protein, matrix metalloproteinases and cerebral natriuretic peptide. Although some biomarkers and neuroimaging techniques have potential predictive value, none of the studies were able to support its use, alone or in association, as a clinically useful functionality predictor model. All the evaluated markers were considered insufficient to predict functional prognosis at three months, when applied in the first hours after stroke. Additional studies are necessary to identify reliable predictive markers for functional

  7. Optimised Selection of Stroke Biomarker Based on Svm and Information Theory

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    Wang Xiang

    2017-01-01

    Full Text Available With the development of molecular biology and gene-engineering technology, gene diagnosis has been an emerging approach for modern life sciences. Biological marker, recognized as the hot topic in the molecular and gene fields, has important values in early diagnosis, malignant tumor stage, treatment and therapeutic efficacy evaluation. So far, the researcher has not found any effective way to predict and distinguish different type of stroke. In this paper, we aim to optimize stroke biomarker and figure out effective stroke detection index based on SVM (support vector machine and information theory. Through mutual information analysis and principal component analysis to complete the selection of biomarkers and then we use SVM to verify our model. According to the testing data of patients provided by Xuanwu Hospital, we explore the significant markers of the stroke through data analysis. Our model can predict stroke well. Then discuss the effects of each biomarker on the incidence of stroke.

  8. Stroke-induced immunodepression and dysphagia independently predict stroke-associated pneumonia - The PREDICT study.

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    Hoffmann, Sarah; Harms, Hendrik; Ulm, Lena; Nabavi, Darius G; Mackert, Bruno-Marcel; Schmehl, Ingo; Jungehulsing, Gerhard J; Montaner, Joan; Bustamante, Alejandro; Hermans, Marcella; Hamilton, Frank; Göhler, Jos; Malzahn, Uwe; Malsch, Carolin; Heuschmann, Peter U; Meisel, Christian; Meisel, Andreas

    2017-12-01

    Stroke-associated pneumonia is a frequent complication after stroke associated with poor outcome. Dysphagia is a known risk factor for stroke-associated pneumonia but accumulating evidence suggests that stroke induces an immunodepressive state increasing susceptibility for stroke-associated pneumonia. We aimed to confirm that stroke-induced immunodepression syndrome is associated with stroke-associated pneumonia independently from dysphagia by investigating the predictive properties of monocytic HLA-DR expression as a marker of immunodepression as well as biomarkers for inflammation (interleukin-6) and infection (lipopolysaccharide-binding protein). This was a prospective, multicenter study with 11 study sites in Germany and Spain, including 486 patients with acute ischemic stroke. Daily screening for stroke-associated pneumonia, dysphagia and biomarkers was performed. Frequency of stroke-associated pneumonia was 5.2%. Dysphagia and decreased monocytic HLA-DR were independent predictors for stroke-associated pneumonia in multivariable regression analysis. Proportion of pneumonia ranged between 0.9% in the higher monocytic HLA-DR quartile (≥21,876 mAb/cell) and 8.5% in the lower quartile (≤12,369 mAb/cell). In the presence of dysphagia, proportion of pneumonia increased to 5.9% and 18.8%, respectively. Patients without dysphagia and normal monocytic HLA-DR expression had no stroke-associated pneumonia risk. We demonstrate that dysphagia and stroke-induced immunodepression syndrome are independent risk factors for stroke-associated pneumonia. Screening for immunodepression and dysphagia might be useful for identifying patients at high risk for stroke-associated pneumonia.

  9. Predictive Biomarkers for Asthma Therapy.

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    Medrek, Sarah K; Parulekar, Amit D; Hanania, Nicola A

    2017-09-19

    Asthma is a heterogeneous disease characterized by multiple phenotypes. Treatment of patients with severe disease can be challenging. Predictive biomarkers are measurable characteristics that reflect the underlying pathophysiology of asthma and can identify patients that are likely to respond to a given therapy. This review discusses current knowledge regarding predictive biomarkers in asthma. Recent trials evaluating biologic therapies targeting IgE, IL-5, IL-13, and IL-4 have utilized predictive biomarkers to identify patients who might benefit from treatment. Other work has suggested that using composite biomarkers may offer enhanced predictive capabilities in tailoring asthma therapy. Multiple biomarkers including sputum eosinophil count, blood eosinophil count, fractional concentration of nitric oxide in exhaled breath (FeNO), and serum periostin have been used to identify which patients will respond to targeted asthma medications. Further work is needed to integrate predictive biomarkers into clinical practice.

  10. Discriminative capacity of biomarkers for acute stroke in the emergency department.

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    Glickman, Seth W; Phillips, Samantha; Anstrom, Kevin J; Laskowitz, Daniel T; Cairns, Charles B

    2011-09-01

    Acute ischemic stroke remains largely a clinical diagnosis. To assess the potential of several biomarkers to distinguish acute ischemic stroke from mimics in the emergency department (ED). In this prospective study, 63 patients with suspected acute stroke were enrolled. Blood samples were collected at ED presentation and assayed for B-type natriuretic peptide, C-reactive protein (CRP), matrix metalloproteinase 9 (MMP-9), D-dimer, and protein S100B. Final diagnosis of stroke was rendered by blinded independent stroke experts after review of all clinical, imaging, and conventional laboratory data during admission. Logistic regression and bootstrapping models were used to evaluate the association between biomarker values and acute stroke. Thirty-four patients had a final diagnosis of stroke and 29 with mimics. The initial ED values of CRP, MMP-9, and S100B (C-indices of 0.808, 0.811, and 0.719, respectively) and the National Institutes of Health Stroke Scale (NIHSS) (C-index 0.887) predicted acute cerebral ischemia. CRP levels added discriminative value over clinical variables alone in the diagnosis of stroke. When the levels of CRP were added to the NIHSS, the combination was highly predictive of stroke (bootstrap mean C-index 0.951, 90% Confidence Interval 0.903-0.991, likelihood test p = 0.004). Biomarker testing with CRP and potentially MMP-9 and S100B, may add valuable and time-sensitive diagnostic information in the early evaluation of patients with suspected stroke in the ED. Future prospective evaluations are necessary to validate the diagnostic capability of these biomarkers for acute ischemic stroke in the ED before they should be considered for use in clinical practice. Copyright © 2011 Elsevier Inc. All rights reserved.

  11. Assessed and Emerging Biomarkers in Stroke and Training-Mediated Stroke Recovery: State of the Art

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    Marialuisa Gandolfi

    2017-01-01

    Full Text Available Since the increasing update of the biomolecular scientific literature, biomarkers in stroke have reached an outstanding and remarkable revision in the very recent years. Besides the diagnostic and prognostic role of some inflammatory markers, many further molecules and biological factors have been added to the list, including tissue derived cytokines, growth factor-like molecules, hormones, and microRNAs. The literatures on brain derived growth factor and other neuroimmune mediators, bone-skeletal muscle biomarkers, cellular and immunity biomarkers, and the role of microRNAs in stroke recovery were reviewed. To date, biomarkers represent a possible challenge in the diagnostic and prognostic evaluation of stroke onset, pathogenesis, and recovery. Many molecules are still under investigation and may become promising and encouraging biomarkers. Experimental and clinical research should increase this list and promote new discoveries in this field, to improve stroke diagnosis and treatment.

  12. Biomarkers of Acute Stroke Etiology (BASE) Study Methodology.

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    Jauch, Edward C; Barreto, Andrew D; Broderick, Joseph P; Char, Doug M; Cucchiara, Brett L; Devlin, Thomas G; Haddock, Alison J; Hicks, William J; Hiestand, Brian C; Jickling, Glen C; June, Jeff; Liebeskind, David S; Lowenkopf, Ted J; Miller, Joseph B; O'Neill, John; Schoonover, Tim L; Sharp, Frank R; Peacock, W Frank

    2017-05-05

    Acute ischemic stroke affects over 800,000 US adults annually, with hundreds of thousands more experiencing a transient ischemic attack. Emergent evaluation, prompt acute treatment, and identification of stroke or TIA (transient ischemic attack) etiology for specific secondary prevention are critical for decreasing further morbidity and mortality of cerebrovascular disease. The Biomarkers of Acute Stroke Etiology (BASE) study is a multicenter observational study to identify serum markers defining the etiology of acute ischemic stroke. Observational trial of patients presenting to the hospital within 24 h of stroke onset. Blood samples are collected at arrival, 24, and 48 h later, and RNA gene expression is utilized to identify stroke etiology marker candidates. The BASE study began January 2014. At the time of writing, there are 22 recruiting sites. Enrollment is ongoing, expected to hit 1000 patients by March 2017. The BASE study could potentially aid in focusing the initial diagnostic evaluation to determine stroke etiology, with more rapidly initiated targeted evaluations and secondary prevention strategies.Clinical Trial Registration Clinicaltrials.gov NCT02014896 https://clinicaltrials.gov/ct2/show/NCT02014896?term=biomarkers+of+acute+stroke+etiology&rank=1.

  13. Biomarkers of stroke recovery: Consensus-based core recommendations from the Stroke Recovery and Rehabilitation Roundtable.

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    Boyd, Lara A; Hayward, Kathryn S; Ward, Nick S; Stinear, Cathy M; Rosso, Charlotte; Fisher, Rebecca J; Carter, Alexandre R; Leff, Alex P; Copland, David A; Carey, Leeanne M; Cohen, Leonardo G; Basso, D Michele; Maguire, Jane M; Cramer, Steven C

    2017-07-01

    The most difficult clinical questions in stroke rehabilitation are "What is this patient's potential for recovery?" and "What is the best rehabilitation strategy for this person, given her/his clinical profile?" Without answers to these questions, clinicians struggle to make decisions regarding the content and focus of therapy, and researchers design studies that inadvertently mix participants who have a high likelihood of responding with those who do not. Developing and implementing biomarkers that distinguish patient subgroups will help address these issues and unravel the factors important to the recovery process. The goal of the present paper is to provide a consensus statement regarding the current state of the evidence for stroke recovery biomarkers. Biomarkers of motor, somatosensory, cognitive and language domains across the recovery timeline post-stroke are considered; with focus on brain structure and function, and exclusion of blood markers and genetics. We provide evidence for biomarkers that are considered ready to be included in clinical trials, as well as others that are promising but not ready and so represent a developmental priority. We conclude with an example that illustrates the utility of biomarkers in recovery and rehabilitation research, demonstrating how the inclusion of a biomarker may enhance future clinical trials. In this way, we propose a way forward for when and where we can include biomarkers to advance the efficacy of the practice of, and research into, rehabilitation and recovery after stroke.

  14. Apolipoprotein E genotype, cardiovascular biomarkers and risk of stroke

    DEFF Research Database (Denmark)

    Khan, Tauseef A; Shah, Tina; Prieto, David

    2013-01-01

    At the APOE gene, encoding apolipoprotein E, genotypes of the ε2/ε3/ε4 alleles associated with higher LDL-cholesterol (LDL-C) levels are also associated with higher coronary risk. However, the association of APOE genotype with other cardiovascular biomarkers and risk of ischaemic stroke is less c...

  15. Use of biomarkers in triage of patients with suspected stroke.

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    Vanni, Simone; Polidori, Gianluca; Pepe, Giuseppe; Chiarlone, Melisenda; Albani, Alberto; Pagnanelli, Adolfo; Grifoni, Stefano

    2011-05-01

    The absence of a rapidly available and sensitive diagnostic test represents an important limitation in the triage of patients with suspected stroke. The aim of the present study was to investigate the triage accuracy of a novel test that measures blood-borne biomarkers (triage stroke panel, TSP) and to compare its accuracy with that of the Cincinnati Prehospital Stroke Scale (CPSS). Consecutive patients with suspected stroke presenting to the Emergency Departments of three Italian hospitals underwent triage by a trained nurse according to the CPSS and had blood drawn for TSP testing. The TSP simultaneously measures four markers (B-type natriuretic peptide, D-dimer, matrix metalloproteinase-9, and S100β) presenting a single composite result, the Multimarker Index (MMX). Stroke diagnosis was established by an expert committee blinded to MMX and CPSS results. There were 155 patients enrolled, 87 (56%) of whom had a final diagnosis of stroke. The area under the receiver operating characteristic (ROC) curve for CPSS was 0.77 (95% confidence interval [CI] 0.70-0.84) and that of MMX was 0.74 (95% CI 0.66-0.82) (p = 0.285). Thus, both tests, when used alone, failed to recognize approximately 25% of strokes. The area under the ROC curve of the combination of the two tests (0.86, 95% CI 0.79-0.91) was significantly greater than that of either single test (p = 0.01 vs. CPSS and p vs. TSP). In an emergency care setting, a panel test using multiple biochemical markers showed triage accuracy similar to that of CPSS. Further studies are needed before biomarkers can be introduced in the clinical work-up of patients with suspected stroke. Copyright © 2011 Elsevier Inc. All rights reserved.

  16. Stroke scale score and early prediction of outcome after stroke

    International Nuclear Information System (INIS)

    Ahmed, R.; Zuberi, F.Z.; Afsar, S.

    2004-01-01

    Objective: To evaluate the baseline National Institute of Health Stroke Scale (NIHSS) score as a predictor of functional outcome after ischemic stroke. Subjects and Methods: The study included 50 patients who presented to Civil Hospital, Karachi, during the study period with acute stroke and were evaluated with CT scan of brain. Only those patients were enrolled in the study that had acute ischemic stroke. The enrolled subjects were then evaluated for the neurological impairment using National Institute of Health Stroke Scale (NIHSS). The subjects were followed-up and their functional outcome was assessed using Barthel index (BI) on the 7th day of their admission. Results: Of the fifty patients enrolled in the study, 31 (62%) were males and 19 (38%) were females, with age ranging from 45 years to 95 years and a mean age of 59.9 years. Neurological impairment at presentation was assessed by NIHSS. The score ranged between 2 and 28. The functional outcome was evaluated on the 7th day using Barthel index (BI), which ranged from 0 to 80. NIHSS score was found to be a good predictor of functional outcome in patients with ischemic stroke (p<0.001). Other factors like gender, hypertension and heart disease did not affect the functional recovery in such patients. Various factors were found to be significant for early prediction of stroke recovery. The NIHSS score was the strongest predictor of outcome after ischemic stroke. Age at the time of the event was also found to be an important predictor for stroke recovery. Conclusion: The NIHSS score is a good predictor of patient's recovery after stroke. Assessing the patient's neurological impairment at first presentation of ischemic stroke can guide the physician regarding the prognosis and management plan. (author)

  17. Update on Inflammatory Biomarkers and Treatments in Ischemic Stroke

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    Aldo Bonaventura

    2016-11-01

    Full Text Available After an acute ischemic stroke (AIS, inflammatory processes are able to concomitantly induce both beneficial and detrimental effects. In this narrative review, we updated evidence on the inflammatory pathways and mediators that are investigated as promising therapeutic targets. We searched for papers on PubMed and MEDLINE up to August 2016. The terms searched alone or in combination were: ischemic stroke, inflammation, oxidative stress, ischemia reperfusion, innate immunity, adaptive immunity, autoimmunity. Inflammation in AIS is characterized by a storm of cytokines, chemokines, and Damage-Associated Molecular Patterns (DAMPs released by several cells contributing to exacerbate the tissue injury both in the acute and reparative phases. Interestingly, many biomarkers have been studied, but none of these reflected the complexity of systemic immune response. Reperfusion therapies showed a good efficacy in the recovery after an AIS. New therapies appear promising both in pre-clinical and clinical studies, but still need more detailed studies to be translated in the ordinary clinical practice. In spite of clinical progresses, no beneficial long-term interventions targeting inflammation are currently available. Our knowledge about cells, biomarkers, and inflammatory markers is growing and is hoped to better evaluate the impact of new treatments, such as monoclonal antibodies and cell-based therapies.

  18. Prediction of Major Vascular Events after Stroke

    DEFF Research Database (Denmark)

    Ovbiagele, Bruce; Goldstein, Larry B.; Amarenco, Pierre

    2014-01-01

    BACKGROUND: Identifying patients with recent stroke or transient ischemic attack (TIA) at high risk of major vascular events (MVEs; stroke, myocardial infarction, or vascular death) may help optimize the intensity of secondary preventive interventions. We evaluated the relationships between...... the baseline Framingham Coronary Risk Score (FCRS) and a novel risk prediction model and with the occurrence of MVEs after stroke or TIA in subjects enrolled in the Stroke Prevention by Aggressive Reduction in Cholesterol Level (SPARCL) trial. METHODS: Data from the 4731 subjects enrolled in the SPARCL study...... were analyzed. Hazard ratios (HRs) from Cox regression models were used to determine the risk of subsequent MVEs based on the FCRS predicting 20% or more 10-year coronary heart disease risk. The novel risk model was derived based on multivariable modeling with backward selection. Model discrimination...

  19. Role of brain natriuretic peptide as a novel prognostic biomarker in acute ischemic stroke

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    Bindu Menon

    2016-01-01

    Full Text Available Aim: We investigated to study the prognostic importance of brain natriuretic peptide (BNP in ischemic stroke. Materials and Methods: We prospectively enrolled 100 patients with acute ischemic stroke and measured plasma BNP levels and compared with age- and sex-matched healthy controls. Risk factors, biochemical parameters, lipid profile, carotid and vertebral Doppler, imaging, and cardiac evaluation were done. Stroke severity was assessed by the National Institutes of Health Stroke Scale (NIHSS score on admission and functional disability by Barthel Index (BI at 3 months. Ischemic stroke subtype was classified according to the Oxfordshire Community Stroke Project (OCSP. Data were entered in MS Excel, and appropriate statistical analysis was done using the SPSS software version 21.0. A P = 0.05 was considered as significant. Results: Mean age of patients was 55.17 ± 11.37 years with a male:female ratio 3:1. OCSP showed total anterior circulation infarct (TACI 35, partial anterior circulation infarct 9, lacunar infarct 12, and posterior circulation infarct 44. NIHSS on admission was average 10 ± 7 and BI was 57 ± 30. BNP in patients (435 ng/ml was very high as compared to controls (<60 ng/ml (P < 0.001. There was a positive correlation between age and BNP (R2 = 0.34; P < 0.00; NIHSS and BNP (R2 = 0.255; P < 0.01, negative correlation between BI and BNP (R2 = −0.064; P < 0.01. Mean BNP levels across the OCSP showed higher values in TACI (F = 4.609 P = 0.005. Regression analysis showed that BNP can predict BI which was statistically significant. Conclusion: Plasma BNP levels was significantly elevated in patients with ischemic stroke. Our study concludes that high BNP levels are seen in large anterior circulation stroke and is a predictor for the poor functional outcome at 3 months. Determination of BNP levels as a biomarker could be helpful in predicting the outcome in stroke patients.

  20. Are we armed with the right data? Pooled individual data review of biomarkers in people with severe upper limb impairment after stroke

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    Kathryn S Hayward, PhD

    2017-01-01

    Full Text Available To build an understanding of the neurobiology underpinning arm recovery in people with severe arm impairment due to stroke, we conducted a pooled individual data systematic review to: 1 characterize brain biomarkers; 2 determine relationship(s between biomarkers and motor outcome; and 3 establish relationship(s between biomarkers and motor recovery. Three electronic databases were searched up to October 2, 2015. Eligible studies included adults with severe arm impairment after stroke. Descriptive statistics were calculated to characterize brain biomarkers, and pooling of individual patient data was performed using mixed-effects linear regression to examine relationships between brain biomarkers and motor outcome and recovery. Thirty-eight articles including individual data from 372 people with severe arm impairment were analysed. The majority of individuals were in the chronic (>6 months phase post stroke (51% and had a subcortical stroke (49%. The presence of a motor evoked potential (indexed by transcranial magnetic stimulation was the only biomarker related to better motor outcome (p = 0.02. There was no relationship between motor outcome and stroke volume (cm3, location (cortical, subcortical, mixed or side (left vs. right, and corticospinal tract asymmetry index (extracted from diffusion weighted imaging. Only one study had longitudinal data, thus no data pooling was possible to address change over time (preventing our third objective. Based on the available evidence, motor evoked potentials at rest were the only biomarker that predicted motor outcome in individuals with severe arm impairment following stroke. Given that few biomarkers emerged, this review highlights the need to move beyond currently known biomarkers and identify new indices with sufficient variability and sensitivity to guide recovery models in individuals with severe motor impairments following stroke. PROSPERO: CRD42015026107.

  1. Perturbation of Brain Oscillations after Ischemic Stroke: A Potential Biomarker for Post-Stroke Function and Therapy

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    Gratianne Rabiller

    2015-10-01

    Full Text Available Brain waves resonate from the generators of electrical current and propagate across brain regions with oscillation frequencies ranging from 0.05 to 500 Hz. The commonly observed oscillatory waves recorded by an electroencephalogram (EEG in normal adult humans can be grouped into five main categories according to the frequency and amplitude, namely δ (1–4 Hz, 20–200 μV, θ (4–8 Hz, 10 μV, α (8–12 Hz, 20–200 μV, β (12–30 Hz, 5–10 μV, and γ (30–80 Hz, low amplitude. Emerging evidence from experimental and human studies suggests that groups of function and behavior seem to be specifically associated with the presence of each oscillation band, although the complex relationship between oscillation frequency and function, as well as the interaction between brain oscillations, are far from clear. Changes of brain oscillation patterns have long been implicated in the diseases of the central nervous system including ischemic stroke, in which the reduction of cerebral blood flow as well as the progression of tissue damage have direct spatiotemporal effects on the power of several oscillatory bands and their interactions. This review summarizes the current knowledge in behavior and function associated with each brain oscillation, and also in the specific changes in brain electrical activities that correspond to the molecular events and functional alterations observed after experimental and human stroke. We provide the basis of the generations of brain oscillations and potential cellular and molecular mechanisms underlying stroke-induced perturbation. We will also discuss the implications of using brain oscillation patterns as biomarkers for the prediction of stroke outcome and therapeutic efficacy.

  2. Explorative investigation of biomarkers of brain damage and coagulation system activation in clinical stroke differentiation

    DEFF Research Database (Denmark)

    Undén, Johan; Strandberg, Karin; Malm, Jan

    2009-01-01

    INTRODUCTION: A simple and accurate method of differentiating ischemic stroke and intracerebral hemorrhage (ICH) is potentially useful to facilitate acute therapeutic management. Blood measurements of biomarkers of brain damage and activation of the coagulation system may potentially serve as nov...

  3. Biomarkers of Atrial Cardiopathy and Atrial Fibrillation Detection on Mobile Outpatient Continuous Telemetry After Embolic Stroke of Undetermined Source.

    Science.gov (United States)

    Sebasigari, Denise; Merkler, Alexander; Guo, Yang; Gialdini, Gino; Kummer, Benjamin; Hemendinger, Morgan; Song, Christopher; Chu, Antony; Cutting, Shawna; Silver, Brian; Elkind, Mitchell S V; Kamel, Hooman; Furie, Karen L; Yaghi, Shadi

    2017-06-01

    Biomarkers of atrial dysfunction or "cardiopathy" are associated with embolic stroke risk. However, it is unclear if this risk is mediated by undiagnosed paroxysmal atrial fibrillation or flutter (AF). We aim to determine whether atrial cardiopathy biomarkers predict AF on continuous heart-rhythm monitoring after embolic stroke of undetermined source (ESUS). This was a single-center retrospective study including all patients with ESUS undergoing 30 days of ambulatory heart-rhythm monitoring to look for AF between January 1, 2013 and December 31, 2015. We reviewed medical records for clinical, radiographic, and cardiac variables. The primary outcome was a new diagnosis of AF detected during heart-rhythm monitoring. The primary predictors were atrial biomarkers: left atrial diameter on echocardiography, P-wave terminal force in electrocardiogram (ECG) lead V1, and P wave - R wave (PR) interval on ECG. A multiple logistic regression model was used to assess the relationship between atrial biomarkers and AF detection. Among 196 eligible patients, 23 (11.7%) were diagnosed with AF. In unadjusted analyses, patients with AF were older (72.4 years versus 61.4 years, P atrial diameter (39.2 mm versus 35.7 mm, P = .03). In a multivariable model, the only predictor of AF was age ≥ 60 years (odds ratio, 3.0; 95% CI, 1.06-8.5; P = .04). Atrial biomarkers were weakly associated with AF after ESUS. This suggests that previously reported associations between these markers and stroke may reflect independent cardiac pathways leading to stroke. Prospective studies are needed to investigate these mechanisms. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  4. Biomarkers for acute diagnosis and management of stroke in neurointensive care units

    Directory of Open Access Journals (Sweden)

    Olena Y Glushakova

    2016-01-01

    Full Text Available The effectiveness of current management of critically ill stroke patients depends on rapid assessment of the type of stroke, ischemic or hemorrhagic, and on a patient′s general clinical status. Thrombolytic therapy with recombinant tissue plasminogen activator (r-tPA is the only effective treatment for ischemic stroke approved by the Food and Drug Administration (FDA, whereas no treatment has been shown to be effective for hemorrhagic stroke. Furthermore, a narrow therapeutic window and fear of precipitating intracranial hemorrhage by administering r-tPA cause many clinicians to avoid using this treatment. Thus, rapid and objective assessments of stroke type at admission would increase the number of patients with ischemic stroke receiving r-tPA treatment and thereby, improve outcome for many additional stroke patients. Considerable literature suggests that brain-specific protein biomarkers of glial [i.e. S100 calcium-binding protein B (S100B, glial fibrillary acidic protein (GFAP] and neuronal cells [e.g., ubiquitin C-terminal hydrolase-L1 (UCH-L1, neuron-specific enolase (NSE, αII-spectrin breakdown products SBDP120, SBDP145, and SBDP150, myelin basic protein (MBP, neurofilament light chain (NF-L, tau protein, visinin-like protein-1 (VLP 1, NR2 peptide] injury that could be detected in the cerebrospinal fluid (CSF and peripheral blood might provide valuable and timely diagnostic information for stroke necessary to make prompt management and decisions, especially when the time of stroke onset cannot be determined. This information could include injury severity, prognosis of short-term and long-term outcomes, and discrimination of ischemic or hemorrhagic stroke. This chapter reviews the current status of the development of biomarker-based diagnosis of stroke and its potential application to improve stroke care.

  5. Predicting activities after stroke : what is clinically relevant?

    NARCIS (Netherlands)

    Kwakkel, G.; Kollen, B. J.

    Knowledge about factors that determine the final outcome after stroke is important for early stroke management, rehabilitation goals, and discharge planning. This narrative review provides an overview of current knowledge about the prediction of activities after stroke. We reviewed the pattern of

  6. Predicting Risk of Cognitive Decline in Very Old Adults Using Three Models: The Framingham Stroke Risk Profile; the Cardiovascular Risk Factors, Aging, and Dementia Model; and Oxi-Inflammatory Biomarkers.

    Science.gov (United States)

    Harrison, Stephanie L; de Craen, Anton J M; Kerse, Ngaire; Teh, Ruth; Granic, Antoneta; Davies, Karen; Wesnes, Keith A; den Elzen, Wendy P J; Gussekloo, Jacobijn; Kirkwood, Thomas B L; Robinson, Louise; Jagger, Carol; Siervo, Mario; Stephan, Blossom C M

    2017-02-01

    To examine the Framingham Stroke Risk Profile (FSRP); the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) risk score, and oxi-inflammatory load (cumulative risk score of three blood biomarkers-homocysteine, interleukin-6, C-reactive protein) for associations with cognitive decline using three cohort studies of very old adults and to examine whether incorporating these biomarkers with the risk scores can affect the association with cognitive decline. Three longitudinal, population-based cohort studies. Newcastle-upon-Tyne, United Kingdom; Leiden, the Netherlands; and Lakes and Bay of Plenty District Health Board areas, New Zealand. Newcastle 85+ Study participants (n = 616), Leiden 85-plus Study participants (n = 444), and Life and Living in Advanced Age, a Cohort Study in New Zealand (LiLACS NZ Study) participants (n = 396). FSRP, CAIDE risk score, oxi-inflammatory load, FSRP incorporating oxi-inflammatory load, and CAIDE risk score incorporating oxi-inflammatory load. Oxi-inflammatory load could be calculated only in the Newcastle 85+ and the Leiden 85-plus studies. Measures of global cognitive function were available for all three data sets. Domain-specific measures were available for the Newcastle 85+ and the Leiden 85-plus studies. Meta-analysis of pooled results showed greater risk of incident global cognitive impairment with higher FSRP (hazard ratio (HR) = 1.46, 95% confidence interval (CI) = 1.08-1.98), CAIDE (HR = 1.53, 95% CI = 1.09-2.14), and oxi-inflammatory load (HR = 1.73, 95% CI = 1.04-2.88) scores. Adding oxi-inflammatory load to the risk scores increased the risk of cognitive impairment for the FSRP (HR = 1.65, 95% CI = 1.17-2.33) and the CAIDE model (HR = 1.93, 95% CI = 1.39-2.67). Adding oxi-inflammatory load to cardiovascular risk scores may be useful for determining risk of cognitive impairment in very old adults. © 2016, Copyright the Authors Journal compilation © 2016, The American Geriatrics Society.

  7. On the Viability of Diffusion MRI-Based Microstructural Biomarkers in Ischemic Stroke

    Directory of Open Access Journals (Sweden)

    Ilaria Boscolo Galazzo

    2018-02-01

    Full Text Available Recent tract-based analyses provided evidence for the exploitability of 3D-SHORE microstructural descriptors derived from diffusion MRI (dMRI in revealing white matter (WM plasticity. In this work, we focused on the main open issues left: (1 the comparative analysis with respect to classical tensor-derived indices, i.e., Fractional Anisotropy (FA and Mean Diffusivity (MD; and (2 the ability to detect plasticity processes in gray matter (GM. Although signal modeling in GM is still largely unexplored, we investigated their sensibility to stroke-induced microstructural modifications occurring in the contralateral hemisphere. A more complete picture could provide hints for investigating the interplay of GM and WM modulations. Ten stroke patients and ten age/gender-matched healthy controls were enrolled in the study and underwent diffusion spectrum imaging (DSI. Acquisitions at three and two time points (tp were performed on patients and controls, respectively. For all subjects and acquisitions, FA and MD were computed along with 3D-SHORE-based indices [Generalized Fractional Anisotropy (GFA, Propagator Anisotropy (PA, Return To the Axis Probability (RTAP, Return To the Plane Probability (RTPP, and Mean Square Displacement (MSD]. Tract-based analysis involving the cortical, subcortical and transcallosal motor networks and region-based analysis in GM were successively performed, focusing on the contralateral hemisphere to the stroke. Reproducibility of all the indices on both WM and GM was quantitatively proved on controls. For tract-based, longitudinal group analyses revealed the highest significant differences across the subcortical and transcallosal networks for all the indices. The optimal regression model for predicting the clinical motor outcome at tp3 included GFA, PA, RTPP, and MSD in the subcortical network in combination with the main clinical information at baseline. Region-based analysis in the contralateral GM highlighted the ability of

  8. Acute ischaemic stroke prediction from physiological time series patterns

    Directory of Open Access Journals (Sweden)

    Qing Zhang,

    2013-05-01

    Full Text Available BackgroundStroke is one of the major diseases with human mortality. Recent clinical research has indicated that early changes in common physiological variables represent a potential therapeutic target, thus the manipulation of these variables may eventually yield an effective way to optimise stroke recovery.AimsWe examined correlations between physiological parameters of patients during the first 48 hours after a stroke, and their stroke outcomes after 3 months. We wanted to discover physiological determinants that could be used to improve health outcomes by supporting the medical decisions that need to be made early on a patient’s stroke experience.Method We applied regression-based machine learning techniques to build a prediction algorithm that can forecast 3-month outcomes from initial physiological time series data during the first 48 hours after stroke. In our method, not only did we use statistical characteristics as traditional prediction features, but also we adopted trend patterns of time series data as new key features.ResultsWe tested our prediction method on a real physiological data set of stroke patients. The experiment results revealed an average high precision rate: 90%. We also tested prediction methods only considering statistical characteristics of physiological data, and concluded an average precision rate: 71%.ConclusionWe demonstrated that using trend pattern features in prediction methods improved the accuracy of stroke outcome prediction. Therefore, trend patterns of physiological time series data have an important role in the early treatment of patients with acute ischaemic stroke.

  9. Early post-stroke cognition in stroke rehabilitation patients predicts functional outcome at 13 months.

    Science.gov (United States)

    Wagle, Jørgen; Farner, Lasse; Flekkøy, Kjell; Bruun Wyller, Torgeir; Sandvik, Leiv; Fure, Brynjar; Stensrød, Brynhild; Engedal, Knut

    2011-01-01

    To identify prognostic factors associated with functional outcome at 13 months in a sample of stroke rehabilitation patients. Specifically, we hypothesized that cognitive functioning early after stroke would predict long-term functional outcome independently of other factors. 163 stroke rehabilitation patients underwent a structured neuropsychological examination 2-3 weeks after hospital admittance, and their functional status was subsequently evaluated 13 months later with the modified Rankin Scale (mRS) as outcome measure. Three predictive models were built using linear regression analyses: a biological model (sociodemographics, apolipoprotein E genotype, prestroke vascular factors, lesion characteristics and neurological stroke-related impairment); a functional model (pre- and early post-stroke cognitive functioning, personal and instrumental activities of daily living, ADL, and depressive symptoms), and a combined model (including significant variables, with p value Stroke Scale; β = 0.402, p stroke cognitive functioning (Repeatable Battery of Neuropsychological Status, RBANS; β = -0.248, p = 0.001) and prestroke personal ADL (Barthel Index; β = -0.217, p = 0.002). Further linear regression analyses of which RBANS indexes and subtests best predicted long-term functional outcome showed that Coding (β = -0.484, p stroke cognitive functioning as measured by the RBANS is a significant and independent predictor of long-term functional post-stroke outcome. Copyright © 2011 S. Karger AG, Basel.

  10. Biomarkers for predicting complete debulking in ovarian cancer

    DEFF Research Database (Denmark)

    Fagö-Olsen, Carsten Lindberg; Ottesen, Bent; Christensen, Ib Jarle

    2014-01-01

    AIM: We aimed to construct and validate a model based on biomarkers to predict complete primary debulking surgery for ovarian cancer patients. PATIENTS AND METHODS: The study consisted of three parts: Part I: Biomarker data obtained from mass spectrometry, baseline data and, surgical outcome were...... used to construct predictive indices for complete tumour resection; Part II: sera from randomly selected patients from part I were analyzed using enzyme-linked immunosorbent assay (ELISA) to investigate the correlation to mass spectrometry; Part III: the indices from part I were validated in a new.......64. CONCLUSION: Our validated model based on biomarkers was unable to predict surgical outcome for patients with ovarian cancer....

  11. Distinguishing prognostic and predictive biomarkers: An information theoretic approach.

    Science.gov (United States)

    Sechidis, Konstantinos; Papangelou, Konstantinos; Metcalfe, Paul D; Svensson, David; Weatherall, James; Brown, Gavin

    2018-05-02

    The identification of biomarkers to support decision-making is central to personalised medicine, in both clinical and research scenarios. The challenge can be seen in two halves: identifying predictive markers, which guide the development/use of tailored therapies; and identifying prognostic markers, which guide other aspects of care and clinical trial planning, i.e. prognostic markers can be considered as covariates for stratification. Mistakenly assuming a biomarker to be predictive, when it is in fact largely prognostic (and vice-versa) is highly undesirable, and can result in financial, ethical and personal consequences. We present a framework for data-driven ranking of biomarkers on their prognostic/predictive strength, using a novel information theoretic method. This approach provides a natural algebra to discuss and quantify the individual predictive and prognostic strength, in a self-consistent mathematical framework. Our contribution is a novel procedure, INFO+, which naturally distinguishes the prognostic vs predictive role of each biomarker and handles higher order interactions. In a comprehensive empirical evaluation INFO+ outperforms more complex methods, most notably when noise factors dominate, and biomarkers are likely to be falsely identified as predictive, when in fact they are just strongly prognostic. Furthermore, we show that our methods can be 1-3 orders of magnitude faster than competitors, making it useful for biomarker discovery in 'big data' scenarios. Finally, we apply our methods to identify predictive biomarkers on two real clinical trials, and introduce a new graphical representation that provides greater insight into the prognostic and predictive strength of each biomarker. R implementations of the suggested methods are available at https://github.com/sechidis. konstantinos.sechidis@manchester.ac.uk. Supplementary data are available at Bioinformatics online.

  12. Biomarkers related to carotid intima-media thickness and plaques in long-term survivors of ischemic stroke

    OpenAIRE

    Waje-Andreassen, Ulrike; Næss, Halvor; Thomassen, Lars; Marøy, Tove Helene; Mazengia, Kibret Yimer; Eide, Geir Egil; Vedeler, Christian A.

    2015-01-01

    Lifestyle risk factors, inflammation and genetics play a role in the development of atherosclerosis. We therefore studied Fc gamma receptor (FcγR) polymorphisms, interleukin (IL)-10 polymorphisms and other biomarkers related to carotid intima-media thickness (cIMT) in patients with ischemic stroke at a young age. Patients were evaluated 12 years after stroke occurrence. Patients (n = 232) 49 years of age or younger with an index stroke between 1988 and 1997 were retrospectively selected. Bloo...

  13. Parietal operculum and motor cortex activities predict motor recovery in moderate to severe stroke

    Directory of Open Access Journals (Sweden)

    Firdaus Fabrice Hannanu

    2017-01-01

    In subacute stroke, fMRI brain activity related to passive movement measured in a sensorimotor network defined by activity during voluntary movement predicted motor recovery better than baseline motor-FMS alone. Furthermore, fMRI sensorimotor network activity measures considered alone allowed excellent clinical recovery prediction and may provide reliable biomarkers for assessing new therapies in clinical trial contexts. Our findings suggest that neural reorganization related to motor recovery from moderate to severe stroke results from balanced changes in ipsilesional MI (BA4a and a set of phylogenetically more archaic sensorimotor regions in the ventral sensorimotor trend, in which OP1 and OP4 processes may complement the ipsilesional dorsal motor cortex in achieving compensatory sensorimotor recovery.

  14. Human cervicovaginal fluid biomarkers to predict term and preterm labor

    Science.gov (United States)

    Heng, Yujing J.; Liong, Stella; Permezel, Michael; Rice, Gregory E.; Di Quinzio, Megan K. W.; Georgiou, Harry M.

    2015-01-01

    Preterm birth (PTB; birth before 37 completed weeks of gestation) remains the major cause of neonatal morbidity and mortality. The current generation of biomarkers predictive of PTB have limited utility. In pregnancy, the human cervicovaginal fluid (CVF) proteome is a reflection of the local biochemical milieu and is influenced by the physical changes occurring in the vagina, cervix and adjacent overlying fetal membranes. Term and preterm labor (PTL) share common pathways of cervical ripening, myometrial activation and fetal membranes rupture leading to birth. We therefore hypothesize that CVF biomarkers predictive of labor may be similar in both the term and preterm labor setting. In this review, we summarize some of the existing published literature as well as our team's breadth of work utilizing the CVF for the discovery and validation of putative CVF biomarkers predictive of human labor. Our team established an efficient method for collecting serial CVF samples for optimal 2-dimensional gel electrophoresis resolution and analysis. We first embarked on CVF biomarker discovery for the prediction of spontaneous onset of term labor using 2D-electrophoresis and solution array multiple analyte profiling. 2D-electrophoretic analyses were subsequently performed on CVF samples associated with PTB. Several proteins have been successfully validated and demonstrate that these biomarkers are associated with term and PTL and may be predictive of both term and PTL. In addition, the measurement of these putative biomarkers was found to be robust to the influences of vaginal microflora and/or semen. The future development of a multiple biomarker bed-side test would help improve the prediction of PTB and the clinical management of patients. PMID:26029118

  15. The Stroke Assessment of Fall Risk (SAFR): predictive validity in inpatient stroke rehabilitation.

    Science.gov (United States)

    Breisinger, Terry P; Skidmore, Elizabeth R; Niyonkuru, Christian; Terhorst, Lauren; Campbell, Grace B

    2014-12-01

    To evaluate relative accuracy of a newly developed Stroke Assessment of Fall Risk (SAFR) for classifying fallers and non-fallers, compared with a health system fall risk screening tool, the Fall Harm Risk Screen. Prospective quality improvement study conducted at an inpatient stroke rehabilitation unit at a large urban university hospital. Patients admitted for inpatient stroke rehabilitation (N = 419) with imaging or clinical evidence of ischemic or hemorrhagic stroke, between 1 August 2009 and 31 July 2010. Not applicable. Sensitivity, specificity, and area under the curve for Receiver Operating Characteristic Curves of both scales' classifications, based on fall risk score completed upon admission to inpatient stroke rehabilitation. A total of 68 (16%) participants fell at least once. The SAFR was significantly more accurate than the Fall Harm Risk Screen (p Fall Harm Risk Screen, area under the curve was 0.56, positive predictive value was 0.19, and negative predictive value was 0.86. Sensitivity and specificity of the SAFR (0.78 and 0.63, respectively) was higher than the Fall Harm Risk Screen (0.57 and 0.48, respectively). An evidence-derived, population-specific fall risk assessment may more accurately predict fallers than a general fall risk screen for stroke rehabilitation patients. While the SAFR improves upon the accuracy of a general assessment tool, additional refinement may be warranted. © The Author(s) 2014.

  16. Biomarkers of Tumour Radiosensitivity and Predicting Benefit from Radiotherapy.

    Science.gov (United States)

    Forker, L J; Choudhury, A; Kiltie, A E

    2015-10-01

    Radiotherapy is an essential component of treatment for more than half of newly diagnosed cancer patients. The response to radiotherapy varies widely between individuals and although advances in technology have allowed the adaptation of radiotherapy fields to tumour anatomy, it is still not possible to tailor radiotherapy based on tumour biology. A biomarker of intrinsic radiosensitivity would be extremely valuable for individual dosing, aiding decision making between radical treatment options and avoiding toxicity of neoadjuvant or adjuvant radiotherapy in those unlikely to benefit. This systematic review summarises the current evidence for biomarkers under investigation as predictors of radiotherapy benefit. Only 10 biomarkers were identified as having been evaluated for their radiotherapy-specific predictive value in over 100 patients in a clinical setting, highlighting that despite a rich literature there were few high-quality studies for inclusion. The most extensively studied radiotherapy predictive biomarkers were the radiosensitivity index and MRE11; however, neither has been evaluated in a randomised controlled trial. Although these biomarkers show promise, there is not enough evidence to justify their use in routine practice. Further validation is needed before biomarkers can fulfil their potential and predict treatment outcomes for large numbers of patients. Copyright © 2015 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

  17. In-Hospital Risk Prediction for Post-stroke Depression. Development and Validation of the Post-stroke Depression Prediction Scale

    NARCIS (Netherlands)

    Thóra Hafsteinsdóttir; Roelof G.A. Ettema; Diederick Grobbee; Prof. Dr. Marieke J. Schuurmans; Janneke van Man-van Ginkel; Eline Lindeman

    2013-01-01

    Background and Purpose—The timely detection of post-stroke depression is complicated by a decreasing length of hospital stay. Therefore, the Post-stroke Depression Prediction Scale was developed and validated. The Post-stroke Depression Prediction Scale is a clinical prediction model for the early

  18. Patient-specific prediction of functional recovery after stroke.

    Science.gov (United States)

    Douiri, Abdel; Grace, Justin; Sarker, Shah-Jalal; Tilling, Kate; McKevitt, Christopher; Wolfe, Charles DA; Rudd, Anthony G

    2017-07-01

    Background and aims Clinical predictive models for stroke recovery could offer the opportunity of targeted early intervention and more specific information for patients and carers. In this study, we developed and validated a patient-specific prognostic model for monitoring recovery after stroke and assessed its clinical utility. Methods Four hundred and ninety-five patients from the population-based South London Stroke Register were included in a substudy between 2002 and 2004. Activities of daily living were assessed using Barthel Index) at one, two, three, four, six, eight, 12, 26, and 52 weeks after stroke. Penalized linear mixed models were developed to predict patients' functional recovery trajectories. An external validation cohort included 1049 newly registered stroke patients between 2005 and 2011. Prediction errors on discrimination and calibration were assessed. The potential clinical utility was evaluated using prognostic accuracy measurements and decision curve analysis. Results Predictive recovery curves showed good accuracy, with root mean squared deviation of 3 Barthel Index points and a R 2 of 83% up to one year after stroke in the external cohort. The negative predictive values of the risk of poor recovery (Barthel Index <8) at three and 12 months were also excellent, 96% (95% CI [93.6-97.4]) and 93% [90.8-95.3], respectively, with a potential clinical utility measured by likelihood ratios (LR+:17 [10.8-26.8] at three months and LR+:11 [6.5-17.2] at 12 months). Decision curve analysis showed an increased clinical benefit, particularly at threshold probabilities of above 5% for predictive risk of poor outcomes. Conclusions A recovery curves tool seems to accurately predict progression of functional recovery in poststroke patients.

  19. Coated-platelets predict stroke at 30 days following TIA.

    Science.gov (United States)

    Kirkpatrick, Angelia C; Vincent, Andrea S; Dale, George L; Prodan, Calin I

    2017-07-11

    To examine the potential for coated-platelets, a subset of highly procoagulant platelets observed on dual agonist stimulation with collagen and thrombin, for predicting stroke at 30 days in patients with TIA. Consecutive patients with TIA were enrolled and followed up prospectively. ABCD2 scores were obtained for each patient. Coated-platelet levels, reported as percent of cells converted to coated-platelets, were determined at baseline. The primary endpoint was the occurrence of stroke at 30 days. Receiver operator characteristic (ROC) analysis was used to calculate area under the curve (AUC) values for a model including coated-platelets to predict incident stroke at 30 days. A total of 171 patients with TIA were enrolled, and 10 strokes were observed at 30 days. A cutoff of 51.1% for coated-platelet levels yielded a sensitivity of 0.80 (95% confidence interval [CI] 0.55-1.0), specificity of 0.73 (95% CI 0.66-0.80), positive predictive value of 0.16 (95% CI 0.06-0.26), and negative predictive value of 0.98 (95% CI 0.96-1.0). The adjusted hazard ratio of incident stroke in patients with coated-platelet levels ≥51.1% was 10.72 compared to those with levels TIA. © 2017 American Academy of Neurology.

  20. The potential role of biomarkers in predicting gestational diabetes

    Directory of Open Access Journals (Sweden)

    Huguette S Brink

    2016-08-01

    Full Text Available Gestational diabetes (GD is a frequent complication during pregnancy and is associated with maternal and neonatal complications. It is suggested that a disturbing environment for the foetus, such as impaired glucose metabolism during intrauterine life, may result in enduring epigenetic changes leading to increased disease risk in adult life. Hence, early prediction of GD is vital. Current risk prediction models are based on maternal and clinical parameters, lacking a strong predictive value. Adipokines are mainly produced by adipocytes and suggested to be a link between obesity and its cardiovascular complications. Various adipokines, including adiponectin, leptin and TNFα, have shown to be dysregulated in GD. This review aims to outline biomarkers potentially associated with the pathophysiology of GD and discuss the role of integrating predictive biomarkers in current clinical risk prediction models, in order to enhance the identification of those at risk.

  1. Clinical studies of biomarkers in suicide prediction

    OpenAIRE

    Jokinen, Jussi

    2007-01-01

    Suicide is a major clinical problem in psychiatry and suicidal behaviours can be seen as a nosological entity per se. Predicting suicide is difficult due to its low base-rate and the limited specificity of clinical predictors. Prospective biological studies suggest that dysfunctions in the hypothalamo pituitary adrenal (HPA) axis and the serotonergic system have predictive power for suicide in mood disorders. Suicide attempt is the most robust clinical predictor making suici...

  2. Potential serum biomarkers and metabonomic profiling of serum in ischemic stroke patients using UPLC/Q-TOF MS/MS.

    Directory of Open Access Journals (Sweden)

    Hongxue Sun

    Full Text Available Stroke still has a high incidence with a tremendous public health burden and it is a leading cause of mortality and disability. However, biomarkers for early diagnosis are absent and the metabolic alterations associated with ischemic stroke are not clearly understood. The objectives of this case-control study are to identify serum biomarkers and explore the metabolic alterations of ischemic stroke.Metabonomic analysis was performed using ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry and multivariate statistical analysis was employed to study 60 patients with or without ischemic stroke (30 cases and 30 controls.Serum metabolic profiling identified a series of 12 metabolites with significant alterations, and the related metabolic pathways involved glycerophospholipid, sphingolipid, phospholipid, fat acid, acylcarnitine, heme, and purine metabolism. Subsequently, multiple logistic regression analyses of these metabolites showed uric acid, sphinganine and adrenoyl ethanolamide were potential biomarkers of ischemic stroke with an area under the receiver operating characteristic curve of 0.941.These findings provide insights into the early diagnosis and potential pathophysiology of ischemic stroke.

  3. Prognostic and predictive biomarkers in colorectal cancer. Towards precision medicine

    NARCIS (Netherlands)

    Reimers, Marlies Suzanne

    2015-01-01

    The aim of this thesis was to define prognostic and predictive biomarkers in colorectal cancer for improved risk stratification and treatment benefit in the individual patient, with the introduction of precision medicine in the near future as the ultimate goal. By definition, precision medicine is

  4. Risk score to predict gastrointestinal bleeding after acute ischemic stroke.

    Science.gov (United States)

    Ji, Ruijun; Shen, Haipeng; Pan, Yuesong; Wang, Penglian; Liu, Gaifen; Wang, Yilong; Li, Hao; Singhal, Aneesh B; Wang, Yongjun

    2014-07-25

    Gastrointestinal bleeding (GIB) is a common and often serious complication after stroke. Although several risk factors for post-stroke GIB have been identified, no reliable or validated scoring system is currently available to predict GIB after acute stroke in routine clinical practice or clinical trials. In the present study, we aimed to develop and validate a risk model (acute ischemic stroke associated gastrointestinal bleeding score, the AIS-GIB score) to predict in-hospital GIB after acute ischemic stroke. The AIS-GIB score was developed from data in the China National Stroke Registry (CNSR). Eligible patients in the CNSR were randomly divided into derivation (60%) and internal validation (40%) cohorts. External validation was performed using data from the prospective Chinese Intracranial Atherosclerosis Study (CICAS). Independent predictors of in-hospital GIB were obtained using multivariable logistic regression in the derivation cohort, and β-coefficients were used to generate point scoring system for the AIS-GIB. The area under the receiver operating characteristic curve (AUROC) and the Hosmer-Lemeshow goodness-of-fit test were used to assess model discrimination and calibration, respectively. A total of 8,820, 5,882, and 2,938 patients were enrolled in the derivation, internal validation and external validation cohorts. The overall in-hospital GIB after AIS was 2.6%, 2.3%, and 1.5% in the derivation, internal, and external validation cohort, respectively. An 18-point AIS-GIB score was developed from the set of independent predictors of GIB including age, gender, history of hypertension, hepatic cirrhosis, peptic ulcer or previous GIB, pre-stroke dependence, admission National Institutes of Health stroke scale score, Glasgow Coma Scale score and stroke subtype (Oxfordshire). The AIS-GIB score showed good discrimination in the derivation (0.79; 95% CI, 0.764-0.825), internal (0.78; 95% CI, 0.74-0.82) and external (0.76; 95% CI, 0.71-0.82) validation cohorts

  5. Bayesian additive decision trees of biomarker by treatment interactions for predictive biomarker detection and subgroup identification.

    Science.gov (United States)

    Zhao, Yang; Zheng, Wei; Zhuo, Daisy Y; Lu, Yuefeng; Ma, Xiwen; Liu, Hengchang; Zeng, Zhen; Laird, Glen

    2017-10-11

    Personalized medicine, or tailored therapy, has been an active and important topic in recent medical research. Many methods have been proposed in the literature for predictive biomarker detection and subgroup identification. In this article, we propose a novel decision tree-based approach applicable in randomized clinical trials. We model the prognostic effects of the biomarkers using additive regression trees and the biomarker-by-treatment effect using a single regression tree. Bayesian approach is utilized to periodically revise the split variables and the split rules of the decision trees, which provides a better overall fitting. Gibbs sampler is implemented in the MCMC procedure, which updates the prognostic trees and the interaction tree separately. We use the posterior distribution of the interaction tree to construct the predictive scores of the biomarkers and to identify the subgroup where the treatment is superior to the control. Numerical simulations show that our proposed method performs well under various settings comparing to existing methods. We also demonstrate an application of our method in a real clinical trial.

  6. Estimating the Accuracy of the Chedoke-McMaster Stroke Assessment Predictive Equations for Stroke Rehabilitation.

    Science.gov (United States)

    Dang, Mia; Ramsaran, Kalinda D; Street, Melissa E; Syed, S Noreen; Barclay-Goddard, Ruth; Stratford, Paul W; Miller, Patricia A

    2011-01-01

    To estimate the predictive accuracy and clinical usefulness of the Chedoke-McMaster Stroke Assessment (CMSA) predictive equations. A longitudinal prognostic study using historical data obtained from 104 patients admitted post cerebrovascular accident was undertaken. Data were abstracted for all patients undergoing rehabilitation post stroke who also had documented admission and discharge CMSA scores. Published predictive equations were used to determine predicted outcomes. To determine the accuracy and clinical usefulness of the predictive model, shrinkage coefficients and predictions with 95% confidence bands were calculated. Complete data were available for 74 patients with a mean age of 65.3±12.4 years. The shrinkage values for the six Impairment Inventory (II) dimensions varied from -0.05 to 0.09; the shrinkage value for the Activity Inventory (AI) was 0.21. The error associated with predictive values was greater than ±1.5 stages for the II dimensions and greater than ±24 points for the AI. This study shows that the large error associated with the predictions (as defined by the confidence band) for the CMSA II and AI limits their clinical usefulness as a predictive measure. Further research to establish predictive models using alternative statistical procedures is warranted.

  7. Estimating the Accuracy of the Chedoke–McMaster Stroke Assessment Predictive Equations for Stroke Rehabilitation

    Science.gov (United States)

    Dang, Mia; Ramsaran, Kalinda D.; Street, Melissa E.; Syed, S. Noreen; Barclay-Goddard, Ruth; Miller, Patricia A.

    2011-01-01

    ABSTRACT Purpose: To estimate the predictive accuracy and clinical usefulness of the Chedoke–McMaster Stroke Assessment (CMSA) predictive equations. Method: A longitudinal prognostic study using historical data obtained from 104 patients admitted post cerebrovascular accident was undertaken. Data were abstracted for all patients undergoing rehabilitation post stroke who also had documented admission and discharge CMSA scores. Published predictive equations were used to determine predicted outcomes. To determine the accuracy and clinical usefulness of the predictive model, shrinkage coefficients and predictions with 95% confidence bands were calculated. Results: Complete data were available for 74 patients with a mean age of 65.3±12.4 years. The shrinkage values for the six Impairment Inventory (II) dimensions varied from −0.05 to 0.09; the shrinkage value for the Activity Inventory (AI) was 0.21. The error associated with predictive values was greater than ±1.5 stages for the II dimensions and greater than ±24 points for the AI. Conclusions: This study shows that the large error associated with the predictions (as defined by the confidence band) for the CMSA II and AI limits their clinical usefulness as a predictive measure. Further research to establish predictive models using alternative statistical procedures is warranted. PMID:22654239

  8. Clinical usefulness of a biomarker-based diagnostic test for acute stroke: the Biomarker Rapid Assessment in Ischemic Injury (BRAIN) study.

    Science.gov (United States)

    Laskowitz, Daniel T; Kasner, Scott E; Saver, Jeffrey; Remmel, Kerri S; Jauch, Edward C

    2009-01-01

    One of the significant limitations in the evaluation and management of patients with suspected acute cerebral ischemia is the absence of a widely available, rapid, and sensitive diagnostic test. The objective of the current study was to assess whether a test using a panel of biomarkers might provide useful diagnostic information in the early evaluation of stroke by differentiating patients with cerebral ischemia from other causes of acute neurological deficit. A total of 1146 patients presenting with neurological symptoms consistent with possible stroke were prospectively enrolled at 17 different sites. Timed blood samples were assayed for matrix metalloproteinase 9, brain natriuretic factor, d-dimer, and protein S100beta. A separate cohort of 343 patients was independently enrolled to validate the multiple biomarker model approach. A diagnostic tool incorporating the values of matrix metalloproteinase 9, brain natriuretic factor, d-dimer, and S-100beta into a composite score was sensitive for acute cerebral ischemia. The multivariate model demonstrated modest discriminative capabilities with an area under the receiver operating characteristic curve of 0.76 for hemorrhagic stroke and 0.69 for all stroke (likelihood test P<0.001). When the threshold for the logistic model was set at the first quartile, this resulted in a sensitivity of 86% for detecting all stroke and a sensitivity of 94% for detecting hemorrhagic stroke. Moreover, results were reproducible in a separate cohort tested on a point-of-care platform. These results suggest that a biomarker panel may add valuable and time-sensitive diagnostic information in the early evaluation of stroke. Such an approach is feasible on a point-of-care platform. The rapid identification of patients with suspected stroke would expand the availability of time-limited treatment strategies. Although the diagnostic accuracy of the current panel is clearly imperfect, this study demonstrates the feasibility of incorporating a

  9. Stroke and TIA survivors’ cognitive beliefs and affective responses regarding treatment and future stroke risk differentially predict medication adherence and categorised stroke risk

    OpenAIRE

    Phillips, L. Alison; Diefenbach, Michael A.; Abrams, Jessica; Horowitz, Carol R.

    2014-01-01

    Cognitive beliefs and affective responses to illness and treatment are known to independently predict health behaviours. The purpose of the current study is to assess the relative importance of four psychological domains – specifically, affective illness, cognitive illness, affective treatment and cognitive treatment – for predicting stroke and transient ischemic attack (TIA) survivors’ adherence to stroke prevention medications as well as their objective, categorised stroke risk. We assessed...

  10. Predicting functional outcomes of posterior circulation acute ischemic stroke in first 36 h of stroke onset.

    Science.gov (United States)

    Lin, Sheng-Feng; Chen, Chin-I; Hu, Han-Hwa; Bai, Chyi-Huey

    2018-04-01

    Posterior circulation acute ischemic stroke constitutes one-fourth of all ischemic strokes and can be efficiently quantified using the posterior circulation Alberta stroke program early computed tomography score (PC-ASPECTS) through diffusion-weighted imaging. We investigated whether the PC-ASPECTS and National Institutes of Health Stroke Scale (NIHSS) facilitate functional outcome prediction among Chinese patients with posterior circulation acute ischemic stroke. Participants were selected from our prospective stroke registry from January 1, 2015, to December 31, 2016. The baseline NIHSS score was assessed on the first day of admission, and brain magnetic resonance imaging was performed within 36 h after stroke onset. Simple and multiple logistic regressions were conducted to determine stroke risk factors and the PC-ASPECTS. Receiver operating characteristics (ROC) curve analysis was performed to compare the NIHSS and PC-ASPECTS. Of 549 patients from our prospective stroke admission registry database, 125 (22.8%) had a diagnosis of posterior circulation acute ischemic stroke. The optimal cutoff for the PC-ASPECTS in predicting outcomes was 7. The odds ratios of the PC-ASPECTS (≤ 7 vs > 7) in predicting outcomes were 6.33 (p = 0.0002) and 8.49 (p = 0.0060) in the univariate and multivariate models, respectively, and 7.52 (p = 0.0041) in the aging group. On ROC curve analysis, the PC-ASPECTS demonstrated more reliability than the baseline NIHSS for predicting functional outcomes of minor posterior circulation stroke. In conclusion, both the PC-ASPECTS and NIHSS help clinicians predict functional outcomes. PC-ASPECTS > 7 is a helpful discriminator for achieving favorable functional outcome prediction in posterior circulation acute ischemic stroke.

  11. Predicting discharge destination after stroke: A systematic review.

    Science.gov (United States)

    Mees, Margot; Klein, Jelle; Yperzeele, Laetitia; Vanacker, Peter; Cras, Patrick

    2016-03-01

    Different factors have been studied and proven to significantly influence discharge destination of acute stroke patients after hospitalization. Few reviews have been published combining the results of these studies. Therefore we aim to present an overview of the studies conducted regarding these predicting factors. Through conducting a systematic review we aimed to study the different predictive factors influencing discharge destination of acute stroke patients after hospitalization. Nineteen articles were selected in accordance with the research question and inclusion criteria. The factors found were, according to their significance in the articles, subcategorized in age, gender, functional status, cognitive status, race and ethnicity, co morbidities, education, stroke characteristics, social and living situation. The main factors significantly associated with other than home discharge were functional dependence/comorbidities, neurocognitive dysfunction and previous living circumstances/marital status. A medium or large infarct is associated with institutionalization. The stroke volume is not associated with home discharge. The effect of other factors remain controversial and results differ between studies. These include: age, gender, race, affected hemisphere and availability of a caregiver not living at home. Factors such as education, hospital complications, geographic location and FIM progression during hospitalization have not been studied sufficiently. Copyright © 2016 Elsevier B.V. All rights reserved.

  12. Serum biomarkers predictive of depressive episodes in panic disorder.

    Science.gov (United States)

    Gottschalk, M G; Cooper, J D; Chan, M K; Bot, M; Penninx, B W J H; Bahn, S

    2016-02-01

    Panic disorder with or without comorbid agoraphobia (PD/PDA) has been linked to an increased risk to develop subsequent depressive episodes, yet the underlying pathophysiology of these disorders remains poorly understood. We aimed to identify a biomarker panel predictive for the development of a depressive disorder (major depressive disorder and/or dysthymia) within a 2-year-follow-up period. Blood serum concentrations of 165 analytes were evaluated in 120 PD/PDA patients without depressive disorder baseline diagnosis (6-month-recency) in the Netherlands Study of Depression and Anxiety (NESDA). We assessed the predictive performance of serum biomarkers, clinical, and self-report variables using receiver operating characteristics curves (ROC) and the area under the ROC curve (AUC). False-discovery-rate corrected logistic regression model selection of serum analytes and covariates identified an optimal predictive panel comprised of tetranectin and creatine kinase MB along with patient gender and scores from the Inventory of Depressive Symptomatology (IDS) rating scale. Combined, an AUC of 0.87 was reached for identifying the PD/PDA patients who developed a depressive disorder within 2 years (n = 44). The addition of biomarkers represented a significant (p = 0.010) improvement over using gender and IDS alone as predictors (AUC = 0.78). For the first time, we report on a combination of biological serum markers, clinical variables and self-report inventories that can detect PD/PDA patients at increased risk of developing subsequent depressive disorders with good predictive performance in a naturalistic cohort design. After an independent validation our proposed biomarkers could prove useful in the detection of at-risk PD/PDA patients, allowing for early therapeutic interventions and improving clinical outcome. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. Amyloid-beta 40 as a biomarker of cognitive impairment in acute ischemic stroke

    Directory of Open Access Journals (Sweden)

    Aleksey A. Kulesh

    2017-01-01

    severity type of post-stroke cognitive impairment. This interaction is probably due to the damage to the hippocampus, thalamus and cingulate tracts. In our opinion, the biomarker reflects both ischemic and neurodegenerative components of the pathogenesis of cognitive impairment in acute ischemic stroke.

  14. Circulating biomarkers for predicting cardiovascular disease risk; a systematic review and comprehensive overview of meta-analyses.

    Directory of Open Access Journals (Sweden)

    Thijs C van Holten

    Full Text Available BACKGROUND: Cardiovascular disease is one of the major causes of death worldwide. Assessing the risk for cardiovascular disease is an important aspect in clinical decision making and setting a therapeutic strategy, and the use of serological biomarkers may improve this. Despite an overwhelming number of studies and meta-analyses on biomarkers and cardiovascular disease, there are no comprehensive studies comparing the relevance of each biomarker. We performed a systematic review of meta-analyses on levels of serological biomarkers for atherothrombosis to compare the relevance of the most commonly studied biomarkers. METHODS AND FINDINGS: Medline and Embase were screened on search terms that were related to "arterial ischemic events" and "meta-analyses". The meta-analyses were sorted by patient groups without pre-existing cardiovascular disease, with cardiovascular disease and heterogeneous groups concerning general populations, groups with and without cardiovascular disease, or miscellaneous. These were subsequently sorted by end-point for cardiovascular disease or stroke and summarized in tables. We have identified 85 relevant full text articles, with 214 meta-analyses. Markers for primary cardiovascular events include, from high to low result: C-reactive protein, fibrinogen, cholesterol, apolipoprotein B, the apolipoprotein A/apolipoprotein B ratio, high density lipoprotein, and vitamin D. Markers for secondary cardiovascular events include, from high to low result: cardiac troponins I and T, C-reactive protein, serum creatinine, and cystatin C. For primary stroke, fibrinogen and serum uric acid are strong risk markers. Limitations reside in that there is no acknowledged search strategy for prognostic studies or meta-analyses. CONCLUSIONS: For primary cardiovascular events, markers with strong predictive potential are mainly associated with lipids. For secondary cardiovascular events, markers are more associated with ischemia. Fibrinogen is a

  15. Transit time homogenization in ischemic stroke - A novel biomarker of penumbral microvascular failure?

    DEFF Research Database (Denmark)

    Engedal, Thorbjørn S; Hjort, Niels; Hougaard, Kristina D

    2017-01-01

    Cerebral ischemia causes widespread capillary no-flow in animal studies. The extent of microvascular impairment in human stroke, however, is unclear. We examined how acute intra-voxel transit time characteristics and subsequent recanalization affect tissue outcome on follow-up MRI in a historic...... cohort of 126 acute ischemic stroke patients. Based on perfusion-weighted MRI data, we characterized voxel-wise transit times in terms of their mean transit time (MTT), standard deviation (capillary transit time heterogeneity - CTH), and the CTH:MTT ratio (relative transit time heterogeneity), which...... tissue, prolonged mean transit time (>5 seconds) and very low cerebral blood flow (≤6 mL/100 mL/min) was associated with high risk of infarction, largely independent of recanalization status. In the remaining mismatch region, low relative transit time heterogeneity predicted subsequent infarction...

  16. Developing and Validating a Predictive Model for Stroke Progression

    Directory of Open Access Journals (Sweden)

    L.E. Craig

    2011-12-01

    Full Text Available Background: Progression is believed to be a common and important complication in acute stroke, and has been associated with increased mortality and morbidity. Reliable identification of predictors of early neurological deterioration could potentially benefit routine clinical care. The aim of this study was to identify predictors of early stroke progression using two independent patient cohorts. Methods: Two patient cohorts were used for this study – the first cohort formed the training data set, which included consecutive patients admitted to an urban teaching hospital between 2000 and 2002, and the second cohort formed the test data set, which included patients admitted to the same hospital between 2003 and 2004. A standard definition of stroke progression was used. The first cohort (n = 863 was used to develop the model. Variables that were statistically significant (p 0.1 in turn. The second cohort (n = 216 was used to test the performance of the model. The performance of the predictive model was assessed in terms of both calibration and discrimination. Multiple imputation methods were used for dealing with the missing values. Results: Variables shown to be significant predictors of stroke progression were conscious level, history of coronary heart disease, presence of hyperosmolarity, CT lesion, living alone on admission, Oxfordshire Community Stroke Project classification, presence of pyrexia and smoking status. The model appears to have reasonable discriminative properties [the median receiver-operating characteristic curve value was 0.72 (range 0.72–0.73] and to fit well with the observed data, which is indicated by the high goodness-of-fit p value [the median p value from the Hosmer-Lemeshow test was 0.90 (range 0.50–0.92]. Conclusion: The predictive model developed in this study contains variables that can be easily collected in practice therefore increasing its usability in clinical practice. Using this analysis approach, the

  17. Developing and validating a predictive model for stroke progression.

    Science.gov (United States)

    Craig, L E; Wu, O; Gilmour, H; Barber, M; Langhorne, P

    2011-01-01

    Progression is believed to be a common and important complication in acute stroke, and has been associated with increased mortality and morbidity. Reliable identification of predictors of early neurological deterioration could potentially benefit routine clinical care. The aim of this study was to identify predictors of early stroke progression using two independent patient cohorts. Two patient cohorts were used for this study - the first cohort formed the training data set, which included consecutive patients admitted to an urban teaching hospital between 2000 and 2002, and the second cohort formed the test data set, which included patients admitted to the same hospital between 2003 and 2004. A standard definition of stroke progression was used. The first cohort (n = 863) was used to develop the model. Variables that were statistically significant (p p > 0.1) in turn. The second cohort (n = 216) was used to test the performance of the model. The performance of the predictive model was assessed in terms of both calibration and discrimination. Multiple imputation methods were used for dealing with the missing values. Variables shown to be significant predictors of stroke progression were conscious level, history of coronary heart disease, presence of hyperosmolarity, CT lesion, living alone on admission, Oxfordshire Community Stroke Project classification, presence of pyrexia and smoking status. The model appears to have reasonable discriminative properties [the median receiver-operating characteristic curve value was 0.72 (range 0.72-0.73)] and to fit well with the observed data, which is indicated by the high goodness-of-fit p value [the median p value from the Hosmer-Lemeshow test was 0.90 (range 0.50-0.92)]. The predictive model developed in this study contains variables that can be easily collected in practice therefore increasing its usability in clinical practice. Using this analysis approach, the discrimination and calibration of the predictive model appear

  18. Developing and Validating a Predictive Model for Stroke Progression

    Science.gov (United States)

    Craig, L.E.; Wu, O.; Gilmour, H.; Barber, M.; Langhorne, P.

    2011-01-01

    Background Progression is believed to be a common and important complication in acute stroke, and has been associated with increased mortality and morbidity. Reliable identification of predictors of early neurological deterioration could potentially benefit routine clinical care. The aim of this study was to identify predictors of early stroke progression using two independent patient cohorts. Methods Two patient cohorts were used for this study – the first cohort formed the training data set, which included consecutive patients admitted to an urban teaching hospital between 2000 and 2002, and the second cohort formed the test data set, which included patients admitted to the same hospital between 2003 and 2004. A standard definition of stroke progression was used. The first cohort (n = 863) was used to develop the model. Variables that were statistically significant (p 0.1) in turn. The second cohort (n = 216) was used to test the performance of the model. The performance of the predictive model was assessed in terms of both calibration and discrimination. Multiple imputation methods were used for dealing with the missing values. Results Variables shown to be significant predictors of stroke progression were conscious level, history of coronary heart disease, presence of hyperosmolarity, CT lesion, living alone on admission, Oxfordshire Community Stroke Project classification, presence of pyrexia and smoking status. The model appears to have reasonable discriminative properties [the median receiver-operating characteristic curve value was 0.72 (range 0.72–0.73)] and to fit well with the observed data, which is indicated by the high goodness-of-fit p value [the median p value from the Hosmer-Lemeshow test was 0.90 (range 0.50–0.92)]. Conclusion The predictive model developed in this study contains variables that can be easily collected in practice therefore increasing its usability in clinical practice. Using this analysis approach, the discrimination and

  19. {sup 18}F-FDG PET/CT imaging factors that predict ischaemic stroke in cancer patients

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jahae; Song, Ho-Chun [Chonnam National University Hospital, Department of Nuclear Medicine, Gwangju (Korea, Republic of); Choi, Kang-Ho [Chonnam National University Hospital, Cerebrovascular Center, Gwangju (Korea, Republic of); Chonnam National University Hwasun Hospital, Department of Neurology, Hwasun-gun, Jeollanam-do (Korea, Republic of); Kim, Joon-Tae; Park, Man-Seok; Cho, Ki-Hyun [Chonnam National University Hospital, Cerebrovascular Center, Gwangju (Korea, Republic of)

    2016-11-15

    {sup 18}F-FDG PET/CT can acquire both anatomical and functional images in a single session. We investigated which factors of {sup 18}F-FDG PET/CT imaging have potential as biomarkers for an increased risk of ischaemic stroke in cancer patients. From among cancer patients presenting with various neurological symptoms and hemiparesis, 134 were selected as eligible for this retrospective analysis. A new infarct lesion on brain MRI within 1 year of FDG PET/CT defined future ischaemic stroke. The target-to-background ratio (TBR) of each arterial segment was used to define arterial inflammation on PET imaging. Abdominal obesity was defined in terms of the area and proportion of visceral adipose tissue (VAT), subcutaneous adipose tissue and total adipose tissue (TAT) on a single CT slice at the umbilical level. Ischaemic stroke confirmed by MRI occurred in 30 patients. Patients with stroke had higher TBRs in the carotid arteries and abdominal aorta (P < 0.001) and a higher VAT proportion (P = 0.021) and TAT proportion (P = 0.041) than patients without stroke. Multiple logistic regression analysis showed that TBRs of the carotid arteries and abdominal aorta, VAT and TAT proportions, and the presence of a metabolically active tumour were significantly associated with future ischaemic stroke. Combining PET and CT variables improved the power for predicting future ischaemic stroke. Our findings suggest that arterial FDG uptake and hypermetabolic malignancy on PET and the VAT proportion on CT could be independent predictors of future ischaemic stroke in patients with cancer and could identify those patients who would benefit from medical treatment. (orig.)

  20. Predictive Biomarkers for Bevacizumab in Anti-tumor Therapy

    Directory of Open Access Journals (Sweden)

    Qingqing PAN

    2011-07-01

    Full Text Available Bevacizumab, the monoclonal antibody of vascular endothelial growth factor (VEGF has been applied to the therapy of several neoplasms, but an appropriate biomarker to predict the efficacy has not been found. Those markers can originate from peripheral circulation, tumor tissue and genes. Some researches have found that low level of vascular cell adhesion molecule-1 (VCAM-1, E-selectin, angiopoietin 2 (Ang-2 in circulation or carbonic anhydrase 9 (CA9, CD31-microvessel density (CD31-MVD in tumor tissue can predict better activity of bevacizumab. Moreover, high level of soluble VEGFR2 (sVEGFR2 in circulation or the ratio of phosphorylated-VEGFR2 (p-VEGFR2 and VEGFR2 in tumor tissue increasing has the same predictive function. As to the gene, VEGF-634 CC, VEGF-1498 TT and VEGFR2 H472Q are only related to the side effct. Thus more clinical tirals and basic researches should be performed to find out effective biomarkers in bevacizumab’s therapy.

  1. Personalized Cancer Medicine: Molecular Diagnostics, Predictive biomarkers, and Drug Resistance

    Science.gov (United States)

    Gonzalez de Castro, D; Clarke, P A; Al-Lazikani, B; Workman, P

    2013-01-01

    The progressive elucidation of the molecular pathogenesis of cancer has fueled the rational development of targeted drugs for patient populations stratified by genetic characteristics. Here we discuss general challenges relating to molecular diagnostics and describe predictive biomarkers for personalized cancer medicine. We also highlight resistance mechanisms for epidermal growth factor receptor (EGFR) kinase inhibitors in lung cancer. We envisage a future requiring the use of longitudinal genome sequencing and other omics technologies alongside combinatorial treatment to overcome cellular and molecular heterogeneity and prevent resistance caused by clonal evolution. PMID:23361103

  2. Prediction of stroke thrombolysis outcome using CT brain machine learning

    Directory of Open Access Journals (Sweden)

    Paul Bentley

    2014-01-01

    Full Text Available A critical decision-step in the emergency treatment of ischemic stroke is whether or not to administer thrombolysis — a treatment that can result in good recovery, or deterioration due to symptomatic intracranial haemorrhage (SICH. Certain imaging features based upon early computerized tomography (CT, in combination with clinical variables, have been found to predict SICH, albeit with modest accuracy. In this proof-of-concept study, we determine whether machine learning of CT images can predict which patients receiving tPA will develop SICH as opposed to showing clinical improvement with no haemorrhage. Clinical records and CT brains of 116 acute ischemic stroke patients treated with intravenous thrombolysis were collected retrospectively (including 16 who developed SICH. The sample was split into training (n = 106 and test sets (n = 10, repeatedly for 1760 different combinations. CT brain images acted as inputs into a support vector machine (SVM, along with clinical severity. Performance of the SVM was compared with established prognostication tools (SEDAN and HAT scores; original, or after adaptation to our cohort. Predictive performance, assessed as area under receiver-operating-characteristic curve (AUC, of the SVM (0.744 compared favourably with that of prognostic scores (original and adapted versions: 0.626–0.720; p < 0.01. The SVM also identified 9 out of 16 SICHs, as opposed to 1–5 using prognostic scores, assuming a 10% SICH frequency (p < 0.001. In summary, machine learning methods applied to acute stroke CT images offer automation, and potentially improved performance, for prediction of SICH following thrombolysis. Larger-scale cohorts, and incorporation of advanced imaging, should be tested with such methods.

  3. Biomarkers for predicting type 2 diabetes development-Can metabolomics improve on existing biomarkers?

    Directory of Open Access Journals (Sweden)

    Otto Savolainen

    Full Text Available The aim was to determine if metabolomics could be used to build a predictive model for type 2 diabetes (T2D risk that would improve prediction of T2D over current risk markers.Gas chromatography-tandem mass spectrometry metabolomics was used in a nested case-control study based on a screening sample of 64-year-old Caucasian women (n = 629. Candidate metabolic markers of T2D were identified in plasma obtained at baseline and the power to predict diabetes was tested in 69 incident cases occurring during 5.5 years follow-up. The metabolomics results were used as a standalone prediction model and in combination with established T2D predictive biomarkers for building eight T2D prediction models that were compared with each other based on their sensitivity and selectivity for predicting T2D.Established markers of T2D (impaired fasting glucose, impaired glucose tolerance, insulin resistance (HOMA, smoking, serum adiponectin alone, and in combination with metabolomics had the largest areas under the curve (AUC (0.794 (95% confidence interval [0.738-0.850] and 0.808 [0.749-0.867] respectively, with the standalone metabolomics model based on nine fasting plasma markers having a lower predictive power (0.657 [0.577-0.736]. Prediction based on non-blood based measures was 0.638 [0.565-0.711].Established measures of T2D risk remain the best predictor of T2D risk in this population. Additional markers detected using metabolomics are likely related to these measures as they did not enhance the overall prediction in a combined model.

  4. Early Change in Stroke Size Performs Best in Predicting Response to Therapy.

    Science.gov (United States)

    Simpkins, Alexis Nétis; Dias, Christian; Norato, Gina; Kim, Eunhee; Leigh, Richard

    2017-01-01

    Reliable imaging biomarkers of response to therapy in acute stroke are needed. The final infarct volume and percent of early reperfusion have been used for this purpose. Early fluctuation in stroke size is a recognized phenomenon, but its utility as a biomarker for response to therapy has not been established. This study examined the clinical relevance of early change in stroke volume and compared it with the final infarct volume and percent of early reperfusion in identifying early neurologic improvement (ENI). Acute stroke patients, enrolled between 2013 and 2014 with serial magnetic resonance imaging (MRI) scans (pretreatment baseline, 2 h post, and 24 h post), who received thrombolysis were included in the analysis. Early change in stroke volume, infarct volume at 24 h on diffusion, and percent of early reperfusion were calculated from the baseline and 2 h MRI scans were compared. ENI was defined as ≥4 point decrease in National Institutes of Health Stroke Scales within 24 h. Logistic regression models and receiver operator characteristics analysis were used to compare the efficacy of 3 imaging biomarkers. Serial MRIs of 58 acute stroke patients were analyzed. Early change in stroke volume was significantly associated with ENI by logistic regression analysis (OR 0.93, p = 0.048) and remained significant after controlling for stroke size and severity (OR 0.90, p = 0.032). Thus, for every 1 mL increase in stroke volume, there was a 10% decrease in the odds of ENI, while for every 1 mL decrease in stroke volume, there was a 10% increase in the odds of ENI. Neither infarct volume at 24 h nor percent of early reperfusion were significantly associated with ENI by logistic regression. Receiver-operator characteristic analysis identified early change in stroke volume as the only biomarker of the 3 that performed significantly different than chance (p = 0.03). Early fluctuations in stroke size may represent a more reliable biomarker for response to therapy than the

  5. In-hospital risk prediction for post-stroke depression: development and validation of the Post-stroke Depression Prediction Scale.

    Science.gov (United States)

    de Man-van Ginkel, Janneke M; Hafsteinsdóttir, Thóra B; Lindeman, Eline; Ettema, Roelof G A; Grobbee, Diederick E; Schuurmans, Marieke J

    2013-09-01

    The timely detection of post-stroke depression is complicated by a decreasing length of hospital stay. Therefore, the Post-stroke Depression Prediction Scale was developed and validated. The Post-stroke Depression Prediction Scale is a clinical prediction model for the early identification of stroke patients at increased risk for post-stroke depression. The study included 410 consecutive stroke patients who were able to communicate adequately. Predictors were collected within the first week after stroke. Between 6 to 8 weeks after stroke, major depressive disorder was diagnosed using the Composite International Diagnostic Interview. Multivariable logistic regression models were fitted. A bootstrap-backward selection process resulted in a reduced model. Performance of the model was expressed by discrimination, calibration, and accuracy. The model included a medical history of depression or other psychiatric disorders, hypertension, angina pectoris, and the Barthel Index item dressing. The model had acceptable discrimination, based on an area under the receiver operating characteristic curve of 0.78 (0.72-0.85), and calibration (P value of the U-statistic, 0.96). Transforming the model to an easy-to-use risk-assessment table, the lowest risk category (sum score, depression, which increased to 82% in the highest category (sum score, >21). The clinical prediction model enables clinicians to estimate the degree of the depression risk for an individual patient within the first week after stroke.

  6. Predictive Biomarkers of Radiation Sensitivity in Rectal Cancer

    Science.gov (United States)

    Tut, Thein Ga

    Colorectal cancer (CRC) is the third most common cancer in the world. Australia, New Zealand, Canada, the United States, and parts of Europe have the highest incidence rates of CRC. China, India, South America and parts of Africa have the lowest risk of CRC. CRC is the second most common cancer in both sexes in Australia. Even though the death rates from CRC involving the colon have diminished, those arising from the rectum have revealed no improvement. The greatest obstacle in attaining a complete surgical resection of large rectal cancers is the close anatomical relation to surrounding structures, as opposed to the free serosal surfaces enfolding the colon. To assist complete resection, pre-operative radiotherapy (DXT) can be applied, but the efficacy of ionising radiation (IR) is extremely variable between individual tumours. Reliable predictive marker/s that enable patient stratification in the application of this otherwise toxic therapy is still not available. Current therapeutic management of rectal cancer can be improved with the availability of better predictive and prognostic biomarkers. Proteins such as Plk1, gammaH2AX and MMR proteins (MSH2, MSH6, MLH1 and PMS2), involved in DNA damage response (DDR) pathway may be possible biomarkers for radiation response prediction and prognostication of rectal cancer. Serine/threonine protein kinase Plk1 is overexpressed in most of cancers including CRC. Plk1 functional activity is essential in the restoration of DNA damage following IR, which causes DNA double strand break (DSB). The earliest manifestation of this reparative process is histone H2AX phosphorylation at serine 139, leading to gammaH2AX. Colorectal normal mucosa showed the lowest level of gammaH2AX with gradually increasing levels in early adenoma and then in advanced malignant colorectal tissues, leading to the possibility that gammaH2AX may be a prospective biomarker in rectal cancer management. There are numerous publications regarding DNA mismatch

  7. Admission body temperature predicts long-term mortality after acute stroke

    DEFF Research Database (Denmark)

    Kammersgaard, L P; Jørgensen, H S; Rungby, Jørgen

    2002-01-01

    Body temperature is considered crucial in the management of acute stroke patients. Recently hypothermia applied as a therapy for stroke has been demonstrated to be feasible and safe in acute stroke patients. In the present study, we investigated the predictive role of admission body temperature...

  8. Phosphoproteomic biomarkers predicting histologic nonalcoholic steatohepatitis and fibrosis.

    Science.gov (United States)

    Younossi, Zobair M; Baranova, Ancha; Stepanova, Maria; Page, Sandra; Calvert, Valerie S; Afendy, Arian; Goodman, Zachary; Chandhoke, Vikas; Liotta, Lance; Petricoin, Emanuel

    2010-06-04

    The progression of nonalcoholic fatty liver disease (NAFLD) has been linked to deregulated exchange of the endocrine signaling between adipose and liver tissue. Proteomic assays for the phosphorylation events that characterize the activated or deactivated state of the kinase-driven signaling cascades in visceral adipose tissue (VAT) could shed light on the pathogenesis of nonalcoholic steatohepatitis (NASH) and related fibrosis. Reverse-phase protein microarrays (RPMA) were used to develop biomarkers for NASH and fibrosis using VAT collected from 167 NAFLD patients (training cohort, N = 117; testing cohort, N = 50). Three types of models were developed for NASH and advanced fibrosis: clinical models, proteomics models, and combination models. NASH was predicted by a model that included measurements of two components of the insulin signaling pathway: AKT kinase and insulin receptor substrate 1 (IRS1). The models for fibrosis were less reliable when predictions were based on phosphoproteomic, clinical, or the combination data. The best performing model relied on levels of the phosphorylation of GSK3 as well as on two subunits of cyclic AMP regulated protein kinase A (PKA). Phosphoproteomics technology could potentially be used to provide pathogenic information about NASH and NASH-related fibrosis. This information can lead to a clinically relevant diagnostic/prognostic biomarker for NASH.

  9. Predicting muscle forces of individuals with hemiparesis following stroke

    Directory of Open Access Journals (Sweden)

    Maladen Ryan

    2008-02-01

    Full Text Available Abstract Background Functional electrical stimulation (FES has been used to improve function in individuals with hemiparesis following stroke. An ideal functional electrical stimulation (FES system needs an accurate mathematical model capable of designing subject and task-specific stimulation patterns. Such a model was previously developed in our laboratory and shown to predict the isometric forces produced by the quadriceps femoris muscles of able-bodied individuals and individuals with spinal cord injury in response to a wide range of clinically relevant stimulation frequencies and patterns. The aim of this study was to test our isometric muscle force model on the quadriceps femoris, ankle dorsiflexor, and ankle plantar-flexor muscles of individuals with post-stroke hemiparesis. Methods Subjects were seated on a force dynamometer and isometric forces were measured in response to a range of stimulation frequencies (10 to 80-Hz and 3 different patterns. Subject-specific model parameter values were obtained by fitting the measured force responses from 2 stimulation trains. The model parameters thus obtained were then used to obtain predicted forces for a range of frequencies and patterns. Predicted and measured forces were compared using intra-class correlation coefficients, r2 values, and model error relative to the physiological error (variability of measured forces. Results Results showed excellent agreement between measured and predicted force-time responses (r2 >0.80, peak forces (ICCs>0.84, and force-time integrals (ICCs>0.82 for the quadriceps, dorsiflexor, and plantar-fexor muscles. The model error was within or below the +95% confidence interval of the physiological error for >88% comparisons between measured and predicted forces. Conclusion Our results show that the model has potential to be incorporated as a feed-forward controller for predicting subject-specific stimulation patterns during FES.

  10. Early prediction of outcome of activities of daily living after stroke: a systematic review

    OpenAIRE

    Veerbeek, J.M.; Kwakkel, G.; Wegen, van, E.E.H.; Ket, J.C.F.; Heijmans, M.W.

    2011-01-01

    BACKGROUND AND PURPOSE-Knowledge about robust and unbiased factors that predict outcome of activities of daily living (ADL) is paramount in stroke management. This review investigates the methodological quality of prognostic studies in the early poststroke phase for final ADL to identify variables that are predictive or not predictive for outcome of ADL after stroke. METHODS-PubMed, Ebsco/Cinahl and Embase were systematically searched for prognostic studies in which stroke patients were inclu...

  11. Prediction of Post-stroke Falls by Quantitative Assessment of Balance

    OpenAIRE

    Lee, Hyun Haeng; Jung, Se Hee

    2017-01-01

    Objective To evaluate characteristics of the postural instability in patients with stroke and to present a prediction model of post-stroke falls. Methods Patients with a first-ever stroke who had been evaluated by the Balance Master (BM) at post-stroke 3 months (?1 month) between August 2011 and December 2015 were enrolled. Parameters for the postural instability, such as the weight bearing asymmetry (WBA) and postural sway velocity (PSV), were obtained. The fall events in daily lives were as...

  12. Stroke and TIA survivors’ cognitive beliefs and affective responses regarding treatment and future stroke risk differentially predict medication adherence and categorised stroke risk

    Science.gov (United States)

    Phillips, L. Alison; Diefenbach, Michael A.; Abrams, Jessica; Horowitz, Carol R.

    2014-01-01

    Cognitive beliefs and affective responses to illness and treatment are known to independently predict health behaviours. The purpose of the current study is to assess the relative importance of four psychological domains – specifically, affective illness, cognitive illness, affective treatment and cognitive treatment – for predicting stroke and transient ischemic attack (TIA) survivors’ adherence to stroke prevention medications as well as their objective, categorised stroke risk. We assessed these domains among stroke/TIA survivors (n = 600), and conducted correlation and regression analyses with concurrent and prospective outcomes to determine the relative importance of each cognitive and affective domain for adherence and stroke risk. As hypothesised, patients’ affective treatment responses explained the greatest unique variance in baseline and six-month adherence reports (8 and 5%, respectively, of the variance in adherence, compared to 1–3% explained by other domains). Counter to hypotheses, patients’ cognitive illness beliefs explained the greatest unique variance in baseline and six-month objective categorised stroke risk (3 and 2%, respectively, compared to 0–1% explained by other domains). Results indicate that domain type (i.e. cognitive and affective) and domain referent (illness and treatment) may be differentially important for providers to assess when treating patients for stroke/TIA. More research is required to further distinguish between these domains and their relative importance for stroke prevention. PMID:25220292

  13. Stroke and TIA survivors' cognitive beliefs and affective responses regarding treatment and future stroke risk differentially predict medication adherence and categorised stroke risk.

    Science.gov (United States)

    Phillips, L Alison; Diefenbach, Michael A; Abrams, Jessica; Horowitz, Carol R

    2015-01-01

    Cognitive beliefs and affective responses to illness and treatment are known to independently predict health behaviours. The purpose of the current study is to assess the relative importance of four psychological domains - specifically, affective illness, cognitive illness, affective treatment and cognitive treatment - for predicting stroke and transient ischemic attack (TIA) survivors' adherence to stroke prevention medications as well as their objective, categorised stroke risk. We assessed these domains among stroke/TIA survivors (n = 600), and conducted correlation and regression analyses with concurrent and prospective outcomes to determine the relative importance of each cognitive and affective domain for adherence and stroke risk. As hypothesised, patients' affective treatment responses explained the greatest unique variance in baseline and six-month adherence reports (8 and 5%, respectively, of the variance in adherence, compared to 1-3% explained by other domains). Counter to hypotheses, patients' cognitive illness beliefs explained the greatest unique variance in baseline and six-month objective categorised stroke risk (3 and 2%, respectively, compared to 0-1% explained by other domains). Results indicate that domain type (i.e. cognitive and affective) and domain referent (illness and treatment) may be differentially important for providers to assess when treating patients for stroke/TIA. More research is required to further distinguish between these domains and their relative importance for stroke prevention.

  14. Prediction of Large Vessel Occlusions in Acute Stroke: National Institute of Health Stroke Scale Is Hard to Beat.

    Science.gov (United States)

    Vanacker, Peter; Heldner, Mirjam R; Amiguet, Michael; Faouzi, Mohamed; Cras, Patrick; Ntaios, George; Arnold, Marcel; Mattle, Heinrich P; Gralla, Jan; Fischer, Urs; Michel, Patrik

    2016-06-01

    Endovascular treatment for acute ischemic stroke with a large vessel occlusion was recently shown to be effective. We aimed to develop a score capable of predicting large vessel occlusion eligible for endovascular treatment in the early hospital management. Retrospective, cohort study. Two tertiary, Swiss stroke centers. Consecutive acute ischemic stroke patients (1,645 patients; Acute STroke Registry and Analysis of Lausanne registry), who had CT angiography within 6 and 12 hours of symptom onset, were categorized according to the occlusion site. Demographic and clinical information was used in logistic regression analysis to derive predictors of large vessel occlusion (defined as intracranial carotid, basilar, and M1 segment of middle cerebral artery occlusions). Based on logistic regression coefficients, an integer score was created and validated internally and externally (848 patients; Bernese Stroke Registry). None. Large vessel occlusions were present in 316 patients (21%) in the derivation and 566 (28%) in the external validation cohort. Five predictors added significantly to the score: National Institute of Health Stroke Scale at admission, hemineglect, female sex, atrial fibrillation, and no history of stroke and prestroke handicap (modified Rankin Scale score, < 2). Diagnostic accuracy in internal and external validation cohorts was excellent (area under the receiver operating characteristic curve, 0.84 both). The score performed slightly better than National Institute of Health Stroke Scale alone regarding prediction error (Wilcoxon signed rank test, p < 0.001) and regarding discriminatory power in derivation and pooled cohorts (area under the receiver operating characteristic curve, 0.81 vs 0.80; DeLong test, p = 0.02). Our score accurately predicts the presence of emergent large vessel occlusions, which are eligible for endovascular treatment. However, incorporation of additional demographic and historical information available on hospital arrival

  15. Biomarker kinetics in the prediction of VAP diagnosis: results from the BioVAP study

    NARCIS (Netherlands)

    Póvoa, Pedro; Martin-Loeches, Ignacio; Ramirez, Paula; Bos, Lieuwe D.; Esperatti, Mariano; Silvestre, Joana; Gili, Gisela; Goma, Gema; Berlanga, Eugenio; Espasa, Mateu; Gonçalves, Elsa; Torres, Antoni; Artigas, Antonio

    2016-01-01

    Prediction of diagnosis of ventilator-associated pneumonia (VAP) remains difficult. Our aim was to assess the value of biomarker kinetics in VAP prediction. We performed a prospective, multicenter, observational study to evaluate predictive accuracy of biomarker kinetics, namely C-reactive protein

  16. Validating the TeleStroke Mimic Score: A Prediction Rule for Identifying Stroke Mimics Evaluated Over Telestroke Networks.

    Science.gov (United States)

    Ali, Syed F; Hubert, Gordian J; Switzer, Jeffrey A; Majersik, Jennifer J; Backhaus, Roland; Shepard, L Wylie; Vedala, Kishore; Schwamm, Lee H

    2018-03-01

    Up to 30% of acute stroke evaluations are deemed stroke mimics, and these are common in telestroke as well. We recently published a risk prediction score for use during telestroke encounters to differentiate stroke mimics from ischemic cerebrovascular disease derived and validated in the Partners TeleStroke Network. Using data from 3 distinct US and European telestroke networks, we sought to externally validate the TeleStroke Mimic (TM) score in a broader population. We evaluated the TM score in 1930 telestroke consults from the University of Utah, Georgia Regents University, and the German TeleMedical Project for Integrative Stroke Care Network. We report the area under the curve in receiver-operating characteristic curve analysis with 95% confidence interval for our previously derived TM score in which lower TM scores correspond with a higher likelihood of being a stroke mimic. Based on final diagnosis at the end of the telestroke consultation, there were 630 of 1930 (32.6%) stroke mimics in the external validation cohort. All 6 variables included in the score were significantly different between patients with ischemic cerebrovascular disease versus stroke mimics. The TM score performed well (area under curve, 0.72; 95% confidence interval, 0.70-0.73; P mimic during telestroke consultation in these diverse cohorts was similar to its performance in our original cohort. Predictive decision-support tools like the TM score may help highlight key clinical differences between mimics and patients with stroke during complex, time-critical telestroke evaluations. © 2018 American Heart Association, Inc.

  17. Improved prediction of breast cancer outcome by identifying heterogeneous biomarkers.

    Science.gov (United States)

    Choi, Jonghwan; Park, Sanghyun; Yoon, Youngmi; Ahn, Jaegyoon

    2017-11-15

    Identification of genes that can be used to predict prognosis in patients with cancer is important in that it can lead to improved therapy, and can also promote our understanding of tumor progression on the molecular level. One of the common but fundamental problems that render identification of prognostic genes and prediction of cancer outcomes difficult is the heterogeneity of patient samples. To reduce the effect of sample heterogeneity, we clustered data samples using K-means algorithm and applied modified PageRank to functional interaction (FI) networks weighted using gene expression values of samples in each cluster. Hub genes among resulting prioritized genes were selected as biomarkers to predict the prognosis of samples. This process outperformed traditional feature selection methods as well as several network-based prognostic gene selection methods when applied to Random Forest. We were able to find many cluster-specific prognostic genes for each dataset. Functional study showed that distinct biological processes were enriched in each cluster, which seems to reflect different aspect of tumor progression or oncogenesis among distinct patient groups. Taken together, these results provide support for the hypothesis that our approach can effectively identify heterogeneous prognostic genes, and these are complementary to each other, improving prediction accuracy. https://github.com/mathcom/CPR. jgahn@inu.ac.kr. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  18. Predicting Age Using Neuroimaging: Innovative Brain Ageing Biomarkers.

    Science.gov (United States)

    Cole, James H; Franke, Katja

    2017-12-01

    The brain changes as we age and these changes are associated with functional deterioration and neurodegenerative disease. It is vital that we better understand individual differences in the brain ageing process; hence, techniques for making individualised predictions of brain ageing have been developed. We present evidence supporting the use of neuroimaging-based 'brain age' as a biomarker of an individual's brain health. Increasingly, research is showing how brain disease or poor physical health negatively impacts brain age. Importantly, recent evidence shows that having an 'older'-appearing brain relates to advanced physiological and cognitive ageing and the risk of mortality. We discuss controversies surrounding brain age and highlight emerging trends such as the use of multimodality neuroimaging and the employment of 'deep learning' methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Predictive cytogenetic biomarkers for colorectal neoplasia in medium risk patients.

    Science.gov (United States)

    Ionescu, E M; Nicolaie, T; Ionescu, M A; Becheanu, G; Andrei, F; Diculescu, M; Ciocirlan, M

    2015-01-01

    DNA damage and chromosomal alterations in peripheral lymphocytes parallels DNA mutations in tumor tissues. The aim of our study was to predict the presence of neoplastic colorectal lesions by specific biomarkers in "medium risk" individuals (age 50 to 75, with no personal or family of any colorectal neoplasia). We designed a prospective cohort observational study including patients undergoing diagnostic or opportunistic screening colonoscopy. Specific biomarkers were analyzed for each patient in peripheral lymphocytes - presence of micronuclei (MN), nucleoplasmic bridges (NPB) and the Nuclear Division Index (NDI) by the cytokinesis-blocked micronucleus assay (CBMN). Of 98 patients included, 57 were "medium risk" individuals. MN frequency and NPB presence were not significantly different in patients with neoplastic lesions compared to controls. In "medium risk" individuals, mean NDI was significantly lower for patients with any neoplastic lesions (adenomas and adenocarcinomas, AUROC 0.668, p 00.5), for patients with advanced neoplasia (advanced adenoma and adenocarcinoma, AUROC 0.636 p 0.029) as well as for patients with adenocarcinoma (AUROC 0.650, p 0.048), for each comparison with the rest of the population. For a cut-off of 1.8, in "medium risk" individuals, an NDI inferior to that value may predict any neoplastic lesion with a sensitivity of 97.7%, an advanced neoplastic lesion with a sensitivity of 97% and adenocarcinoma with a sensitivity of 94.4%. NDI score may have a role as a colorectal cancer-screening test in "medium risk" individuals. DNA = deoxyribonucleic acid; CRC = colorectal cancer; EU = European Union; WHO = World Health Organization; FOBT = fecal occult blood test; CBMN = cytokinesis-blocked micronucleus assay; MN = micronuclei; NPB = nucleoplasmic bridges; NDI = Nuclear Division Index; FAP = familial adenomatous polyposis; HNPCC = hereditary non-polypoid colorectal cancer; IBD = inflammatory bowel diseases; ROC = receiver operating

  20. Early functional MRI activation predicts motor outcome after ischemic stroke: a longitudinal, multimodal study.

    Science.gov (United States)

    Du, Juan; Yang, Fang; Zhang, Zhiqiang; Hu, Jingze; Xu, Qiang; Hu, Jianping; Zeng, Fanyong; Lu, Guangming; Liu, Xinfeng

    2018-05-15

    An accurate prediction of long term outcome after stroke is urgently required to provide early individualized neurorehabilitation. This study aimed to examine the added value of early neuroimaging measures and identify the best approaches for predicting motor outcome after stroke. This prospective study involved 34 first-ever ischemic stroke patients (time since stroke: 1-14 days) with upper limb impairment. All patients underwent baseline multimodal assessments that included clinical (age, motor impairment), neurophysiological (motor-evoked potentials, MEP) and neuroimaging (diffusion tensor imaging and motor task-based fMRI) measures, and also underwent reassessment 3 months after stroke. Bivariate analysis and multivariate linear regression models were used to predict the motor scores (Fugl-Meyer assessment, FMA) at 3 months post-stroke. With bivariate analysis, better motor outcome significantly correlated with (1) less initial motor impairment and disability, (2) less corticospinal tract injury, (3) the initial presence of MEPs, (4) stronger baseline motor fMRI activations. In multivariate analysis, incorporating neuroimaging data improved the predictive accuracy relative to only clinical and neurophysiological assessments. Baseline fMRI activation in SMA was an independent predictor of motor outcome after stroke. A multimodal model incorporating fMRI and clinical measures best predicted the motor outcome following stroke. fMRI measures obtained early after stroke provided independent prediction of long-term motor outcome.

  1. Predictive value of upper-limb accelerometry in acute stroke with hemiparesis

    NARCIS (Netherlands)

    Gebruers, Nick; Truijen, Steven; Engelborghs, Sebastiaan; De Deyn, Peter P.

    2013-01-01

    Few studies have investigated how well early activity measurements by accelerometers predict recovery after stroke. First, we assessed the predictive value of accelerometer-based measurements of upper-limb activity in patients with acute stroke with a hemiplegic arm. Second, we established the

  2. Predictive biomarker discovery through the parallel integration of clinical trial and functional genomics datasets

    DEFF Research Database (Denmark)

    Swanton, C.; Larkin, J.M.; Gerlinger, M.

    2010-01-01

    -cancer agents. The consortium focuses on the identification of reliable predictive biomarkers to approved agents with anti-angiogenic activity for which no reliable predictive biomarkers exist: sunitinib, a multi-targeted tyrosine kinase inhibitor and everolimus, a mammalian target of rapamycin (mTOR) pathway...

  3. Frontoparietal white matter integrity predicts haptic performance in chronic stroke

    Directory of Open Access Journals (Sweden)

    Alexandra L. Borstad

    2016-01-01

    Full Text Available Frontoparietal white matter supports information transfer between brain areas involved in complex haptic tasks such as somatosensory discrimination. The purpose of this study was to gain an understanding of the relationship between microstructural integrity of frontoparietal network white matter and haptic performance in persons with chronic stroke and to compare frontoparietal network integrity in participants with stroke and age matched control participants. Nineteen individuals with stroke and 16 controls participated. Haptic performance was quantified using the Hand Active Sensation Test (HASTe, an 18-item match-to-sample test of weight and texture discrimination. Three tesla MRI was used to obtain diffusion-weighted and high-resolution anatomical images of the whole brain. Probabilistic tractography was used to define 10 frontoparietal tracts total; Four intrahemispheric tracts measured bilaterally 1 thalamus to primary somatosensory cortex (T–S1, 2 thalamus to primary motor cortex (T–M1, 3 primary to secondary somatosensory cortex (S1 to SII and 4 primary somatosensory cortex to middle frontal gyrus (S1 to MFG and, 2 interhemispheric tracts; S1–S1 and precuneus interhemispheric. A control tract outside the network, the cuneus interhemispheric tract, was also examined. The diffusion metrics fractional anisotropy (FA, mean diffusivity (MD, axial (AD and radial diffusivity (RD were quantified for each tract. Diminished FA and elevated MD values are associated with poorer white matter integrity in chronic stroke. Nine of 10 tracts quantified in the frontoparietal network had diminished structural integrity poststroke compared to the controls. The precuneus interhemispheric tract was not significantly different between groups. Principle component analysis across all frontoparietal white matter tract MD values indicated a single factor explained 47% and 57% of the variance in tract mean diffusivity in stroke and control groups respectively

  4. Frontoparietal white matter integrity predicts haptic performance in chronic stroke.

    Science.gov (United States)

    Borstad, Alexandra L; Choi, Seongjin; Schmalbrock, Petra; Nichols-Larsen, Deborah S

    2016-01-01

    Frontoparietal white matter supports information transfer between brain areas involved in complex haptic tasks such as somatosensory discrimination. The purpose of this study was to gain an understanding of the relationship between microstructural integrity of frontoparietal network white matter and haptic performance in persons with chronic stroke and to compare frontoparietal network integrity in participants with stroke and age matched control participants. Nineteen individuals with stroke and 16 controls participated. Haptic performance was quantified using the Hand Active Sensation Test (HASTe), an 18-item match-to-sample test of weight and texture discrimination. Three tesla MRI was used to obtain diffusion-weighted and high-resolution anatomical images of the whole brain. Probabilistic tractography was used to define 10 frontoparietal tracts total; Four intrahemispheric tracts measured bilaterally 1) thalamus to primary somatosensory cortex (T-S1), 2) thalamus to primary motor cortex (T-M1), 3) primary to secondary somatosensory cortex (S1 to SII) and 4) primary somatosensory cortex to middle frontal gyrus (S1 to MFG) and, 2 interhemispheric tracts; S1-S1 and precuneus interhemispheric. A control tract outside the network, the cuneus interhemispheric tract, was also examined. The diffusion metrics fractional anisotropy (FA), mean diffusivity (MD), axial (AD) and radial diffusivity (RD) were quantified for each tract. Diminished FA and elevated MD values are associated with poorer white matter integrity in chronic stroke. Nine of 10 tracts quantified in the frontoparietal network had diminished structural integrity poststroke compared to the controls. The precuneus interhemispheric tract was not significantly different between groups. Principle component analysis across all frontoparietal white matter tract MD values indicated a single factor explained 47% and 57% of the variance in tract mean diffusivity in stroke and control groups respectively. Age

  5. Evaluation of a web based informatics system with data mining tools for predicting outcomes with quantitative imaging features in stroke rehabilitation clinical trials

    Science.gov (United States)

    Wang, Ximing; Kim, Bokkyu; Park, Ji Hoon; Wang, Erik; Forsyth, Sydney; Lim, Cody; Ravi, Ragini; Karibyan, Sarkis; Sanchez, Alexander; Liu, Brent

    2017-03-01

    Quantitative imaging biomarkers are used widely in clinical trials for tracking and evaluation of medical interventions. Previously, we have presented a web based informatics system utilizing quantitative imaging features for predicting outcomes in stroke rehabilitation clinical trials. The system integrates imaging features extraction tools and a web-based statistical analysis tool. The tools include a generalized linear mixed model(GLMM) that can investigate potential significance and correlation based on features extracted from clinical data and quantitative biomarkers. The imaging features extraction tools allow the user to collect imaging features and the GLMM module allows the user to select clinical data and imaging features such as stroke lesion characteristics from the database as regressors and regressands. This paper discusses the application scenario and evaluation results of the system in a stroke rehabilitation clinical trial. The system was utilized to manage clinical data and extract imaging biomarkers including stroke lesion volume, location and ventricle/brain ratio. The GLMM module was validated and the efficiency of data analysis was also evaluated.

  6. Stroke

    Science.gov (United States)

    ... doctor Preventing falls Stroke - discharge Swallowing problems Images Brain Carotid stenosis, x-ray of the left artery Carotid stenosis, x-ray of the right artery Stroke Brainstem function Cerebellum - function Circle of Willis Left cerebral hemisphere - ...

  7. The current status of biomarkers for predicting toxicity

    Science.gov (United States)

    Campion, Sarah; Aubrecht, Jiri; Boekelheide, Kim; Brewster, David W; Vaidya, Vishal S; Anderson, Linnea; Burt, Deborah; Dere, Edward; Hwang, Kathleen; Pacheco, Sara; Saikumar, Janani; Schomaker, Shelli; Sigman, Mark; Goodsaid, Federico

    2013-01-01

    Introduction There are significant rates of attrition in drug development. A number of compounds fail to progress past preclinical development due to limited tools that accurately monitor toxicity in preclinical studies and in the clinic. Research has focused on improving tools for the detection of organ-specific toxicity through the identification and characterization of biomarkers of toxicity. Areas covered This article reviews what we know about emerging biomarkers in toxicology, with a focus on the 2012 Northeast Society of Toxicology meeting titled ‘Translational Biomarkers in Toxicology.’ The areas covered in this meeting are summarized and include biomarkers of testicular injury and dysfunction, emerging biomarkers of kidney injury and translation of emerging biomarkers from preclinical species to human populations. The authors also provide a discussion about the biomarker qualification process and possible improvements to this process. Expert opinion There is currently a gap between the scientific work in the development and qualification of novel biomarkers for nonclinical drug safety assessment and how these biomarkers are actually used in drug safety assessment. A clear and efficient path to regulatory acceptance is needed so that breakthroughs in the biomarker toolkit for nonclinical drug safety assessment can be utilized to aid in the drug development process. PMID:23961847

  8. Immunohistochemistry for predictive biomarkers in non-small cell lung cancer.

    Science.gov (United States)

    Mino-Kenudson, Mari

    2017-10-01

    In the era of targeted therapy, predictive biomarker testing has become increasingly important for non-small cell lung cancer. Of multiple predictive biomarker testing methods, immunohistochemistry (IHC) is widely available and technically less challenging, can provide clinically meaningful results with a rapid turn-around-time and is more cost efficient than molecular platforms. In fact, several IHC assays for predictive biomarkers have already been implemented in routine pathology practice. In this review, we will discuss: (I) the details of anaplastic lymphoma kinase (ALK) and proto-oncogene tyrosine-protein kinase ROS (ROS1) IHC assays including the performance of multiple antibody clones, pros and cons of IHC platforms and various scoring systems to design an optimal algorithm for predictive biomarker testing; (II) issues associated with programmed death-ligand 1 (PD-L1) IHC assays; (III) appropriate pre-analytical tissue handling and selection of optimal tissue samples for predictive biomarker IHC.

  9. Early Dynamics of P-selectin and Interleukin 6 Predicts Outcomes in Ischemic Stroke

    DEFF Research Database (Denmark)

    Pusch, Gabriella; Debrabant, Birgit; Molnar, Tihamer

    2015-01-01

    with acute ischemic stroke (6, 24, and 72 hours after onset); (2) compared with 44 patients with asymptomatic severe (≥70%) carotid stenosis and 66 patients with Parkinson disease; and (3) we applied multiple regression methods, relating biological biomarkers combined with demographic data and comorbidities......BACKGROUND: Thromboinflammatory molecules connect the prothrombotic state, endothelial dysfunction, and systemic/local inflammation in the acute phase of ischemic stroke. METHODS: We prospectively investigated (1) serial changes in the levels of thromboinflammatory biomarkers in 76 patients...... hours were higher in patients with large-artery versus lacunar stroke. High concentration of IL-6, monocyte chemotactic protein 1, and S100B at 6 hours were associated with poststroke infections; high concentration of IL-6, S100B, and high-sensitivity C-reactive protein (hsCRP) correlated with death...

  10. A biomarker profile for predicting efficacy of cisplatin-vinorelbine therapy in malignant pleural mesothelioma

    DEFF Research Database (Denmark)

    Zimling, Zarah Glad; Sørensen, Jens Benn; Gerds, Thomas Alexander

    2012-01-01

    Malignant pleural mesothelioma (MPM) has a dismal prognosis. Treatment results may be improved by biomarker-directed therapy. We investigated the baseline expression and impact on outcome of predictive biomarkers ERCC1, BRCA1, and class III β-tubulin in a cohort of MPM patients treated with cispl......Malignant pleural mesothelioma (MPM) has a dismal prognosis. Treatment results may be improved by biomarker-directed therapy. We investigated the baseline expression and impact on outcome of predictive biomarkers ERCC1, BRCA1, and class III β-tubulin in a cohort of MPM patients treated...

  11. Stroke survivors' endorsement of a "stress belief model" of stroke prevention predicts control of risk factors for recurrent stroke.

    Science.gov (United States)

    Phillips, L Alison; Tuhrim, Stanley; Kronish, Ian M; Horowitz, Carol R

    2014-01-01

    Perceptions that stress causes and stress-reduction controls hypertension have been associated with poorer blood pressure (BP) control in hypertension populations. The current study investigated these "stress-model perceptions" in stroke survivors regarding prevention of recurrent stroke and the influence of these perceptions on patients' stroke risk factor control. Stroke and transient ischemic attack survivors (N=600) participated in an in-person interview in which they were asked about their beliefs regarding control of future stroke; BP and cholesterol were measured directly after the interview. Counter to expectations, patients who endorsed a "stress-model" but not a "medication-model" of stroke prevention were in better control of their stroke risk factors (BP and cholesterol) than those who endorsed a medication-model but not a stress-model of stroke prevention (OR for poor control=.54, Wald statistic=6.07, p=.01). This result was not explained by between group differences in patients' reported medication adherence. The results have implications for theory and practice, regarding the role of stress belief models and acute cardiac events, compared to chronic hypertension.

  12. Early Prediction and Outcome of Septic Encephalopathy in Acute Stroke Patients With Nosocomial Coma

    OpenAIRE

    Tong, Dao-Ming; Zhou, Ye-Ting; Wang, Guang-Sheng; Chen, Xiao-Dong; Yang, Tong-Hui

    2015-01-01

    Background Septic encephalopathy (SE) is the most common acute encephalopathy in ICU; however, little attention has been focused on risk of SE in the course of acute stroke. Our aim is to investigate the early prediction and outcome of SE in stroke patients with nosocomial coma (NC). Methods A retrospective cohort study was conducted in an ICU of the tertiary teaching hospital in China from January 2006 to December 2009. Ninety-four acute stroke patients with NC were grouped according to with...

  13. External Validation of the Prestroke Independence, Sex, Age, National Institutes of Health Stroke Scale Score for Predicting Pneumonia After Stroke Using Data From the China National Stroke Registry.

    Science.gov (United States)

    Zhang, Runhua; Ji, Ruijun; Pan, Yuesong; Jiang, Yong; Liu, Gaifen; Wang, Yilong; Wang, Yongjun

    2017-05-01

    Pneumonia is an important risk factor for mortality and morbidity after stroke. The Prestroke Independence, Sex, Age, National Institutes of Health Stroke Scale (ISAN) score was shown to be a useful tool for predicting stroke-associated pneumonia based on UK multicenter cohort study. We aimed to externally validate the score using data from the China National Stroke Registry (CNSR). Eligible patients with acute ischemic stroke (AIS) and intracerebral hemorrhage (ICH) in the CNSR from 2007 to 2008 were included. The area under the receiver operating characteristic (AUC) curve was used to evaluate discrimination. The Hosmer-Lemeshow goodness of fit test and Pearson correlation coefficient were performed to assess calibration of the model. A total of 19,333 patients (AIS = 14400; ICH = 4933) were included and the overall pneumonia rate was 12.7%. The AUC was .76 (95% confidence interval [CI]: .75-.78) for the subgroup of AIS and .70 (95% CI: .68-.72) for the subgroup of ICH. The Hosmer-Lemeshow test showed the ISAN score with the good calibration for AIS and ICH (P = .177 and .405, respectively). The plot of observed versus predicted pneumonia rates suggested higher correlation for patients with AIS than with ICH (Pearson correlation coefficient = .99 and .83, respectively). The ISAN score was a useful tool for predicting in-hospital pneumonia after acute stroke, especially for patients with AIS. Further validations need to be done in different populations. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  14. Breast cancer biomarkers predict weight loss after gastric bypass surgery

    Directory of Open Access Journals (Sweden)

    Sauter Edward R

    2012-01-01

    Full Text Available Abstract Background Obesity has long been associated with postmenopausal breast cancer risk and more recently with premenopausal breast cancer risk. We previously observed that nipple aspirate fluid (n levels of prostate specific antigen (PSA were associated with obesity. Serum (s levels of adiponectin are lower in women with higher body mass index (BMI and with breast cancer. We conducted a prospective study of obese women who underwent gastric bypass surgery to determine: 1 change in n- and s-adiponectin and nPSA after surgery and 2 if biomarker change is related to change in BMI. Samples (30-s, 28-n and BMI were obtained from women 0, 3, 6 and 12 months after surgery. Findings There was a significant increase after surgery in pre- but not postmenopausal women at all time points in s-adiponectin and at 3 and 6 months in n-adiponectin. Low n-PSA and high s-adiponectin values were highly correlated with decrease in BMI from baseline. Conclusions Adiponectin increases locally in the breast and systemically in premenopausal women after gastric bypass. s-adiponectin in pre- and nPSA in postmenopausal women correlated with greater weight loss. This study provides preliminary evidence for biologic markers to predict weight loss after gastric bypass surgery.

  15. Slower EEG alpha generation, synchronization and "flow"-possible biomarkers of cognitive impairment and neuropathology of minor stroke.

    Science.gov (United States)

    Petrovic, Jelena; Milosevic, Vuk; Zivkovic, Miroslava; Stojanov, Dragan; Milojkovic, Olga; Kalauzi, Aleksandar; Saponjic, Jasna

    2017-01-01

    transient phenomenon, the increased alpha intra-hemispheric synchronization, overlying the ipsi-lesional hemisphere, the increased alpha F3-F4 inter-hemispheric synchronization, the delayed alpha waves, and the newly established inter-hemispheric "alpha flow" within the frontal cortex, remained as a permanent consequence of the minor stroke. This newly established frontal inter-hemispheric "alpha flow" represented a permanent consequence of the "hidden" stroke neuropathology, despite the fact that cognitive impairment has been returned to the control values. All the detected permanent changes at the EEG level with no cognitive impairment after a minor stroke could be a way for the brain to compensate for the lesion and restore the lost function. Our study indicates slower EEG alpha generation, synchronization and "flow" as potential biomarkers of cognitive impairment onset and/or compensatory post-stroke re-organizational processes.

  16. Slower EEG alpha generation, synchronization and “flow”—possible biomarkers of cognitive impairment and neuropathology of minor stroke

    Directory of Open Access Journals (Sweden)

    Jelena Petrovic

    2017-09-01

    . Although the stroke induced slower alpha was a transient phenomenon, the increased alpha intra-hemispheric synchronization, overlying the ipsi-lesional hemisphere, the increased alpha F3–F4 inter-hemispheric synchronization, the delayed alpha waves, and the newly established inter-hemispheric “alpha flow” within the frontal cortex, remained as a permanent consequence of the minor stroke. This newly established frontal inter-hemispheric “alpha flow” represented a permanent consequence of the “hidden” stroke neuropathology, despite the fact that cognitive impairment has been returned to the control values. All the detected permanent changes at the EEG level with no cognitive impairment after a minor stroke could be a way for the brain to compensate for the lesion and restore the lost function. Discussion Our study indicates slower EEG alpha generation, synchronization and “flow” as potential biomarkers of cognitive impairment onset and/or compensatory post-stroke re-organizational processes.

  17. Integrative EEG biomarkers predict progression to Alzheimer's disease at the MCI stage

    Directory of Open Access Journals (Sweden)

    Simon-Shlomo ePoil

    2013-10-01

    Full Text Available Alzheimer's disease (AD is a devastating disorder of increasing prevalence in modern society. Mild cognitive impairment (MCI is considered a transitional stage between normal aging and AD; however, not all subjects with MCI progress to AD. Prediction of conversion to AD at an early stage would enable an earlier, and potentially more effective, treatment of AD. Electroencephalography (EEG biomarkers would provide a non-invasive and relatively cheap screening tool to predict conversion to AD; however, traditional EEG biomarkers have not been considered accurate enough to be useful in clinical practice. Here, we aim to combine the information from multiple EEG biomarkers into a diagnostic classification index in order to improve the accuracy of predicting conversion from MCI to AD within a two-year period. We followed 86 patients initially diagnosed with MCI for two years during which 25 patients converted to AD. We show that multiple EEG biomarkers mainly related to activity in the beta-frequency range (13–30 Hz can predict conversion from MCI to AD. Importantly, by integrating six EEG biomarkers into a diagnostic index using logistic regression the prediction improved compared with the classification using the individual biomarkers, with a sensitivity of 88% and specificity of 82%, compared with a sensitivity of 64% and specificity of 62% of the best individual biomarker in this index. In order to identify this diagnostic index we developed a data mining approach implemented in the Neurophysiological Biomarker Toolbox (http://www.nbtwiki.net/. We suggest that this approach can be used to identify optimal combinations of biomarkers (integrative biomarkers also in other modalities. Potentially, these integrative biomarkers could be more sensitive to disease progression and response to therapeutic intervention.

  18. Fusion of multiscale wavelet-based fractal analysis on retina image for stroke prediction.

    Science.gov (United States)

    Che Azemin, M Z; Kumar, Dinesh K; Wong, T Y; Wang, J J; Kawasaki, R; Mitchell, P; Arjunan, Sridhar P

    2010-01-01

    In this paper, we present a novel method of analyzing retinal vasculature using Fourier Fractal Dimension to extract the complexity of the retinal vasculature enhanced at different wavelet scales. Logistic regression was used as a fusion method to model the classifier for 5-year stroke prediction. The efficacy of this technique has been tested using standard pattern recognition performance evaluation, Receivers Operating Characteristics (ROC) analysis and medical prediction statistics, odds ratio. Stroke prediction model was developed using the proposed system.

  19. The role of novel biomarkers in predicting diabetic nephropathy: a review

    Directory of Open Access Journals (Sweden)

    Uwaezuoke SN

    2017-08-01

    Full Text Available Samuel N Uwaezuoke Pediatric Nephrology Firm, Department of Pediatrics, University of Nigeria Teaching Hospital, Ituku-Ozalla, Enugu, Nigeria Abstract: Diabetic nephropathy (DN is one of the microvascular complications of the kidney arising commonly from type 1 diabetes mellitus (T1DM, and occasionally from type 2 diabetes mellitus (T2DM. Microalbuminuria serves as an early indicator of DN risk and a predictor of its progression as well as cardiovascular disease risk in both T1DM and T2DM. Although microalbuminuria remains the gold standard for early detection of DN, it is not a sufficiently accurate predictor of DN risk due to some limitations. Thus, there is a paradigm shift to novel biomarkers which would help to predict DN risk early enough and possibly prevent the occurrence of end-stage kidney disease. These new biomarkers have been broadly classified into glomerular biomarkers, tubular biomarkers, biomarkers of inflammation, biomarkers of oxidative stress, and miscellaneous biomarkers which also include podocyte biomarkers, some of which are also considered as tubular and glomerular biomarkers. Although they are potentially useful for the evaluation of DN, current data still preclude the routine clinical use of majority of them. However, their validation using high-quality and large longitudinal studies is of paramount importance, as well as the subsequent development of a biomarker panel which can reliably predict and evaluate this renal microvascular disease. This paper aims to review the predictive role of these biomarkers in the evaluation of DN. Keywords: type 1 diabetes mellitus, renal microvascular complication, microalbuminuria, end-stage kidney disease, biomarker panel

  20. Biomarkers of World Trade Center Particulate Matter Exposure: Physiology of distal airway and blood biomarkers that predict FEV1 decline

    Science.gov (United States)

    Weiden, Michael D.; Kwon, Sophia; Caraher, Erin; Berger, Kenneth I.; Reibman, Joan; Rom, William N.; Prezant, David J.; Nolan, Anna

    2016-01-01

    Biomarkers can be important predictors of disease severity and progression. The intense exposure to particulates and other toxins from the destruction of the World Trade Center (WTC) overwhelmed the lung’s normal protective barriers. The Fire Department of New York (FDNY) cohort not only had baseline pre-exposure lung function measures but also had serum samples banked soon after their WTC exposure. This well phenotyped group of highly exposed first responders is an ideal cohort for biomarker discovery and eventual validation. Disease progression was heterogeneous in this group in that some individuals subsequently developed abnormal lung function while others recovered. Airflow obstruction predominated in WTC exposed patients who were symptomatic. Multiple independent disease pathways may cause this abnormal FEV1 after irritant exposure. WTC exposure activates one or more of these pathways causing abnormal FEV1 in an individual. Our hypothesis was that serum biomarkers expressed within 6 months after World Trade Center (WTC) exposure reflect active disease pathways and predict subsequent development or protection from abnormal FEV1predictive biomarkers of WTC-LI. We have identified biomarkers of Inflammation, metabolic derangement, protease/antiprotease balance and vascular injury expressed in serum within 6 months of WTC exposure that were predictive of their FEV1 up to 7 years after their WTC exposure. Predicting future risk of airway injury after particulate exposures can focus monitoring and early treatment on a subset of patients in greatest need of these services. PMID:26024341

  1. Prediction of Post-stroke Falls by Quantitative Assessment of Balance.

    Science.gov (United States)

    Lee, Hyun Haeng; Jung, Se Hee

    2017-06-01

    To evaluate characteristics of the postural instability in patients with stroke and to present a prediction model of post-stroke falls. Patients with a first-ever stroke who had been evaluated by the Balance Master (BM) at post-stroke 3 months (±1 month) between August 2011 and December 2015 were enrolled. Parameters for the postural instability, such as the weight bearing asymmetry (WBA) and postural sway velocity (PSV), were obtained. The fall events in daily lives were assessed via structured telephone interview with a fall related questionnaire. A total of 71 patients (45 men; 45 with ischemic stroke) were enrolled in this study. All subjects underwent BM evaluation at 3.03±0.40 months after stroke. The mean WBA was 17.18%±13.10% and mean PSV (measured as °/s) were noted as 0.66±0.37 (eyes-open on firm surface), 0.89±0.75 (eyes-closed on firm surface), 1.45±1.09 (eyes-open on soft surface), and 3.10±1.76 (eyes-closed on soft surface). A prediction model of post-stroke falls was drawn by multiple logistic regression analysis as follows: Risk of post-stroke falls = -2.848 + 1.878 x (PSV ECSS ) + 0.154 x (age=1 if age≥65; age=0 if agerisk of post-stroke falls.

  2. Added value of CT perfusion compared to CT angiography in predicting clinical outcomes of stroke patients treated with mechanical thrombectomy

    Energy Technology Data Exchange (ETDEWEB)

    Tsogkas, Ioannis; Knauth, Michael; Schregel, Katharina; Behme, Daniel; Psychogios, Marios Nikos [University Medicine Goettingen, Department of Neuroradiology, Goettingen (Germany); Wasser, Katrin; Maier, Ilko; Liman, Jan [University Medicine Goettingen, Department of Neurology, Goettingen (Germany)

    2016-11-15

    CTP images analyzed with the Alberta stroke program early CT scale (ASPECTS) have been shown to be optimal predictors of clinical outcome. In this study we compared two biomarkers, the cerebral blood volume (CBV)-ASPECTS and the CTA-ASPECTS as predictors of clinical outcome after thrombectomy. Stroke patients with thrombosis of the M1 segment of the middle cerebral artery were included in our study. All patients underwent initial multimodal CT with CTP and CTA on a modern CT scanner. Treatment consisted of full dose intravenous tissue plasminogen activator, when applicable, and mechanical thrombectomy. Three neuroradiologists separately scored CTP and CTA images with the ASPECTS score. Sixty-five patients were included. Median baseline CBV-ASPECTS and CTA-ASPECTS for patients with favourable clinical outcome at follow-up were 8 [interquartile range (IQR) 8-9 and 7-9 respectively]. Patients with poor clinical outcome showed a median baseline CBV-ASPECTS of 6 (IQR 5-8, P < 0.0001) and a median baseline CTA-ASPECTS of 7 (IQR 7-8, P = 0.18). Using CBV-ASPECTS and CTA-ASPECTS raters predicted futile reperfusions in 96 % and 56 % of the cases, respectively. CBV-ASPECTS is a significant predictor of clinical outcome in patients with acute ischemic stroke treated with mechanical thrombectomy. (orig.)

  3. Can diffusion tensor imaging predict the functional outcome of supra-tentorial stroke?

    International Nuclear Information System (INIS)

    Maeda, Takahiro; Ishizaki, Ken-ichi; Yura, Shigeki

    2005-01-01

    We used diffusion tensor imaging (DTI) to assess wallerian degeneration of the pyramidal tract after the onset of supra-tentorial stroke, and correlation of the extent of Wallerian degeneration with the motor function at 3 months after stroke. Twenty eight patients with supra-tentorial acute stroke were examined, two weeks and one month after stroke by DTI. We measured fractional anisotropy (FA) of affected side/unaffected side (FA ratio) in the cerebral peduncle. We used modified Rankin Scale (mRS) for assessment of motor function at 3 months after stroke. FA ratio was significantly reduced at 2 weeks after stroke (0.833±0.146) compared to on admission (0.979±0.0797). But no significant change of FA ratio was seen between two weeks and one month after stroke in 7 cases examined (0.758±0.183 vs. 0.754±0.183). In all patients in whom the FA ratio was under 0.8 at 2 weeks after stroke, motor function showed poor recovery (mRS 4 and 5) at 3 months after stroke. When FA ratio was over 0.8 at 2 weeks after stroke, motor function at 3 months after stroke showed good recovery (mRS 0 to 3) expect for three elderly patients. With the use of DTI, Wallerian degeneration could be detected in the corticospinal tracts at midbrain level during the early phase of supra-tentorial stroke. We conclude that DTI may be useful for early prediction of motor function prognosis in patients with supra-tentorial acute stroke. (author)

  4. Artificial neural network prediction of ischemic tissue fate in acute stroke imaging

    Science.gov (United States)

    Huang, Shiliang; Shen, Qiang; Duong, Timothy Q

    2010-01-01

    Multimodal magnetic resonance imaging of acute stroke provides predictive value that can be used to guide stroke therapy. A flexible artificial neural network (ANN) algorithm was developed and applied to predict ischemic tissue fate on three stroke groups: 30-, 60-minute, and permanent middle cerebral artery occlusion in rats. Cerebral blood flow (CBF), apparent diffusion coefficient (ADC), and spin–spin relaxation time constant (T2) were acquired during the acute phase up to 3 hours and again at 24 hours followed by histology. Infarct was predicted on a pixel-by-pixel basis using only acute (30-minute) stroke data. In addition, neighboring pixel information and infarction incidence were also incorporated into the ANN model to improve prediction accuracy. Receiver-operating characteristic analysis was used to quantify prediction accuracy. The major findings were the following: (1) CBF alone poorly predicted the final infarct across three experimental groups; (2) ADC alone adequately predicted the infarct; (3) CBF+ADC improved the prediction accuracy; (4) inclusion of neighboring pixel information and infarction incidence further improved the prediction accuracy; and (5) prediction was more accurate for permanent occlusion, followed by 60- and 30-minute occlusion. The ANN predictive model could thus provide a flexible and objective framework for clinicians to evaluate stroke treatment options on an individual patient basis. PMID:20424631

  5. Serum C-Reactive Protein Level as a Biomarker for Differentiation of Ischemic from Hemorrhagic Stroke

    Directory of Open Access Journals (Sweden)

    Seyed Ali Roudbary

    2011-03-01

    Full Text Available Cerebrovascular accidents rank first in the frequency and importance among all neurological disease. Although a number of studies had shown increased level of the high sensitive C-reactive protein (hs-CRP in patients with ischemic stroke, the association of increased hs-CRP with various type of stroke especially the assessment hs-CRP level in ischemic and hemorrhagic stroke have not been investigated. In the present study, we assessed the concentration of hs-CRP in patients with documented ischemic and hemorrhagic stroke in the first 24 hours of the onset of symptoms. Thirty-two patients with Ischemic and hemorrhagic stroke were evaluated at neurology department of Poursina Hospital. The presence of baseline vascular risk factors, including hypertension, diabetes mellitus, hypercholesterolemia, obesity, and smoking, was determined. The blood samples were then collected and routine hematology and biochemistry tests were done. hs-CRP levels were determined using a highly sensitive immunonephelometric method. In this cross sectional study, the age of patient varied from 45-85 years (Mean 70.9  9.4. Serum level of hs-CRP in Ischemic patients were 18.92  11.28 and in hemorrhagic group was 2.65  1.7. This relationship was statistically significant (P<0.0001. It might be concluded that hs-CRP might be considered as a usefully adjunct method for the initial diagnosis of the type of stroke.

  6. Predictive value of stroke discharge diagnoses in the Danish National Patient Register.

    Science.gov (United States)

    Lühdorf, Pernille; Overvad, Kim; Schmidt, Erik B; Johnsen, Søren P; Bach, Flemming W

    2017-08-01

    To determine the positive predictive values for stroke discharge diagnoses, including subarachnoidal haemorrhage, intracerebral haemorrhage and cerebral infarction in the Danish National Patient Register. Participants in the Danish cohort study Diet, Cancer and Health with a stroke discharge diagnosis in the National Patient Register between 1993 and 2009 were identified and their medical records were retrieved for validation of the diagnoses. A total of 3326 records of possible cases of stroke were reviewed. The overall positive predictive value for stroke was 69.3% (95% confidence interval (CI) 67.8-70.9%). The predictive values differed according to hospital characteristics, with the highest predictive value of 87.8% (95% CI 85.5-90.1%) found in departments of neurology and the lowest predictive value of 43.0% (95% CI 37.6-48.5%) found in outpatient clinics. The overall stroke diagnosis in the Danish National Patient Register had a limited predictive value. We therefore recommend the critical use of non-validated register data for research on stroke. The possibility of optimising the predictive values based on more advanced algorithms should be considered.

  7. The Stroke Assessment of Fall Risk (SAFR): predictive validity in inpatient stroke rehabilitation

    Science.gov (United States)

    Breisinger, Terry P; Skidmore, Elizabeth R; Niyonkuru, Christian; Terhorst, Lauren; Campbell, Grace B

    2014-01-01

    Objective To evaluate relative accuracy of a newly developed Stroke Assessment of Fall Risk (SAFR) for classifying fallers and non-fallers, compared with a health system fall risk screening tool, the Fall Harm Risk Screen. Design and setting Prospective quality improvement study conducted at an inpatient stroke rehabilitation unit at a large urban university hospital. Participants Patients admitted for inpatient stroke rehabilitation (N = 419) with imaging or clinical evidence of ischemic or hemorrhagic stroke, between 1 August 2009 and 31 July 2010. Interventions Not applicable. Main outcome measure(s) Sensitivity, specificity, and area under the curve for Receiver Operating Characteristic Curves of both scales’ classifications, based on fall risk score completed upon admission to inpatient stroke rehabilitation. Results A total of 68 (16%) participants fell at least once. The SAFR was significantly more accurate than the Fall Harm Risk Screen (p stroke rehabilitation patients. While the SAFR improves upon the accuracy of a general assessment tool, additional refinement may be warranted. PMID:24849795

  8. Developing risk prediction models for kidney injury and assessing incremental value for novel biomarkers.

    Science.gov (United States)

    Kerr, Kathleen F; Meisner, Allison; Thiessen-Philbrook, Heather; Coca, Steven G; Parikh, Chirag R

    2014-08-07

    The field of nephrology is actively involved in developing biomarkers and improving models for predicting patients' risks of AKI and CKD and their outcomes. However, some important aspects of evaluating biomarkers and risk models are not widely appreciated, and statistical methods are still evolving. This review describes some of the most important statistical concepts for this area of research and identifies common pitfalls. Particular attention is paid to metrics proposed within the last 5 years for quantifying the incremental predictive value of a new biomarker. Copyright © 2014 by the American Society of Nephrology.

  9. ASTRAL, DRAGON and SEDAN scores predict stroke outcome more accurately than physicians.

    Science.gov (United States)

    Ntaios, G; Gioulekas, F; Papavasileiou, V; Strbian, D; Michel, P

    2016-11-01

    ASTRAL, SEDAN and DRAGON scores are three well-validated scores for stroke outcome prediction. Whether these scores predict stroke outcome more accurately compared with physicians interested in stroke was investigated. Physicians interested in stroke were invited to an online anonymous survey to provide outcome estimates in randomly allocated structured scenarios of recent real-life stroke patients. Their estimates were compared to scores' predictions in the same scenarios. An estimate was considered accurate if it was within 95% confidence intervals of actual outcome. In all, 244 participants from 32 different countries responded assessing 720 real scenarios and 2636 outcomes. The majority of physicians' estimates were inaccurate (1422/2636, 53.9%). 400 (56.8%) of physicians' estimates about the percentage probability of 3-month modified Rankin score (mRS) > 2 were accurate compared with 609 (86.5%) of ASTRAL score estimates (P DRAGON score estimates (P DRAGON score estimates (P DRAGON and SEDAN scores predict outcome of acute ischaemic stroke patients with higher accuracy compared to physicians interested in stroke. © 2016 EAN.

  10. Developing and validating a predictive model for stroke progression

    OpenAIRE

    Craig, L.E.; Wu, Olivia; Gilmour, H.; Barber, M.; Langhorne, P.

    2011-01-01

    Background: Progression is believed to be a common and important complication in acute stroke, and has been associated with increased mortality and morbidity. Reliable identification of predictors of early neurological deterioration could potentially benefit routine clinical care. The aim of this study was to identify predictors of early stroke progression using two independent patient cohorts. \\ud \\ud Methods: Two patient cohorts were used for this study – the first cohort formed the trainin...

  11. Transthyretin Concentrations in Acute Stroke Patients Predict Convalescent Rehabilitation.

    Science.gov (United States)

    Isono, Naofumi; Imamura, Yuki; Ohmura, Keiko; Ueda, Norihide; Kawabata, Shinji; Furuse, Motomasa; Kuroiwa, Toshihiko

    2017-06-01

    For stroke patients, intensive nutritional management is an important and effective component of inpatient rehabilitation. Accordingly, acute care hospitals must detect and prevent malnutrition at an early stage. Blood transthyretin levels are widely used as a nutritional monitoring index in critically ill patients. Here, we had analyzed the relationship between the transthyretin levels during the acute phase and Functional Independence Measure in stroke patients undergoing convalescent rehabilitation. We investigated 117 patients who were admitted to our hospital with acute ischemic or hemorrhagic stroke from February 2013 to October 2015 and subsequently transferred to convalescent hospitals after receiving acute treatment. Transthyretin concentrations were evaluated at 3 time points as follows: at admission, and 5 and 10 days after admission. After categorizing patients into 3 groups according to the minimum transthyretin level, we analyzed the association between transthyretin and Functional Independence Measure. In our patients, transthyretin levels decreased during the first 5 days after admission and recovered slightly during the subsequent 5 days. Notably, Functional Independence Measure efficiency was significantly associated with the decrease in transthyretin levels during the 5 days after admission. Patients with lower transthyretin levels had poorer Functional Independence Measure outcomes and tended not to be discharged to their own homes. A minimal transthyretin concentration (stroke patients undergoing convalescent rehabilitation. In particular, an early decrease in transthyretin levels suggests restricted rehabilitation efficiency. Accordingly, transthyretin levels should be monitored in acute stroke patients to indicate mid-term rehabilitation prospects. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  12. GRECOS Project (Genotyping Recurrence Risk of Stroke): The Use of Genetics to Predict the Vascular Recurrence After Stroke.

    Science.gov (United States)

    Fernández-Cadenas, Israel; Mendióroz, Maite; Giralt, Dolors; Nafria, Cristina; Garcia, Elena; Carrera, Caty; Gallego-Fabrega, Cristina; Domingues-Montanari, Sophie; Delgado, Pilar; Ribó, Marc; Castellanos, Mar; Martínez, Sergi; Freijo, Marimar; Jiménez-Conde, Jordi; Rubiera, Marta; Alvarez-Sabín, José; Molina, Carlos A; Font, Maria Angels; Grau Olivares, Marta; Palomeras, Ernest; Perez de la Ossa, Natalia; Martinez-Zabaleta, Maite; Masjuan, Jaime; Moniche, Francisco; Canovas, David; Piñana, Carlos; Purroy, Francisco; Cocho, Dolores; Navas, Inma; Tejero, Carlos; Aymerich, Nuria; Cullell, Natalia; Muiño, Elena; Serena, Joaquín; Rubio, Francisco; Davalos, Antoni; Roquer, Jaume; Arenillas, Juan Francisco; Martí-Fábregas, Joan; Keene, Keith; Chen, Wei-Min; Worrall, Bradford; Sale, Michele; Arboix, Adrià; Krupinski, Jerzy; Montaner, Joan

    2017-05-01

    Vascular recurrence occurs in 11% of patients during the first year after ischemic stroke (IS) or transient ischemic attack. Clinical scores do not predict the whole vascular recurrence risk; therefore, we aimed to find genetic variants associated with recurrence that might improve the clinical predictive models in IS. We analyzed 256 polymorphisms from 115 candidate genes in 3 patient cohorts comprising 4482 IS or transient ischemic attack patients. The discovery cohort was prospectively recruited and included 1494 patients, 6.2% of them developed a new IS during the first year of follow-up. Replication analysis was performed in 2988 patients using SNPlex or HumanOmni1-Quad technology. We generated a predictive model using Cox regression (GRECOS score [Genotyping Reurrence Risk of Stroke]) and generated risk groups using a classification tree method. The analyses revealed that rs1800801 in the MGP gene (hazard ratio, 1.33; P =9×10 - 03 ), a gene related to artery calcification, was associated with new IS during the first year of follow-up. This polymorphism was replicated in a Spanish cohort (n=1.305); however, it was not significantly associated in a North American cohort (n=1.683). The GRECOS score predicted new IS ( P =3.2×10 - 09 ) and could classify patients, from low risk of stroke recurrence (1.9%) to high risk (12.6%). Moreover, the addition of genetic risk factors to the GRECOS score improves the prediction compared with previous Stroke Prognosis Instrument-II score ( P =0.03). The use of genetics could be useful to estimate vascular recurrence risk after IS. Genetic variability in the MGP gene was associated with vascular recurrence in the Spanish population. © 2017 American Heart Association, Inc.

  13. EEG-based motor network biomarkers for identifying target patients with stroke for upper limb rehabilitation and its construct validity.

    Directory of Open Access Journals (Sweden)

    Chun-Chuan Chen

    Full Text Available Rehabilitation is the main therapeutic approach for reducing poststroke functional deficits in the affected upper limb; however, significant between-patient variability in rehabilitation efficacy indicates the need to target patients who are likely to have clinically significant improvement after treatment. Many studies have determined robust predictors of recovery and treatment gains and yielded many great results using linear approachs. Evidence has emerged that the nonlinearity is a crucial aspect to study the inter-areal communication in human brains and abnormality of oscillatory activities in the motor system is linked to the pathological states. In this study, we hypothesized that combinations of linear and nonlinear (cross-frequency network connectivity parameters are favourable biomarkers for stratifying patients for upper limb rehabilitation with increased accuracy. We identified the biomarkers by using 37 prerehabilitation electroencephalogram (EEG datasets during a movement task through effective connectivity and logistic regression analyses. The predictive power of these biomarkers was then tested by using 16 independent datasets (i.e. construct validation. In addition, 14 right handed healthy subjects were also enrolled for comparisons. The result shows that the beta plus gamma or theta network features provided the best classification accuracy of 92%. The predictive value and the sensitivity of these biomarkers were 81.3% and 90.9%, respectively. Subcortical lesion, the time poststroke and initial Wolf Motor Function Test (WMFT score were identified as the most significant clinical variables affecting the classification accuracy of this predictive model. Moreover, 12 of 14 normal controls were classified as having favourable recovery. In conclusion, EEG-based linear and nonlinear motor network biomarkers are robust and can help clinical decision making.

  14. Biomarkers Related to Carotid Intima-Media Thickness and Plaques in Long-Term Survivors of Ischemic Stroke.

    Science.gov (United States)

    Waje-Andreassen, Ulrike; Naess, Halvor; Thomassen, Lars; Maroy, Tove Helene; Mazengia, Kibret Yimer; Eide, Geir Egil; Vedeler, Christian Alexander

    2015-08-01

    Lifestyle risk factors, inflammation and genetics play a role in the development of atherosclerosis. We therefore studied Fc gamma receptor (FcγR) polymorphisms, interleukin (IL)-10 polymorphisms and other biomarkers related to carotid intima-media thickness (cIMT) in patients with ischemic stroke at a young age. Patients were evaluated 12 years after stroke occurrence. Patients (n = 232) 49 years of age or younger with an index stroke between 1988 and 1997 were retrospectively selected. Blood samples were taken at a first follow-up 6 years after the stroke. At a second follow-up, additional arterial events were registered for 140 patients, new blood samples were taken, and measurements of cIMT and blood pressure (BP) were performed. Unadjusted logistic regression analysis showed that cIMT ≥1 mm was associated with age, male gender, additional arterial events, BP, cholesterol, sedimentation rate, haemoglobin, triglycerides, creatinine, glycolysed haemoglobin (HbA1c) and FcγRIIIB-NaII/NaII. Adjusted backward stepwise logistic regression showed significance for age (odds ratio (OR) 1.13, 95% confidence interval (CI) 1.04 to1.23, p = 0.003), male gender (OR 4.07, 95% CI 1.15 to 14.5, p = 0.030), HbA1c (OR 6.65, 95% CI 1.21 to 36.5, p = 0.029) and FcγRIIIB-NaII/NaII (OR 3.94, 95% CI 1.08 to 14.3, p = 0.037). In this long-term follow-up study of patients with ischemic stroke at a young age, FcγRIIIB-NaII/NaII was identified as a possible contributing factor for cIMT ≥1 mm together with known risk factors, such as age, male gender, systolic BP, additional arterial events and HbA1c.

  15. Use of APACHE II and SAPS II to predict mortality for hemorrhagic and ischemic stroke patients.

    Science.gov (United States)

    Moon, Byeong Hoo; Park, Sang Kyu; Jang, Dong Kyu; Jang, Kyoung Sool; Kim, Jong Tae; Han, Yong Min

    2015-01-01

    We studied the applicability of the Acute Physiology and Chronic Health Evaluation II (APACHE II) and Simplified Acute Physiology Score II (SAPS II) in patients admitted to the intensive care unit (ICU) with acute stroke and compared the results with the Glasgow Coma Scale (GCS) and National Institutes of Health Stroke Scale (NIHSS). We also conducted a comparative study of accuracy for predicting hemorrhagic and ischemic stroke mortality. Between January 2011 and December 2012, ischemic or hemorrhagic stroke patients admitted to the ICU were included in the study. APACHE II and SAPS II-predicted mortalities were compared using a calibration curve, the Hosmer-Lemeshow goodness-of-fit test, and the receiver operating characteristic (ROC) curve, and the results were compared with the GCS and NIHSS. Overall 498 patients were included in this study. The observed mortality was 26.3%, whereas APACHE II and SAPS II-predicted mortalities were 35.12% and 35.34%, respectively. The mean GCS and NIHSS scores were 9.43 and 21.63, respectively. The calibration curve was close to the line of perfect prediction. The ROC curve showed a slightly better prediction of mortality for APACHE II in hemorrhagic stroke patients and SAPS II in ischemic stroke patients. The GCS and NIHSS were inferior in predicting mortality in both patient groups. Although both the APACHE II and SAPS II systems can be used to measure performance in the neurosurgical ICU setting, the accuracy of APACHE II in hemorrhagic stroke patients and SAPS II in ischemic stroke patients was superior. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Early warning score predicts acute mortality in stroke patients

    DEFF Research Database (Denmark)

    Liljehult, J; Christensen, Thomas

    2016-01-01

    OBJECTIVES: Clinical deterioration and death among patients with acute stroke are often preceded by detrimental changes in physiological parameters. Systematic and effective tools to identify patients at risk of deterioration early enough to intervene are therefore needed. The aim of the study wa...... tool for identifying patients at risk of dying after acute stroke. Readily available physiological parameters are converted to a single score, which can guide both nurses and physicians in clinical decision making and resource allocation.......OBJECTIVES: Clinical deterioration and death among patients with acute stroke are often preceded by detrimental changes in physiological parameters. Systematic and effective tools to identify patients at risk of deterioration early enough to intervene are therefore needed. The aim of the study...

  17. Early prediction and outcome of septic encephalopathy in acute stroke patients with nosocomial coma.

    Science.gov (United States)

    Tong, Dao-Ming; Zhou, Ye-Ting; Wang, Guang-Sheng; Chen, Xiao-Dong; Yang, Tong-Hui

    2015-07-01

    Septic encephalopathy (SE) is the most common acute encephalopathy in ICU; however, little attention has been focused on risk of SE in the course of acute stroke. Our aim is to investigate the early prediction and outcome of SE in stroke patients with nosocomial coma (NC). A retrospective cohort study was conducted in an ICU of the tertiary teaching hospital in China from January 2006 to December 2009. Ninety-four acute stroke patients with NC were grouped according to with or without SE. Risk factors for patients with SE were compared with those without SE by univariate and multivariate analysis. Of 94 stroke patients with NC, 46 (49%) had NC with SE and 48 (51%) had NC without SE. The onset-to-NC time was significant later in stroke patients with SE than those without SE (P stroke patients with SE was higher than those without SE (76.1% vs. 45.8%, P = 0.003). High fever and severe SIRS are two early predictors of stroke patients with SE, and survival rates were worse in stroke patients with SE than those without SE.

  18. Strategies to design clinical studies to identify predictive biomarkers in cancer research.

    Science.gov (United States)

    Perez-Gracia, Jose Luis; Sanmamed, Miguel F; Bosch, Ana; Patiño-Garcia, Ana; Schalper, Kurt A; Segura, Victor; Bellmunt, Joaquim; Tabernero, Josep; Sweeney, Christopher J; Choueiri, Toni K; Martín, Miguel; Fusco, Juan Pablo; Rodriguez-Ruiz, Maria Esperanza; Calvo, Alfonso; Prior, Celia; Paz-Ares, Luis; Pio, Ruben; Gonzalez-Billalabeitia, Enrique; Gonzalez Hernandez, Alvaro; Páez, David; Piulats, Jose María; Gurpide, Alfonso; Andueza, Mapi; de Velasco, Guillermo; Pazo, Roberto; Grande, Enrique; Nicolas, Pilar; Abad-Santos, Francisco; Garcia-Donas, Jesus; Castellano, Daniel; Pajares, María J; Suarez, Cristina; Colomer, Ramon; Montuenga, Luis M; Melero, Ignacio

    2017-02-01

    The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  19. Rehabilitation after stroke: predictive power of Barthel Index versus a cognitive and a motor index

    DEFF Research Database (Denmark)

    Engberg, A; Bentzen, L; Garde, B

    1995-01-01

    The aim of the present study was to investigate the predictive power of ratings of Barthel Index at Day 40 post stroke, compared with and/or combined with simultaneous ratings from a mobility scale (EG motor index) and a rather simple cognitive test scale (CT50). The parameter to be individually...... predicted was the need for special living facilities and support at discharge from a rehabilitation hospital, as well as six months later; 53 stroke patients with age median 68 years were included in this prospective study. It was shown that a combination of Barthel Index and CT50 had a stronger predictive...

  20. Biomarkers and insulin sensitivity in women with Polycystic Ovary Syndrome: Characteristics and predictive capacity.

    Science.gov (United States)

    Cassar, Samantha; Teede, Helena J; Harrison, Cheryce L; Joham, Anju E; Moran, Lisa J; Stepto, Nigel K

    2015-07-01

    Polycystic ovary syndrome (PCOS) is a common endocrine disorder associated with metabolic complications. Metabolic biomarkers with roles in obesity, glycaemic control and lipid metabolism are potentially relevant in PCOS. The aim was to investigate metabolic biomarkers in lean and overweight women with and without PCOS and to determine whether any biomarker was able to predict insulin resistance in PCOS. Cross-sectional study. Eighty-four women (22 overweight and 22 lean women with PCOS, 18 overweight and 22 lean women without PCOS) were recruited from the community and categorized based on PCOS and BMI status. Primary outcomes were metabolic biomarkers [ghrelin, resistin, visfatin, glucagon-like peptide-1 (GLP-1), leptin, plasminogen activator inhibitor -1 (PAI-1), glucose-dependent insulinotropic polypeptide (GIP) and C-Peptide] measured using the Bio-Plex Pro Diabetes assay and insulin sensitivity as assessed by glucose infusion rate on euglycaemic-hyperinsulinaemic clamp. The biomarkers C-peptide, leptin, ghrelin and visfatin were different between overweight and lean women, irrespective of PCOS status. The concentration of circulating biomarkers did not differ between women with PCOS diagnosed by the Rotterdam criteria or National Institute of Health criteria. PAI-1 was the only biomarker that significantly predicted insulin resistance in both control women (P = 0.04) and women with PCOS (P = 0.01). Biomarkers associated with metabolic diseases appear more strongly associated with obesity rather than PCOS status. PAI-1 may also be a novel independent biomarker and predictor of insulin resistance in women with and without PCOS. © 2014 John Wiley & Sons Ltd.

  1. Caregiver burden and emotional problems in partners of stroke patients at two months and one year post-stroke : Determinants and prediction

    NARCIS (Netherlands)

    Kruithof, Willeke J.; Post, Marcel W. M.; van Mierlo, Maria L.; van den Bos, Geertrudis A. M.; de Man-van Ginkel, Janneke M.; Visser-Meily, Johanna M. A.

    2016-01-01

    Objectives: (a) To determine levels of and factors explaining partners' burden, anxiety and depressive symptoms at two months post-stroke, (b) to predict partners' burden, anxiety and depressive symptoms at one year post-stroke based on patient and partner characteristics available at two months

  2. Serum hsCRP: A Novel Marker for Prediction of Cerebrovascular Accidents (Stroke).

    Science.gov (United States)

    Patgiri, Dibyaratna; Pathak, Mauchumi Saikia; Sharma, Pradeep; Kutum, Tridip; Mattack, Nirmali

    2014-12-01

    Strokes are caused by disruption of the blood supply to the brain. This may result from either blockage or rupture of a blood vessel. Yearly 15 million people worldwide suffer a stroke. India ranks second worldwide in terms of deaths from stroke. The incidence of stroke increases with age affecting the economically productive middle aged population. Hypertension and male sex are other risk factors for stroke. C-Reactive Protein (CRP) is an acute phase protein whose concentration rises in blood following inflammation. Formerly, assays for CRP detected its rise only after significant inflammation. However, recently developed high sensitivity assays (hsCRP) enable the measurement of CRP in individuals who are apparently healthy. Several studies indicate that hsCRP is elevated in individuals who are at risk of developing Coronary Artery Disease or Cerebrovascular events, the elevation may be found years before the first detection of vascular problems. In the absence of other biochemical markers, the present study aimed to evaluate the predictive and diagnostic role of hsCRP in stroke. The study consisted of 50 patients of acute stroke admitted in Gauhati Medical College and Hospital. The control population consisted of two groups - 50 age and sex matched controls with hypertension (Hypertensive control group) and 50 age and sex matched controls with no obvious disease constituted the Normal control group. hsCRP levels were measured in all the groups and compared statistically. hsCRP is an acute phase reactant whose concentration rises in stroke as well as in those at risk. The rise may be identified even before the appearance of risk factors. Hence, hsCRP may be useful as a predictive and diagnostic marker in stroke.

  3. Prognostic and predictive potential molecular biomarkers in colon cancer.

    Science.gov (United States)

    Nastase, A; Pâslaru, L; Niculescu, A M; Ionescu, M; Dumitraşcu, T; Herlea, V; Dima, S; Gheorghe, C; Lazar, V; Popescu, I

    2011-01-01

    An important objective in nowadays research is the discovery of new biomarkers that can detect colon tumours in early stages and indicate with accuracy the status of the disease. The aim of our study was to identify potential biomarkers for colon cancer onset and progression. We assessed gene expression profiles of a list of 10 candidate genes (MMP-1, MMP-3, MMP-7, DEFA 1, DEFA-5, DEFA-6, IL-8, CXCL-1, SPP-1, CTHRC-1) by quantitative real time PCR in triplets of colonic mucosa (normal, adenoma, tumoral tissue) collected from the same patient during surgery for a group of 20 patients. Additionally we performed immunohistochemistry for DEFA1-3 and SPP1. We remarked that DEFA5 and DEFA6 are key factors in adenoma formation (p<0.05). MMP7 is important in the transition from a benign to a malignant status (p <0.01) and further in metastasis being a prognostic indicator for tumor transformation and for the metastatic potential of cancer cells. IL8, irrespective of tumor stage, has a high mRNA level in adenocarcinoma (p< 0.05). The level of expression for SPP1 is correlated with tumor level. We suggest that high levels of DEFAS, DEFA6 (key elements in adenoma formation), MMP7 (marker of colon cancer onset and progression to metastasis), SPP1 (marker of progression) and IL8 could be used to diagnose an early stage colon cancer and to evaluate the prognostic of progression for colon tumors. Further, if DEFA5 and DEFA6 level of expression are low but MMP7, SPP1 and IL8 level are high we could point out that the transition from adenoma to adenocarcinoma had already occurred. Thus, DEFA5, DEFA6, MMP7, IL8 and SPP1 consist in a valuable panel of biomarkers, whose detection can be used in early detection and progressive disease and also in prognostic of colon cancer.

  4. Enhancing the 'real world' prediction of cardiovascular events and major bleeding with the CHA2DS2-VASc and HAS-BLED scores using multiple biomarkers.

    Science.gov (United States)

    Roldán, Vanessa; Rivera-Caravaca, José Miguel; Shantsila, Alena; García-Fernández, Amaya; Esteve-Pastor, María Asunción; Vilchez, Juan Antonio; Romera, Marta; Valdés, Mariano; Vicente, Vicente; Marín, Francisco; Lip, Gregory Y H

    2018-02-01

    Atrial fibrillation (AF)-European guidelines suggest the use of biomarkers to stratify patients for stroke and bleeding risks. We investigated if a multibiomarker strategy improved the predictive performance of CHA 2 DS 2 -VASc and HAS-BLED in anticoagulated AF patients. We included consecutive patients stabilized for six months on vitamin K antagonists (INRs 2.0-3.0). High sensitivity troponin T, NT-proBNP, interleukin-6, von Willebrand factor concentrations and glomerular filtration rate (eGFR; using MDRD-4 formula) were quantified at baseline. Time in therapeutic range (TTR) was recorded at six months after inclusion. Patients were follow-up during a median of 2375 (IQR 1564-2887) days and all adverse events were recorded. In 1361 patients, adding four blood biomarkers, TTR and MDRD-eGFR, the predictive value of CHA 2 DS 2 -VASc increased significantly by c-index (0.63 vs. 0.65; p = .030) and IDI (0.85%; p originals scores. Addition of biomarkers enhanced the predictive value of CHA 2 DS 2 -VASc and HAS-BLED, although the overall improvement was modest and the added predictive advantage over original scores was marginal. Key Messages Recent atrial fibrillation (AF)-European guidelines for the first time suggest the use of biomarkers to stratify patients for stroke and bleeding risks, but their usefulness in real world for risk stratification is still questionable. In this cohort study involving 1361 AF patients optimally anticoagulated with vitamin K antagonists, adding high sensitivity troponin T, N-terminal pro-B-type natriuretic peptide, interleukin 6, von Willebrand factor, glomerular filtration rate (by the MDRD-4 formula) and time in therapeutic range, increased the predictive value of CHA 2 DS 2 -VASc for cardiovascular events, but not the predictive value of HAS-BLED for major bleeding. Reclassification analyses did not show improvement adding multiple biomarkers. Despite the improvement observed, the added predictive advantage is marginal and

  5. Predicting fitness-to-drive following stroke using the Occupational Therapy - Driver Off Road Assessment Battery.

    Science.gov (United States)

    Unsworth, Carolyn A; Baker, Anne; Lannin, Natasha; Harries, Priscilla; Strahan, Janene; Browne, Matthew

    2018-02-28

    It is difficult to determine if, or when, individuals with stroke are ready to undergo on-road fitness-to-drive assessment. The Occupational Therapy - Driver Off Road Assessment Battery was developed to determine client suitability to resume driving. The predictive validity of the Battery needs to be verified for people with stroke. Examine the predictive validity of the Occupational Therapy - Driver Off Road Assessment Battery for on-road performance among people with stroke. Off-road data were collected from 148 people post stroke on the Battery and the outcome of their on-road assessment was recorded as: fit-to-drive or not fit-to-drive. The majority of participants (76%) were able to resume driving. A classification and regression tree (CART) analysis using four subtests (three cognitive and one physical) from the Battery demonstrated an area under the curve (AUC) of 0.8311. Using a threshold of 0.5, the model correctly predicted 98/112 fit-to-drive (87.5%) and 26/36 people not fit-to-drive (72.2%). The three cognitive subtests from the Occupational Therapy - Driver Off Road Assessment Battery and potentially one of the physical tests have good predictive validity for client fitness-to-drive. These tests can be used to screen client suitability for proceeding to an on-road test following stroke. Implications for Rehabilitation: Following stroke, drivers should be counseled (including consideration of local legislation) concerning return to driving. The Occupational Therapy - Driver Off Road Assessment Battery can be used in the clinic to screen people for suitability to undertake on road assessment. Scores on four of the Occupational Therapy - Driver Off Road Assessment Battery subtests are predictive of resumption of driving following stroke.

  6. Machine learning for outcome prediction of acute ischemic stroke post intra-arterial therapy.

    Directory of Open Access Journals (Sweden)

    Hamed Asadi

    Full Text Available INTRODUCTION: Stroke is a major cause of death and disability. Accurately predicting stroke outcome from a set of predictive variables may identify high-risk patients and guide treatment approaches, leading to decreased morbidity. Logistic regression models allow for the identification and validation of predictive variables. However, advanced machine learning algorithms offer an alternative, in particular, for large-scale multi-institutional data, with the advantage of easily incorporating newly available data to improve prediction performance. Our aim was to design and compare different machine learning methods, capable of predicting the outcome of endovascular intervention in acute anterior circulation ischaemic stroke. METHOD: We conducted a retrospective study of a prospectively collected database of acute ischaemic stroke treated by endovascular intervention. Using SPSS®, MATLAB®, and Rapidminer®, classical statistics as well as artificial neural network and support vector algorithms were applied to design a supervised machine capable of classifying these predictors into potential good and poor outcomes. These algorithms were trained, validated and tested using randomly divided data. RESULTS: We included 107 consecutive acute anterior circulation ischaemic stroke patients treated by endovascular technique. Sixty-six were male and the mean age of 65.3. All the available demographic, procedural and clinical factors were included into the models. The final confusion matrix of the neural network, demonstrated an overall congruency of ∼ 80% between the target and output classes, with favourable receiving operative characteristics. However, after optimisation, the support vector machine had a relatively better performance, with a root mean squared error of 2.064 (SD: ± 0.408. DISCUSSION: We showed promising accuracy of outcome prediction, using supervised machine learning algorithms, with potential for incorporation of larger multicenter

  7. Do measures of reactive balance control predict falls in people with stroke returning to the community?

    Science.gov (United States)

    Mansfield, A; Wong, J S; McIlroy, W E; Biasin, L; Brunton, K; Bayley, M; Inness, E L

    2015-12-01

    To determine if reactive balance control measures predict falls after discharge from stroke rehabilitation. Prospective cohort study. Rehabilitation hospital and community. Independently ambulatory individuals with stroke who were discharged home after inpatient rehabilitation (n=95). Balance and gait measures were obtained from a clinical assessment at discharge from inpatient stroke rehabilitation. Measures of reactive balance control were obtained: (1) during quiet standing; (2) when walking; and (3) in response to large postural perturbations. Participants reported falls and activity levels up to 6 months post-discharge. Logistic and Poisson regressions were used to identify measures of reactive balance control that were related to falls post-discharge. Decreased paretic limb contribution to standing balance control [rate ratio 0.8, 95% confidence interval (CI) 0.7 to 1.0; P=0.011], reduced between-limb synchronisation of quiet standing balance control (rate ratio 0.9, 95% CI 0.8 to 0.9; Pfall rates when controlling for age, stroke severity, functional balance and daily walking activity. Impaired reactive balance control in standing and walking predicted increased risk of falls post-discharge from stroke rehabilitation. Specifically, measures that revealed the capacity of both limbs to respond to instability were related to increased risk of falls. These results suggest that post-stroke rehabilitation strategies for falls prevention should train responses to instability, and focus on remediating dyscontrol in the more-affected limb. Copyright © 2015 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

  8. Prediction of Chronic Kidney Disease Stage 3 by CKD273, a Urinary Proteomic Biomarker

    DEFF Research Database (Denmark)

    Pontillo, Claudia; Zhang, Zhen-Yu; Schanstra, Joost P

    2017-01-01

    Introduction: CKD273 is a urinary biomarker, which in advanced chronic kidney disease predicts further deterioration. We investigated whether CKD273 can also predict a decline of estimated glomerular filtration rate (eGFR) to ... threshold (P = 0.086). Discussion: In conclusion, while accounting for baseline eGFR, albuminuria, and covariables, CKD273 adds to the prediction of stage 3 chronic kidney disease, at which point intervention remains an achievable therapeutic target....

  9. The long-term nutritional status in stroke patients and its predictive factors.

    Science.gov (United States)

    Paquereau, Julie; Allart, Etienne; Romon, Monique; Rousseaux, Marc

    2014-07-01

    Malnutrition is common in the first few months after stroke and contributes to a poor overall outcome. We analyzed long-term weight changes and their predictive factors. A total of 71 first-ever stroke patients were included in the study and examined (1) their weight on admission to the acute stroke unit (usual weight [UW]), on admission to the rehabilitation unit, on discharge from the rehabilitation unit, and then 1 year or more after the stroke (median time: 2.5 years), (2) the presence of malnutrition after stroke, and (3) possible predictive factors, namely, sociodemographic factors, clinical characteristics (concerning the stroke, the patient's current neurologic status and the presence of diabetes mellitus and depression), and the present nutritional state (including eating difficulties, anorexia, and changes in food intake and food preferences). Body weight fell (4.0 kg) during the patients' stay in the stroke unit, increased moderately in the rehabilitation unit (2.0 kg), and returned to the UW by the long-term measurement. However, at the last observation, 40.1% of the patients weighed markedly less than their UW, 38.0% weighed markedly more, and 21.1% were relatively stable. Predictors of weight change were a change in preferences for sweet food products and a change in food intake. Malnutrition was frequent (47.9%) and associated with reduced food intake, residence in an institution, and diabetes mellitus. Malnutrition was highly prevalent, with an important role of change in food intake and food preferences, which could result from brain lesions and specific regimens. Living in an institution needs consideration, as its negative effects can be prevented. Copyright © 2014 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  10. Can common serum biomarkers predict complicated appendicitis in children?

    Science.gov (United States)

    Zani, Augusto; Teague, Warwick J; Clarke, Simon A; Haddad, Munther J; Khurana, Sanjeev; Tsang, Thomas; Nataraja, Ramesh M

    2017-07-01

    As appendicitis in children can be managed differently according to the severity of the disease, we investigated whether commonly used serum biomarkers on admission could distinguish between simple and complicated appendicitis. Admission white blood cell (WBC), neutrophil (NEU), and C-reactive protein (CRP) levels were analysed by ROC curve, and Kruskal-Wallis and contingency tests. Patients were divided according to age and histology [normal appendix (NA), simple appendicitis (SA), complicated appendicitis (CA)]. Of 1197 children (NA = 186, SA = 685, CA = 326), 7% were 40 mg/L in 58% CA and 37% SA (p 15 × 10 9 /L in 58% CA and 43% SA (p appendicitis in children older than 5 years of age. Early distinction of appendicitis severity using these tests may guide caregivers in the preoperative decision-making process.

  11. Comparison of statistical and clinical predictions of functional outcome after ischemic stroke.

    Directory of Open Access Journals (Sweden)

    Douglas D Thompson

    Full Text Available To determine whether the predictions of functional outcome after ischemic stroke made at the bedside using a doctor's clinical experience were more or less accurate than the predictions made by clinical prediction models (CPMs.A prospective cohort study of nine hundred and thirty one ischemic stroke patients recruited consecutively at the outpatient, inpatient and emergency departments of the Western General Hospital, Edinburgh between 2002 and 2005. Doctors made informal predictions of six month functional outcome on the Oxford Handicap Scale (OHS. Patients were followed up at six months with a validated postal questionnaire. For each patient we calculated the absolute predicted risk of death or dependence (OHS≥3 using five previously described CPMs. The specificity of a doctor's informal predictions of OHS≥3 at six months was good 0.96 (95% CI: 0.94 to 0.97 and similar to CPMs (range 0.94 to 0.96; however the sensitivity of both informal clinical predictions 0.44 (95% CI: 0.39 to 0.49 and clinical prediction models (range 0.38 to 0.45 was poor. The prediction of the level of disability after stroke was similar for informal clinical predictions (ordinal c-statistic 0.74 with 95% CI 0.72 to 0.76 and CPMs (range 0.69 to 0.75. No patient or clinician characteristic affected the accuracy of informal predictions, though predictions were more accurate in outpatients.CPMs are at least as good as informal clinical predictions in discriminating between good and bad functional outcome after ischemic stroke. The place of these models in clinical practice has yet to be determined.

  12. Quantifying Treatment Benefit in Molecular Subgroups to Assess a Predictive Biomarker.

    Science.gov (United States)

    Iasonos, Alexia; Chapman, Paul B; Satagopan, Jaya M

    2016-05-01

    An increased interest has been expressed in finding predictive biomarkers that can guide treatment options for both mutation carriers and noncarriers. The statistical assessment of variation in treatment benefit (TB) according to the biomarker carrier status plays an important role in evaluating predictive biomarkers. For time-to-event endpoints, the hazard ratio (HR) for interaction between treatment and a biomarker from a proportional hazards regression model is commonly used as a measure of variation in TB. Although this can be easily obtained using available statistical software packages, the interpretation of HR is not straightforward. In this article, we propose different summary measures of variation in TB on the scale of survival probabilities for evaluating a predictive biomarker. The proposed summary measures can be easily interpreted as quantifying differential in TB in terms of relative risk or excess absolute risk due to treatment in carriers versus noncarriers. We illustrate the use and interpretation of the proposed measures with data from completed clinical trials. We encourage clinical practitioners to interpret variation in TB in terms of measures based on survival probabilities, particularly in terms of excess absolute risk, as opposed to HR. Clin Cancer Res; 22(9); 2114-20. ©2016 AACR. ©2016 American Association for Cancer Research.

  13. In-treatment stroke volume predicts cardiovascular risk in hypertension

    DEFF Research Database (Denmark)

    Lønnebakken, Mai T; Gerdts, Eva; Boman, Kurt

    2011-01-01

    , the prespecified primary study endpoint, was assessed in Cox regression analysis using data from baseline and annual follow-up visits in 855 patients during 4.8 years of randomized losartan-based or atenolol-based treatment in the Losartan Intervention For Endpoint reduction in hypertension (LIFE) echocardiography...... with higher risk of cardiovascular events {hazard ratio 1.69 per 1 SD (6 ml/m2.04) lower stroke volume [95% confidence interval (CI) 1.35–2.11], P secondary model also independent of stress-corrected midwall shortening......, hence, adds information on cardiovascular risk in treated hypertensive patients beyond assessment of left ventricular structure alone....

  14. Perceived participation and autonomy: aspects of functioning and contextual factors predicting participation after stroke.

    Science.gov (United States)

    Fallahpour, Mandana; Tham, Kerstin; Joghataei, Mohammad Taghi; Jonsson, Hans

    2011-04-01

    To describe perceived participation and autonomy among a sample of persons with stroke in Iran and to identify different aspects of functioning and contextual factors predicting participation after stroke. A cross-sectional study. A total of 102 persons, between 27 and 75 years of age, diagnosed with first-ever stroke. Participants were assessed for different aspects of functioning, contextual factors and health conditions. Participation was assessed using the Persian version of the Impact on Participation and Autonomy questionnaire. This study demonstrated that the majority of the study population perceived their participation and autonomy to be good to fair in the different domains of their participation, but not with respect to the autonomy outdoors domain. In addition, physical function was found to be the most important variable predicting performance-based participation, whereas mood state was the most important variable predicting social-based participation. The results emphasize the importance of physical function, mood state and access to caregiving services as predictors of participation in everyday life after stroke. Whilst there are two dimensions of participation in this Persian sample of persons with stroke, the factors explaining participation seem to be the same across the cultures.

  15. Slower EEG alpha generation, synchronization and “flow”—possible biomarkers of cognitive impairment and neuropathology of minor stroke

    OpenAIRE

    Petrovic, Jelena; Milosevic, Vuk; Zivkovic, Miroslava; Stojanov, Dragan; Milojkovic, Olga; Kalauzi, Aleksandar; Saponjic, Jasna

    2017-01-01

    Background We investigated EEG rhythms, particularly alpha activity, and their relationship to post-stroke neuropathology and cognitive functions in the subacute and chronic stages of minor strokes. Methods We included 10 patients with right middle cerebral artery (MCA) ischemic strokes and 11 healthy controls. All the assessments of stroke patients were done both in the subacute and chronic stages. Neurological impairment was measured using the National Institute of Health Stroke Scale (NIHS...

  16. Computational Prediction of Human Salivary Proteins from Blood Circulation and Application to Diagnostic Biomarker Identification

    Science.gov (United States)

    Wang, Jiaxin; Liang, Yanchun; Wang, Yan; Cui, Juan; Liu, Ming; Du, Wei; Xu, Ying

    2013-01-01

    Proteins can move from blood circulation into salivary glands through active transportation, passive diffusion or ultrafiltration, some of which are then released into saliva and hence can potentially serve as biomarkers for diseases if accurately identified. We present a novel computational method for predicting salivary proteins that come from circulation. The basis for the prediction is a set of physiochemical and sequence features we found to be discerning between human proteins known to be movable from circulation to saliva and proteins deemed to be not in saliva. A classifier was trained based on these features using a support-vector machine to predict protein secretion into saliva. The classifier achieved 88.56% average recall and 90.76% average precision in 10-fold cross-validation on the training data, indicating that the selected features are informative. Considering the possibility that our negative training data may not be highly reliable (i.e., proteins predicted to be not in saliva), we have also trained a ranking method, aiming to rank the known salivary proteins from circulation as the highest among the proteins in the general background, based on the same features. This prediction capability can be used to predict potential biomarker proteins for specific human diseases when coupled with the information of differentially expressed proteins in diseased versus healthy control tissues and a prediction capability for blood-secretory proteins. Using such integrated information, we predicted 31 candidate biomarker proteins in saliva for breast cancer. PMID:24324552

  17. New and emerging prognostic and predictive genetic biomarkers in B-cell precursor acute lymphoblastic leukemia

    Science.gov (United States)

    Moorman, Anthony V.

    2016-01-01

    Acute lymphoblastic leukemia (ALL) is a heterogeneous disease at the genetic level. Chromosomal abnormalities are used as diagnostic, prognostic and predictive biomarkers to provide subtype, outcome and drug response information. t(12;21)/ETV6-RUNX1 and high hyper-diploidy are good-risk prognostic biomarkers whereas KMT2A (MLL) translocations, t(17;19)/TCF3-HLF, haploidy or low hypodiploidy are high-risk biomarkers. t(9;22)/BCR-ABL1 patients require targeted treatment (imatinib/dasatinib), whereas iAMP21 patients achieve better outcomes when treated intensively. High-risk genetic biomarkers are four times more prevalent in adults compared to children. The application of genomic technologies to cases without an established abnormality (B-other) reveals copy number alterations which can be used either individually or in combination as prognostic biomarkers. Transcriptome sequencing studies have identified a network of fusion genes involving kinase genes - ABL1, ABL2, PDGFRB, CSF1R, CRLF2, JAK2 and EPOR. In vitro and in vivo studies along with emerging clinical observations indicate that patients with a kinase-activating aberration may respond to treatment with small molecular inhibitors like imatinib/dasatinib and ruxolitinib. Further work is required to determine the true frequency of these abnormalities across the age spectrum and the optimal way to incorporate such inhibitors into protocols. In conclusion, genetic biomarkers are playing an increasingly important role in the management of patients with ALL. PMID:27033238

  18. Resting Heart Rate Predicts Depression and Cognition Early after Ischemic Stroke: A Pilot Study.

    Science.gov (United States)

    Tessier, Arnaud; Sibon, Igor; Poli, Mathilde; Audiffren, Michel; Allard, Michèle; Pfeuty, Micha

    2017-10-01

    Early detection of poststroke depression (PSD) and cognitive impairment (PSCI) remains challenging. It is well documented that the function of autonomic nervous system is associated with depression and cognition. However, their relationship has never been investigated in the early poststroke phase. This pilot study aimed at determining whether resting heart rate (HR) parameters measured in early poststroke phase (1) are associated with early-phase measures of depression and cognition and (2) could be used as new tools for early objective prediction of PSD or PSCI, which could be applicable to patients unable to answer usual questionnaires. Fifty-four patients with first-ever ischemic stroke, without cardiac arrhythmia, were assessed for resting HR and heart rate variability (HRV) within the first week after stroke and for depression and cognition during the first week and at 3 months after stroke. Multiple regression analyses controlled for age, gender, and stroke severity revealed that higher HR, lower HRV, and higher sympathovagal balance (low-frequency/high-frequency ratio of HRV) were associated with higher severity of depressive symptoms within the first week after stroke. Furthermore, higher sympathovagal balance in early phase predicted higher severity of depressive symptoms at the 3-month follow-up, whereas higher HR and lower HRV in early phase predicted lower global cognitive functioning at the 3-month follow-up. Resting HR measurements obtained in early poststroke phase could serve as an objective tool, applicable to patients unable to complete questionnaires, to help in the early prediction of PSD and PSCI. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  19. Factors Predicting Recovery of Oral Intake in Stroke Survivors with Dysphagia in a Convalescent Rehabilitation Ward.

    Science.gov (United States)

    Ikenaga, Yasunori; Nakayama, Sayaka; Taniguchi, Hiroki; Ohori, Isao; Komatsu, Nahoko; Nishimura, Hitoshi; Katsuki, Yasuo

    2017-05-01

    Percutaneous endoscopic gastrostomy may be performed in dysphagic stroke patients. However, some patients regain complete oral intake without gastrostomy. This study aimed to investigate the predictive factors of intake, thereby determining gastrostomy indications. Stroke survivors admitted to our convalescent rehabilitation ward who underwent gastrostomy or nasogastric tube placement from 2009 to 2015 were divided into 2 groups based on intake status at discharge. Demographic data and Functional Independence Measure (FIM), Dysphagia Severity Scale (DSS), National Institutes of Health Stroke Scale, and Glasgow Coma Scale (GCS) scores on admission were compared between groups. We evaluated the factors predicting intake using a stepwise logistic regression analysis. Thirty-four patients recovered intake, whereas 38 achieved incomplete intake. Mean age was lower, mean body mass index (BMI) was higher, and mean time from stroke onset to admission was shorter in the complete intake group. The complete intake group had less impairment in terms of GCS, FIM, and DSS scores. In the stepwise logistic regression analysis, BMI, FIM-cognitive score, and DSS score were significant independent factors predicting intake. The formula of BMI × .26 + FIM cognitive score × .19 + DSS score × 1.60 predicted recovery of complete intake with a sensitivity of 88.2% and a specificity of 84.2%. Stroke survivors with dysphagia with a high BMI and FIM-cognitive and DSS scores tended to recover oral intake. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  20. Systems Biology-Derived Biomarkers to Predict Progression of Renal Function Decline in Type 2 Diabetes

    NARCIS (Netherlands)

    Mayer, Gert; Heerspink, Hiddo J. L.; Aschauer, Constantin; Heinzel, Andreas; Heinze, Georg; Kainz, Alexander; Sunzenauer, Judith; Perco, Paul; de Zeeuw, Dick; Rossing, Peter; Pena, Michelle; Oberbauer, Rainer

    OBJECTIVE: Chronic kidney disease (CKD) in diabetes has a complex molecular and likely multifaceted pathophysiology. We aimed to validate a panel of biomarkers identified using a systems biology approach to predict the individual decline of estimated glomerular filtration rate (eGFR) in a large

  1. Prediction of outcome in neurogenic oropharyngeal dysphagia within 72 hours of acute stroke.

    Science.gov (United States)

    Ickenstein, Guntram W; Höhlig, Carolin; Prosiegel, Mario; Koch, Horst; Dziewas, Rainer; Bodechtel, Ulf; Müller, Rainer; Reichmann, Heinz; Riecker, Axel

    2012-10-01

    Stroke is the most frequent cause of neurogenic oropharyngeal dysphagia (NOD). In the acute phase of stroke, the frequency of NOD is greater than 50% and, half of this patient population return to good swallowing within 14 days while the other half develop chronic dysphagia. Because dysphagia leads to aspiration pneumonia, malnutrition, and in-hospital mortality, it is important to pay attention to swallowing problems. The question arises if a prediction of severe chronic dysphagia is possible within the first 72 hours of acute stroke. On admission to the stroke unit, all stroke patients were screened for swallowing problems by the nursing staff within 2 hours. Patients showing signs of aspiration were included in the study (n = 114) and were given a clinical swallowing examination (CSE) by the swallowing/speech therapist within 24 hours and a swallowing endoscopy within 72 hours by the physician. The primary outcome of the study was the functional communication measure (FCM) of swallowing (score 1-3, tube feeding dependency) on day 90. The grading system with the FCM swallowing and the penetration-aspiration scale (PAS) in the first 72 hours was tested in a multivariate analysis for its predictive value for tube feeding-dependency on day 90. For the FCM level 1 to 3 (P dysphagia scales to prevent aspiration pneumonia and malnutrition. A dysphagia program can lead to better communication within the stroke unit team to initiate the appropriate diagnostics and swallowing therapy as soon as possible. Copyright © 2012 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  2. Predicting Discharge to Institutional Long-Term Care After Stroke: A Systematic Review and Metaanalysis.

    Science.gov (United States)

    Burton, Jennifer K; Ferguson, Eilidh E C; Barugh, Amanda J; Walesby, Katherine E; MacLullich, Alasdair M J; Shenkin, Susan D; Quinn, Terry J

    2018-01-01

    Stroke is a leading cause of disability worldwide, and a significant proportion of stroke survivors require long-term institutional care. Understanding who cannot be discharged home is important for health and social care planning. Our aim was to establish predictive factors for discharge to institutional care after hospitalization for stroke. We registered and conducted a systematic review and meta-analysis (PROSPERO: CRD42015023497) of observational studies. We searched MEDLINE, EMBASE, and CINAHL Plus to February 2017. Quantitative synthesis was performed where data allowed. Acute and rehabilitation hospitals. Adults hospitalized for stroke who were newly admitted directly to long-term institutional care at the time of hospital discharge. Factors associated with new institutionalization. From 10,420 records, we included 18 studies (n = 32,139 participants). The studies were heterogeneous and conducted in Europe, North America, and East Asia. Eight studies were at high risk of selection bias. The proportion of those surviving to discharge who were newly discharged to long-term care varied from 7% to 39% (median 17%, interquartile range 12%), and the model of care received in the long-term care setting was not defined. Older age and greater stroke severity had a consistently positive association with the need for long-term care admission. Individuals who had a severe stroke were 26 times as likely to be admitted to long-term care than those who had a minor stroke. Individuals aged 65 and older had a risk of stroke that was three times as great as that of younger individuals. Potentially modifiable factors were rarely examined. Age and stroke severity are important predictors of institutional long-term care admission directly from the hospital after an acute stroke. Potentially modifiable factors should be the target of future research. Stroke outcome studies should report discharge destination, defining the model of care provided in the long-term care setting.

  3. Predicting Hemorrhagic Transformation of Acute Ischemic Stroke: Prospective Validation of the HeRS Score.

    Science.gov (United States)

    Marsh, Elisabeth B; Llinas, Rafael H; Schneider, Andrea L C; Hillis, Argye E; Lawrence, Erin; Dziedzic, Peter; Gottesman, Rebecca F

    2016-01-01

    Hemorrhagic transformation (HT) increases the morbidity and mortality of ischemic stroke. Anticoagulation is often indicated in patients with atrial fibrillation, low ejection fraction, or mechanical valves who are hospitalized with acute stroke, but increases the risk of HT. Risk quantification would be useful. Prior studies have investigated risk of systemic hemorrhage in anticoagulated patients, but none looked specifically at HT. In our previously published work, age, infarct volume, and estimated glomerular filtration rate (eGFR) significantly predicted HT. We created the hemorrhage risk stratification (HeRS) score based on regression coefficients in multivariable modeling and now determine its validity in a prospectively followed inpatient cohort.A total of 241 consecutive patients presenting to 2 academic stroke centers with acute ischemic stroke and an indication for anticoagulation over a 2.75-year period were included. Neuroimaging was evaluated for infarct volume and HT. Hemorrhages were classified as symptomatic versus asymptomatic, and by severity. HeRS scores were calculated for each patient and compared to actual hemorrhage status using receiver operating curve analysis.Area under the curve (AUC) comparing predicted odds of hemorrhage (HeRS score) to actual hemorrhage status was 0.701. Serum glucose (P hemorrhages were more likely to be symptomatic and more severe.The HeRS score is a valid predictor of HT in patients with ischemic stroke and indication for anticoagulation.

  4. Rehabilitation after stroke: predictive power of Barthel Index versus a cognitive and a motor index

    DEFF Research Database (Denmark)

    Engberg, A; Bentzen, L; Garde, B

    1995-01-01

    The aim of the present study was to investigate the predictive power of ratings of Barthel Index at Day 40 post stroke, compared with and/or combined with simultaneous ratings from a mobility scale (EG motor index) and a rather simple cognitive test scale (CT50). The parameter to be individually...

  5. Using gene co-expression network analysis to predict biomarkers for chronic lymphocytic leukemia

    Directory of Open Access Journals (Sweden)

    Borlawsky Tara B

    2010-10-01

    Full Text Available Abstract Background Chronic lymphocytic leukemia (CLL is the most common adult leukemia. It is a highly heterogeneous disease, and can be divided roughly into indolent and progressive stages based on classic clinical markers. Immunoglobin heavy chain variable region (IgVH mutational status was found to be associated with patient survival outcome, and biomarkers linked to the IgVH status has been a focus in the CLL prognosis research field. However, biomarkers highly correlated with IgVH mutational status which can accurately predict the survival outcome are yet to be discovered. Results In this paper, we investigate the use of gene co-expression network analysis to identify potential biomarkers for CLL. Specifically we focused on the co-expression network involving ZAP70, a well characterized biomarker for CLL. We selected 23 microarray datasets corresponding to multiple types of cancer from the Gene Expression Omnibus (GEO and used the frequent network mining algorithm CODENSE to identify highly connected gene co-expression networks spanning the entire genome, then evaluated the genes in the co-expression network in which ZAP70 is involved. We then applied a set of feature selection methods to further select genes which are capable of predicting IgVH mutation status from the ZAP70 co-expression network. Conclusions We have identified a set of genes that are potential CLL prognostic biomarkers IL2RB, CD8A, CD247, LAG3 and KLRK1, which can predict CLL patient IgVH mutational status with high accuracies. Their prognostic capabilities were cross-validated by applying these biomarker candidates to classify patients into different outcome groups using a CLL microarray datasets with clinical information.

  6. Evaluation of candidate biomarkers to predict cancer cell sensitivity or resistance to PARP-1 inhibitor treatment

    DEFF Research Database (Denmark)

    Oplustilova, L.; Wolanin, K.; Bartkova, J.

    2012-01-01

    combinations with camptothecin or ionizing radiation. Furthermore, monitoring pARsylation and Rad51 foci formation as surrogate markers for PARP activity and HR, respectively, supported their candidacy for biomarkers of PARP-1i responses. As to resistance mechanisms, we confrmed the role of the multidrug......(ADp-ribose) polymerase-1 (PARP-1), an enzyme critical for repair pathways alternative to HR. While promising, treatment with PARP-1 inhibitors (PARP-1i) faces some hurdles, including (1) acquired resistance, (2) search for other sensitizing, non-BRCA1/2 cancer defects and (3) lack of biomarkers to predict response...

  7. Predicting recovery of cognitive function soon after stroke: differential modeling of logarithmic and linear regression.

    Science.gov (United States)

    Suzuki, Makoto; Sugimura, Yuko; Yamada, Sumio; Omori, Yoshitsugu; Miyamoto, Masaaki; Yamamoto, Jun-ichi

    2013-01-01

    Cognitive disorders in the acute stage of stroke are common and are important independent predictors of adverse outcome in the long term. Despite the impact of cognitive disorders on both patients and their families, it is still difficult to predict the extent or duration of cognitive impairments. The objective of the present study was, therefore, to provide data on predicting the recovery of cognitive function soon after stroke by differential modeling with logarithmic and linear regression. This study included two rounds of data collection comprising 57 stroke patients enrolled in the first round for the purpose of identifying the time course of cognitive recovery in the early-phase group data, and 43 stroke patients in the second round for the purpose of ensuring that the correlation of the early-phase group data applied to the prediction of each individual's degree of cognitive recovery. In the first round, Mini-Mental State Examination (MMSE) scores were assessed 3 times during hospitalization, and the scores were regressed on the logarithm and linear of time. In the second round, calculations of MMSE scores were made for the first two scoring times after admission to tailor the structures of logarithmic and linear regression formulae to fit an individual's degree of functional recovery. The time course of early-phase recovery for cognitive functions resembled both logarithmic and linear functions. However, MMSE scores sampled at two baseline points based on logarithmic regression modeling could estimate prediction of cognitive recovery more accurately than could linear regression modeling (logarithmic modeling, R(2) = 0.676, PLogarithmic modeling based on MMSE scores could accurately predict the recovery of cognitive function soon after the occurrence of stroke. This logarithmic modeling with mathematical procedures is simple enough to be adopted in daily clinical practice.

  8. Large arterial occlusive strokes as a medical emergency: need to accurately predict clot location.

    Science.gov (United States)

    Vanacker, Peter; Faouzi, Mohamed; Eskandari, Ashraf; Maeder, Philippe; Meuli, Reto; Michel, Patrik

    2017-10-01

    Endovascular treatment for acute ischemic stroke with a large intracranial occlusion was recently shown to be effective. Timely knowledge of the presence, site, and extent of arterial occlusions in the ischemic territory has the potential to influence patient selection for endovascular treatment. We aimed to find predictors of large vessel occlusive strokes, on the basis of available demographic, clinical, radiological, and laboratory data in the emergency setting. Patients enrolled in ASTRAL registry with acute ischemic stroke and computed tomography (CT)-angiography within 12 h of stroke onset were selected and categorized according to occlusion site. Easily accessible variables were used in a multivariate analysis. Of 1645 patients enrolled, a significant proportion (46.2%) had a large vessel occlusion in the ischemic territory. The main clinical predictors of any arterial occlusion were in-hospital stroke [odd ratios (OR) 2.1, 95% confidence interval 1.4-3.1], higher initial National Institute of Health Stroke Scale (OR 1.1, 1.1-1.2), presence of visual field defects (OR 1.9, 1.3-2.6), dysarthria (OR 1.4, 1.0-1.9), or hemineglect (OR 2.0, 1.4-2.8) at admission and atrial fibrillation (OR 1.7, 1.2-2.3). Further, the following radiological predictors were identified: time-to-imaging (OR 0.9, 0.9-1.0), early ischemic changes (OR 2.3, 1.7-3.2), and silent lesions on CT (OR 0.7, 0.5-1.0). The area under curve for this analysis was 0.85. Looking at different occlusion sites, National Institute of Health Stroke Scale and early ischemic changes on CT were independent predictors in all subgroups. Neurological deficits, stroke risk factors, and CT findings accurately identify acute ischemic stroke patients at risk of symptomatic vessel occlusion. Predicting the presence of these occlusions may impact emergency stroke care in regions with limited access to noninvasive vascular imaging.

  9. Clinical Relevance and Predictive Value of Damage Biomarkers of Drug-Induced Kidney Injury.

    Science.gov (United States)

    Kane-Gill, Sandra L; Smithburger, Pamela L; Kashani, Kianoush; Kellum, John A; Frazee, Erin

    2017-11-01

    Nephrotoxin exposure accounts for up to one-fourth of acute kidney injury episodes in hospitalized patients, and the associated consequences are as severe as acute kidney injury due to other etiologies. As the use of nephrotoxic agents represents one of the few modifiable risk factors for acute kidney injury, clinicians must be able to identify patients at high risk for drug-induced kidney injury rapidly. Recently, significant advancements have been made in the field of biomarker utilization for the prediction and detection of acute kidney injury. Such biomarkers may have a role both for detection of drug-induced kidney disease and implementation of preventative and therapeutic strategies designed to mitigate injury. In this article, basic principles of renal biomarker use in practice are summarized, and the existing evidence for six markers specifically used to detect drug-induced kidney injury are outlined, including liver-type fatty acid binding protein, neutrophil gelatinase-associated lipocalin, tissue inhibitor of metalloproteinase-2 times insulin-like growth factor-binding protein 7 ([TIMP-2]·[IGFBP7]), kidney injury molecule-1 and N-acetyl-β-D-glucosaminidase. The results of the literature search for these six kidney damage biomarkers identified 29 unique articles with none detected for liver-type fatty acid binding protein and [TIMP-2]·[IGFBP7]. For three biomarkers, kidney injury molecule-1, neutrophil gelatinase-associated lipocalin and N-acetyl-β-D-glucosaminidase, the majority of the studies suggest utility in clinical practice. While many questions need to be answered to clearly articulate the use of biomarkers to predict drug-induced kidney disease, current data are promising.

  10. MTR-18 Predictive Biomarkers Of Bevacizumab Response In Recurrent Glioblastoma Patients

    DEFF Research Database (Denmark)

    Urup, Thomas; Michaelsen, Signe Regner; Olsen, Lars Rønn

    2015-01-01

    Bevacizumab (BEV) plus chemotherapy has shown activity in recurrent glioblastoma (GBM). However, the prognosis varies and only one third of patients have a durable clinical response to BEV combination therapy. Recent findings from a randomized phase-3 study (AVAglio) indicate that patients...... with the proneural GBM subtype have a survival benefit when treated with BEV in combination with standard treatment. However, no validated biomarkers able to predict BEV response have been identified and the biology reflecting a clinical BEV response is poorly understood. The primary objective of this study...... was to evaluate the predictive and prognostic value of GBM subtypes in recurrent GBM patients treated with BEV therapy. The secondary objective was to identify biomarkers able to predict response to BEV therapy in recurrent GBM patients. METHODS: A total of 90 recurrent GBM patients treated with BEV combination...

  11. Systems Biology-Derived Biomarkers to Predict Progression of Renal Function Decline in Type 2 Diabetes

    DEFF Research Database (Denmark)

    Mayer, Gert; Heerspink, Hiddo J L; Aschauer, Constantin

    2017-01-01

    hormone 1, hepatocyte growth factor, matrix metalloproteinase (MMP) 2, MMP7, MMP8, MMP13, tyrosine kinase, and tumor necrosis factor receptor-1. These biomarkers were measured in baseline serum samples from 1,765 patients recruited into two large clinical trials. eGFR decline was predicted based...... on molecular markers, clinical risk factors (including baseline eGFR and albuminuria), and both combined, and these predictions were evaluated using mixed linear regression models for longitudinal data. RESULTS: The variability of annual eGFR loss explained by the biomarkers, indicated by the adjusted R2 value......, combined with clinical variables, enhances the prediction of renal function loss over a wide range of baseline eGFR values in patients with type 2 diabetes and CKD....

  12. Aspects correlates with Scandinavian Stroke Scale for predicting early neurological impairment

    Directory of Open Access Journals (Sweden)

    Gustavo José Luvizutto

    2015-05-01

    Full Text Available Objective To investigate the correlation between the Alberta Program Early CT Score (ASPECTS and the Scandinavian Stroke Scale (SSS for the evaluation of neurological impairment in patients with acute stroke. Method 59 patients with a first acute ischemic stroke were evaluated. The ASPECTS were evaluated by 2 neurologists at admission and by another neurologist after 48 hours. The NIHSS and SSS was applied to determinate stroke severity. Correlations and agreements were analysed statistically by Spearman and Kappa tests. Results ASPECTS was correlated with National Institute of Health Stroke Scale (NIHSS at admission (r = -0.52; p < 0.001 and SSS (r = 0.50; p < 0.001. The ASPECTS and SSS items were most correlated with arm (r = 0.52; p < 0.001 and hand (r = 0.49; p < 0.001 motor power, and speech (r = 0.51; p < 0.001. The SSS of 25.5 shows sensitivity (68% and specificity (72% when associated with ASPECTS ≤ 7. Conclusion The SSS can predict worst neurological impairment when associated with lower values of ASPECTS.

  13. Circulating predictive and diagnostic biomarkers for hepatitis B virus-associated hepatocellular carcinoma

    Science.gov (United States)

    Van Hees, Stijn; Michielsen, Peter; Vanwolleghem, Thomas

    2016-01-01

    Chronic hepatitis B virus (HBV) infected patients have an almost 100-fold increased risk to develop hepatocellular carcinoma (HCC). HCC is the fifth most common and third most deadly cancer worldwide. Up to 50% of newly diagnosed HCC cases are attributed to HBV infection. Early detection improves survival and can be achieved through regular screening. Six-monthly abdominal ultrasound, either alone or in combination with alpha-fetoprotein serum levels, has been widely endorsed for this purpose. Both techniques however yield limited diagnostic accuracy, which is not improved when they are combined. Alternative circulating or histological markers to predict or diagnose HCC are therefore urgently needed. Recent advances in systems biology technologies have enabled the identification of several new putative circulating biomarkers. Although results from studies assessing combinations of these biomarkers are promising, evidence for their clinical utility remains low. In addition, most of the studies conducted so far show limitations in design. Attention must be paid for instance to different ethnicities and different etiologies when studying biomarkers for hepatocellular carcinoma. This review provides an overview on the current understandings and recent progress in the field of diagnostic and predictive circulating biomarkers for hepatocellular carcinoma in chronically infected HBV patients and discusses the future prospects. PMID:27729734

  14. MAGIC biomarkers predict long term outcomes for steroid-resistant acute GVHD.

    Science.gov (United States)

    Major-Monfried, Hannah; Renteria, Anne S; Pawarode, Attaphol; Reddy, Pavan; Ayuk, Francis; Holler, Ernst; Efebera, Yvonne A; Hogan, William J; Wölfl, Matthias; Qayed, Muna; Hexner, Elizabeth O; Wudhikarn, Kitsada; Ordemann, Rainer; Young, Rachel; Shah, Jay; Hartwell, Matthew J; Chaudhry, Mohammed; Aziz, Mina; Etra, Aaron; Yanik, Gregory A; Kröger, Nicolaus; Weber, Daniela; Chen, Yi-Bin; Nakamura, Ryotaro; Rösler, Wolf; Kitko, Carrie L; Harris, Andrew C; Pulsipher, Michael; Reshef, Ran; Kowalyk, Steven; Morales, George; Torres, Ivan; Özbek, Umut; Ferrara, James L M; Levine, John E

    2018-03-15

    Acute graft versus host disease (GVHD) is treated with systemic corticosteroid immunosuppression. Clinical response after one week of therapy often guides further treatment decisions, but long term outcomes vary widely between centers and more accurate predictive tests are urgently needed. We analyzed clinical data and blood samples taken after one week of systemic treatment for GVHD from 507 patients from 17 centers of the Mount Sinai Acute GVHD International Consortium (MAGIC), dividing them into test (n=236) and two validation cohorts separated in time (n = 142 and 129, respectively). Initial response to systemic steroids correlated with response at four weeks, one-year non-relapse mortality (NRM) and overall survival (OS). A previously validated algorithm of two MAGIC biomarkers (ST2 and REG3α) consistently separated steroid resistant patients into two groups with dramatically different NRM and OS (p<0.001 for all three cohorts). High biomarker probability, resistance to steroids and GVHD severity (Minnesota risk) were all significant predictors of NRM in multivariate analysis. A direct comparison of receiver operating curves showed the area under the curve for biomarker probability (0.82) was significantly greater than that for steroid response (0.68, p=0.004) and for Minnesota risk (0.72, p=0.005). In conclusion, MAGIC biomarker probabilities generated after one week of systemic treatment for GVHD predict long term outcomes in steroid resistant GVHD better than clinical criteria and should prove useful in developing better treatment strategies. Copyright © 2018 American Society of Hematology.

  15. Elevation in inflammatory serum biomarkers predicts response to trastuzumab-containing therapy.

    Directory of Open Access Journals (Sweden)

    Ahmed A Alkhateeb

    Full Text Available Approximately half of all HER2/neu-overexpressing breast cancer patients do not respond to trastuzumab-containing therapy. Therefore, there remains an urgent and unmet clinical need for the development of predictive biomarkers for trastuzumab response. Recently, several lines of evidence have demonstrated that the inflammatory tumor microenvironment is a major contributor to therapy resistance in breast cancer. In order to explore the predictive value of inflammation in breast cancer patients, we measured the inflammatory biomarkers serum ferritin and C-reactive protein (CRP in 66 patients immediately before undergoing trastuzumab-containing therapy and evaluated their progression-free and overall survival. The elevation in pre-treatment serum ferritin (>250 ng/ml or CRP (>7.25 mg/l was a significant predictor of reduced progression-free survival and shorter overall survival. When patients were stratified based on their serum ferritin and CRP levels, patients with elevation in both inflammatory biomarkers had a markedly poorer response to trastuzumab-containing therapy. Therefore, the elevation in inflammatory serum biomarkers may reflect a pathological state that decreases the clinical efficacy of this therapy. Anti-inflammatory drugs and life-style changes to decrease inflammation in cancer patients should be explored as possible strategies to sensitize patients to anti-cancer therapeutics.

  16. Prospective evaluation of biomarkers for prediction of quality of life in community-acquired pneumonia.

    Science.gov (United States)

    Nickler, Manuela; Schaffner, Daniela; Christ-Crain, Mirjam; Ottiger, Manuel; Thomann, Robert; Hoess, Claus; Henzen, Christoph; Mueller, Beat; Schuetz, Philipp

    2016-11-01

    Most clinical research investigated prognostic biomarkers for their ability to predict cardiovascular events or mortality. It is unknown whether biomarkers allow prediction of quality of life (QoL) after survival of the acute event. Herein, we investigated the prognostic potential of well-established inflammatory/cardiovascular blood biomarkers including white blood cells (WBC), C-reactive protein (CRP), procalcitonin (PCT), pro-adrenomedullin (proADM) and pro-atrial natriuretic peptide (proANP) in regard to a decline in QoL in a well-defined cohort of patients with community-acquired pneumonia (CAP). Within this secondary analysis including 753 patients with a final inpatient diagnosis of CAP from a multicenter trial, we investigated associations between admission biomarker levels and decline in QoL assessed by the EQ-5D health questionnaire from admission to day 30 and after 6 years. Admission proADM and proANP levels significantly predicted decline of the weighted EQ-5D index after 30 days (n=753) with adjusted odds ratios (ORs) of 2.0 ([95% CI 1.1-3.8]; p=0.027) and 3.7 ([95% CI 2.2-6.0]; pscale (VAS). Initial WBC, PCT and CRP values did not well predict QoL at any time point. ProADM and proANP accurately predict short- and long-term decline in QoL across most dimensions in CAP patients. It will be interesting to reveal underlying physiopathology in future studies.

  17. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error.

    Science.gov (United States)

    Shipitsin, M; Small, C; Choudhury, S; Giladi, E; Friedlander, S; Nardone, J; Hussain, S; Hurley, A D; Ernst, C; Huang, Y E; Chang, H; Nifong, T P; Rimm, D L; Dunyak, J; Loda, M; Berman, D M; Blume-Jensen, P

    2014-09-09

    Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. Prostatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy-sampling error, a core from a high- and a low-Gleason area from each patient sample was used to generate a 'high' and a 'low' tumour microarray, respectively. Using a quantitative proteomics approach, we identified from 160 candidates 12 biomarkers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high- and low-Gleason areas. Conversely, a previously reported lethal outcome-predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sampling error. Our results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.

  18. Robust prediction of anti-cancer drug sensitivity and sensitivity-specific biomarker.

    Directory of Open Access Journals (Sweden)

    Heewon Park

    Full Text Available The personal genomics era has attracted a large amount of attention for anti-cancer therapy by patient-specific analysis. Patient-specific analysis enables discovery of individual genomic characteristics for each patient, and thus we can effectively predict individual genetic risk of disease and perform personalized anti-cancer therapy. Although the existing methods for patient-specific analysis have successfully uncovered crucial biomarkers, their performance takes a sudden turn for the worst in the presence of outliers, since the methods are based on non-robust manners. In practice, clinical and genomic alterations datasets usually contain outliers from various sources (e.g., experiment error, coding error, etc. and the outliers may significantly affect the result of patient-specific analysis. We propose a robust methodology for patient-specific analysis in line with the NetwrokProfiler. In the proposed method, outliers in high dimensional gene expression levels and drug response datasets are simultaneously controlled by robust Mahalanobis distance in robust principal component space. Thus, we can effectively perform for predicting anti-cancer drug sensitivity and identifying sensitivity-specific biomarkers for individual patients. We observe through Monte Carlo simulations that the proposed robust method produces outstanding performances for predicting response variable in the presence of outliers. We also apply the proposed methodology to the Sanger dataset in order to uncover cancer biomarkers and predict anti-cancer drug sensitivity, and show the effectiveness of our method.

  19. Utility of Urinary Biomarkers in Predicting Loss of Residual Renal Function: The balANZ Trial

    Science.gov (United States)

    Cho, Yeoungjee; Johnson, David W.; Vesey, David A.; Hawley, Carmel M.; Clarke, Margaret; Topley, Nicholas

    2015-01-01

    ♦ Background: The ability of urinary biomarkers to predict residual renal function (RRF) decline in peritoneal dialysis (PD) patients has not been defined. The present study aimed to explore the utility of established biomarkers from kidney injury models for predicting loss of RRF in incident PD patients, and to evaluate the impact on RRF of using neutral-pH PD solution low in glucose degradation products. ♦ Methods: The study included 50 randomly selected participants from the balANZ trial who had completed 24 months of follow-up. A change in glomerular filtration rate (GFR) was used as the primary clinical outcome measure. In a mixed-effects general linear model, baseline measurements of 18 novel urinary biomarkers and albumin were used to predict GFR change. The model was further used to evaluate the impact of biocompatible PD solution on RRF, adjusted for each biomarker. ♦ Results: Baseline albuminuria was not a useful predictor of change in RRF in PD patients (p = 0.84). Only clusterin was a significant predictor of GFR decline in the whole population (p = 0.04, adjusted for baseline GFR and albuminuria). However, the relationship was no longer apparent when albuminuria was removed from the model (p = 0.31). When the effect of the administered PD solutions was examined using a model adjusted for PD solution type, baseline albuminuria, and GFR, higher baseline urinary concentrations of trefoil factor 3 (TFF3, p = 0.02), kidney injury molecule 1 (KIM-1, p = 0.04), and interferon γ-induced protein 10 (IP-10, p = 0.03) were associated with more rapid decline of RRF in patients receiving conventional PD solution compared with biocompatible PD solution. ♦ Conclusions: Higher urinary levels of kidney injury biomarkers (TFF3, KIM-1, IP-10) at baseline predicted significantly slower RRF decline in patients receiving biocompatible PD solutions. Findings from the present investigation should help to guide future studies to validate the utility of urinary

  20. Robust early pregnancy prediction of later preeclampsia using metabolomic biomarkers.

    LENUS (Irish Health Repository)

    Kenny, Louise C

    2012-01-31

    Preeclampsia is a pregnancy-specific syndrome that causes substantial maternal and fetal morbidity and mortality. The etiology is incompletely understood, and there is no clinically useful screening test. Current metabolomic technologies have allowed the establishment of metabolic signatures of preeclampsia in early pregnancy. Here, a 2-phase discovery\\/validation metabolic profiling study was performed. In the discovery phase, a nested case-control study was designed, using samples obtained at 15+\\/-1 weeks\\' gestation from 60 women who subsequently developed preeclampsia and 60 controls taking part in the prospective Screening for Pregnancy Endpoints cohort study. Controls were proportionally population matched for age, ethnicity, and body mass index at booking. Plasma samples were analyzed using ultra performance liquid chromatography-mass spectrometry. A multivariate predictive model combining 14 metabolites gave an odds ratio for developing preeclampsia of 36 (95% CI: 12 to 108), with an area under the receiver operator characteristic curve of 0.94. These findings were then validated using an independent case-control study on plasma obtained at 15+\\/-1 weeks from 39 women who subsequently developed preeclampsia and 40 similarly matched controls from a participating center in a different country. The same 14 metabolites produced an odds ratio of 23 (95% CI: 7 to 73) with an area under receiver operator characteristic curve of 0.92. The finding of a consistent discriminatory metabolite signature in early pregnancy plasma preceding the onset of preeclampsia offers insight into disease pathogenesis and offers the tantalizing promise of a robust presymptomatic screening test.

  1. Robust Early Pregnancy Prediction of Later Preeclampsia Using Metabolomic Biomarkers.

    LENUS (Irish Health Repository)

    Kenny, Louise C

    2010-09-13

    Preeclampsia is a pregnancy-specific syndrome that causes substantial maternal and fetal morbidity and mortality. The etiology is incompletely understood, and there is no clinically useful screening test. Current metabolomic technologies have allowed the establishment of metabolic signatures of preeclampsia in early pregnancy. Here, a 2-phase discovery\\/validation metabolic profiling study was performed. In the discovery phase, a nested case-control study was designed, using samples obtained at 15±1 weeks\\' gestation from 60 women who subsequently developed preeclampsia and 60 controls taking part in the prospective Screening for Pregnancy Endpoints cohort study. Controls were proportionally population matched for age, ethnicity, and body mass index at booking. Plasma samples were analyzed using ultra performance liquid chromatography-mass spectrometry. A multivariate predictive model combining 14 metabolites gave an odds ratio for developing preeclampsia of 36 (95% CI: 12 to 108), with an area under the receiver operator characteristic curve of 0.94. These findings were then validated using an independent case-control study on plasma obtained at 15±1 weeks from 39 women who subsequently developed preeclampsia and 40 similarly matched controls from a participating center in a different country. The same 14 metabolites produced an odds ratio of 23 (95% CI: 7 to 73) with an area under receiver operator characteristic curve of 0.92. The finding of a consistent discriminatory metabolite signature in early pregnancy plasma preceding the onset of preeclampsia offers insight into disease pathogenesis and offers the tantalizing promise of a robust presymptomatic screening test.

  2. Towards understanding and predicting suicidality in women: biomarkers and clinical risk assessment.

    Science.gov (United States)

    Levey, D F; Niculescu, E M; Le-Niculescu, H; Dainton, H L; Phalen, P L; Ladd, T B; Weber, H; Belanger, E; Graham, D L; Khan, F N; Vanipenta, N P; Stage, E C; Ballew, A; Yard, M; Gelbart, T; Shekhar, A; Schork, N J; Kurian, S M; Sandusky, G E; Salomon, D R; Niculescu, A B

    2016-06-01

    Women are under-represented in research on suicidality to date. Although women have a lower rate of suicide completion than men, due in part to the less-violent methods used, they have a higher rate of suicide attempts. Our group has previously identified genomic (blood gene expression biomarkers) and clinical information (apps) predictors for suicidality in men. We now describe pilot studies in women. We used a powerful within-participant discovery approach to identify genes that change in expression between no suicidal ideation (no SI) and high suicidal ideation (high SI) states (n=12 participants out of a cohort of 51 women psychiatric participants followed longitudinally, with diagnoses of bipolar disorder, depression, schizoaffective disorder and schizophrenia). We then used a Convergent Functional Genomics (CFG) approach to prioritize the candidate biomarkers identified in the discovery step by using all the prior evidence in the field. Next, we validated for suicidal behavior the top-ranked biomarkers for SI, in a demographically matched cohort of women suicide completers from the coroner's office (n=6), by assessing which markers were stepwise changed from no SI to high SI to suicide completers. We then tested the 50 biomarkers that survived Bonferroni correction in the validation step, as well as top increased and decreased biomarkers from the discovery and prioritization steps, in a completely independent test cohort of women psychiatric disorder participants for prediction of SI (n=33) and in a future follow-up cohort of psychiatric disorder participants for prediction of psychiatric hospitalizations due to suicidality (n=24). Additionally, we examined how two clinical instruments in the form of apps, Convergent Functional Information for Suicidality (CFI-S) and Simplified Affective State Scale (SASS), previously tested in men, perform in women. The top CFI-S item distinguishing high SI from no SI states was the chronic stress of social isolation. We

  3. ASTRAL-R score predicts non-recanalisation after intravenous thrombolysis in acute ischaemic stroke.

    Science.gov (United States)

    Vanacker, Peter; Heldner, Mirjam R; Seiffge, David; Mueller, Hubertus; Eskandari, Ashraf; Traenka, Christopher; Ntaios, George; Mosimann, Pascal J; Sztajzel, Roman; Mendes Pereira, Vitor; Cras, Patrick; Engelter, Stefan; Lyrer, Philippe; Fischer, Urs; Lambrou, Dimitris; Arnold, Marcel; Michel, Patrik

    2015-05-01

    Intravenous thrombolysis (IVT) as treatment in acute ischaemic strokes may be insufficient to achieve recanalisation in certain patients. Predicting probability of non-recanalisation after IVT may have the potential to influence patient selection to more aggressive management strategies. We aimed at deriving and internally validating a predictive score for post-thrombolytic non-recanalisation, using clinical and radiological variables. In thrombolysis registries from four Swiss academic stroke centres (Lausanne, Bern, Basel and Geneva), patients were selected with large arterial occlusion on acute imaging and with repeated arterial assessment at 24 hours. Based on a logistic regression analysis, an integer-based score for each covariate of the fitted multivariate model was generated. Performance of integer-based predictive model was assessed by bootstrapping available data and cross validation (delete-d method). In 599 thrombolysed strokes, five variables were identified as independent predictors of absence of recanalisation: Acute glucose > 7 mmol/l (A), significant extracranial vessel STenosis (ST), decreased Range of visual fields (R), large Arterial occlusion (A) and decreased Level of consciousness (L). All variables were weighted 1, except for (L) which obtained 2 points based on β-coefficients on the logistic scale. ASTRAL-R scores 0, 3 and 6 corresponded to non-recanalisation probabilities of 18, 44 and 74 % respectively. Predictive ability showed AUC of 0.66 (95 %CI, 0.61-0.70) when using bootstrap and 0.66 (0.63-0.68) when using delete-d cross validation. In conclusion, the 5-item ASTRAL-R score moderately predicts non-recanalisation at 24 hours in thrombolysed ischaemic strokes. If its performance can be confirmed by external validation and its clinical usefulness can be proven, the score may influence patient selection for more aggressive revascularisation strategies in routine clinical practice.

  4. Prehospital Acute Stroke Severity Scale to Predict Large Artery Occlusion: Design and Comparison With Other Scales.

    Science.gov (United States)

    Hastrup, Sidsel; Damgaard, Dorte; Johnsen, Søren Paaske; Andersen, Grethe

    2016-07-01

    We designed and validated a simple prehospital stroke scale to identify emergent large vessel occlusion (ELVO) in patients with acute ischemic stroke and compared the scale to other published scales for prediction of ELVO. A national historical test cohort of 3127 patients with information on intracranial vessel status (angiography) before reperfusion therapy was identified. National Institutes of Health Stroke Scale (NIHSS) items with the highest predictive value of occlusion of a large intracranial artery were identified, and the most optimal combination meeting predefined criteria to ensure usefulness in the prehospital phase was determined. The predictive performance of Prehospital Acute Stroke Severity (PASS) scale was compared with other published scales for ELVO. The PASS scale was composed of 3 NIHSS scores: level of consciousness (month/age), gaze palsy/deviation, and arm weakness. In derivation of PASS 2/3 of the test cohort was used and showed accuracy (area under the curve) of 0.76 for detecting large arterial occlusion. Optimal cut point ≥2 abnormal scores showed: sensitivity=0.66 (95% CI, 0.62-0.69), specificity=0.83 (0.81-0.85), and area under the curve=0.74 (0.72-0.76). Validation on 1/3 of the test cohort showed similar performance. Patients with a large artery occlusion on angiography with PASS ≥2 had a median NIHSS score of 17 (interquartile range=6) as opposed to PASS <2 with a median NIHSS score of 6 (interquartile range=5). The PASS scale showed equal performance although more simple when compared with other scales predicting ELVO. The PASS scale is simple and has promising accuracy for prediction of ELVO in the field. © 2016 American Heart Association, Inc.

  5. Using Brain Oscillations and Corticospinal Excitability to Understand and Predict Post-Stroke Motor Function

    Directory of Open Access Journals (Sweden)

    Aurore Thibaut

    2017-05-01

    Full Text Available What determines motor recovery in stroke is still unknown and finding markers that could predict and improve stroke recovery is a challenge. In this study, we aimed at understanding the neural mechanisms of motor function recovery after stroke using neurophysiological markers by means of cortical excitability (transcranial magnetic stimulation—TMS and brain oscillations (electroencephalography—EEG. In this cross-sectional study, 55 subjects with chronic stroke (62 ± 14 yo, 17 women, 32 ± 42 months post-stroke were recruited in two sites. We analyzed TMS measures (i.e., motor threshold—MT—of the affected and unaffected sides and EEG variables (i.e., power spectrum in different frequency bands and different brain regions of the affected and unaffected hemispheres and their correlation with motor impairment as measured by Fugl-Meyer. Multiple univariate and multivariate linear regression analyses were performed to identify the predictors of good motor function. A significant interaction effect of MT in the affected hemisphere and power in beta bandwidth over the central region for both affected and unaffected hemispheres was found. We identified that motor function positively correlates with beta rhythm over the central region of the unaffected hemisphere, while it negatively correlates with beta rhythm in the affected hemisphere. Our results suggest that cortical activity in the affected and unaffected hemisphere measured by EEG provides new insights on the association between high-frequency rhythms and motor impairment, highlighting the role of an excess of beta in the affected central cortical region in poor motor function in stroke recovery.

  6. The development and implementation of stroke risk prediction model in National Health Insurance Service's personal health record.

    Science.gov (United States)

    Lee, Jae-Woo; Lim, Hyun-Sun; Kim, Dong-Wook; Shin, Soon-Ae; Kim, Jinkwon; Yoo, Bora; Cho, Kyung-Hee

    2018-01-01

    The purpose of this study was to build a 10-year stroke prediction model and categorize a probability of stroke using the Korean national health examination data. Then it intended to develop the algorithm to provide a personalized warning on the basis of each user's level of stroke risk and a lifestyle correction message about the stroke risk factors. Subject to national health examinees in 2002-2003, the stroke prediction model identified when stroke was first diagnosed by following-up the cohort until 2013 and estimated a 10-year probability of stroke. It sorted the user's individual probability of stroke into five categories - normal, slightly high, high, risky, very risky, according to the five ranges of average probability of stroke in comparison to total population - less than 50 percentile, 50-70, 70-90, 90-99.9, more than 99.9 percentile, and constructed the personalized warning and lifestyle correction messages by each category. Risk factors in stroke risk model include the age, BMI, cholesterol, hypertension, diabetes, smoking status and intensity, physical activity, alcohol drinking, past history (hypertension, coronary heart disease) and family history (stroke, coronary heart disease). The AUC values of stroke risk prediction model from the external validation data set were 0.83 in men and 0.82 in women, which showed a high predictive power. The probability of stroke within 10 years for men in normal group (less than 50 percentile) was less than 3.92% and those in very risky group (top 0.01 percentile) was 66.2% and over. The women's probability of stroke within 10 years was less than 3.77% in normal group (less than 50 percentile) and 55.24% and over in very risky group. This study developed the stroke risk prediction model and the personalized warning and the lifestyle correction message based on the national health examination data and uploaded them to the personal health record service called My Health Bank in the health information website - Health

  7. IGFBP3 methylation is a novel diagnostic and predictive biomarker in colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Lucia Perez-Carbonell

    Full Text Available Aberrant hypermethylation of cancer-related genes has emerged as a promising strategy for the development of diagnostic, prognostic and predictive biomarkers in human cancer, including colorectal cancer (CRC. The aim of this study was to perform a systematic and comprehensive analysis of a panel of CRC-specific genes as potential diagnostic, prognostic and predictive biomarkers in a large, population-based CRC cohort.Methylation status of the SEPT9, TWIST1, IGFBP3, GAS7, ALX4 and miR137 genes was studied by quantitative bisulfite pyrosequencing in a population-based cohort of 425 CRC patients.Methylation levels of all genes analyzed were significantly higher in tumor tissues compared to normal mucosa (p<0.0001; however, cancer-associated hypermethylation was most frequently observed for miR137 (86.7% and IGFBP3 (83% in CRC patients. Methylation analysis using the combination of these two genes demonstrated greatest accuracy for the identification of colonic tumors (sensitivity 95.5%; specificity 90.5%. Low levels of IGFBP3 promoter methylation emerged as an independent risk factor for predicting poor disease free survival in stage II and III CRC patients (HR = 0.49, 95% CI: 0.28-0.85, p = 0.01. Our results also suggest that stage II & III CRC patients with high levels of IGFBP3 methylation do not benefit from adjuvant 5FU-based chemotherapy.By analyzing a large, population-based CRC cohort, we demonstrate the potential clinical significance of miR137 and IGFBP3 hypermethylation as promising diagnostic biomarkers in CRC. Our data also revealed that IGFBP3 hypermethylation may serve as an independent prognostic and predictive biomarker in stage II and III CRC patients.

  8. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error

    OpenAIRE

    Shipitsin, M; Small, C; Choudhury, S; Giladi, E; Friedlander, S; Nardone, J; Hussain, S; Hurley, A D; Ernst, C; Huang, Y E; Chang, H; Nifong, T P; Rimm, D L; Dunyak, J; Loda, M

    2014-01-01

    Background: Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. Methods: Prostatectom...

  9. Discovery of serum biomarkers predicting development of a subsequent depressive episode in social anxiety disorder.

    Science.gov (United States)

    Gottschalk, M G; Cooper, J D; Chan, M K; Bot, M; Penninx, B W J H; Bahn, S

    2015-08-01

    Although social anxiety disorder (SAD) is strongly associated with the subsequent development of a depressive disorder (major depressive disorder or dysthymia), no underlying biological risk factors are known. We aimed to identify biomarkers which predict depressive episodes in SAD patients over a 2-year follow-up period. One hundred sixty-five multiplexed immunoassay analytes were investigated in blood serum of 143 SAD patients without co-morbid depressive disorders, recruited within the Netherlands Study of Depression and Anxiety (NESDA). Predictive performance of identified biomarkers, clinical variables and self-report inventories was assessed using receiver operating characteristics curves (ROC) and represented by the area under the ROC curve (AUC). Stepwise logistic regression resulted in the selection of four serum analytes (AXL receptor tyrosine kinase, vascular cell adhesion molecule 1, vitronectin, collagen IV) and four additional variables (Inventory of Depressive Symptomatology, Beck Anxiety Inventory somatic subscale, depressive disorder lifetime diagnosis, BMI) as optimal set of patient parameters. When combined, an AUC of 0.86 was achieved for the identification of SAD individuals who later developed a depressive disorder. Throughout our analyses, biomarkers yielded superior discriminative performance compared to clinical variables and self-report inventories alone. We report the discovery of a serum marker panel with good predictive performance to identify SAD individuals prone to develop subsequent depressive episodes in a naturalistic cohort design. Furthermore, we emphasise the importance to combine biological markers, clinical variables and self-report inventories for disease course predictions in psychiatry. Following replication in independent cohorts, validated biomarkers could help to identify SAD patients at risk of developing a depressive disorder, thus facilitating early intervention. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. External Validation of the ISAN, A2DS2, and AIS-APS Scores for Predicting Stroke-Associated Pneumonia.

    Science.gov (United States)

    Zapata-Arriaza, Elena; Moniche, Francisco; Blanca, Pardo-Galiana; Bustamante, Alejandro; Escudero-Martínez, Irene; Uclés, Oscar; Ollero-Ortiz, Ángela; Sánchez-García, Jose Antonio; Gamero, Miguel Ángel; Quesada, Ángeles; Vidal De Francisco, Diana; Romera, Mercedes; De la Cruz, Carlos; Sanz, Gema; Montaner, Joan

    2018-03-01

    The Prestroke Independence, Sex, Age, National Institutes of Health Stroke Scale (ISAN), Age, Atrial Fibrillation, Dysphagia, male sex, and National Institutes of Health Stroke Scale (A2DS2), and acute ischemic stroke-associated pneumonia score (AIS-APS) scores were created to predict stroke-associated pneumonia (SAP), one of the most important medical stroke complications. External validation of all such scores in an acute stroke population was the aim of our study. Patients with ischemic or hemorrhagic stroke were prospectively enrolled in the multicenter Stroke-Induced Pneumonia in Andalucía project between October 2014 and May 2016. Receiver operating characteristic curves and linear regression analyses were used to determine discrimination ability of the scores. The Hosmer-Lemeshow goodness-of-fit test and the plot of observed versus predicted SAP risk were used to assess model calibration. Among 201 included patients, SAP rate was 15.5% (31). Higher ISAN, A2DS2, and AIS-APS scores were related to SAP (all P manage SAP. The AIS-APS score would be recommendable for the development of future clinical trials. Copyright © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  11. Sputum biomarkers and the prediction of clinical outcomes in patients with cystic fibrosis.

    Directory of Open Access Journals (Sweden)

    Theodore G Liou

    Full Text Available Lung function, acute pulmonary exacerbations (APE, and weight are the best clinical predictors of survival in cystic fibrosis (CF; however, underlying mechanisms are incompletely understood. Biomarkers of current disease state predictive of future outcomes might identify mechanisms and provide treatment targets, trial endpoints and objective clinical monitoring tools. Such CF-specific biomarkers have previously been elusive. Using observational and validation cohorts comprising 97 non-transplanted consecutively-recruited adult CF patients at the Intermountain Adult CF Center, University of Utah, we identified biomarkers informative of current disease and predictive of future clinical outcomes. Patients represented the majority of sputum producers. They were recruited March 2004-April 2007 and followed through May 2011. Sputum biomarker concentrations were measured and clinical outcomes meticulously recorded for a median 5.9 (interquartile range 5.0 to 6.6 years to study associations between biomarkers and future APE and time-to-lung transplantation or death. After multivariate modeling, only high mobility group box-1 protein (HMGB-1, mean=5.84 [log ng/ml], standard deviation [SD] =1.75 predicted time-to-first APE (hazard ratio [HR] per log-unit HMGB-1=1.56, p-value=0.005, number of future APE within 5 years (0.338 APE per log-unit HMGB-1, p<0.001 by quasi-Poisson regression and time-to-lung transplantation or death (HR=1.59, p=0.02. At APE onset, sputum granulocyte macrophage colony stimulating factor (GM-CSF, mean 4.8 [log pg/ml], SD=1.26 was significantly associated with APE-associated declines in lung function (-10.8 FEV(1% points per log-unit GM-CSF, p<0.001 by linear regression. Evaluation of validation cohorts produced similar results that passed tests of mutual consistency. In CF sputum, high HMGB-1 predicts incidence and recurrence of APE and survival, plausibly because it mediates long-term airway inflammation. High APE-associated GM

  12. AUC-based biomarker ensemble with an application on gene scores predicting low bone mineral density.

    Science.gov (United States)

    Zhao, X G; Dai, W; Li, Y; Tian, L

    2011-11-01

    The area under the receiver operating characteristic (ROC) curve (AUC), long regarded as a 'golden' measure for the predictiveness of a continuous score, has propelled the need to develop AUC-based predictors. However, the AUC-based ensemble methods are rather scant, largely due to the fact that the associated objective function is neither continuous nor concave. Indeed, there is no reliable numerical algorithm identifying optimal combination of a set of biomarkers to maximize the AUC, especially when the number of biomarkers is large. We have proposed a novel AUC-based statistical ensemble methods for combining multiple biomarkers to differentiate a binary response of interest. Specifically, we propose to replace the non-continuous and non-convex AUC objective function by a convex surrogate loss function, whose minimizer can be efficiently identified. With the established framework, the lasso and other regularization techniques enable feature selections. Extensive simulations have demonstrated the superiority of the new methods to the existing methods. The proposal has been applied to a gene expression dataset to construct gene expression scores to differentiate elderly women with low bone mineral density (BMD) and those with normal BMD. The AUCs of the resulting scores in the independent test dataset has been satisfactory. Aiming for directly maximizing AUC, the proposed AUC-based ensemble method provides an efficient means of generating a stable combination of multiple biomarkers, which is especially useful under the high-dimensional settings. lutian@stanford.edu. Supplementary data are available at Bioinformatics online.

  13. Predictive validity of the Sødring Motor Evaluation of Stroke Patients (SMES).

    Science.gov (United States)

    Wyller, T B; Sødring, K M; Sveen, U; Ljunggren, A E; Bautz-Holter, E

    1996-12-01

    The Sødring Motor Evaluation of Stroke Patients (SMES) has been developed as an instrument for the evaluation by physiotherapists of motor function and activities in stroke patients. The predictive validity of the instrument was studied in a consecutive sample of 93 acute stroke patients, assessed in the acute phase and after one year. The outcome measures were: survival, residence at home or in institution, the Barthel ADL index (dichotomized at 19/20), and the Frenchay Activities Index (FAI) (dichotomized at 9/10). The SMES, scored in the acute phase, demonstrated a marginally significant predictive power regarding survival, but was a highly significant predictor regarding the other outcomes. The adjusted odds ratio for a good versus a poor outcome for patients in the upper versus the lower tertile of the SMES arm subscore was 5.4 (95% confidence interval 0.9-59) for survival, 11.5 (2.1-88) for living at home, 86.3 (11-infinity) for a high Barthel score, and 31.4 (5.2-288) for a high FAI score. We conclude that SMES has high predictive validity.

  14. Doppler Ultrasonographic Parameters for Predicting Cerebral Vascular Reserve in Patients with Acute Ischemic Stroke

    International Nuclear Information System (INIS)

    Jung, Han Young; Lee, Hui Joong; Kim, Hye Jung; Kim, Yong Sun; Kang, Duk Sik

    2006-01-01

    We investigated Doppler ultrasonographic (US) parameters of patients with acute stroke to predict the cerebral vascular reserve (CVR) measured by SPECT. We reviewed the flow velocity and cross-sectional area of the circular vessel at the common, external, and internal carotid arteries (ICA) and the vertebral arteries (VA) in 109 acute stroke patients who underwent SPECT. Flow volume (FV) of each artery was calculated as the product of the angle-corrected time averaged flow velocity and cross-sectional area of the circular vessel. Total cerebral FV (TCBFV) was determined as the sum of the FVs of the right and left ICA and VA. We compared the Doppler US parameters between 44 cases of preserved and 65 cases of impaired CVR. In the preserved CVR group, ICA FV, anterior circulating FV (ACFV) and TCBFV were higher than in the impaired CVR group (p < 0.05, independent t-test). In the impaired CVR group, the ROC curves showed ACFV and TCBFV were suitable parameters to predict CVR (p < 0.05). Doppler US was helpful for understanding the hemodynamic state of acute stroke. FV measurement by Doppler US was useful for predicting CVR

  15. Atrophy of spared grey matter tissue predicts poorer motor recovery and rehabilitation response in chronic stroke

    Science.gov (United States)

    Gauthier, Lynne V.; Taub, Edward; Mark, Victor W.; Barghi, Ameen; Uswatte, Gitendra

    2011-01-01

    Background and Purpose Although the motor deficit following stroke is clearly due to the structural brain damage that has been sustained, this relationship is attenuated from the acute to chronic phases. We investigated the possibility that motor impairment and response to Constraint-Induced Movement therapy (CI therapy) in chronic stroke patients may relate more strongly to the structural integrity of brain structures remote from the lesion than to measures of overt tissue damage. Methods Voxel-based morphometry (VBM) analysis was performed on MRI scans from 80 chronic stroke patients to investigate whether variations in grey matter density were correlated with extent of residual motor impairment or with CI therapy-induced motor recovery. Results Decreased grey matter density in non-infarcted motor regions was significantly correlated with magnitude of residual motor deficit. In addition, reduced grey matter density in multiple remote brain regions predicted a lesser extent of motor improvement from CI therapy. Conclusions Atrophy in seemingly healthy parts of the brain that are distant from the infarct accounts for at least a portion of the sustained motor deficit in chronic stroke. PMID:22096036

  16. Posterior superior temporal sulcus responses predict perceived pleasantness of skin stroking

    Directory of Open Access Journals (Sweden)

    Monika Davidovic

    2016-09-01

    Full Text Available Love and affection is expressed through a range of physically intimate gestures, including caresses. Recent studies suggest that posterior temporal lobe areas typically associated with visual processing of social cues also respond to interpersonal touch. Here, we asked whether these areas are selective to caress-like skin stroking. We collected functional magnetic resonance imaging (fMRI data from 23 healthy participants and compared brain responses to skin stroking and vibration. We did not find any significant differences between stroking and vibration in the posterior temporal lobe; however, right posterior superior temporal sulcus (pSTS responses predicted healthy participant's perceived pleasantness of skin stroking, but not vibration. These findings link right pSTS responses to individual variability in perceived pleasantness of caress-like tactile stimuli. We speculate that the right pSTS may play a role in the translation of tactile stimuli into positively valenced, socially relevant interpersonal touch and that this system may be affected in disorders associated with impaired attachment.

  17. Baseline Vascular Cognitive Impairment Predicts the Course of Apathetic Symptoms After Stroke: The CASPER Study.

    Science.gov (United States)

    Douven, Elles; Köhler, Sebastian; Schievink, Syenna H J; van Oostenbrugge, Robert J; Staals, Julie; Verhey, Frans R J; Aalten, Pauline

    2018-03-01

    To examine the influence of vascular cognitive impairment (VCI) on the course of poststroke depression (PSD) and poststroke apathy (PSA). Included were 250 stroke patients who underwent neuropsychological and neuropsychiatric assessment 3 months after stroke (baseline) and at a 6- and 12-month follow-up after baseline. Linear mixed models tested the influence of VCI in at least one cognitive domain (any VCI) or multidomain VCI (VCI in multiple cognitive domains) at baseline and domain-specific VCI at baseline on levels of depression and apathy over time, with random effects for intercept and slope. Almost half of the patients showed any VCI at baseline, and any VCI was associated with increasing apathy levels from baseline to the 12-month follow-up. Patients with multidomain VCI had higher apathy scores at the 6- and 12-month follow-up compared with patients with VCI in a single cognitive domain. Domain-specific analyses showed that impaired executive function and slowed information processing speed went together with increasing apathy levels from baseline to 6- and 12-month follow-up. None of the cognitive variables predicted the course of depressive symptoms. Baseline VCI is associated with increasing apathy levels from baseline to the chronic stroke phase, whereas no association was found between baseline VCI and the course of depressive symptoms. Health professionals should be aware that apathy might be absent early after stroke but may evolve over time in patients with VCI. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  18. Inflammatory and Other Biomarkers: Role in Pathophysiology and Prediction of Gestational Diabetes Mellitus

    Science.gov (United States)

    Abell, Sally K.; De Courten, Barbora; Boyle, Jacqueline A.; Teede, Helena J.

    2015-01-01

    Understanding pathophysiology and identifying mothers at risk of major pregnancy complications is vital to effective prevention and optimal management. However, in current antenatal care, understanding of pathophysiology of complications is limited. In gestational diabetes mellitus (GDM), risk prediction is mostly based on maternal history and clinical risk factors and may not optimally identify high risk pregnancies. Hence, universal screening is widely recommended. Here, we will explore the literature on GDM and biomarkers including inflammatory markers, adipokines, endothelial function and lipids to advance understanding of pathophysiology and explore risk prediction, with a goal to guide prevention and treatment of GDM. PMID:26110385

  19. Development and Validation of a Predictive Model for Functional Outcome After Stroke Rehabilitation: The Maugeri Model.

    Science.gov (United States)

    Scrutinio, Domenico; Lanzillo, Bernardo; Guida, Pietro; Mastropasqua, Filippo; Monitillo, Vincenzo; Pusineri, Monica; Formica, Roberto; Russo, Giovanna; Guarnaschelli, Caterina; Ferretti, Chiara; Calabrese, Gianluigi

    2017-12-01

    Prediction of outcome after stroke rehabilitation may help clinicians in decision-making and planning rehabilitation care. We developed and validated a predictive tool to estimate the probability of achieving improvement in physical functioning (model 1) and a level of independence requiring no more than supervision (model 2) after stroke rehabilitation. The models were derived from 717 patients admitted for stroke rehabilitation. We used multivariable logistic regression analysis to build each model. Then, each model was prospectively validated in 875 patients. Model 1 included age, time from stroke occurrence to rehabilitation admission, admission motor and cognitive Functional Independence Measure scores, and neglect. Model 2 included age, male gender, time since stroke onset, and admission motor and cognitive Functional Independence Measure score. Both models demonstrated excellent discrimination. In the derivation cohort, the area under the curve was 0.883 (95% confidence intervals, 0.858-0.910) for model 1 and 0.913 (95% confidence intervals, 0.884-0.942) for model 2. The Hosmer-Lemeshow χ 2 was 4.12 ( P =0.249) and 1.20 ( P =0.754), respectively. In the validation cohort, the area under the curve was 0.866 (95% confidence intervals, 0.840-0.892) for model 1 and 0.850 (95% confidence intervals, 0.815-0.885) for model 2. The Hosmer-Lemeshow χ 2 was 8.86 ( P =0.115) and 34.50 ( P =0.001), respectively. Both improvement in physical functioning (hazard ratios, 0.43; 0.25-0.71; P =0.001) and a level of independence requiring no more than supervision (hazard ratios, 0.32; 0.14-0.68; P =0.004) were independently associated with improved 4-year survival. A calculator is freely available for download at https://goo.gl/fEAp81. This study provides researchers and clinicians with an easy-to-use, accurate, and validated predictive tool for potential application in rehabilitation research and stroke management. © 2017 American Heart Association, Inc.

  20. MRI texture features as biomarkers to predict MGMT methylation status in glioblastomas

    Energy Technology Data Exchange (ETDEWEB)

    Korfiatis, Panagiotis; Kline, Timothy L.; Erickson, Bradley J., E-mail: bje@mayo.edu [Department of Radiology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Coufalova, Lucie [Department of Radiology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Department of Neurosurgery of First Faculty of Medicine, Charles University in Prague, Military University Hospital, Prague 128 21 (Czech Republic); International Clinical Research Center, St. Anne’s University Hospital Brno, Brno 656 91 (Czech Republic); Lachance, Daniel H. [Department of Neurology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Parney, Ian F. [Department of Neurologic Surgery, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Carter, Rickey E. [Department of Health Sciences Research, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Buckner, Jan C. [Department of Medical Oncology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States)

    2016-06-15

    Purpose: Imaging biomarker research focuses on discovering relationships between radiological features and histological findings. In glioblastoma patients, methylation of the O{sup 6}-methylguanine methyltransferase (MGMT) gene promoter is positively correlated with an increased effectiveness of current standard of care. In this paper, the authors investigate texture features as potential imaging biomarkers for capturing the MGMT methylation status of glioblastoma multiforme (GBM) tumors when combined with supervised classification schemes. Methods: A retrospective study of 155 GBM patients with known MGMT methylation status was conducted. Co-occurrence and run length texture features were calculated, and both support vector machines (SVMs) and random forest classifiers were used to predict MGMT methylation status. Results: The best classification system (an SVM-based classifier) had a maximum area under the receiver-operating characteristic (ROC) curve of 0.85 (95% CI: 0.78–0.91) using four texture features (correlation, energy, entropy, and local intensity) originating from the T2-weighted images, yielding at the optimal threshold of the ROC curve, a sensitivity of 0.803 and a specificity of 0.813. Conclusions: Results show that supervised machine learning of MRI texture features can predict MGMT methylation status in preoperative GBM tumors, thus providing a new noninvasive imaging biomarker.

  1. Improving diagnosis, prognosis and prediction by using biomarkers in CRC patients (Review).

    Science.gov (United States)

    Nikolouzakis, Taxiarchis Konstantinos; Vassilopoulou, Loukia; Fragkiadaki, Persefoni; Mariolis Sapsakos, Theodoros; Papadakis, Georgios Z; Spandidos, Demetrios A; Tsatsakis, Aristides M; Tsiaoussis, John

    2018-06-01

    Colorectal cancer (CRC) is among the most common cancers. In fact, it is placed in the third place among the most diagnosed cancer in men, after lung and prostate cancer, and in the second one for the most diagnosed cancer in women, following breast cancer. Moreover, its high mortality rates classifies it among the leading causes of cancer‑related death worldwide. Thus, in order to help clinicians to optimize their practice, it is crucial to introduce more effective tools that will improve not only early diagnosis, but also prediction of the most likely progression of the disease and response to chemotherapy. In that way, they will be able to decrease both morbidity and mortality of their patients. In accordance with that, colon cancer research has described numerous biomarkers for diagnostic, prognostic and predictive purposes that either alone or as part of a panel would help improve patient's clinical management. This review aims to describe the most accepted biomarkers among those proposed for use in CRC divided based on the clinical specimen that is examined (tissue, faeces or blood) along with their restrictions. Lastly, new insight in CRC monitoring will be discussed presenting promising emerging biomarkers (telomerase activity, telomere length and micronuclei frequency).

  2. MRI texture features as biomarkers to predict MGMT methylation status in glioblastomas

    International Nuclear Information System (INIS)

    Korfiatis, Panagiotis; Kline, Timothy L.; Erickson, Bradley J.; Coufalova, Lucie; Lachance, Daniel H.; Parney, Ian F.; Carter, Rickey E.; Buckner, Jan C.

    2016-01-01

    Purpose: Imaging biomarker research focuses on discovering relationships between radiological features and histological findings. In glioblastoma patients, methylation of the O 6 -methylguanine methyltransferase (MGMT) gene promoter is positively correlated with an increased effectiveness of current standard of care. In this paper, the authors investigate texture features as potential imaging biomarkers for capturing the MGMT methylation status of glioblastoma multiforme (GBM) tumors when combined with supervised classification schemes. Methods: A retrospective study of 155 GBM patients with known MGMT methylation status was conducted. Co-occurrence and run length texture features were calculated, and both support vector machines (SVMs) and random forest classifiers were used to predict MGMT methylation status. Results: The best classification system (an SVM-based classifier) had a maximum area under the receiver-operating characteristic (ROC) curve of 0.85 (95% CI: 0.78–0.91) using four texture features (correlation, energy, entropy, and local intensity) originating from the T2-weighted images, yielding at the optimal threshold of the ROC curve, a sensitivity of 0.803 and a specificity of 0.813. Conclusions: Results show that supervised machine learning of MRI texture features can predict MGMT methylation status in preoperative GBM tumors, thus providing a new noninvasive imaging biomarker.

  3. Blood DNA methylation biomarkers predict clinical reactivity in food-sensitized infants.

    Science.gov (United States)

    Martino, David; Dang, Thanh; Sexton-Oates, Alexandra; Prescott, Susan; Tang, Mimi L K; Dharmage, Shyamali; Gurrin, Lyle; Koplin, Jennifer; Ponsonby, Anne-Louise; Allen, Katrina J; Saffery, Richard

    2015-05-01

    The diagnosis of food allergy (FA) can be challenging because approximately half of food-sensitized patients are asymptomatic. Current diagnostic tests are excellent makers of sensitization but poor predictors of clinical reactivity. Thus oral food challenges (OFCs) are required to determine a patient's risk of reactivity. We sought to discover genomic biomarkers of clinical FA with utility for predicting food challenge outcomes. Genome-wide DNA methylation (DNAm) profiling was performed on blood mononuclear cells from volunteers who had undergone objective OFCs, concurrent skin prick tests, and specific IgE tests. Fifty-eight food-sensitized patients (aged 11-15 months) were assessed, half of whom were clinically reactive. Thirteen nonallergic control subjects were also assessed. Reproducibility was assessed in an additional 48 samples by using methylation data from an independent population of patients with clinical FA. Using a supervised learning approach, we discovered a DNAm signature of 96 CpG sites that predict clinical outcomes. Diagnostic scores were derived from these 96 methylation sites, and cutoffs were determined in a sensitivity analysis. Methylation biomarkers outperformed allergen-specific IgE and skin prick tests for predicting OFC outcomes. FA status was correctly predicted in the replication cohort with an accuracy of 79.2%. DNAm biomarkers with clinical utility for predicting food challenge outcomes are readily detectable in blood. The development of this technology in detailed follow-up studies will yield highly innovative diagnostic assays. Copyright © 2015 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

  4. Common genetic markers and prediction of recurrent events after ischemic stroke in young adults.

    Science.gov (United States)

    Pezzini, A; Grassi, M; Del Zotto, E; Lodigiani, C; Ferrazzi, P; Spalloni, A; Patella, R; Giossi, A; Volonghi, I; Iacoviello, L; Magoni, M; Rota, L L; Rasura, M; Padovani, A

    2009-09-01

    Scarce information is available on the usefulness of new prediction markers for identifying young ischemic stroke patients at highest risk of recurrence. The predictive effect of traditional risk factors as well as of the 20210A variant of prothrombin gene, the 1691A variant of factor V gene, and the TT677 genotype of the methylenetetrahydrofolate reductase (MTHFR) gene on the risk of recurrence was investigated in a hospital-based cohort study of 511 ischemic stroke patients younger than 45 years followed up for a mean of 43.4 months. Outcome measures were fatal/nonfatal myocardial infarction, ischemic stroke, or TIA. Risk prediction was assessed with the use of the concordance c (c index), and the Net Reclassification Improvement (NRI). The risk of recurrence increased with increasing number of traditional factors (hazard ratio [HR] 2.29, 95% confidence interval [CI] 1.57-3.35 for subjects with 1 factor: HR 5.25, 95% CI 2.45-11.2 for subjects with 2), as well as with that of predisposing genotypes (HR 1.96, 95% CI 1.33-2.89 for subjects carrying 1 at-risk genotype; HR 3.83, 95% CI 1.76-8.34 for those carrying 2). The c statistics increased significantly when the genotypes were included into a model with traditional risk factors (0.696 vs 0.635, test z = 2.41). The NRI was also significant (NRI = 0.172, test z = 2.17). Addition of common genetic variants to traditional risk factors may be an effective method for discriminating young stroke patients at different risk of future ischemic events.

  5. Predictive Power Estimation Algorithm (PPEA--a new algorithm to reduce overfitting for genomic biomarker discovery.

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    Jiangang Liu

    Full Text Available Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA, which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1 PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2 the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3 using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4 more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses.

  6. Improved Outcome Prediction Using CT Angiography in Addition to Standard Ischemic Stroke Assessment: Results from the STOPStroke Study

    Science.gov (United States)

    González, R. Gilberto; Lev, Michael H.; Goldmacher, Gregory V.; Smith, Wade S.; Payabvash, Seyedmehdi; Harris, Gordon J.; Halpern, Elkan F.; Koroshetz, Walter J.; Camargo, Erica C. S.; Dillon, William P.; Furie, Karen L.

    2012-01-01

    Purpose To improve ischemic stroke outcome prediction using imaging information from a prospective cohort who received admission CT angiography (CTA). Methods In a prospectively designed study, 649 stroke patients diagnosed with acute ischemic stroke had admission NIH stroke scale scores, noncontrast CT (NCCT), CTA, and 6-month outcome assessed using the modified Rankin scale (mRS) scores. Poor outcome was defined as mRS>2. Strokes were classified as “major” by the (1) Alberta Stroke Program Early CT Score (ASPECTS+) if NCCT ASPECTS was≤7; (2) Boston Acute Stroke Imaging Scale (BASIS+) if they were ASPECTS+ or CTA showed occlusion of the distal internal carotid, proximal middle cerebral, or basilar arteries; and (3) NIHSS for scores>10. Results Of 649 patients, 253 (39.0%) had poor outcomes. NIHSS, BASIS, and age, but not ASPECTS, were independent predictors of outcome. BASIS and NIHSS had similar sensitivities, both superior to ASPECTS (p10/BASIS+ had poor outcomes, versus 21.5% (77/358) with NIHSS≤10/BASIS− (p10/BASIS+ compared to patients who are NIHSS≤10/BASIS−; the odds ratio is 5.4 (95% CI: 3.5 to 8.5) when compared to patients who are only NIHSS>10 or BASIS+. Conclusions BASIS and NIHSS are independent outcome predictors. Their combination is stronger than either instrument alone in predicting outcomes. The findings suggest that CTA is a significant clinical tool in routine acute stroke assessment. PMID:22276182

  7. Effects and mechanism of the HECT study (hybrid exercise-cognitive trainings in mild ischemic stroke with cognitive decline: fMRI for brain plasticity, biomarker and behavioral analysis

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    Ting-ting Yeh

    2018-03-01

    Methods and significance: This study is a single-blind randomized controlled trial. A target sample size of 75 participants is needed to obtain a statistical power of 95% with a significance level of 5%. Stroke survivors with mild cognitive decline will be stratified by Mini-Mental State Examination scores and then randomized 1:1:1 to sequential exercise-cognitive training, dual-task exercise-cognitive training or control groups. All groups will undergo training 60 min/day, 3 days/week, for a total of 12 weeks. The primary outcome is the resting-state functional connectivity and neural activation in the frontal, parietal and occipital lobes in functional magnetic resonance imaging. Secondary outcomes include physiological biomarkers, cognitive functions, physical function, daily functions and quality of life. This study may differentiate the effects of two hybridized trainings on cognitive function and health-related conditions and detect appropriate neurological and physiological indices to predict training effects. This study capitalizes on the groundwork for a non-pharmacological intervention of cognitive decline after stroke.

  8. Development and validation of clinical prediction models for mortality, functional outcome and cognitive impairment after stroke: a study protocol.

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    Fahey, Marion; Rudd, Anthony; Béjot, Yannick; Wolfe, Charles; Douiri, Abdel

    2017-08-18

    Stroke is a leading cause of adult disability and death worldwide. The neurological impairments associated with stroke prevent patients from performing basic daily activities and have enormous impact on families and caregivers. Practical and accurate tools to assist in predicting outcome after stroke at patient level can provide significant aid for patient management. Furthermore, prediction models of this kind can be useful for clinical research, health economics, policymaking and clinical decision support. 2869 patients with first-ever stroke from South London Stroke Register (SLSR) (1995-2004) will be included in the development cohort. We will use information captured after baseline to construct multilevel models and a Cox proportional hazard model to predict cognitive impairment, functional outcome and mortality up to 5 years after stroke. Repeated random subsampling validation (Monte Carlo cross-validation) will be evaluated in model development. Data from participants recruited to the stroke register (2005-2014) will be used for temporal validation of the models. Data from participants recruited to the Dijon Stroke Register (1985-2015) will be used for external validation. Discrimination, calibration and clinical utility of the models will be presented. Patients, or for patients who cannot consent their relatives, gave written informed consent to participate in stroke-related studies within the SLSR. The SLSR design was approved by the ethics committees of Guy's and St Thomas' NHS Foundation Trust, Kings College Hospital, Queens Square and Westminster Hospitals (London). The Dijon Stroke Registry was approved by the Comité National des Registres and the InVS and has authorisation of the Commission Nationale de l'Informatique et des Libertés. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  9. External validation of the MRI-DRAGON score: early prediction of stroke outcome after intravenous thrombolysis.

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    Turc, Guillaume; Aguettaz, Pierre; Ponchelle-Dequatre, Nelly; Hénon, Hilde; Naggara, Olivier; Leclerc, Xavier; Cordonnier, Charlotte; Leys, Didier; Mas, Jean-Louis; Oppenheim, Catherine

    2014-01-01

    The aim of our study was to validate in an independent cohort the MRI-DRAGON score, an adaptation of the (CT-) DRAGON score to predict 3-month outcome in acute ischemic stroke patients undergoing MRI before intravenous thrombolysis (IV-tPA). We reviewed consecutive (2009-2013) anterior circulation stroke patients treated within 4.5 hours by IV-tPA in the Lille stroke unit (France), where MRI is the first-line pretherapeutic work-up. We assessed the discrimination and calibration of the MRI-DRAGON score to predict poor 3-month outcome, defined as modified Rankin Score >2, using c-statistic and the Hosmer-Lemeshow test, respectively. We included 230 patients (mean ±SD age 70.4±16.0 years, median [IQR] baseline NIHSS 8 [5]-[14]; poor outcome in 78(34%) patients). The c-statistic was 0.81 (95%CI 0.75-0.87), and the Hosmer-Lemeshow test was not significant (p = 0.54). The MRI-DRAGON score showed good prognostic performance in the external validation cohort. It could therefore be used to inform the patient's relatives about long-term prognosis and help to identify poor responders to IV-tPA alone, who may be candidates for additional therapeutic strategies, if they are otherwise eligible for such procedures based on the institutional criteria.

  10. External validation of the MRI-DRAGON score: early prediction of stroke outcome after intravenous thrombolysis.

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    Guillaume Turc

    Full Text Available The aim of our study was to validate in an independent cohort the MRI-DRAGON score, an adaptation of the (CT- DRAGON score to predict 3-month outcome in acute ischemic stroke patients undergoing MRI before intravenous thrombolysis (IV-tPA.We reviewed consecutive (2009-2013 anterior circulation stroke patients treated within 4.5 hours by IV-tPA in the Lille stroke unit (France, where MRI is the first-line pretherapeutic work-up. We assessed the discrimination and calibration of the MRI-DRAGON score to predict poor 3-month outcome, defined as modified Rankin Score >2, using c-statistic and the Hosmer-Lemeshow test, respectively.We included 230 patients (mean ±SD age 70.4±16.0 years, median [IQR] baseline NIHSS 8 [5]-[14]; poor outcome in 78(34% patients. The c-statistic was 0.81 (95%CI 0.75-0.87, and the Hosmer-Lemeshow test was not significant (p = 0.54.The MRI-DRAGON score showed good prognostic performance in the external validation cohort. It could therefore be used to inform the patient's relatives about long-term prognosis and help to identify poor responders to IV-tPA alone, who may be candidates for additional therapeutic strategies, if they are otherwise eligible for such procedures based on the institutional criteria.

  11. Lower limb SSEP changes in stroke-predictive values regarding functional recovery.

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    Tzvetanov, Pl; Rousseff, R T; Milanov, Iv

    2003-04-01

    To assess the predictive value of lower limbs somatosensory evoked potentials (SSEPs) in the acute phase of stroke. 94 stroke patients (mean age: 61.2; S.D.: 11.8; 43 women) were included. Computed tomography confirmed diagnosis was cortical middle cerebral artery (MCA) infarction in 35, subcortical MCA in 11, and mixed in 25. By size, infarctions were large (29), limited (33), and lacunar (9). Thalamic haemorrhage was found in eight patients, putaminal in seven, small capsular in two, massive in two and lobar in four patients. All patients presented with hemiparesis (54) or hemiplegia (40), pure in five and combined with hemihypesthesia in 89. Tibial nerve SSEPs were recorded early in the course of the disease (up to third day). SSEP parameters (presence/absence of SSEP, absolute P40 latency, amplitude and amplitude ratio-affected/healthy side of P40-N50) were evaluated and compared with motor ability using the Medical Research Council (MRC) scale, and daily living activities using Barthel index (ADLB) followed for 3 months after stroke. Disability was assessed after the Rankin scale. The absolute amplitude of P40 has moderately strong correlation with Barthel index (r=0.63) and nearly moderate (r=-0.46) with Rankin scale at 3 months. P40 ratio exhibits weaker correlations with clinical outcome parameters. The combination of SSEP abnormalities and MRC has stronger predictive value than MRC alone (Pvs Pstroke, independently or combined with muscle power assessment, significantly increases prognostic capability.

  12. A new method for predicting functional recovery of stroke patients with hemiplegia: logarithmic modelling.

    Science.gov (United States)

    Koyama, Tetsuo; Matsumoto, Kenji; Okuno, Taiji; Domen, Kazuhisa

    2005-10-01

    To examine the validity and applicability of logarithmic modelling for predicting functional recovery of stroke patients with hemiplegia. Longitudinal postal survey. Stroke patients with hemiplegia staying in a long-term rehabilitation facility, who had been referred from acute medical service 30-60 days after onset. Functional Independence Measure (FIM) scores were periodically assessed during hospitalization. For each individual, a logarithmic formula that was scaled by an interval increase in FIM scores during the initial 2-6 weeks was used for predicting functional recovery. For the study, we recruited 18 patients who showed a wide variety of disability levels on admission (FIM scores 25-107). For each patient, the predicted FIM scores derived from the logarithmic formula matched the actual change in FIM scores. The changes predicted the recovery of motor rather than cognitive functions. Regression analysis showed a close fit between logarithmic modelling and actual FIM scores (across-subject R2 = 0.945). Provided with two initial time-point samplings, logarithmic modelling allows accurate prediction of functional recovery for individuals. Because the modelling is mathematically simple, it can be widely applied in daily clinical practice.

  13. Alberta Stroke Program Early CT Score-Time Score Predicts Outcome after Endovascular Therapy in Patients with Acute Ischemic Stroke: A Retrospective Single-Center Study.

    Science.gov (United States)

    Todo, Kenichi; Sakai, Nobuyuki; Kono, Tomoyuki; Hoshi, Taku; Imamura, Hirotoshi; Adachi, Hidemitsu; Yamagami, Hiroshi; Kohara, Nobuo

    2018-04-01

    Clinical outcomes after successful endovascular therapy in patients with acute ischemic stroke are associated with several factors including onset-to-reperfusion time (ORT), the National Institute of Health Stroke Scale (NIHSS) score, and the Alberta Stroke Program Early CT Score (ASPECTS). The NIHSS-time score, calculated as follows: [NIHSS score] × [onset-to-treatment time (h)] or [NIHSS score] × [ORT (h)], has been reported to predict clinical outcomes after intravenous recombinant tissue plasminogen activator therapy and endovascular therapy for acute stroke. The objective of the current study was to assess whether the combination of the ASPECTS and the ORT can predict the outcomes after endovascular therapy. The charts of 117 consecutive ischemic stroke patients with successful reperfusion after endovascular therapy were retrospectively reviewed. We analyzed the association of ORT, ASPECTS, and ASPECTS-time score with clinical outcome. ASPECTS-time score was calculated as follows: [11 - ASPECTS] × [ORT (h)]. Rates of good outcome for patients with ASPECTS-time scores of tertile values, scores 5.67 or less, scores greater than 5.67 to 10.40 or less, and scores greater than 10.40, were 66.7%, 56.4%, and 33.3%, respectively (P < .05). Ordinal logistic regression analysis showed that the ASPECTS-time score (per category increase) was an independent predictor for better outcome (common odds ratio: .374; 95% confidence interval: .150-0.930; P < .05). A lower ASPECTS-time score may predict better clinical outcomes after endovascular treatment. Copyright © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  14. Measure of functional independence dominates discharge outcome prediction after inpatient rehabilitation for stroke.

    Science.gov (United States)

    Brown, Allen W; Therneau, Terry M; Schultz, Billie A; Niewczyk, Paulette M; Granger, Carl V

    2015-04-01

    Identifying clinical data acquired at inpatient rehabilitation admission for stroke that accurately predict key outcomes at discharge could inform the development of customized plans of care to achieve favorable outcomes. The purpose of this analysis was to use a large comprehensive national data set to consider a wide range of clinical elements known at admission to identify those that predict key outcomes at rehabilitation discharge. Sample data were obtained from the Uniform Data System for Medical Rehabilitation data set with the diagnosis of stroke for the years 2005 through 2007. This data set includes demographic, administrative, and medical variables collected at admission and discharge and uses the FIM (functional independence measure) instrument to assess functional independence. Primary outcomes of interest were functional independence measure gain, length of stay, and discharge to home. The sample included 148,367 people (75% white; mean age, 70.6±13.1 years; 97% with ischemic stroke) admitted to inpatient rehabilitation a mean of 8.2±12 days after symptom onset. The total functional independence measure score, the functional independence measure motor subscore, and the case-mix group were equally the strongest predictors for any of the primary outcomes. The most clinically relevant 3-variable model used the functional independence measure motor subscore, age, and walking distance at admission (r(2)=0.107). No important additional effect for any other variable was detected when added to this model. This analysis shows that a measure of functional independence in motor performance and age at rehabilitation hospital admission for stroke are predominant predictors of outcome at discharge in a uniquely large US national data set. © 2015 American Heart Association, Inc.

  15. How Nanotechnology and Biomedical Engineering Are Supporting the Identification of Predictive Biomarkers in Neuro-Oncology.

    Science.gov (United States)

    Ganau, Mario; Paris, Marco; Syrmos, Nikolaos; Ganau, Laura; Ligarotti, Gianfranco K I; Moghaddamjou, Ali; Prisco, Lara; Ambu, Rossano; Chibbaro, Salvatore

    2018-02-26

    The field of neuro-oncology is rapidly progressing and internalizing many of the recent discoveries coming from research conducted in basic science laboratories worldwide. This systematic review aims to summarize the impact of nanotechnology and biomedical engineering in defining clinically meaningful predictive biomarkers with a potential application in the management of patients with brain tumors. Data were collected through a review of the existing English literature performed on Scopus, MEDLINE, MEDLINE in Process, EMBASE, and/or Cochrane Central Register of Controlled Trials: all available basic science and clinical papers relevant to address the above-stated research question were included and analyzed in this study. Based on the results of this systematic review we can conclude that: (1) the advances in nanotechnology and bioengineering are supporting tremendous efforts in optimizing the methods for genomic, epigenomic and proteomic profiling; (2) a successful translational approach is attempting to identify a growing number of biomarkers, some of which appear to be promising candidates in many areas of neuro-oncology; (3) the designing of Randomized Controlled Trials will be warranted to better define the prognostic value of those biomarkers and biosignatures.

  16. Predictive inference for best linear combination of biomarkers subject to limits of detection.

    Science.gov (United States)

    Coolen-Maturi, Tahani

    2017-08-15

    Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine, machine learning and credit scoring. The receiver operating characteristic (ROC) curve is a useful tool to assess the ability of a diagnostic test to discriminate between two classes or groups. In practice, multiple diagnostic tests or biomarkers are combined to improve diagnostic accuracy. Often, biomarker measurements are undetectable either below or above the so-called limits of detection (LoD). In this paper, nonparametric predictive inference (NPI) for best linear combination of two or more biomarkers subject to limits of detection is presented. NPI is a frequentist statistical method that is explicitly aimed at using few modelling assumptions, enabled through the use of lower and upper probabilities to quantify uncertainty. The NPI lower and upper bounds for the ROC curve subject to limits of detection are derived, where the objective function to maximize is the area under the ROC curve. In addition, the paper discusses the effect of restriction on the linear combination's coefficients on the analysis. Examples are provided to illustrate the proposed method. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  17. How Nanotechnology and Biomedical Engineering Are Supporting the Identification of Predictive Biomarkers in Neuro-Oncology

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    Mario Ganau

    2018-02-01

    Full Text Available The field of neuro-oncology is rapidly progressing and internalizing many of the recent discoveries coming from research conducted in basic science laboratories worldwide. This systematic review aims to summarize the impact of nanotechnology and biomedical engineering in defining clinically meaningful predictive biomarkers with a potential application in the management of patients with brain tumors. Data were collected through a review of the existing English literature performed on Scopus, MEDLINE, MEDLINE in Process, EMBASE, and/or Cochrane Central Register of Controlled Trials: all available basic science and clinical papers relevant to address the above-stated research question were included and analyzed in this study. Based on the results of this systematic review we can conclude that: (1 the advances in nanotechnology and bioengineering are supporting tremendous efforts in optimizing the methods for genomic, epigenomic and proteomic profiling; (2 a successful translational approach is attempting to identify a growing number of biomarkers, some of which appear to be promising candidates in many areas of neuro-oncology; (3 the designing of Randomized Controlled Trials will be warranted to better define the prognostic value of those biomarkers and biosignatures.

  18. Performance of diagnostic biomarkers in predicting liver fibrosis among hepatitis C virus-infected Egyptian children

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    Yasser E Nassef

    2013-11-01

    Full Text Available The aim of the present study was to identify specific markers that mirror liver fibrosis progression as an alternative to biopsy when biopsy is contraindicated, especially in children. After liver biopsies were performed, serum samples from 30 hepatitis C virus (HCV paediatric patients (8-14 years were analysed and compared with samples from 30 healthy subjects. All subjects were tested for the presence of serum anti-HCV antibodies. Direct biomarkers for liver fibrosis, including transforming growth factor-β1, tissue inhibitor of matrix metalloproteinase-1 (TIMP-1, hyaluronic acid (HA, procollagen type III amino-terminal peptide (PIIINP and osteopontin (OPN, were measured. The indirect biomarkers aspartate and alanine aminotransferases, albumin and bilirubin were also tested. The results revealed a significant increase in the serum marker levels in HCV-infected children compared with the healthy group, whereas albumin levels exhibited a significant decrease. Significantly higher levels of PIIINP, TIMP-1, OPN and HA were detected in HCV-infected children with moderate to severe fibrosis compared with children with mild fibrosis (p < 0.05. The diagnostic accuracy of these direct biomarkers, represented by sensitivity, specificity and positive predictive value, emphasises the utility of PIIINP, TIMP-1, OPN and HA as indicators of liver fibrosis among HCV-infected children.

  19. National Institutes of Health Stroke Scale-Time Score Predicts Outcome after Endovascular Therapy in Acute Ischemic Stroke: A Retrospective Single-Center Study.

    Science.gov (United States)

    Todo, Kenichi; Sakai, Nobuyuki; Kono, Tomoyuki; Hoshi, Taku; Imamura, Hirotoshi; Adachi, Hidemitsu; Kohara, Nobuo

    2016-05-01

    Outcomes after successful endovascular therapy in acute ischemic stroke are associated with onset-to-reperfusion time (ORT) and the National Institutes of Health Stroke Scale (NIHSS) score. In intravenous recombinant tissue plasminogen activator therapy, the NIHSS-time score, calculated by multiplying onset-to-treatment time with the NIHSS score, has been shown to predict clinical outcomes. In this study, we assessed whether a similar combination of the ORT and the NIHSS score can be applied to predict the outcomes after endovascular therapy. We retrospectively reviewed the charts of 128 consecutive ischemic stroke patients with successful reperfusion after endovascular therapy. We analyzed the association of the ORT, the NIHSS score, and the NIHSS-time score with good outcome (modified Rankin Scale score ≤ 2 at 3 months). Good outcome rates for patients with NIHSS-time scores of 84.7 or lower, scores higher than 84.7 up to 127.5 or lower, and scores higher than 127.5 were 72.1%, 44.2%, and 14.3%, respectively (P < .01). Multivariate logistic regression analysis revealed that the NIHSS-time score was an independent predictor of good outcomes (odds ratio, .372; 95% confidence interval, .175-.789) after adjusting for age, sex, internal carotid artery occlusion, plasma glucose level, ORT, and NIHSS score. The NIHSS-time score can predict good clinical outcomes after endovascular treatment. Copyright © 2016 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  20. Urinary aminopeptidase activities as early and predictive biomarkers of renal dysfunction in cisplatin-treated rats.

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    Andrés Quesada

    Full Text Available This study analyzes the fluorimetric determination of alanyl- (Ala, glutamyl- (Glu, leucyl-cystinyl- (Cys and aspartyl-aminopeptidase (AspAp urinary enzymatic activities as early and predictive biomarkers of renal dysfunction in cisplatin-treated rats. Male Wistar rats (n = 8 each group received a single subcutaneous injection of either saline or cisplatin 3.5 or 7 mg/kg, and urine samples were taken at 0, 1, 2, 3 and 14 days after treatment. In urine samples we determined Ala, Glu, Cys and AspAp activities, proteinuria, N-acetyl-β-D-glucosaminidase (NAG, albumin, and neutrophil gelatinase-associated lipocalin (NGAL. Plasma creatinine, creatinine clearance and renal morphological variables were measured at the end of the experiment. CysAp, NAG and albumin were increased 48 hours after treatment in the cisplatin 3.5 mg/kg treated group. At 24 hours, all urinary aminopeptidase activities and albuminuria were significantly increased in the cisplatin 7 mg/kg treated group. Aminopeptidase urinary activities correlated (p0.259 with plasma creatinine, creatinine clearance and/or kidney weight/body weight ratio at the end of the experiment and they could be considered as predictive biomarkers of renal injury severity. ROC-AUC analysis was made to study their sensitivity and specificity to distinguish between treated and untreated rats at day 1. All aminopeptidase activities showed an AUC>0.633. We conclude that Ala, Cys, Glu and AspAp enzymatic activities are early and predictive urinary biomarkers of the renal dysfunction induced by cisplatin. These determinations can be very useful in the prognostic and diagnostic of renal dysfunction in preclinical research and clinical practice.

  1. Plasma sCD14 as a biomarker to predict pulmonary exacerbations in cystic fibrosis.

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    Bradley S Quon

    Full Text Available BACKGROUND: One in four cystic fibrosis (CF patients diagnosed with a pulmonary exacerbation will not recover their baseline lung function despite standard treatment. This highlights the importance of preventing such events. Clinical decision-making can be improved through a simple blood test that predicts individuals at elevated short-term risk of an exacerbation. METHODS: We obtained plasma samples from 30 stable CF patients from the St. Paul's Hospital Adult CF Clinic (Vancouver, Canada. For 15 patients, an additional plasma sample was obtained during an exacerbation. Soluble CD14 (sCD14 and C-reactive protein (CRP were quantified using ELISA kits. Myeloperoxidase (MPO, interleukin(IL-6, IL-1β, monocyte chemoattractant protein-1 (MCP-1, vascular endothelial growth factor (VEGF, and granulocyte colony-stimulating factor (G-CSF were quantified using Luminex™ immunoassays. Stable state biomarker levels were examined in their ability to predict individuals that would experience a pulmonary exacerbation requiring intravenous (IV antibiotics within 4 months. Paired stable and exacerbation plasma biomarker levels were also compared. RESULTS: sCD14 levels were significantly higher in patients that experienced a pulmonary exacerbation requiring IV antibiotics within 4 months (p = 0.001. sCD14 cut-off value of 1450 ng/mL was associated with an area under the curve of 0.91 (95% CI 0.83-0.99 for predicting an exacerbation within 4 months of a stable visit, with a sensitivity of 100% and specificity of 82%. Plasma sCD14 levels were significantly higher during exacerbations than during periods of clinical stability (p = 0.03. CONCLUSIONS: Plasma sCD14 is a promising biomarker for identifying CF patients who will exacerbate within 4 months of a stable visit but requires further study in larger, independent cohorts.

  2. A Proteomic Approach Identifies Candidate Early Biomarkers to Predict Severe Dengue in Children.

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    Dang My Nhi

    2016-02-01

    Full Text Available Severe dengue with severe plasma leakage (SD-SPL is the most frequent of dengue severe form. Plasma biomarkers for early predictive diagnosis of SD-SPL are required in the primary clinics for the prevention of dengue death.Among 63 confirmed dengue pediatric patients recruited, hospital based longitudinal study detected six SD-SPL and ten dengue with warning sign (DWS. To identify the specific proteins increased or decreased in the SD-SPL plasma obtained 6-48 hours before the shock compared with the DWS, the isobaric tags for relative and absolute quantification (iTRAQ technology was performed using four patients each group. Validation was undertaken in 6 SD-SPL and 10 DWS patients.Nineteen plasma proteins exhibited significantly different relative concentrations (p<0.05, with five over-expressed and fourteen under-expressed in SD-SPL compared with DWS. The individual protein was classified to either blood coagulation, vascular regulation, cellular transport-related processes or immune response. The immunoblot quantification showed angiotensinogen and antithrombin III significantly increased in SD-SPL whole plasma of early stage compared with DWS subjects. Even using this small number of samples, antithrombin III predicted SD-SPL before shock occurrence with accuracy.Proteins identified here may serve as candidate predictive markers to diagnose SD-SPL for timely clinical management. Since the number of subjects are small, so further studies are needed to confirm all these biomarkers.

  3. Exploring the Limitations of Peripheral Blood Transcriptional Biomarkers in Predicting Influenza Vaccine Responsiveness

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    Luca Marchetti

    2017-01-01

    Full Text Available Systems biology has been recently applied to vaccinology to better understand immunological responses to the influenza vaccine. Particular attention has been paid to the identification of early signatures capable of predicting vaccine immunogenicity. Building from previous studies, we employed a recently established algorithm for signature-based clustering of expression profiles, SCUDO, to provide new insights into why blood-derived transcriptome biomarkers often fail to predict the seroresponse to the influenza virus vaccination. Specifically, preexisting immunity against one or more vaccine antigens, which was found to negatively affect the seroresponse, was identified as a confounding factor able to decouple early transcriptome from later antibody responses, resulting in the degradation of a biomarker predictive power. Finally, the broadly accepted definition of seroresponse to influenza virus vaccine, represented by the maximum response across the vaccine-targeted strains, was compared to a composite measure integrating the responses against all strains. This analysis revealed that composite measures provide a more accurate assessment of the seroresponse to multicomponent influenza vaccines.

  4. Identification of predictive biomarkers of disease state in transition dairy cows.

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    Hailemariam, D; Mandal, R; Saleem, F; Dunn, S M; Wishart, D S; Ametaj, B N

    2014-05-01

    In dairy cows, periparturient disease states, such as metritis, mastitis, and laminitis, are leading to increasingly significant economic losses for the dairy industry. Treatments for these pathologies are often expensive, ineffective, or not cost-efficient, leading to production losses, high veterinary bills, or early culling of the cows. Early diagnosis or detection of these conditions before they manifest themselves could lower their incidence, level of morbidity, and the associated economic losses. In an effort to identify predictive biomarkers for postpartum or periparturient disease states in dairy cows, we undertook a cross-sectional and longitudinal metabolomics study to look at plasma metabolite levels of dairy cows during the transition period, before and after becoming ill with postpartum diseases. Specifically we employed a targeted quantitative metabolomics approach that uses direct flow injection mass spectrometry to track the metabolite changes in 120 different plasma metabolites. Blood plasma samples were collected from 12 dairy cows at 4 time points during the transition period (-4 and -1 wk before and 1 and 4 wk after parturition). Out of the 12 cows studied, 6 developed multiple periparturient disorders in the postcalving period, whereas the other 6 remained healthy during the entire experimental period. Multivariate data analysis (principal component analysis and partial least squares discriminant analysis) revealed a clear separation between healthy controls and diseased cows at all 4 time points. This analysis allowed us to identify several metabolites most responsible for separating the 2 groups, especially before parturition and the start of any postpartum disease. Three metabolites, carnitine, propionyl carnitine, and lysophosphatidylcholine acyl C14:0, were significantly elevated in diseased cows as compared with healthy controls as early as 4 wk before parturition, whereas 2 metabolites, phosphatidylcholine acyl-alkyl C42:4 and

  5. Improving prediction of recanalization in acute large-vessel occlusive stroke.

    Science.gov (United States)

    Vanacker, P; Lambrou, D; Eskandari, A; Maeder, P; Meuli, R; Ntaios, G; Michel, P

    2014-06-01

    Recanalization in acute ischemic stroke with large-vessel occlusion is a potent indicator of good clinical outcome. To identify easily available clinical and radiologic variables predicting recanalization at various occlusion sites. All consecutive, acute stroke patients from the Acute STroke Registry and Analysis of Lausanne (2003-2011) who had a large-vessel occlusion on computed tomographic angiography (CTA) (< 12 h) were included. Recanalization status was assessed at 24 h (range: 12-48 h) with CTA, magnetic resonance angiography, or ultrasonography. Complete and partial recanalization (corresponding to the modified Treatment in Cerebral Ischemia scale 2-3) were grouped together. Patients were categorized according to occlusion site and treatment modality. Among 439 patients, 51% (224) showed complete or partial recanalization. In multivariate analysis, recanalization of any occlusion site was most strongly associated with endovascular treatment, including bridging therapy (odds ratio [OR] 7.1, 95% confidence interval [CI] 2.2-23.2), and less so with intravenous thrombolysis (OR 1.6, 95% CI 1.0-2.6) and recanalization treatments performed beyond guidelines (OR 2.6, 95% CI 1.2-5.7). Clot location (large vs. intermediate) and tandem pathology (the combination of intracranial occlusion and symptomatic extracranial stenosis) were other variables discriminating between recanalizers and non-recanalizers. For patients with intracranial occlusions, the variables significantly associated with recanalization after 24 h were: baseline National Institutes of Health Stroke Scale (NIHSS) (OR 1.04, 95% CI 1.02-1.1), Alberta Stroke Program Early CT Score (ASPECTS) on initial computed tomography (OR 1.2, 95% CI 1.1-1.3), and an altered level of consciousness (OR 0.2, 95% CI 0.1-0.5). Acute endovascular treatment is the single most important factor promoting recanalization in acute ischemic stroke. The presence of extracranial vessel stenosis or occlusion decreases

  6. Low free triiodothyronine predicts poor functional outcome after acute ischemic stroke.

    Science.gov (United States)

    Suda, Satoshi; Muraga, Kanako; Kanamaru, Takuya; Okubo, Seiji; Abe, Arata; Aoki, Junya; Suzuki, Kentaro; Sakamoto, Yuki; Shimoyama, Takashi; Nito, Chikako; Kimura, Kazumi

    2016-09-15

    The aim of this study was to investigate the association of admission serum thyroid hormone concentration with clinical characteristics and functional outcomes in patients after acute ischemic stroke. We retrospectively enrolled 398 consecutive patients admitted to our stroke center between July 2010 and April 2012. Serum thyroid stimulating hormone (TSH), free triiodothyronine (FT3), and free thyroxine (FT4) were evaluated upon admission. Neurological severity was evaluated using the National Institutes of Health Stroke Scale (NIHSS) upon admission and the modified Rankin Scale (mRS) upon discharge. Poor outcome was defined as a mRS score of 3-5 or death (mRS score 6). Separate analyses were conducted according to outcome and quartile serum FT3 concentration. In total, 164 patients (41.2%) demonstrated a poor outcome. Age, male gender, blood glucose level, arterial fibrillation, dyslipidemia, smoking, NIHSS score, cardioembolic stroke type, and periventricular hyperintensities, but not FT4 or TSH, were significantly associated with poor functional outcome. Furthermore, poor functional outcome was independently associated with low FT3 (<2.29pg/mL). In comparisons between FT3 quartiles (Q1 [≤2.11pg/mL], Q2 [2.12-2.45pg/mL], Q3 [2.46-2.77pg/mL], Q4 [≥2.78pg/mL]), patients with poor outcomes were more frequent in Q1 than in Q4 after multivariate adjustment. Death was more frequent in Q1 than in Q4 after adjustment for risk factors and comorbidities, but this difference was non-significant after additional adjustment for age and NIHSS score. Our data suggest that a lower FT3 value upon admission may predict a poor functional outcome in patients with acute ischemic stroke. Further large-scale prospective studies are required to clarify the role of thyroid hormone in the acute phase of ischemic stroke. Copyright © 2016 Elsevier B.V. All rights reserved.

  7. [Application of Competing Risks Model in Predicting Smoking Relapse Following Ischemic Stroke].

    Science.gov (United States)

    Hou, Li-Sha; Li, Ji-Jie; Du, Xu-Dong; Yan, Pei-Jing; Zhu, Cai-Rong

    2017-07-01

    To determine factors associated with smoking relapse in men who survived from their first stroke. Data were collected through face to face interviews with stroke patients in the hospital, and then repeated every three months via telephone over the period from 2010 to 2014. Kaplan-Meier method and competing risk model were adopted to estimate and predict smoking relapse rates. The Kaplan-Meier method estimated a higher relapse rate than the competing risk model. The four-year relapse rate was 43.1% after adjustment of competing risk. Exposure to environmental tobacco smoking outside of home and workplace (such as bars and restaurants) ( P =0.01), single ( P <0.01), and prior history of smoking at least 20 cigarettes per day ( P =0.02) were significant predictors of smoking relapse. When competing risks exist, competing risks model should be used in data analyses. Smoking interventions should give priorities to those without a spouse and those with a heavy smoking history. Smoking ban in public settings can reduce smoking relapse in stroke patients.

  8. Metabolomics biomarkers to predict acamprosate treatment response in alcohol-dependent subjects.

    Science.gov (United States)

    Hinton, David J; Vázquez, Marely Santiago; Geske, Jennifer R; Hitschfeld, Mario J; Ho, Ada M C; Karpyak, Victor M; Biernacka, Joanna M; Choi, Doo-Sup

    2017-05-31

    Precision medicine for alcohol use disorder (AUD) allows optimal treatment of the right patient with the right drug at the right time. Here, we generated multivariable models incorporating clinical information and serum metabolite levels to predict acamprosate treatment response. The sample of 120 patients was randomly split into a training set (n = 80) and test set (n = 40) five independent times. Treatment response was defined as complete abstinence (no alcohol consumption during 3 months of acamprosate treatment) while nonresponse was defined as any alcohol consumption during this period. In each of the five training sets, we built a predictive model using a least absolute shrinkage and section operator (LASSO) penalized selection method and then evaluated the predictive performance of each model in the corresponding test set. The models predicted acamprosate treatment response with a mean sensitivity and specificity in the test sets of 0.83 and 0.31, respectively, suggesting our model performed well at predicting responders, but not non-responders (i.e. many non-responders were predicted to respond). Studies with larger sample sizes and additional biomarkers will expand the clinical utility of predictive algorithms for pharmaceutical response in AUD.

  9. Hyperdense basilar artery sign diagnoses acute posterior circulation stroke and predicts short-term outcome

    Energy Technology Data Exchange (ETDEWEB)

    Tan, Xiaoping [Affiliated Hospital of China Medical University at Shenyang, Department of Neurology, Shengjing Hospital, Shenyang (China); Guo, Yang [Shengjing Hospital, Department of Neurology, Shenyang (China)

    2010-12-15

    It is well established that the hyperdense middle cerebral artery sign is a specific marker for early ischemia in anterior circulation. However, little is known about the hyperdense basilar artery sign (HDBA) in posterior circulation. Our aim was to determine whether the HDBA sign has utility in early diagnosis of acute posterior circulation stroke and prediction of short-term outcome. Three-blinded readers examined unenhanced computed tomography scans for the HDBA sign, and materials were classified into two groups according to this sign. Vascular risk factors, admission and discharge National Institute of Health Stroke Scale (NIHSS) scores, short-term outcome, and radiological findings between the two groups were compared. One hundred and twenty-six cases of acute posterior circulation stroke (PCS) were included in the study. No statistically significant differences were found in risk factors of ischemic stroke, except atrial fibrillation (P = 0.025). Admission and discharge NIHSS scores for the positive HDBA group were significantly higher than scores for the negative HDBA group (P = 0.001, 0.002, respectively). The infarction territory for the positive HDBA group was mainly multi-region in nature (51.6%, P < 0.001), while the negative HDBA group showed mainly middle territory infarction. Significant independent predictors of short-term outcome included the HDBA sign (P < 0.001) and admission NIHSS scores (P < 0.001). Approximately half of the HDBA patients showed multi-region infarction and a serious neurological symptom. Based on our results, this sign might not only be helpful in early diagnosis of acute PCS but also be able to correlate with a poor short-term outcome. (orig.)

  10. Cutoff Value of Pharyngeal Residue in Prognosis Prediction After Neuromuscular Electrical Stimulation Therapy for Dysphagia in Subacute Stroke Patients

    OpenAIRE

    Park, Jeong Mee; Yong, Sang Yeol; Kim, Ji Hyun; Jung, Hong Sun; Chang, Sei Jin; Kim, Ki Young; Kim, Hee

    2014-01-01

    Objective To determine the cutoff value of the pharyngeal residue for predicting reduction of aspiration, by measuring the residue of valleculae and pyriformis sinuses through videofluoroscopic swallowing studies (VFSS) after treatment with neuromuscular electrical stimulator (VitalStim) in stroke patients with dysphagia. Methods VFSS was conducted on first-time stroke patients before and after the VitalStim therapy. The results were analyzed for comparison of the pharyngeal residue in the im...

  11. DR6 as a diagnostic and predictive biomarker in adult sarcoma.

    Directory of Open Access Journals (Sweden)

    Kun Yang

    Full Text Available The Death Receptor 6 (DR6 protein is elevated in the serum of ovarian cancer patients. We tested DR6 serum protein levels as a diagnostic/predictive biomarker in several epithelial tumors and sarcomas.DR6 gene expression profiles were screened in publically available arrays of solid tumors. A quantitative immunofluorescent western blot analysis was developed to test the serum of healthy controls and patients with sarcoma, uterine carcinosarcoma, bladder, liver, and pancreatic carcinomas. Change in DR6 serum levels was used to assay the ability of DR6 to predict the response to therapy of sarcoma patients.DR6 mRNA is highly expressed in all tumor types assayed. Western blot analysis of serum DR6 protein demonstrated high reproducibility (r = 0.97. Compared to healthy donor controls, DR6 serum levels were not elevated in patients with uterine carcinosarcoma, bladder, liver, or pancreatic cancers. Serum DR6 protein levels from adult sarcoma patients were significantly elevated (p<0.001. This was most evident for patients with synovial sarcoma. Change in serum DR6 levels during therapy correlated with clinical benefit from therapy (sensitivity 75%, and positive predictive value 87%.DR6 may be a clinically useful diagnostic and predictive serum biomarker for some adult sarcoma subtypes.Diagnosis of sarcoma can be difficult and can lead to improper management of these cancers. DR6 serum protein may be a tool to aid in the diagnosis of some sarcomatous tumors to improve treatment planning. For patients with advanced disease, rising DR6 levels predict non-response to therapy and may expedite therapeutic decision making and reduce reliance on radiologic imaging.

  12. Evaluation of biomarkers for the prediction of pre-eclampsia in women with type 1 diabetes mellitus: A systematic review.

    Science.gov (United States)

    Wotherspoon, Amy C; Young, Ian S; McCance, David R; Holmes, Valerie A

    2016-07-01

    Pre-eclampsia is a leading cause of maternal and perinatal morbidity and mortality. Women with type 1 diabetes are considered a high-risk group for developing pre-eclampsia. Much research has focused on biomarkers as a means of screening for pre-eclampsia in the general maternal population; however, there is a lack of evidence for women with type 1 diabetes. To undertake a systematic review to identify potential biomarkers for the prediction of pre-eclampsia in women with type 1 diabetes. We searched Medline, EMBASE, Maternity and Infant Care, Scopus, Web of Science and CINAHL SELECTION CRITERIA: Studies were included if they measured biomarkers in blood or urine of women who developed pre-eclampsia and had pre-gestational type 1 diabetes mellitus Data collection and analysis A narrative synthesis was adopted as a meta-analysis could not be performed, due to high study heterogeneity. A total of 72 records were screened, with 21 eligible studies being included in the review. A wide range of biomarkers was investigated and study size varied from 34 to 1258 participants. No single biomarker appeared to be effective in predicting pre-eclampsia; however, glycaemic control was associated with an increased risk while a combination of angiogenic and anti-angiogenic factors seemed to be potentially useful. Limited evidence suggests that combinations of biomarkers may be more effective in predicting pre-eclampsia than single biomarkers. Further research is needed to verify the predictive potential of biomarkers that have been measured in the general maternal population, as many studies exclude women with diabetes preceding pregnancy. Copyright © 2016 Elsevier Inc. All rights reserved.

  13. Increasing the predictive accuracy of amyloid-β blood-borne biomarkers in Alzheimer's disease.

    Science.gov (United States)

    Watt, Andrew D; Perez, Keyla A; Faux, Noel G; Pike, Kerryn E; Rowe, Christopher C; Bourgeat, Pierrick; Salvado, Olivier; Masters, Colin L; Villemagne, Victor L; Barnham, Kevin J

    2011-01-01

    Diagnostic measures for Alzheimer's disease (AD) commonly rely on evaluating the levels of amyloid-β (Aβ) peptides within the cerebrospinal fluid (CSF) of affected individuals. These levels are often combined with levels of an additional non-Aβ marker to increase predictive accuracy. Recent efforts to overcome the invasive nature of CSF collection led to the observation of Aβ species within the blood cellular fraction, however, little is known of what additional biomarkers may be found in this membranous fraction. The current study aimed to undertake a discovery-based proteomic investigation of the blood cellular fraction from AD patients (n = 18) and healthy controls (HC; n = 15) using copper immobilized metal affinity capture and Surface Enhanced Laser Desorption/Ionisation Time-Of-Flight Mass Spectrometry. Three candidate biomarkers were observed which could differentiate AD patients from HC (ROC AUC > 0.8). Bivariate pairwise comparisons revealed significant correlations between these markers and measures of AD severity including; MMSE, composite memory, brain amyloid burden, and hippocampal volume. A partial least squares regression model was generated using the three candidate markers along with blood levels of Aβ. This model was able to distinguish AD from HC with high specificity (90%) and sensitivity (77%) and was able to separate individuals with mild cognitive impairment (MCI) who converted to AD from MCI non-converters. While requiring further characterization, these candidate biomarkers reaffirm the potential efficacy of blood-based investigations into neurodegenerative conditions. Furthermore, the findings indicate that the incorporation of non-amyloid markers into predictive models, function to increase the accuracy of the diagnostic potential of Aβ.

  14. Biomarkers of evasive resistance predict disease progression in cancer patients treated with antiangiogenic therapies

    Science.gov (United States)

    Pircher, Andreas; Jöhrer, Karin; Kocher, Florian; Steiner, Normann; Graziadei, Ivo; Heidegger, Isabel; Pichler, Renate; Leonhartsberger, Nicolai; Kremser, Christian; Kern, Johann; Untergasser, Gerold; Gunsilius, Eberhard; Hilbe, Wolfgang

    2016-01-01

    Numerous antiangiogenic agents are approved for the treatment of oncological diseases. However, almost all patients develop evasive resistance mechanisms against antiangiogenic therapies. Currently no predictive biomarker for therapy resistance or response has been established. Therefore, the aim of our study was to identify biomarkers predicting the development of therapy resistance in patients with hepatocellular cancer (n = 11), renal cell cancer (n = 7) and non-small cell lung cancer (n = 2). Thereby we measured levels of angiogenic growth factors, tumor perfusion, circulating endothelial cells (CEC), circulating endothelial progenitor cells (CEP) and tumor endothelial markers (TEM) in patients during the course of therapy with antiangiogenic agents, and correlated them with the time to antiangiogenic progression (aTTP). Importantly, at disease progression, we observed an increase of proangiogenic factors, upregulation of CEC/CEP levels and downregulation of TEMs, such as Robo4 and endothelial cell-specific chemotaxis regulator (ECSCR), reflecting the formation of torturous tumor vessels. Increased TEM expression levels tended to correlate with prolonged aTTP (ECSCR high = 275 days vs. ECSCR low = 92.5 days; p = 0.07 and for Robo4 high = 387 days vs. Robo4 low = 90.0 days; p = 0.08). This indicates that loss of vascular stabilization factors aggravates the development of antiangiogenic resistance. Thus, our observations confirm that CEP/CEC populations, proangiogenic cytokines and TEMs contribute to evasive resistance in antiangiogenic treated patients. Higher TEM expression during disease progression may have clinical and pathophysiological implications, however, validation of our results is warranted for further biomarker development. PMID:26956051

  15. MMP-7 is a predictive biomarker of disease progression in patients with idiopathic pulmonary fibrosis

    Directory of Open Access Journals (Sweden)

    Yasmina Bauer

    2017-03-01

    Full Text Available Idiopathic pulmonary fibrosis (IPF is a progressive interstitial lung disease with poor prognosis, which is characterised by destruction of normal lung architecture and excessive deposition of lung extracellular matrix. The heterogeneity of disease progression in patients with IPF poses significant obstacles to patient care and prevents efficient development of novel therapeutic interventions. Blood biomarkers, reflecting pathobiological processes in the lung, could provide objective evidence of the underlying disease. Longitudinally collected serum samples from the Bosentan Use in Interstitial Lung Disease (BUILD-3 trial were used to measure four biomarkers (metalloproteinase-7 (MMP-7, Fas death receptor ligand, osteopontin and procollagen type I C-peptide, to assess their potential prognostic capabilities and to follow changes during disease progression in patients with IPF. In baseline BUILD-3 samples, only MMP-7 showed clearly elevated protein levels compared with samples from healthy controls, and further investigations demonstrated that MMP-7 levels also increased over time. Baseline levels of MMP-7 were able to predict patients who had higher risk of worsening and, notably, baseline levels of MMP-7 could predict changes in FVC as early as month 4. MMP-7 shows potential to be a reliable predictor of lung function decline and disease progression.

  16. Screening Preoperative Peptide Biomarkers for Predicting Postoperative Myocardial Infarction after Coronary Artery Bypass Grafting

    Science.gov (United States)

    Jiang, Zhibin; Hu, Ping; Liu, Jianxin; Wang, Dianjun; Jin, Longyu; Hong, Chao

    2014-01-01

    Postoperative myocardial infarction (PMI) is one of the most serious complications of cardiac surgeries. No preoperative biomarker is currently available for predicting PMI after cardiac surgeries. In the present study, we used a phage display peptide library to screen potential preoperative peptide biomarkers for predicting PMI after coronary artery bypass grafting (CABG) surgery. Twenty patients who developed PMI after CABG and 20 age-, sex-, and body mass index-matched patients without PMI after CABG were enrolled as a discovery cohort. Another 50 patients who developed PMI after CABG and 50 randomly selected patients without PMI after CABG were enrolled as a validation cohort to validate the potential peptide biomarkers identified in the discovery cohort. Fifty randomly selected healthy volunteers were also enrolled in the validation phase as a healthy control group. In the discovery/screening phase, 17 out of 20 randomly selected phage clones exhibited specific reaction with purified sera IgG from the PMI group, among which 11 came from the same phage clone with inserted peptide sequence GVIMVIAVSCVF (named PMI-1). In the validation phase, phage ELISA showed that serum IgG from 90% of patients in the PMI group had a positive reaction with PMI-1; in contrast, only 14% and 6% of patients in the non-PMI group and the healthy control group had a positive reaction with PMI-1, respectively. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of the PMI-1 phage clone to preoperatively identify patients who would develop PMI after CABG were 90.0%, 86.0%, 86.5, 89.5% and 88.0%, respectively. The absorbance value of the PMI-1 phage clone showed statistically significant correlation with the peak postoperative serum cardiac troponin I level (r = 0.349, p = 0.012) in the PMI group. In conclusion, we for the first time identified a mimic peptide (PMI-1) with high validity in preoperative prediction of PMI after CABG. PMID

  17. Prediction of fruit and vegetable intake from biomarkers using individual participant data of diet-controlled intervention studies

    DEFF Research Database (Denmark)

    Souverein, Olga W; de Vries, Jeanne H M; Freese, Riitta

    2015-01-01

    concentrations. Furthermore, a prediction model of fruit and vegetable intake based on these biomarkers and subject characteristics (i.e. age, sex, BMI and smoking status) was established. Data from twelve diet-controlled intervention studies were obtained to develop a prediction model for fruit and vegetable...

  18. Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker

    NARCIS (Netherlands)

    Cole, James H.; Poudel, Rudra P. K.; Tsagkrasoulis, Dimosthenis; Caan, Matthan W. A.; Steves, Claire; Spector, Tim D.; Montana, Giovanni

    2017-01-01

    Machine learning analysis of neuroimaging data can accurately predict chronological age in healthy people. Deviations from healthy brain ageing have been associated with cognitive impairment and disease. Here we sought to further establish the credentials of 'brain-predicted age' as a biomarker of

  19. Thalamic functional connectivity predicts seizure laterality in individual TLE patients: Application of a biomarker development strategy

    Directory of Open Access Journals (Sweden)

    Daniel S. Barron

    2015-01-01

    No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons. Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses.

  20. Toxicogenomic multigene biomarker for predicting the future onset of proximal tubular injury in rats

    International Nuclear Information System (INIS)

    Minowa, Yohsuke; Kondo, Chiaki; Uehara, Takeki; Morikawa, Yuji; Okuno, Yasushi; Nakatsu, Noriyuki; Ono, Atsushi; Maruyama, Toshiyuki; Kato, Ikuo; Yamate, Jyoji; Yamada, Hiroshi; Ohno, Yasuo; Urushidani, Tetsuro

    2012-01-01

    Drug-induced renal tubular injury is a major concern in the preclinical safety evaluation of drug candidates. Toxicogenomics is now a generally accepted tool for identifying chemicals with potential safety problems. The specific aim of the present study was to develop a model for use in predicting the future onset of drug-induced proximal tubular injury following repeated dosing with various nephrotoxicants. In total, 41 nephrotoxic and nonnephrotoxic compounds were used for the present analysis. Male Sprague-Dawley rats were dosed orally or intravenously once daily. Animals were exposed to three different doses (low, middle, and high) of each compound, and kidney tissue was collected at 3, 6, 9, and 24 h after single dosing, and on days 4, 8, 15, and 29 after repeated dosing. Gene expression profiles were generated from kidney total RNA using Affymetrix DNA microarrays. Filter-type gene selection and linear classification algorithms were employed to discriminate future onset of proximal tubular injury. We identified genomic biomarkers for use in future onset prediction using the gene expression profiles determined on day 1, when most of the nephrotoxicants had yet to produce detectable histopathological changes. The model was evaluated using a five-fold cross validation, and achieved a sensitivity of 93% and selectivity of 90% with 19 probes. We also found that the prediction accuracy of the optimized model was substantially higher than that produced by any of the single genomic biomarkers or histopathology. The genes included in our model were primarily involved in DNA replication, cell cycle control, apoptosis, and responses to oxidative stress and chemical stimuli. In summary, our toxicogenomic model is particularly useful for predicting the future onset of proximal tubular injury.

  1. Infarct volume predicts critical care needs in stroke patients treated with intravenous thrombolysis

    Energy Technology Data Exchange (ETDEWEB)

    Faigle, Roland; Marsh, Elisabeth B.; Llinas, Rafael H.; Urrutia, Victor C. [Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD (United States); Wozniak, Amy W. [Johns Hopkins University, Department of Biostatistics, Bloomberg School of Public Health, Baltimore, MD (United States)

    2014-10-26

    Patients receiving intravenous thrombolysis with recombinant tissue plasminogen activator (IVT) for ischemic stroke are monitored in an intensive care unit (ICU) or a comparable unit capable of ICU interventions due to the high frequency of standardized neurological exams and vital sign checks. The present study evaluates quantitative infarct volume on early post-IVT MRI as a predictor of critical care needs and aims to identify patients who may not require resource intense monitoring. We identified 46 patients who underwent MRI within 6 h of IVT. Infarct volume was measured using semiautomated software. Logistic regression and receiver operating characteristics (ROC) analysis were used to determine factors associated with ICU needs. Infarct volume was an independent predictor of ICU need after adjusting for age, sex, race, systolic blood pressure, NIH Stroke Scale (NIHSS), and coronary artery disease (odds ratio 1.031 per cm{sup 3} increase in volume, 95 % confidence interval [CI] 1.004-1.058, p = 0.024). The ROC curve with infarct volume alone achieved an area under the curve (AUC) of 0.766 (95 % CI 0.605-0.927), while the AUC was 0.906 (95 % CI 0.814-0.998) after adjusting for race, systolic blood pressure, and NIHSS. Maximum Youden index calculations identified an optimal infarct volume cut point of 6.8 cm{sup 3} (sensitivity 75.0 %, specificity 76.7 %). Infarct volume greater than 3 cm{sup 3} predicted need for critical care interventions with 81.3 % sensitivity and 66.7 % specificity. Infarct volume may predict needs for ICU monitoring and interventions in stroke patients treated with IVT. (orig.)

  2. Infarct volume predicts critical care needs in stroke patients treated with intravenous thrombolysis

    International Nuclear Information System (INIS)

    Faigle, Roland; Marsh, Elisabeth B.; Llinas, Rafael H.; Urrutia, Victor C.; Wozniak, Amy W.

    2015-01-01

    Patients receiving intravenous thrombolysis with recombinant tissue plasminogen activator (IVT) for ischemic stroke are monitored in an intensive care unit (ICU) or a comparable unit capable of ICU interventions due to the high frequency of standardized neurological exams and vital sign checks. The present study evaluates quantitative infarct volume on early post-IVT MRI as a predictor of critical care needs and aims to identify patients who may not require resource intense monitoring. We identified 46 patients who underwent MRI within 6 h of IVT. Infarct volume was measured using semiautomated software. Logistic regression and receiver operating characteristics (ROC) analysis were used to determine factors associated with ICU needs. Infarct volume was an independent predictor of ICU need after adjusting for age, sex, race, systolic blood pressure, NIH Stroke Scale (NIHSS), and coronary artery disease (odds ratio 1.031 per cm 3 increase in volume, 95 % confidence interval [CI] 1.004-1.058, p = 0.024). The ROC curve with infarct volume alone achieved an area under the curve (AUC) of 0.766 (95 % CI 0.605-0.927), while the AUC was 0.906 (95 % CI 0.814-0.998) after adjusting for race, systolic blood pressure, and NIHSS. Maximum Youden index calculations identified an optimal infarct volume cut point of 6.8 cm 3 (sensitivity 75.0 %, specificity 76.7 %). Infarct volume greater than 3 cm 3 predicted need for critical care interventions with 81.3 % sensitivity and 66.7 % specificity. Infarct volume may predict needs for ICU monitoring and interventions in stroke patients treated with IVT. (orig.)

  3. GRECOS project. The use of genetics to predict the vascular recurrence after stroke

    Science.gov (United States)

    Fernández-Cadenas, Israel; Mendióroz, Maite; Giralt, Dolors; Nafria, Cristina; Garcia, Elena; Carrera, Caty; Gallego-Fabrega, Cristina; Domingues-Montanari, Sophie; Delgado, Pilar; Ribó, Marc; Castellanos, Mar; Martínez, Sergi; Freijo, Mari Mar; Jiménez-Conde, Jordi; Rubiera, Marta; Alvarez-Sabín, José; Molina, Carlos A.; Font, Maria Angels; Olivares, Marta Grau; Palomeras, Ernest; de la Ossa, Natalia Perez; Martinez-Zabaleta, Maite; Masjuan, Jaime; Moniche, Francisco; Canovas, David; Piñana, Carlos; Purroy, Francisco; Cocho, Dolores; Navas, Inma; Tejero, Carlos; Aymerich, Nuria; Cullell, Natalia; Muiño, Elena; Serena, Joaquín; Rubio, Francisco; Davalos, Antoni; Roquer, Jaume; Arenillas, Juan Francisco; Martí-Fábregas, Joan; Keene, Keith; Chen, Wei-Min; Worrall, Bradford; Sale, Michele; Arboix, Adrià; Krupinski, Jerzy; Montaner, Joan

    2017-01-01

    Background and Purpose Vascular recurrence occurs in 11% of patients during the first year after ischemic stroke (IS) or transient ischemic attack (TIA). Clinical scores do not predict the whole vascular recurrence risk, therefore we aimed to find genetic variants associated with recurrence that might improve the clinical predictive models in IS. Methods We analyzed 256 polymorphisms from 115 candidate genes in three patient cohorts comprising 4,482 IS or TIA patients. The discovery cohort was prospectively recruited and included 1,494 patients, 6.2% of them developed a new IS during the first year of follow-up. Replication analysis was performed in 2,988 patients using SNPlex or HumanOmni1-Quad technology. We generated a predictive model using Cox regression (GRECOS score), and generated risk groups using a classification tree method. Results The analyses revealed that rs1800801 in the MGP gene (HR: 1.33, p= 9×10−03), a gene related to artery calcification, was associated with new IS during the first year of follow-up. This polymorphism was replicated in a Spanish cohort (n=1.305), however it was not significantly associated in a North American cohort (n=1.683). The GRECOS score predicted new IS (p= 3.2×10−09) and could classify patients, from low risk of stroke recurrence (1.9%) to high risk (12.6%). Moreover, the addition of genetic risk factors to the GRECOS score improves the prediction compared to previous SPI-II score (p=0.03). Conclusions The use of genetics could be useful to estimate vascular recurrence risk after IS. Genetic variability in the MGP gene was associated with vascular recurrence in the Spanish population. PMID:28411264

  4. High-permeability region size on perfusion CT predicts hemorrhagic transformation after intravenous thrombolysis in stroke.

    Directory of Open Access Journals (Sweden)

    Josep Puig

    Full Text Available Blood-brain barrier (BBB permeability has been proposed as a predictor of hemorrhagic transformation (HT after tissue plasminogen activator (tPA administration; however, the reliability of perfusion computed tomography (PCT permeability imaging for predicting HT is uncertain. We aimed to determine the performance of high-permeability region size on PCT (HPrs-PCT in predicting HT after intravenous tPA administration in patients with acute stroke.We performed a multimodal CT protocol (non-contrast CT, PCT, CT angiography to prospectively study patients with middle cerebral artery occlusion treated with tPA within 4.5 hours of symptom onset. HT was graded at 24 hours using the European-Australasian Acute Stroke Study II criteria. ROC curves selected optimal volume threshold, and multivariate logistic regression analysis identified predictors of HT.The study included 156 patients (50% male, median age 75.5 years. Thirty-seven (23,7% developed HT [12 (7,7%, parenchymal hematoma type 2 (PH-2]. At admission, patients with HT had lower platelet values, higher NIHSS scores, increased ischemic lesion volumes, larger HPrs-PCT, and poorer collateral status. The negative predictive value of HPrs-PCT at a threshold of 7mL/100g/min was 0.84 for HT and 0.93 for PH-2. The multiple regression analysis selected HPrs-PCT at 7mL/100g/min combined with platelets and baseline NIHSS score as the best model for predicting HT (AUC 0.77. HPrs-PCT at 7mL/100g/min was the only independent predictor of PH-2 (OR 1, AUC 0.68, p = 0.045.HPrs-PCT can help predict HT after tPA, and is particularly useful in identifying patients at low risk of developing HT.

  5. High-permeability region size on perfusion CT predicts hemorrhagic transformation after intravenous thrombolysis in stroke

    Science.gov (United States)

    Puig, Josep; Blasco, Gerard; Daunis-i-Estadella, Pepus; van Eendendburg, Cecile; Carrillo-García, María; Aboud, Carlos; Hernández-Pérez, María; Serena, Joaquín; Biarnés, Carles; Nael, Kambiz; Liebeskind, David S.; Thomalla, Götz; Menon, Bijoy K.; Demchuk, Andrew; Wintermark, Max; Pedraza, Salvador

    2017-01-01

    Objective Blood-brain barrier (BBB) permeability has been proposed as a predictor of hemorrhagic transformation (HT) after tissue plasminogen activator (tPA) administration; however, the reliability of perfusion computed tomography (PCT) permeability imaging for predicting HT is uncertain. We aimed to determine the performance of high-permeability region size on PCT (HPrs-PCT) in predicting HT after intravenous tPA administration in patients with acute stroke. Methods We performed a multimodal CT protocol (non-contrast CT, PCT, CT angiography) to prospectively study patients with middle cerebral artery occlusion treated with tPA within 4.5 hours of symptom onset. HT was graded at 24 hours using the European-Australasian Acute Stroke Study II criteria. ROC curves selected optimal volume threshold, and multivariate logistic regression analysis identified predictors of HT. Results The study included 156 patients (50% male, median age 75.5 years). Thirty-seven (23,7%) developed HT [12 (7,7%), parenchymal hematoma type 2 (PH-2)]. At admission, patients with HT had lower platelet values, higher NIHSS scores, increased ischemic lesion volumes, larger HPrs-PCT, and poorer collateral status. The negative predictive value of HPrs-PCT at a threshold of 7mL/100g/min was 0.84 for HT and 0.93 for PH-2. The multiple regression analysis selected HPrs-PCT at 7mL/100g/min combined with platelets and baseline NIHSS score as the best model for predicting HT (AUC 0.77). HPrs-PCT at 7mL/100g/min was the only independent predictor of PH-2 (OR 1, AUC 0.68, p = 0.045). Conclusions HPrs-PCT can help predict HT after tPA, and is particularly useful in identifying patients at low risk of developing HT. PMID:29182658

  6. Metabolic Syndrome Predicts Refractoriness to Intravenous Thrombolysis in Acute Ischemic Stroke.

    Science.gov (United States)

    Dorado, Laura; Arenillas, Juan F; López-Cancio, Elena; Hernández-Pérez, María; Pérez de la Ossa, Natalia; Gomis, Meritxell; Millán, Mònica; Granada, María Luisa; Galán, Amparo; Palomeras, Ernest; Dávalos, Antoni

    2015-11-01

    Metabolic syndrome (MetS) has been associated with higher resistance to clot lysis at 24 hours after tissue plasminogen activator (tPA) administration in patients with acute ischemic stroke. We aimed to test this hypothesis at earlier time points, when neurointerventional rescue procedures may still be indicated to achieve arterial recanalization. This is a prospective and observational study in consecutive stroke patients with MCA occlusion treated with IV tPA. MetS was diagnosed following the unified criteria of the last Joint Interim Statement 2009 participating several major organizations. The primary outcome variable was resistance to thrombolysis, defined as the absence of complete middle cerebral artery recanalization 2 hours after tPA bolus assessed by transcranial color-coded duplex or when rescue mechanical thrombectomy after IV tPA was required. Secondary outcome variables were dramatic neurological improvement (decrease in ≥10 points, or a National Institutes of Health Stroke Scale [NIHSS] score of 0-1 at 24 hours), symptomatic intracerebral hemorrhage following European-Australasian Acute Stroke Study II criteria, infarct volume at 24 hours (calculated by using the formula for irregular volumes, ABC/2), and good outcome (modified Rankin Scale score < 3) at 3 months. A total of 234 patients (median baseline NIHSS score 16 [10-20]) were included and 146 (62.4%) fulfilled MetS criteria. After multivariate analysis, MetS emerged as an independent predictor of resistance to thrombolysis (odds ratio = 2.2 [1.3-4.2], P = .01) and absence of dramatic neurological improvement (odds ratio = .5 [.28-.97], P = .04). In addition, MetS conferred poorer functional outcome, higher symptomatic intracerebral hemorrhage rate, and increased infarct volume, although these associations disappeared after adjustment for covariates. MetS predicts patients with middle cerebral artery occlusion refractory to early clot dissolution after IV tPA. This

  7. Identification of potential prognostic microRNA biomarkers for predicting survival in patients with hepatocellular carcinoma

    Directory of Open Access Journals (Sweden)

    Liao X

    2018-04-01

    Full Text Available Xiwen Liao,1 Guangzhi Zhu,1 Rui Huang,2 Chengkun Yang,1 Xiangkun Wang,1 Ketuan Huang,1 Tingdong Yu,1 Chuangye Han,1 Hao Su,1 Tao Peng1 1Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China; 2Department of Hematology, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China Background: The aim of the present study was to identify potential prognostic microRNA (miRNA biomarkers for hepatocellular carcinoma (HCC prognosis prediction based on a dataset from The Cancer Genome Atlas (TCGA. Materials and methods: A miRNA sequencing dataset and corresponding clinical parameters of HCC were obtained from TCGA. Genome-wide univariate Cox regression analysis was used to screen prognostic differentially expressed miRNAs (DEMs, and multivariable Cox regression analysis was used for prognostic signature construction. Comprehensive survival analysis was performed to evaluate the prognostic value of the prognostic signature. Results: Five miRNAs were regarded as prognostic DEMs and used for prognostic signature construction. The five-DEM prognostic signature performed well in prognosis prediction (adjusted P < 0.0001, adjusted hazard ratio = 2.249, 95% confidence interval =1.491–3.394, and time-dependent receiver–operating characteristic (ROC analysis showed an area under the curve (AUC of 0.765, 0.745, 0.725, and 0.687 for 1-, 2-, 3-, and 5-year HCC overall survival (OS prediction, respectively. Comprehensive survival analysis of the prognostic signature suggests that the risk score model could serve as an independent factor of HCC and perform better in prognosis prediction than other traditional clinical indicators. Functional assessment of the target genes of hsa-mir-139 and hsa-mir-5003 indicates that they were significantly enriched in multiple biological processes and pathways, including cell proliferation and cell migration

  8. Is blood pressure reduction a valid surrogate endpoint for stroke prevention? an analysis incorporating a systematic review of randomised controlled trials, a by-trial weighted errors-in-variables regression, the surrogate threshold effect (STE and the biomarker-surrogacy (BioSurrogate evaluation schema (BSES

    Directory of Open Access Journals (Sweden)

    Lassere Marissa N

    2012-03-01

    Full Text Available Abstract Background Blood pressure is considered to be a leading example of a valid surrogate endpoint. The aims of this study were to (i formally evaluate systolic and diastolic blood pressure reduction as a surrogate endpoint for stroke prevention and (ii determine what blood pressure reduction would predict a stroke benefit. Methods We identified randomised trials of at least six months duration comparing any pharmacologic anti-hypertensive treatment to placebo or no treatment, and reporting baseline blood pressure, on-trial blood pressure, and fatal and non-fatal stroke. Trials with fewer than five strokes in at least one arm were excluded. Errors-in-variables weighted least squares regression modelled the reduction in stroke as a function of systolic blood pressure reduction and diastolic blood pressure reduction respectively. The lower 95% prediction band was used to determine the minimum systolic blood pressure and diastolic blood pressure difference, the surrogate threshold effect (STE, below which there would be no predicted stroke benefit. The STE was used to generate the surrogate threshold effect proportion (STEP, a surrogacy metric, which with the R-squared trial-level association was used to evaluate blood pressure as a surrogate endpoint for stroke using the Biomarker-Surrogacy Evaluation Schema (BSES3. Results In 18 qualifying trials representing all pharmacologic drug classes of antihypertensives, assuming a reliability coefficient of 0.9, the surrogate threshold effect for a stroke benefit was 7.1 mmHg for systolic blood pressure and 2.4 mmHg for diastolic blood pressure. The trial-level association was 0.41 and 0.64 and the STEP was 66% and 78% for systolic and diastolic blood pressure respectively. The STE and STEP were more robust to measurement error in the independent variable than R-squared trial-level associations. Using the BSES3, assuming a reliability coefficient of 0.9, systolic blood pressure was a B + grade and

  9. Is blood pressure reduction a valid surrogate endpoint for stroke prevention? an analysis incorporating a systematic review of randomised controlled trials, a by-trial weighted errors-in-variables regression, the surrogate threshold effect (STE) and the biomarker-surrogacy (BioSurrogate) evaluation schema (BSES)

    Science.gov (United States)

    2012-01-01

    Background Blood pressure is considered to be a leading example of a valid surrogate endpoint. The aims of this study were to (i) formally evaluate systolic and diastolic blood pressure reduction as a surrogate endpoint for stroke prevention and (ii) determine what blood pressure reduction would predict a stroke benefit. Methods We identified randomised trials of at least six months duration comparing any pharmacologic anti-hypertensive treatment to placebo or no treatment, and reporting baseline blood pressure, on-trial blood pressure, and fatal and non-fatal stroke. Trials with fewer than five strokes in at least one arm were excluded. Errors-in-variables weighted least squares regression modelled the reduction in stroke as a function of systolic blood pressure reduction and diastolic blood pressure reduction respectively. The lower 95% prediction band was used to determine the minimum systolic blood pressure and diastolic blood pressure difference, the surrogate threshold effect (STE), below which there would be no predicted stroke benefit. The STE was used to generate the surrogate threshold effect proportion (STEP), a surrogacy metric, which with the R-squared trial-level association was used to evaluate blood pressure as a surrogate endpoint for stroke using the Biomarker-Surrogacy Evaluation Schema (BSES3). Results In 18 qualifying trials representing all pharmacologic drug classes of antihypertensives, assuming a reliability coefficient of 0.9, the surrogate threshold effect for a stroke benefit was 7.1 mmHg for systolic blood pressure and 2.4 mmHg for diastolic blood pressure. The trial-level association was 0.41 and 0.64 and the STEP was 66% and 78% for systolic and diastolic blood pressure respectively. The STE and STEP were more robust to measurement error in the independent variable than R-squared trial-level associations. Using the BSES3, assuming a reliability coefficient of 0.9, systolic blood pressure was a B + grade and diastolic blood pressure

  10. CT Angiography and Presentation NIH stroke Scale in Predicting TIA in Patients Presenting with Acute Stroke Symptoms.

    Science.gov (United States)

    Karaman, Bedriye; Selph, James; Burdine, Joselyn; Graham, Cole Blease; Sen, Souvik

    2013-11-08

    Patient candidacy for acute stroke intervention, is currently assessed using brain computed tomography angiography (CTA) evidence of significant stenosis/occlusion (SSO) with a high National Institutes of Health Stroke Scale (NIHSS) (>6). This study examined the association between CTA without significant stenosis/occlusion (NSSO) and lower NIHSS (≤ 6) with transient ischemic attack (TIA) and other good clinical outcomes at discharge. Patients presenting TIA, modified Rankin Score [mRS] ≤ 1, and home as the discharge disposition. Eighty-five patients received both an NIHSS at presentation and a CTA at 4.2 ± 2.2 hours from stroke symptom onset. Patients with NSSO on CTA as well as those with NIHSS≤6 had better outcomes at discharge (pTIA (pTIA. Addition of NIHSS ≤ 6 to NSSO on CTA proved to be a stronger independent predictor of TIA (Adjusted OR 18.7 95% CI: 3.5-98.9, p=0.001).

  11. The hemorrhagic transformation index score: a prediction tool in middle cerebral artery ischemic stroke.

    Science.gov (United States)

    Kalinin, Mikhail N; Khasanova, Dina R; Ibatullin, Murat M

    2017-09-07

    We aimed to develop a tool, the hemorrhagic transformation (HT) index (HTI), to predict any HT within 14 days after middle cerebral artery (MCA) stroke onset regardless of the intravenous recombinant tissue plasminogen activator (IV rtPA) use. That is especially important in the light of missing evidence-based data concerning the timing of anticoagulant resumption after stroke in patients with atrial fibrillation (AF). We retrospectively analyzed 783 consecutive MCA stroke patients. Clinical and brain imaging data at admission were recorded. A follow-up period was 2 weeks after admission. The patients were divided into derivation (DC) and validation (VC) cohorts by generating Bernoulli variates with probability parameter 0.7. Univariate/multivariate logistic regression, and factor analysis were used to extract independent predictors. Validation was performed with internal consistency reliability and receiver operating characteristic (ROC) analysis. Bootstrapping was used to reduce bias. The HTI was composed of 4 items: Alberta Stroke Program Early CT score (ASPECTS), National Institutes of Health Stroke Scale (NIHSS), hyperdense MCA (HMCA) sign, and AF on electrocardiogram (ECG) at admission. According to the predicted probability (PP) range, scores were allocated to ASPECTS as follows: 10-7 = 0; 6-5 = 1; 4-3 = 2; 2-0 = 3; to NIHSS: 0-11 = 0; 12-17 = 1; 18-23 = 2; >23 = 3; to HMCA sign: yes = 1; to AF on ECG: yes = 1. The HTI score varied from 0 to 8. For each score, adjusted PP of any HT with 95% confidence intervals (CI) was as follows: 0 = 0.027 (0.011-0.042); 1 = 0.07 (0.043-0.098); 2 = 0.169 (0.125-0.213); 3 = 0.346 (0.275-0.417); 4 = 0.571 (0.474-0.668); 5 = 0.768 (0.676-0.861); 6 = 0.893 (0.829-0.957); 7 = 0.956 (0.92-0.992); 8 = 0.983 (0.965-1.0). The optimal cutpoint score to differentiate between HT-positive and negative groups was 2 (95% normal-based CI, 1-3) for the DC and VC alike. ROC area

  12. Apolipoprotein E genotype, cardiovascular biomarkers and risk of stroke : Systematic review and meta-analysis of 14 015 stroke cases and pooled analysis of primary biomarker data from up to 60 883 individuals

    NARCIS (Netherlands)

    Khan, Tauseef A.; Shah, Tina; Prieto, David; Zhang, Weili; Price, Jackie; Fowkes, Gerald R.; Cooper, Jackie; Talmud, Philippa J.; Humphries, Steve E.; Sundstrom, Johan; Hubacek, Jaroslav A.; Ebrahim, Shah; Lawlor, Debbie A.; Ben-Shlomo, Yoav; Abdollahi, Mohammad R.; Slooter, Arjen J. C.; Szolnoki, Zoltan; Sandhu, Manjinder; Wareham, Nicholas; Frikke-Schmidt, Ruth; Tybjaerg-Hansen, Anne; Fillenbaum, Gerda; Heijmans, Bastiaan T.; Katsuya, Tomohiro; Gromadzka, Grazyna; Singleton, Andrew; Ferrucci, Luigi; Hardy, John; Worrall, Bradford; Rich, Stephen S.; Matarin, Mar; Whittaker, John; Gaunt, Tom R.; Whincup, Peter; Morris, Richard; Deanfield, John; Donald, Ann; Smith, George Davey; Kivimaki, Mika; Kumari, Meena; Smeeth, Liam; Khaw, Kay-Tee; Nalls, Michael; Meschia, James; Sun, Kai; Hui, Rutai; Day, Ian; Hingorani, Aroon D.; Casas, Juan P.

    Background At the APOE gene, encoding apolipoprotein E, genotypes of the epsilon 2/epsilon 3/epsilon 4 alleles associated with higher LDL-cholesterol (LDL-C) levels are also associated with higher coronary risk. However, the association of APOE genotype with other cardiovascular biomarkers and risk

  13. An early-biomarker algorithm predicts lethal graft-versus-host disease and survival.

    Science.gov (United States)

    Hartwell, Matthew J; Özbek, Umut; Holler, Ernst; Renteria, Anne S; Major-Monfried, Hannah; Reddy, Pavan; Aziz, Mina; Hogan, William J; Ayuk, Francis; Efebera, Yvonne A; Hexner, Elizabeth O; Bunworasate, Udomsak; Qayed, Muna; Ordemann, Rainer; Wölfl, Matthias; Mielke, Stephan; Pawarode, Attaphol; Chen, Yi-Bin; Devine, Steven; Harris, Andrew C; Jagasia, Madan; Kitko, Carrie L; Litzow, Mark R; Kröger, Nicolaus; Locatelli, Franco; Morales, George; Nakamura, Ryotaro; Reshef, Ran; Rösler, Wolf; Weber, Daniela; Wudhikarn, Kitsada; Yanik, Gregory A; Levine, John E; Ferrara, James L M

    2017-02-09

    BACKGROUND. No laboratory test can predict the risk of nonrelapse mortality (NRM) or severe graft-versus-host disease (GVHD) after hematopoietic cellular transplantation (HCT) prior to the onset of GVHD symptoms. METHODS. Patient blood samples on day 7 after HCT were obtained from a multicenter set of 1,287 patients, and 620 samples were assigned to a training set. We measured the concentrations of 4 GVHD biomarkers (ST2, REG3α, TNFR1, and IL-2Rα) and used them to model 6-month NRM using rigorous cross-validation strategies to identify the best algorithm that defined 2 distinct risk groups. We then applied the final algorithm in an independent test set ( n = 309) and validation set ( n = 358). RESULTS. A 2-biomarker model using ST2 and REG3α concentrations identified patients with a cumulative incidence of 6-month NRM of 28% in the high-risk group and 7% in the low-risk group ( P < 0.001). The algorithm performed equally well in the test set (33% vs. 7%, P < 0.001) and the multicenter validation set (26% vs. 10%, P < 0.001). Sixteen percent, 17%, and 20% of patients were at high risk in the training, test, and validation sets, respectively. GVHD-related mortality was greater in high-risk patients (18% vs. 4%, P < 0.001), as was severe gastrointestinal GVHD (17% vs. 8%, P < 0.001). The same algorithm can be successfully adapted to define 3 distinct risk groups at GVHD onset. CONCLUSION. A biomarker algorithm based on a blood sample taken 7 days after HCT can consistently identify a group of patients at high risk for lethal GVHD and NRM. FUNDING. The National Cancer Institute, American Cancer Society, and the Doris Duke Charitable Foundation.

  14. CT angiography and CT perfusion improve prediction of infarct volume in patients with anterior circulation stroke

    Energy Technology Data Exchange (ETDEWEB)

    Seeters, Tom van; Schaaf, Irene C. van der; Dankbaar, Jan Willem; Horsch, Alexander D.; Niesten, Joris M.; Luitse, Merel J.A.; Mali, Willem P.T.M.; Velthuis, Birgitta K. [University Medical Center Utrecht, Department of Radiology, Utrecht (Netherlands); Biessels, Geert Jan; Kappelle, L.J. [University Medical Center Utrecht, Department of Neurology, Brain Center Rudolf Magnus, Utrecht (Netherlands); Majoie, Charles B.L.M. [Academic Medical Center, Department of Radiology, Amsterdam (Netherlands); Vos, Jan Albert [St. Antonius Hospital, Department of Radiology, Nieuwegein (Netherlands); Schonewille, Wouter J. [St. Antonius Hospital, Department of Neurology, Nieuwegein (Netherlands); Walderveen, Marianne A.A. van [Leiden University Medical Center, Department of Radiology, Leiden (Netherlands); Wermer, Marieke J.H. [Leiden University Medical Center, Department of Neurology, Leiden (Netherlands); Duijm, Lucien E.M. [Catharina Hospital, Department of Radiology, Eindhoven (Netherlands); Keizer, Koos [Catharina Hospital, Department of Neurology, Eindhoven (Netherlands); Bot, Joseph C.J. [VU University Medical Center, Department of Radiology, Amsterdam (Netherlands); Visser, Marieke C. [VU University Medical Center, Department of Neurology, Amsterdam (Netherlands); Lugt, Aad van der [Erasmus MC University Medical Center, Department of Radiology, Rotterdam (Netherlands); Dippel, Diederik W.J. [Erasmus MC University Medical Center, Department of Neurology, Rotterdam (Netherlands); Kesselring, F.O.H.W. [Rijnstate Hospital, Department of Radiology, Arnhem (Netherlands); Hofmeijer, Jeannette [Rijnstate Hospital, Department of Neurology, Arnhem (Netherlands); Lycklama a Nijeholt, Geert J. [Medical Center Haaglanden, Department of Radiology, The Hague (Netherlands); Boiten, Jelis [Medical Center Haaglanden, Department of Neurology, The Hague (Netherlands); Rooij, Willem Jan van [St. Elisabeth Hospital, Department of Radiology, Tilburg (Netherlands); Kort, Paul L.M. de [St. Elisabeth Hospital, Department of Neurology, Tilburg (Netherlands); Roos, Yvo B.W.E.M. [Academic Medical Center, Department of Neurology, Amsterdam (Netherlands); Meijer, Frederick J.A. [Radboud University Medical Center, Department of Radiology, Nijmegen (Netherlands); Pleiter, C.C. [St. Franciscus Hospital, Department of Radiology, Rotterdam (Netherlands); Graaf, Yolanda van der [University Medical Center Utrecht, Julius Center for Health Sciences and Primary Care, Utrecht (Netherlands); Collaboration: Dutch acute stroke study (DUST) investigators

    2016-04-15

    We investigated whether baseline CT angiography (CTA) and CT perfusion (CTP) in acute ischemic stroke could improve prediction of infarct presence and infarct volume on follow-up imaging. We analyzed 906 patients with suspected anterior circulation stroke from the prospective multicenter Dutch acute stroke study (DUST). All patients underwent baseline non-contrast CT, CTA, and CTP and follow-up non-contrast CT/MRI after 3 days. Multivariable regression models were developed including patient characteristics and non-contrast CT, and subsequently, CTA and CTP measures were added. The increase in area under the curve (AUC) and R{sup 2} was assessed to determine the additional value of CTA and CTP. At follow-up, 612 patients (67.5 %) had a detectable infarct on CT/MRI; median infarct volume was 14.8 mL (interquartile range (IQR) 2.8-69.6). Regarding infarct presence, the AUC of 0.82 (95 % confidence interval (CI) 0.79-0.85) for patient characteristics and non-contrast CT was improved with addition of CTA measures (AUC 0.85 (95 % CI 0.82-0.87); p < 0.001) and was even higher after addition of CTP measures (AUC 0.89 (95 % CI 0.87-0.91); p < 0.001) and combined CTA/CTP measures (AUC 0.89 (95 % CI 0.87-0.91); p < 0.001). For infarct volume, adding combined CTA/CTP measures (R{sup 2} = 0.58) was superior to patient characteristics and non-contrast CT alone (R{sup 2} = 0.44) and to addition of CTA alone (R{sup 2} = 0.55) or CTP alone (R{sup 2} = 0.54; all p < 0.001). In the acute stage, CTA and CTP have additional value over patient characteristics and non-contrast CT for predicting infarct presence and infarct volume on follow-up imaging. These findings could be applied for patient selection in future trials on ischemic stroke treatment. (orig.)

  15. Thalamic functional connectivity predicts seizure laterality in individual TLE patients: application of a biomarker development strategy.

    Science.gov (United States)

    Barron, Daniel S; Fox, Peter T; Pardoe, Heath; Lancaster, Jack; Price, Larry R; Blackmon, Karen; Berry, Kristen; Cavazos, Jose E; Kuzniecky, Ruben; Devinsky, Orrin; Thesen, Thomas

    2015-01-01

    Noninvasive markers of brain function could yield biomarkers in many neurological disorders. Disease models constrained by coordinate-based meta-analysis are likely to increase this yield. Here, we evaluate a thalamic model of temporal lobe epilepsy that we proposed in a coordinate-based meta-analysis and extended in a diffusion tractography study of an independent patient population. Specifically, we evaluated whether thalamic functional connectivity (resting-state fMRI-BOLD) with temporal lobe areas can predict seizure onset laterality, as established with intracranial EEG. Twenty-four lesional and non-lesional temporal lobe epilepsy patients were studied. No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons). Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength) successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional) predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional) achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses.

  16. Fetal hemoglobin, α1-microglobulin and hemopexin are potential predictive first trimester biomarkers for preeclampsia.

    Science.gov (United States)

    Anderson, Ulrik Dolberg; Gram, Magnus; Ranstam, Jonas; Thilaganathan, Basky; Kerström, Bo; Hansson, Stefan R

    2016-04-01

    Overproduction of cell-free fetal hemoglobin (HbF) in the preeclamptic placenta has been recently implicated as a new etiological factor of preeclampsia. In this study, maternal serum levels of HbF and the endogenous hemoglobin/heme scavenging systems were evaluated as predictive biomarkers for preeclampsia in combination with uterine artery Doppler ultrasound. Case-control study including 433 women in early pregnancy (mean 13.7weeks of gestation) of which 86 subsequently developed preeclampsia. The serum concentrations of HbF, total cell-free hemoglobin, hemopexin, haptoglobin and α1-microglobulin were measured in maternal serum. All patients were examined with uterine artery Doppler ultrasound. Logistic regression models were developed, which included the biomarkers, ultrasound indices, and maternal risk factors. There were significantly higher serum concentrations of HbF and α1-microglobulin and significantly lower serum concentrations of hemopexin in patients who later developed preeclampsia. The uterine artery Doppler ultrasound results showed significantly higher pulsatility index values in the preeclampsia group. The optimal prediction model was obtained by combining HbF, α1-microglobulin and hemopexin in combination with the maternal characteristics parity, diabetes and pre-pregnancy hypertension. The optimal sensitivity for all preeclampsia was 60% at 95% specificity. Overproduction of placentally derived HbF and depletion of hemoglobin/heme scavenging mechanisms are involved in the pathogenesis of preeclampsia. The combination of HbF and α1-microglobulin and/or hemopexin may serve as a prediction model for preeclampsia in combination with maternal risk factors and/or uterine artery Doppler ultrasound. Copyright © 2016 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.

  17. Triaging TIA/minor stroke patients using the ABCD2 score does not predict those with significant carotid disease.

    Science.gov (United States)

    Walker, J; Isherwood, J; Eveson, D; Naylor, A R

    2012-05-01

    'Rapid Access' TIA Clinics use the ABCD(2) score to triage patients as it is not possible to see everyone with a suspected TIA TIA/minor stroke or 'carotid territory' TIA/minor stroke. Between 1.10.2008 and 31.04.2011, 2452 patients were referred to the Leicester Rapid Access TIA Service. After Stroke Physician review, 1273 (52%) were thought to have suffered a minor stroke/TIA. Of these, both FD/ED referrer and Specialist Stroke Consultant ABCD(2) scores and carotid Duplex ultrasound studies were available for 843 (66%). The yield for identifying a ≥50% stenosis or carotid occlusion was 109/843 (12.9%) in patients with 'any territory' TIA/minor stroke and 101/740 (13.6%) in those with a clinical diagnosis of 'carotid territory' TIA/minor stroke. There was no association between ABCD(2) score and the likelihood of encountering significant carotid disease and analyses of the area under the receiver operating characteristic curve (AUC) for FD/ED referrer and stroke specialist ABCD(2) scores showed no prediction of carotid stenosis (FD/ED: AUC 0.50 (95%CI 0.44-0.55, p = 0.9), Specialist: AUC 0.51 (95%CI 0.45-0.57, p = 0.78). The ABCD(2) score was unable to identify TIA/minor stroke patients with a higher prevalence of clinically important ipsilateral carotid disease. Copyright © 2012 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.

  18. Does caregiver well-being predict stroke survivor depressive symptoms? A mediation analysis.

    Science.gov (United States)

    Grant, Joan S; Clay, Olivio J; Keltner, Norman L; Haley, William E; Wadley, Virginia G; Perkins, Martinique M; Roth, David L

    2013-01-01

    Studies suggest that family caregiver well-being (ie, depressive symptoms and life satisfaction) may affect stroke survivor depressive symptoms. We used mediation analysis to assess whether caregiver well-being might be a factor explaining stroke survivor depressive symptoms, after controlling for demographic factors and stroke survivor impairments and problems. Caregiver/stroke participant dyads (N = 146) completed measures of stroke survivor impairments and problems and depressive symptoms and caregiver depressive symptoms and life satisfaction. Mediation analysis was used to examine whether caregiver well-being mediated the relationship between stroke survivor impairments and problems and stroke survivor depressive symptoms. As expected, more stroke survivor problems and impairments were associated with higher levels of stroke survivor depressive symptoms (P mediated by caregiver life satisfaction (29.29%) and caregiver depressive symptoms (32.95%). Although these measures combined to account for 40.50% of the relationship between survivor problems and impairments and depressive symptoms, the direct effect remained significant. Findings indicate that stroke survivor impairments and problems may affect family caregivers and stroke survivors and a high level of caregiver distress may result in poorer outcomes for stroke survivors. Results highlight the likely importance of intervening with both stroke survivors and family caregivers to optimize recovery after stroke.

  19. MicroRNAs as biomarkers for early breast cancer diagnosis, prognosis and therapy prediction.

    Science.gov (United States)

    Nassar, Farah J; Nasr, Rihab; Talhouk, Rabih

    2017-04-01

    Breast cancer is a major health problem that affects one in eight women worldwide. As such, detecting breast cancer at an early stage anticipates better disease outcome and prolonged patient survival. Extensive research has shown that microRNA (miRNA) are dysregulated at all stages of breast cancer. miRNA are a class of small noncoding RNA molecules that can modulate gene expression and are easily accessible and quantifiable. This review highlights miRNA as diagnostic, prognostic and therapy predictive biomarkers for early breast cancer with an emphasis on the latter. It also examines the challenges that lie ahead in their use as biomarkers. Noteworthy, this review addresses miRNAs reported in patients with early breast cancer prior to chemotherapy, radiotherapy, surgical procedures or distant metastasis (unless indicated otherwise). In this context, miRNA that are mentioned in this review were significantly modulated using more than one statistical test and/or validated by at least two studies. A standardized protocol for miRNA assessment is proposed starting from sample collection to data analysis that ensures comparative analysis of data and reproducibility of results. Copyright © 2016 Elsevier Inc. All rights reserved.

  20. The Functional Diffusion Map: An Imaging Biomarker for the Early Prediction of Cancer Treatment Outcome

    Directory of Open Access Journals (Sweden)

    Bradford A. Moffat

    2006-04-01

    Full Text Available Functional diffusion map (fDM has been recently reported as an early and quantitative biomarker of clinical brain tumor treatment outcome. This MRI approach spatially maps and quantifies treatment-induced changes in tumor water diffusion values resulting from alterations in cell density/cell membrane function and microenvironment. This current study was designed to evaluate the capability of fDM for preclinical evaluation of dose escalation studies and to determine if these changes were correlated with outcome measures (cell kill and overall survival. Serial T2-weighted and diffusion MRI were carried out on rodents with orthotopically implanted 9L brain tumors receiving three doses of 1,3-bis(2-chloroethyl-1-nitrosourea (6.65, 13.3, and 26.6 mg/kg, i.p.. All images were coregistered to baseline T2-weighted images for fDM analysis. Analysis of tumor fDM data on day 4 posttreatment detected dosedependent changes in tumor diffusion values, which were also found to be spatially dependent. Histologic analysis of treated tumors confirmed spatial changes in cellularity as observed by fDM. Early changes in tumor diffusion values were found to be highly correlative with drug dose and independent biologic outcome measures (cell kill and survival. Therefore, the fDM imaging biomarker for early prediction of treatment efficacy can be used in the drug development process.

  1. Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets

    Directory of Open Access Journals (Sweden)

    Karacali Bilge

    2007-10-01

    Full Text Available Abstract Background Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles from publicly available microarray datasets of cancer (breast, lymphoma and renal samples linked to clinical information with an iterative machine learning algorithm. ROC curves were used to assess the prediction error of each profile for classification. We compared the prediction error of profiles correlated with molecular phenotype against profiles correlated with relapse-free status. Prediction error of profiles identified with supervised univariate feature selection algorithms were compared to profiles selected randomly from a all genes on the microarray platform and b a list of known disease-related genes (a priori selection. We also determined the relevance of expression profiles on test arrays from independent datasets, measured on either the same or different microarray platforms. Results Highly discriminative expression profiles were produced on both simulated gene expression data and expression data from breast cancer and lymphoma datasets on the basis of ER and BCL-6 expression, respectively. Use of relapse-free status to identify profiles for prognosis prediction resulted in poorly discriminative decision rules. Supervised feature selection resulted in more accurate classifications than random or a priori selection, however, the difference in prediction error decreased as the number of features increased. These results held when decision rules were applied across-datasets to samples profiled on the same microarray platform. Conclusion Our results show that many gene sets predict molecular phenotypes accurately. Given this, expression profiles identified using different training datasets should be expected to show little agreement. In addition, we demonstrate the difficulty in predicting relapse directly from microarray data using supervised machine

  2. Genomic biomarkers of prenatal intrauterine inflammation in umbilical cord tissue predict later life neurological outcomes.

    Directory of Open Access Journals (Sweden)

    Sloane K Tilley

    Full Text Available Preterm birth is a major risk factor for neurodevelopmental delays and disorders. This study aimed to identify genomic biomarkers of intrauterine inflammation in umbilical cord tissue in preterm neonates that predict cognitive impairment at 10 years of age.Genome-wide messenger RNA (mRNA levels from umbilical cord tissue were obtained from 43 neonates born before 28 weeks of gestation. Genes that were differentially expressed across four indicators of intrauterine inflammation were identified and their functions examined. Exact logistic regression was used to test whether expression levels in umbilical cord tissue predicted neurocognitive function at 10 years of age.Placental indicators of inflammation were associated with changes in the mRNA expression of 445 genes in umbilical cord tissue. Transcripts with decreased expression showed significant enrichment for biological signaling processes related to neuronal development and growth. The altered expression of six genes was found to predict neurocognitive impairment when children were 10 years old These genes include two that encode for proteins involved in neuronal development.Prenatal intrauterine inflammation is associated with altered gene expression in umbilical cord tissue. A set of six of the differentially expressed genes predict cognitive impairment later in life, suggesting that the fetal environment is associated with significant adverse effects on neurodevelopment that persist into later childhood.

  3. Validation of the DRAGON Score in a Chinese Population to Predict Functional Outcome of Intravenous Thrombolysis-Treated Stroke Patients.

    Science.gov (United States)

    Zhang, Xinmiao; Liao, Xiaoling; Wang, Chunjuan; Liu, Liping; Wang, Chunxue; Zhao, Xingquan; Pan, Yuesong; Wang, Yilong; Wang, Yongjun

    2015-08-01

    The DRAGON score predicts functional outcome of ischemic stroke patients treated with intravenous thrombolysis. Our aim was to evaluate its utility in a Chinese stroke population. Patients with acute ischemic stroke treated with intravenous thrombolysis were prospectively registered in the Thrombolysis Implementation and Monitor of acute ischemic Stroke in China. We excluded patients with basilar artery occlusion and missing data, leaving 970 eligible patients. We calculated the DRAGON score, and the clinical outcome was measured by the modified Rankin Scale at 3 months. Model discrimination was quantified by calculating the C statistic. Calibration was assessed using Pearson correlation coefficient. The C statistic was .73 (.70-.76) for good outcome and .75 (.70-.79) for miserable outcome. Proportions of patients with good outcome were 94%, 83%, 70%, and 0% for 0 to 1, 2, 3, and 8 to 10 score points, respectively. Proportions of patients with miserable outcome were 0%, 3%, 9%, and 50% for 0 to 1, 2, 3, and 8 to 10 points, respectively. There was high correlation between predicted and observed probability of 3-month favorable and miserable outcome in the external validation cohort (Pearson correlation coefficient, .98 and .98, respectively, both P DRAGON score showed good performance to predict functional outcome after tissue-type plasminogen activator treatment in the Chinese population. This study demonstrated the accuracy and usability of the DRAGON score in the Chinese population in daily practice. Copyright © 2015 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  4. Automated prediction of tissue outcome after acute ischemic stroke in computed tomography perfusion images

    Science.gov (United States)

    Vos, Pieter C.; Bennink, Edwin; de Jong, Hugo; Velthuis, Birgitta K.; Viergever, Max A.; Dankbaar, Jan Willem

    2015-03-01

    Assessment of the extent of cerebral damage on admission in patients with acute ischemic stroke could play an important role in treatment decision making. Computed tomography perfusion (CTP) imaging can be used to determine the extent of damage. However, clinical application is hindered by differences among vendors and used methodology. As a result, threshold based methods and visual assessment of CTP images has not yet shown to be useful in treatment decision making and predicting clinical outcome. Preliminary results in MR studies have shown the benefit of using supervised classifiers for predicting tissue outcome, but this has not been demonstrated for CTP. We present a novel method for the automatic prediction of tissue outcome by combining multi-parametric CTP images into a tissue outcome probability map. A supervised classification scheme was developed to extract absolute and relative perfusion values from processed CTP images that are summarized by a trained classifier into a likelihood of infarction. Training was performed using follow-up CT scans of 20 acute stroke patients with complete recanalization of the vessel that was occluded on admission. Infarcted regions were annotated by expert neuroradiologists. Multiple classifiers were evaluated in a leave-one-patient-out strategy for their discriminating performance using receiver operating characteristic (ROC) statistics. Results showed that a RandomForest classifier performed optimally with an area under the ROC of 0.90 for discriminating infarct tissue. The obtained results are an improvement over existing thresholding methods and are in line with results found in literature where MR perfusion was used.

  5. Predictive biomarkers for death and rehospitalization in comorbid frail elderly heart failure patients.

    Science.gov (United States)

    Pacho, Cristina; Domingo, Mar; Núñez, Raquel; Lupón, Josep; Núñez, Julio; Barallat, Jaume; Moliner, Pedro; de Antonio, Marta; Santesmases, Javier; Cediel, Germán; Roura, Santiago; Pastor, M Cruz; Tor, Jordi; Bayes-Genis, Antoni

    2018-05-09

    Heart failure (HF) is associated with a high rate of readmissions within 30 days post-discharge and in the following year, especially in frail elderly patients. Biomarker data are scarce in this high-risk population. This study assessed the value of early post-discharge circulating levels of ST2, NT-proBNP, CA125, and hs-TnI for predicting 30-day and 1-year outcomes in comorbid frail elderly patients with HF with mainly preserved ejection fraction (HFpEF). Blood samples were obtained at the first visit shortly after discharge (4.9 ± 2 days). The primary endpoint was the composite of all-cause mortality or HF-related rehospitalization at 30 days and at 1 year. All-cause mortality alone at one year was also a major endpoint. HF-related rehospitalizations alone were secondary end-points. From February 2014 to November 2016, 522 consecutive patients attending the STOP-HF Clinic were included (57.1% women, age 82 ± 8.7 years, mean Barthel index 70 ± 25, mean Charlson comorbidity index 5.6 ± 2.2). The composite endpoint occurred in 8.6% patients at 30 days and in 38.5% at 1 year. In multivariable analysis, ST2 [hazard ratio (HR) 1.53; 95% CI 1.19-1.97; p = 0.001] was the only predictive biomarker at 30 days; at 1 year, both ST2 (HR 1.34; 95% CI 1.15-1.56; p < 0.001) and NT-proBNP (HR 1.19; 95% CI 1.02-1.40; p = 0.03) remained significant. The addition of ST2 and NT-proBNP into a clinical predictive model increased the AUC from 0.70 to 0.75 at 30 days (p = 0.02) and from 0.71 to 0.74 at 1 year (p < 0.05). For all-cause death at 1 year, ST2 (HR 1.50; 95% CI 1.26-1.80; p < 0.001), and CA125 (HR 1.41; 95% CI 1.21-1.63; p < 0.001) remained independent predictors in multivariable analysis. The addition of ST2 and CA125 into a clinical predictive model increased the AUC from 0.74 to 0.78 (p = 0.03). For HF-related hospitalizations, ST2 was the only predictive biomarker in multivariable analyses, both at 30

  6. Tissue Biomarkers in Predicting Response to Sunitinib Treatment of Metastatic Renal Cell Carcinoma.

    Science.gov (United States)

    Trávníček, Ivan; Branžovský, Jindřich; Kalusová, Kristýna; Hes, Ondřej; Holubec, Luboš; Pele, Kevin Bauleth; Ürge, Tomáš; Hora, Milan

    2015-10-01

    To identify tissue biomarkers that are predictive of the therapeutic effect of sunitinib in treatment of metastatic clear cell renal cell carcinoma (mCRCC). Our study included 39 patients with mCRCC treated with sunitinib. Patients were stratified into two groups based on their response to sunitinib treatment: non-responders (progression), and responders (stable disease, regression). The effect of treatment was measured by comparing imaging studies before the initiation treatment with those performed at between 3rd and 7th months of treatment, depending on the patient. Histological samples of tumor tissue and healthy renal parenchyma, acquired during surgery of the primary tumor, were examined with immunohistochemistry to detect tissue targets involved in the signaling pathways of tumor growth and neoangiogenesis. We selected mammalian target of rapamycine, p53, vascular endothelial growth factor, hypoxia-inducible factor 1 and 2 and carbonic anhydrase IX. We compared the average levels of biomarker expression in both, tumor tissue, as well as in healthy renal parenchyma. Results were evaluated using the Student's t-test. For responders, statistically significant differences in marker expression in tumor tissue versus healthy parenchyma were found for mTOR (4%/16.7%; p=0.01031), p53 (4%/12.7%; p=0.042019), VEGF (62.7%/45%; p=0.019836) and CAIX (45%/15.33%; p=0.001624). A further significant difference was found in the frequency of high expression (more than 60%) between tumor tissue and healthy parenchyma in VEGF (65%/35%; p=0.026487) and CAIX (42%/8%; p=0.003328). CAIX was expressed at high levels in the tumor tissue in both evaluated groups. A significantly higher expression of VEGF in CRCC in comparison to healthy parenchyma can predict a better response to sunitinib. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  7. Prediction of postpercutaneous coronary intervention myocardial infarction: insights from intravascular imaging, coronary flow, and biomarker evaluation.

    Science.gov (United States)

    Hoole, Stephen P; Hernández-Sánchez, Jules; Brown, Adam J; Giblett, Joel P; Bennett, Martin R; West, Nick E J

    2018-05-01

    Percutaneous coronary intervention-induced myocardial infarction (PMI) has prognostic significance. Identifying patients at high risk for PMI is desirable as it may alter strategy and facilitate early preventative therapy. We therefore sought to establish whether preprocedural demographic, interventional (plaque characteristics and coronary microcirculatory function), and inflammatory, endothelial damage, and platelet-derived biomarker data could predict the risk of PMI. We performed target vessel pressure wire to assess fractional flow reserve, index of microcirculatory resistance (IMR) and coronary flow reserve, plaque characterization by virtual histology intravascular ultrasound, and assayed peripheral biomarkers before uncomplicated PCI in 88 patients. We then analyzed post-PCI cardiac troponin level to adjudicate PMI based on the third universal definition of myocardial infarction. Overall incidence of PMI was 27%. Women [10/15 (66%) vs. 14/73 (19%), PPMI. Preprocedural coronary flow reserve was lower in individuals with a subsequent PMI (1.8±1.2 vs. 2.1±1.3. P=0.03), and patients with higher pre-PCI IMR were more likely to sustain PMI [IMR>22: 10/23 (44%) vs. ≤22: 14/65 (22%), P=0.04], although neither was predictive after multivariate analysis. Plaque characterization by virtual histology intravascular ultrasound did not discriminate those at risk of PMI. However, peripheral venous interleukin (IL)-18 and IL-8 levels were independently negatively and positively associated with PMI, respectively. Women and those with low BMI, particularly when associated with high IL-8 and low IL-18 levels, appear to be at increased risk of PMI.

  8. Myopodin methylation is a prognostic biomarker and predicts antiangiogenic response in advanced kidney cancer.

    Science.gov (United States)

    Pompas-Veganzones, N; Sandonis, V; Perez-Lanzac, Alberto; Beltran, M; Beardo, P; Juárez, A; Vazquez, F; Cozar, J M; Alvarez-Ossorio, J L; Sanchez-Carbayo, Marta

    2016-10-01

    Myopodin is a cytoskeleton protein that shuttles to the nucleus depending on the cellular differentiation and stress. It has shown tumor suppressor functions. Myopodin methylation status was useful for staging bladder and colon tumors and predicting clinical outcome. To our knowledge, myopodin has not been tested in kidney cancer to date. The purpose of this study was to evaluate whether myopodin methylation status could be clinically useful in renal cancer (1) as a prognostic biomarker and 2) as a predictive factor of response to antiangiogenic therapy in patients with metastatic disease. Methylation-specific polymerase chain reactions (MS-PCR) were used to evaluate myopodin methylation in 88 kidney tumors. These belonged to patients with localized disease and no evidence of disease during follow-up (n = 25) (group 1), and 63 patients under antiangiogenic therapy (sunitinib, sorafenib, pazopanib, and temsirolimus), from which group 2 had non-metastatic disease at diagnosis (n = 32), and group 3 showed metastatic disease at diagnosis (n = 31). Univariate and multivariate Cox analyses were utilized to assess outcome and response to antiangiogenic agents taking progression, disease-specific survival, and overall survival as clinical endpoints. Myopodin was methylated in 50 out of the 88 kidney tumors (56.8 %). Among the 88 cases analyzed, 10 of them recurred (11.4 %), 51 progressed (57.9 %), and 40 died of disease (45.4 %). Myopodin methylation status correlated to MSKCC Risk score (p = 0.050) and the presence of distant metastasis (p = 0.039). Taking all patients, an unmethylated myopodin identified patients with shorter progression-free survival, disease-specific survival, and overall survival. Using also in univariate and multivariate models, an unmethylated myopodin predicted response to antiangiogenic therapy (groups 2 and 3) using progression-free survival, disease-specific, and overall survival as clinical endpoints. Myopodin was revealed

  9. Intracranial pressure-induced optic nerve sheath response as a predictive biomarker for optic disc edema in astronauts.

    Science.gov (United States)

    Wostyn, Peter; De Deyn, Peter Paul

    2017-11-01

    A significant proportion of the astronauts who spend extended periods in microgravity develop ophthalmic abnormalities. Understanding this syndrome, called visual impairment and intracranial pressure (VIIP), has become a high priority for National Aeronautics and Space Administration, especially in view of future long-duration missions (e.g., Mars missions). Moreover, to ensure selection of astronaut candidates who will be able to complete long-duration missions with low risk of the VIIP syndrome, it is imperative to identify biomarkers for VIIP risk prediction. Here, we hypothesize that the optic nerve sheath response to alterations in intracranial pressure may be a potential predictive biomarker for optic disc edema in astronauts. If confirmed, this biomarker could be used for preflight identification of astronauts at risk for developing VIIP-associated optic disc edema.

  10. Response-driven imaging biomarkers for predicting radiation necrosis of the brain

    International Nuclear Information System (INIS)

    Nazem-Zadeh, Mohammad-Reza; Chapman, Christopher H; Lawrence, Theodore S; Ten Haken, Randall K; Tsien, Christina I; Cao, Yue; Chenevert, Thomas

    2014-01-01

    Radiation necrosis is an uncommon but severe adverse effect of brain radiation therapy (RT). Current predictive models based on radiation dose have limited accuracy. We aimed to identify early individual response biomarkers based upon diffusion tensor (DT) imaging and incorporated them into a response model for prediction of radiation necrosis. Twenty-nine patients with glioblastoma received six weeks of intensity modulated RT and concurrent temozolomide. Patients underwent DT-MRI scans before treatment, at three weeks during RT, and one, three, and six months after RT. Cases with radiation necrosis were classified based on generalized equivalent uniform dose (gEUD) of whole brain and DT index early changes in the corpus callosum and its substructures. Significant covariates were used to develop normal tissue complication probability models using binary logistic regression. Seven patients developed radiation necrosis. Percentage changes of radial diffusivity (RD) in the splenium at three weeks during RT and at six months after RT differed significantly between the patients with and without necrosis (p = 0.05 and p = 0.01). Percentage change of RD at three weeks during RT in the 30 Gy dose–volume of the splenium and brain gEUD combined yielded the best-fit logistic regression model. Our findings indicate that early individual response during the course of RT, assessed by radial diffusivity, has the potential to aid the prediction of delayed radiation necrosis, which could provide guidance in dose-escalation trials. (paper)

  11. Population-based study of ABCD2 score, carotid stenosis, and atrial fibrillation for early stroke prediction after transient ischemic attack: the North Dublin TIA study.

    LENUS (Irish Health Repository)

    Sheehan, Orla C

    2010-05-01

    Transient ischemic attack (TIA) etiologic data and the ABCD(2) score may improve early stroke risk prediction, but studies are required in population-based cohorts. We investigated the external validity of the ABCD(2) score, carotid stenosis, and atrial fibrillation for prediction of early recurrent stroke after TIA.

  12. Evaluation of stroke volume variation obtained by arterial pulse contour analysis to predict fluid responsiveness intraoperatively.

    Science.gov (United States)

    Lahner, D; Kabon, B; Marschalek, C; Chiari, A; Pestel, G; Kaider, A; Fleischmann, E; Hetz, H

    2009-09-01

    Fluid management guided by oesophageal Doppler monitor has been reported to improve perioperative outcome. Stroke volume variation (SVV) is considered a reliable clinical predictor of fluid responsiveness. Consequently, the aim of the present trial was to evaluate the accuracy of SVV determined by arterial pulse contour (APCO) analysis, using the FloTrac/Vigileo system, to predict fluid responsiveness as measured by the oesophageal Doppler. Patients undergoing major abdominal surgery received intraoperative fluid management guided by oesophageal Doppler monitoring. Fluid boluses of 250 ml each were administered in case of a decrease in corrected flow time (FTc) to 10%. The ability of SVV to predict fluid responsiveness was assessed by calculation of the area under the receiver operating characteristic (ROC) curve. Twenty patients received 67 fluid boluses. Fifty-two of the 67 fluid boluses administered resulted in fluid responsiveness. SVV achieved an area under the ROC curve of 0.512 [confidence interval (CI) 0.32-0.70]. A cut-off point for fluid responsiveness was found for SVV > or =8.5% (sensitivity: 77%; specificity: 43%; positive predictive value: 84%; and negative predictive value: 33%). This prospective, interventional observer-blinded study demonstrates that SVV obtained by APCO, using the FloTrac/Vigileo system, is not a reliable predictor of fluid responsiveness in the setting of major abdominal surgery.

  13. Integration and relative value of biomarkers for prediction of MCI to AD progression: Spatial patterns of brain atrophy, cognitive scores, APOE genotype and CSF biomarkers

    Directory of Open Access Journals (Sweden)

    Xiao Da

    2014-01-01

    Full Text Available This study evaluates the individual, as well as relative and joint value of indices obtained from magnetic resonance imaging (MRI patterns of brain atrophy (quantified by the SPARE-AD index, cerebrospinal fluid (CSF biomarkers, APOE genotype, and cognitive performance (ADAS-Cog in progression from mild cognitive impairment (MCI to Alzheimer's disease (AD within a variable follow-up period up to 6 years, using data from the Alzheimer's Disease Neuroimaging Initiative-1 (ADNI-1. SPARE-AD was first established as a highly sensitive and specific MRI-marker of AD vs. cognitively normal (CN subjects (AUC = 0.98. Baseline predictive values of all aforementioned indices were then compared using survival analysis on 381 MCI subjects. SPARE-AD and ADAS-Cog were found to have similar predictive value, and their combination was significantly better than their individual performance. APOE genotype did not significantly improve prediction, although the combination of SPARE-AD, ADAS-Cog and APOE ε4 provided the highest hazard ratio estimates of 17.8 (last vs. first quartile. In a subset of 192 MCI patients who also had CSF biomarkers, the addition of Aβ1–42, t-tau, and p-tau181p to the previous model did not improve predictive value significantly over SPARE-AD and ADAS-Cog combined. Importantly, in amyloid-negative patients with MCI, SPARE-AD had high predictive power of clinical progression. Our findings suggest that SPARE-AD and ADAS-Cog in combination offer the highest predictive power of conversion from MCI to AD, which is improved, albeit not significantly, by APOE genotype. The finding that SPARE-AD in amyloid-negative MCI patients was predictive of clinical progression is not expected under the amyloid hypothesis and merits further investigation.

  14. ERic Acute StrokE Recanalization: A study using predictive analytics to assess a new device for mechanical thrombectomy.

    Science.gov (United States)

    Siemonsen, Susanne; Forkert, Nils D; Bernhardt, Martina; Thomalla, Götz; Bendszus, Martin; Fiehler, Jens

    2017-08-01

    Aim and hypothesis Using a new study design, we investigate whether next-generation mechanical thrombectomy devices improve clinical outcomes in ischemic stroke patients. We hypothesize that this new methodology is superior to intravenous tissue plasminogen activator therapy alone. Methods and design ERic Acute StrokE Recanalization is an investigator-initiated prospective single-arm, multicenter, controlled, open label study to compare the safety and effectiveness of a new recanalization device and distal access catheter in acute ischemic stroke patients with symptoms attributable to acute ischemic stroke and vessel occlusion of the internal cerebral artery or middle cerebral artery. Study outcome The primary effectiveness endpoint is the volume of saved tissue. Volume of saved tissue is defined as difference of the actual infarct volume and the brain volume that is predicted to develop infarction by using an optimized high-level machine learning model that is trained on data from a historical cohort treated with IV tissue plasminogen activator. Sample size estimates Based on own preliminary data, 45 patients fulfilling all inclusion criteria need to complete the study to show an efficacy >38% with a power of 80% and a one-sided alpha error risk of 0.05 (based on a one sample t-test). Discussion ERic Acute StrokE Recanalization is the first prospective study in interventional stroke therapy to use predictive analytics as primary and secondary endpoint. Such trial design cannot replace randomized controlled trials with clinical endpoints. However, ERic Acute StrokE Recanalization could serve as an exemplary trial design for evaluating nonpivotal neurovascular interventions.

  15. Identification of a 5-protein biomarker molecular signature for predicting Alzheimer's disease.

    Directory of Open Access Journals (Sweden)

    Martín Gómez Ravetti

    Full Text Available BACKGROUND: Alzheimer's disease (AD is a progressive brain disease with a huge cost to human lives. The impact of the disease is also a growing concern for the governments of developing countries, in particular due to the increasingly high number of elderly citizens at risk. Alzheimer's is the most common form of dementia, a common term for memory loss and other cognitive impairments. There is no current cure for AD, but there are drug and non-drug based approaches for its treatment. In general the drug-treatments are directed at slowing the progression of symptoms. They have proved to be effective in a large group of patients but success is directly correlated with identifying the disease carriers at its early stages. This justifies the need for timely and accurate forms of diagnosis via molecular means. We report here a 5-protein biomarker molecular signature that achieves, on average, a 96% total accuracy in predicting clinical AD. The signature is composed of the abundances of IL-1alpha, IL-3, EGF, TNF-alpha and G-CSF. METHODOLOGY/PRINCIPAL FINDINGS: Our results are based on a recent molecular dataset that has attracted worldwide attention. Our paper illustrates that improved results can be obtained with the abundance of only five proteins. Our methodology consisted of the application of an integrative data analysis method. This four step process included: a abundance quantization, b feature selection, c literature analysis, d selection of a classifier algorithm which is independent of the feature selection process. These steps were performed without using any sample of the test datasets. For the first two steps, we used the application of Fayyad and Irani's discretization algorithm for selection and quantization, which in turn creates an instance of the (alpha-beta-k-Feature Set problem; a numerical solution of this problem led to the selection of only 10 proteins. CONCLUSIONS/SIGNIFICANCE: the previous study has provided an extremely

  16. A predictive model for diagnosing stroke-related apraxia of speech.

    Science.gov (United States)

    Ballard, Kirrie J; Azizi, Lamiae; Duffy, Joseph R; McNeil, Malcolm R; Halaki, Mark; O'Dwyer, Nicholas; Layfield, Claire; Scholl, Dominique I; Vogel, Adam P; Robin, Donald A

    2016-01-29

    Diagnosis of the speech motor planning/programming disorder, apraxia of speech (AOS), has proven challenging, largely due to its common co-occurrence with the language-based impairment of aphasia. Currently, diagnosis is based on perceptually identifying and rating the severity of several speech features. It is not known whether all, or a subset of the features, are required for a positive diagnosis. The purpose of this study was to assess predictor variables for the presence of AOS after left-hemisphere stroke, with the goal of increasing diagnostic objectivity and efficiency. This population-based case-control study involved a sample of 72 cases, using the outcome measure of expert judgment on presence of AOS and including a large number of independently collected candidate predictors representing behavioral measures of linguistic, cognitive, nonspeech oral motor, and speech motor ability. We constructed a predictive model using multiple imputation to deal with missing data; the Least Absolute Shrinkage and Selection Operator (Lasso) technique for variable selection to define the most relevant predictors, and bootstrapping to check the model stability and quantify the optimism of the developed model. Two measures were sufficient to distinguish between participants with AOS plus aphasia and those with aphasia alone, (1) a measure of speech errors with words of increasing length and (2) a measure of relative vowel duration in three-syllable words with weak-strong stress pattern (e.g., banana, potato). The model has high discriminative ability to distinguish between cases with and without AOS (c-index=0.93) and good agreement between observed and predicted probabilities (calibration slope=0.94). Some caution is warranted, given the relatively small sample specific to left-hemisphere stroke, and the limitations of imputing missing data. These two speech measures are straightforward to collect and analyse, facilitating use in research and clinical settings. Copyright

  17. Stroke volume variation compared with pulse pressure variation and cardiac index changes for prediction of fluid responsiveness in mechanically ventilated patients

    Directory of Open Access Journals (Sweden)

    Randa Aly Soliman

    2015-04-01

    Conclusions: Baseline stroke volume variation ⩾8.15% predicted fluid responsiveness in mechanically ventilated patients with acute circulatory failure. The study also confirmed the ability of pulse pressure variation to predict fluid responsiveness.

  18. Noninvasive pulse pressure variation and stroke volume variation to predict fluid responsiveness at multiple thresholds : a prospective observational study

    NARCIS (Netherlands)

    Vos, Jaap Jan; Poterman, Marieke; Papineau Salm, Pieternel; Van Amsterdam, Kai; Struys, Michel M. R. F.; Scheeren, Thomas W. L.; Kalmar, Alain F.

    2015-01-01

    Pulse pressure variation (PPV) and stroke volume variation (SVV) are dynamic preload variables that can be measured noninvasively to assess fluid responsiveness (FR) in anesthetized patients with mechanical ventilation. Few studies have examined the effectiveness of predicting FR according to the

  19. External validation of the DRAGON score in an elderly Spanish population: prediction of stroke prognosis after IV thrombolysis.

    Science.gov (United States)

    Giralt-Steinhauer, Eva; Rodríguez-Campello, Ana; Cuadrado-Godia, Elisa; Ois, Ángel; Jiménez-Conde, Jordi; Soriano-Tárraga, Carolina; Roquer, Jaume

    2013-01-01

    Intravenous (i.v.) thrombolysis within 4.5 h of symptom onset has proven efficacy in acute ischemic stroke treatment, although half of all outcomes are unfavorable. The recently published DRAGON score aims to predict the 3-month outcome in stroke patients who have received i.v. alteplase. The purpose of this study was an external validation of the results of the DRAGON score in a Spanish cohort. Patients with acute stroke treated with alteplase were prospectively registered in our BasicMar database. We collected demographic characteristics, vascular risk factors, the time from stroke onset to treatment, baseline serum glucose levels and stroke severity for this population. We then reviewed hyperdense cerebral artery signs and signs of early infarct on the admission CT scan. We calculated the DRAGON score and used the developers' 3-month prognosis categories: good [modified Rankin Scale score (mRS) 0-2], poor (mRS 3-6) and miserable (mRS 5-6) outcome. Discrimination was tested using the area under the receiver operator curve (AUC-ROC). Calibration was assessed by the Hosmer-Lemeshow test. Our final cohort of 297 patients was older (median age 74 years, IQR 65-80) and had more risk factors and severe strokes [median National Institutes of Health Stroke Scale (NIHSS) points 13, IQR 7-19] than the original study population. Poor prognosis was observed in 143 (48.1%) patients. Higher DRAGON scores were associated with a higher risk of poor prognosis. None of our treated stroke patients with a DRAGON score ≥8 at admission experienced a favorable outcome after 3 months. All DRAGON variables were significantly associated with a worse outcome in the multivariate analysis except for onset-to-treatment time (p = 0.334). Discrimination to predict poor prognosis was very good (AUC-ROC 0.84) and the score had good Hosmer-Lemeshow calibration (p = 0.84). The DRAGON score is easy to perform and offers a rapid, reliable prediction of poor prognosis in acute-stroke patients

  20. External validation of the A2SD2 and ISAN scales for predicting infectious respiratory complications of ischaemic stroke.

    Science.gov (United States)

    Ramírez-Moreno, J M; Martínez-Acevedo, M; Cordova, R; Roa, A M; Constantino, A B; Ceberino, D; Muñoz, P

    2016-10-21

    Pneumonia as a complication of stroke is associated with poor outcomes. The A2DS2 and ISAN scales were developed by German and English researchers, respectively, to predict in-hospital stroke-associated pneumonia. We conducted an external validation study of these scales in a series of consecutive patients admitted to our hospital due to ischaemic stroke. These predictive models were applied to a sample of 340 consecutive patients admitted to hospital in 2015 due to stroke. Discrimination was assessed by calculating the area under the ROC curve for diagnostic efficacy. Calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test and graphing the corresponding curve. Logistic regression analysis was performed to determine the independent predictors of respiratory infection secondary to stroke. We included 285 patients, of whom 45 (15.8%) had respiratory infection after stroke according to the study criteria. Mean age was 71.01±12.62 years; men accounted for 177 of the patients (62.1%). Seventy-two patients (25.3%) had signs or symptoms of dysphagia, 42 (14.7%) had atrial fibrillation, and 14 (4.9%) were functionally dependent before stroke; the median NIHSS score was 4 points. Mean scores on A2DS2 and ISAN were 3.25±2.54 and 6.49±3.64, respectively. Our analysis showed that higher A2DS2 scores were associated with an increased risk of infection (OR=1.576; 95% CI: 1.363-1.821); the same was true for ISAN scores (OR=1.350; 95% CI: 1.214-1.501). High scores on A2DS2 and ISAN were found to be a strong predictor of respiratory infection associated with acute stroke in a cohort of consecutive patients with stroke. These easy-to-use scales are promising tools for predicting this complication in routine clinical practice. Copyright © 2016 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

  1. DNA Repair Biomarkers Predict Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer

    International Nuclear Information System (INIS)

    Alexander, Brian M.; Wang Xiaozhe; Niemierko, Andrzej; Weaver, David T.; Mak, Raymond H.; Roof, Kevin S.; Fidias, Panagiotis; Wain, John; Choi, Noah C.

    2012-01-01

    Purpose: The addition of neoadjuvant chemoradiotherapy prior to surgical resection for esophageal cancer has improved clinical outcomes in some trials. Pathologic complete response (pCR) following neoadjuvant therapy is associated with better clinical outcome in these patients, but only 22% to 40% of patients achieve pCR. Because both chemotherapy and radiotherapy act by inducing DNA damage, we analyzed proteins selected from multiple DNA repair pathways, using quantitative immunohistochemistry coupled with a digital pathology platform, as possible biomarkers of treatment response and clinical outcome. Methods and Materials: We identified 79 patients diagnosed with esophageal cancer between October 1994 and September 2002, with biopsy tissue available, who underwent neoadjuvant chemoradiotherapy prior to surgery at the Massachusetts General Hospital and used their archived, formalin-fixed, paraffin-embedded biopsy samples to create tissue microarrays (TMA). TMA sections were stained using antibodies against proteins in various DNA repair pathways including XPF, FANCD2, PAR, MLH1, PARP1, and phosphorylated MAPKAP kinase 2 (pMK2). Stained TMA slides were evaluated using machine-based image analysis, and scoring incorporated both the intensity and the quantity of positive tumor nuclei. Biomarker scores and clinical data were assessed for correlations with clinical outcome. Results: Higher scores for MLH1 (p = 0.018) and lower scores for FANCD2 (p = 0.037) were associated with pathologic response to neoadjuvant chemoradiation on multivariable analysis. Staining of MLH1, PARP1, XPF, and PAR was associated with recurrence-free survival, and staining of PARP1 and FANCD2 was associated with overall survival on multivariable analysis. Conclusions: DNA repair proteins analyzed by immunohistochemistry may be useful as predictive markers for response to neoadjuvant chemoradiotherapy in patients with esophageal cancer. These results are hypothesis generating and need

  2. Urinary biomarkers TIMP-2 and IGFBP7 early predict acute kidney injury after major surgery.

    Directory of Open Access Journals (Sweden)

    Ivan Gocze

    Full Text Available To assess the ability of the urinary biomarkers IGFBP7 (insulin-like growth factor-binding protein 7 and TIMP-2 (tissue inhibitor of metalloproteinase 2 to early predict acute kidney injury (AKI in high-risk surgical patients.Postoperative AKI is associated with an increase in short and long-term mortality. Using IGFBP7 and TIMP-2 for early detection of cellular kidney injury, thus allowing the early initiation of renal protection measures, may represent a new concept of evaluating renal function.In this prospective study, urinary [TIMP-2]×[IGFBP7] was measured in surgical patients at high risk for AKI. A predefined cut-off value of [TIMP-2]×[IGFBP7] >0.3 was used for assessing diagnostic accuracy. Perioperative characteristics were evaluated, and ROC analyses as well as logistic regression models of risk assessment were calculated with and without a [TIMP-2]×[IGFBP7] test.107 patients were included in the study, of whom 45 (42% developed AKI. The highest median values of biomarker were detected in septic, transplant and patients after hepatic surgery (1.24 vs 0.45 vs 0.47 ng/l²/1000. The area under receiving operating characteristic curve (AUC for the risk of any AKI was 0.85, for early use of RRT 0.83 and for 28-day mortality 0.77. In a multivariable model with established perioperative risk factors, the [TIMP-2]×[IGFBP7] test was the strongest predictor of AKI and significantly improved the risk assessment (p<0.001.Urinary [TIMP-2]×[IGFBP7] test sufficiently detect patients with risk of AKI after major non-cardiac surgery. Due to its rapid responsiveness it extends the time frame for intervention to prevent development of AKI.

  3. Intracellular signaling entropy can be a biomarker for predicting the development of cervical intraepithelial neoplasia.

    Directory of Open Access Journals (Sweden)

    Masakazu Sato

    Full Text Available While the mortality rates for cervical cancer have been drastically reduced after the introduction of the Pap smear test, it still is one of the leading causes of death in women worldwide. Additionally, studies that appropriately evaluate the risk of developing cervical lesions are needed. Therefore, we investigated whether intracellular signaling entropy, which is measured with microarray data, could be useful for predicting the risks of developing cervical lesions. We used three datasets, GSE63514 (histology, GSE27678 (cytology and GSE75132 (cytology, a prospective study. From the data in GSE63514, the entropy rate was significantly increased with disease progression (normal < cervical intraepithelial neoplasia, CIN < cancer (Kruskal-Wallis test, p < 0.0001. From the data in GSE27678, similar results (normal < low-grade squamous intraepithelial lesions, LSILs < high-grade squamous intraepithelial lesions, HSILs ≤ cancer were obtained (Kruskal-Wallis test, p < 0.001. From the data in GSE75132, the entropy rate tended to be higher in the HPV-persistent groups than the HPV-negative group. The group that was destined to progress to CIN 3 or higher had a tendency to have a higher entropy rate than the HPV16-positive without progression group. In conclusion, signaling entropy was suggested to be different for different lesion statuses and could be a useful biomarker for predicting the development of cervical intraepithelial neoplasia.

  4. Effect of Prior Atorvastatin Treatment on the Frequency of Hospital Acquired Pneumonia and Evolution of Biomarkers in Patients with Acute Ischemic Stroke: A Multicenter Prospective Study

    Directory of Open Access Journals (Sweden)

    Yuetian Yu

    2017-01-01

    Full Text Available Objective. To investigate whether prior treatment of atorvastatin reduces the frequency of hospital acquired pneumonia (HAP. Methods. Totally, 492 patients with acute ischemic stroke and Glasgow Coma Scale ≤ 8 were enrolled in this study. Subjects were assigned to prior atorvastatin treatment group (n=268, PG and no prior treatment group (n=224, NG. All the patients were given 20 mg atorvastatin every night during their hospital stay. HAP frequency and 28-day mortality were measured. Levels of inflammatory biomarkers [white blood cell (WBC, procalcitonin (PCT, tumor necrosis factor-alpha (TNF-α, and interleukin-6 (IL-6] were tested. Results. There was no significant difference in the incidence of HAP between PG and NG (25.74% versus. 24.55%, p>0.05 and 28-day mortality (50.72% versus 58.18%, p>0.05. However, prior statin treatment did modify the mortality of ventilator associated pneumonia (VAP (36.54% versus 58.14%, p=0.041 and proved to be a protective factor (HR, 0.564; 95% CI, 0.310~0.825, p=0.038. Concentrations of TNF-α and IL-6 in PG VAP cases were lower than those in NG VAP cases (p<0.01. Conclusions. Prior atorvastatin treatment in patients with ischemic stroke was associated with a lower concentration of IL-6 and TNF-α and improved the outcome of VAP. This clinical study has been registered with ChiCTR-ROC-17010633 in Chinese Clinical Trial Registry.

  5. Clinical risk stratification optimizes value of biomarkers to predict new-onset heart failure in a community-based cohort.

    Science.gov (United States)

    Brouwers, Frank P; van Gilst, Wiek H; Damman, Kevin; van den Berg, Maarten P; Gansevoort, Ron T; Bakker, Stephan J L; Hillege, Hans L; van Veldhuisen, Dirk J; van der Harst, Pim; de Boer, Rudolf A

    2014-09-01

    We aim to identify and quantify the value of biomarkers for incident new-onset heart failure (HF) in a community-based cohort and subgroups based on cardiovascular risk and evaluate the prognostic value of 13 biomarkers for HF with reduced and preserved ejection fraction. Thirteen biomarkers reflecting diverse pathophysiologic domains were examined in 8569 HF-free participants in Prevention of Vascular and Renal Endstage Disease (mean age, 49 years; 50% men). Subjects were categorized in 2 risk groups based on cardiovascular history. Incremental value per biomarker was assessed using Harrell C-indices. One hundred sixty-eight subjects (2.4%) were diagnosed with new-onset HF in the low-risk group (n=6915; Framingham Risk Score, 5.9%) and 206 (12.2%) subjects in the high-risk group (n=1654; Framingham Risk Score, 18.6%). The association of natriuretic peptides, adrenomedullin, endothelin, and galectin-3 with new-onset HF was stronger in the high-risk group (all Prisk for new-onset HF between both risk groups. The best model for new-onset HF included the combination of N-terminal pro-B-type natriuretic peptide, troponin-T, and urinary albumin excretion, increasing model accuracy to 0.81 (9.5%, Prisk group. Except for a modest effect of cystatin-C, no biomarker was associated with increased risk for HF with preserved ejection fraction. Risk stratification increases the incremental value per biomarker to predict new-onset HF, especially HF with reduced ejection fraction. We suggest that routine biomarker testing should be limited to the use of natriuretic peptides and troponin-T in patients with increased cardiovascular risk. © 2014 American Heart Association, Inc.

  6. Role of biomarkers in predicting CVD risk in the setting of HIV infection?

    DEFF Research Database (Denmark)

    Worm, Signe W; Hsue, Priscilla

    2010-01-01

    with risk of CVD. Biomarkers associated with inflammation such as C-reactive protein and interleukin-6 have been suggested to improve risk stratification among intermediate-risk persons; however, their routine use is not recommended in the general population. Both biomarkers have recently been reported......-infected population and will increase as this population continues to age. Identification of intermediate-risk individuals using biomarkers will be an important tool for clinicians in the future to be able to treat HIV-infected individuals aggressively. Future studies of biomarkers among individuals with HIV...

  7. Cardiovascular Disease Biomarkers Predict Susceptibility or Resistance to Lung Injury in World Trade Center Dust Exposed Firefighters

    Science.gov (United States)

    Weiden, Michael D.; Naveed, Bushra; Kwon, Sophia; Cho, Soo Jung; Comfort, Ashley L.; Prezant, David J.; Rom, William N.; Nolan, Anna

    2013-01-01

    Pulmonary vascular loss is an early feature of chronic obstructive pulmonary disease. Biomarkers of inflammation and of metabolic syndrome, predicts loss of lung function in World Trade Center Lung Injury (WTC-LI). We investigated if other cardiovascular disease (CVD) biomarkers also predicted WTC-LI. This nested case-cohort study used 801 never smoker, WTC exposed firefighters with normal pre-9/11 lung function presenting for subspecialty pulmonary evaluation (SPE) before March, 2008. A representative sub-cohort of 124/801 with serum drawn within six months of 9/11 defined CVD biomarker distribution. Post-9/11/01 FEV1 at subspecialty exam defined cases: susceptible WTC-LI cases with FEV1≤77% predicted (66/801) and resistant WTC-LI cases with FEV1≥107% (68/801). All models were adjusted for WTC exposure intensity, BMI at SPE, age at 9/11, and pre-9/11 FEV1. Susceptible WTC-LI cases had higher levels of Apo-AII, CRP, and MIP-4 with significant RRs of 3.85, 3.93, and 0.26 respectively with an area under the curve (AUC) of 0.858. Resistant WTC-LI cases had significantly higher sVCAM and lower MPO with RRs of 2.24, and 2.89 respectively; AUC 0.830. Biomarkers of CVD in serum six-month post-9/11 predicted either susceptibility or resistance to WTC-LI. These biomarkers may define pathways producing or protecting subjects from pulmonary vascular disease and associated loss of lung function after an irritant exposure. PMID:22903969

  8. Prediction of the survival and functional ability of severe stroke patients after ICU therapeutic intervention

    Directory of Open Access Journals (Sweden)

    Aoun-Bacha Zeina

    2008-06-01

    Full Text Available Abstract Background This study evaluated the benefits and impact of ICU therapeutic interventions on the survival and functional ability of severe cerebrovascular accident (CVA patients. Methods Sixty-two ICU patients suffering from severe ischemic/haemorrhagic stroke were evaluated for CVA severity using APACHE II and the Glasgow coma scale (GCS. Survival was determined using Kaplan-Meier survival tables and survival prediction factors were determined by Cox multivariate analysis. Functional ability was assessed using the stroke impact scale (SIS-16 and Karnofsky score. Risk factors, life support techniques and neurosurgical interventions were recorded. One year post-CVA dependency was investigated using multivariate analysis based on linear regression. Results The study cohort constituted 6% of all CVA (37.8% haemorrhagic/62.2% ischemic admissions. Patient mean(SD age was 65.8(12.3 years with a 1:1 male: female ratio. During the study period 16 patients had died within the ICU and seven in the year following hospital release. The mean(SD APACHE II score at hospital admission was 14.9(6.0 and ICU mean duration of stay was 11.2(15.4 days. Mechanical ventilation was required in 37.1% of cases. Risk ratios were; GCS at admission 0.8(0.14, (p = 0.024, APACHE II 1.11(0.11, (p = 0.05 and duration of mechanical ventilation 1.07(0.07, (p = 0.046. Linear coefficients were: type of CVA – haemorrhagic versus ischemic: -18.95(4.58 (p = 0.007, GCS at hospital admission: -6.83(1.08, (p = 0.001, and duration of hospital stay -0.38(0.14, (p = 0.40. Conclusion To ensure a better prognosis CVA patients require ICU therapeutic interventions. However, as we have shown, where tests can determine the worst affected patients with a poor vital and functional outcome should treatment be withheld?

  9. Tailoring the implementation of new biomarkers based on their added predictive value in subgroups of individuals.

    Directory of Open Access Journals (Sweden)

    A van Giessen

    Full Text Available The value of new biomarkers or imaging tests, when added to a prediction model, is currently evaluated using reclassification measures, such as the net reclassification improvement (NRI. However, these measures only provide an estimate of improved reclassification at population level. We present a straightforward approach to characterize subgroups of reclassified individuals in order to tailor implementation of a new prediction model to individuals expected to benefit from it.In a large Dutch population cohort (n = 21,992 we classified individuals to low (< 5% and high (≥ 5% fatal cardiovascular disease risk by the Framingham risk score (FRS and reclassified them based on the systematic coronary risk evaluation (SCORE. Subsequently, we characterized the reclassified individuals and, in case of heterogeneity, applied cluster analysis to identify and characterize subgroups. These characterizations were used to select individuals expected to benefit from implementation of SCORE.Reclassification after applying SCORE in all individuals resulted in an NRI of 5.00% (95% CI [-0.53%; 11.50%] within the events, 0.06% (95% CI [-0.08%; 0.22%] within the nonevents, and a total NRI of 0.051 (95% CI [-0.004; 0.116]. Among the correctly downward reclassified individuals cluster analysis identified three subgroups. Using the characterizations of the typically correctly reclassified individuals, implementing SCORE only in individuals expected to benefit (n = 2,707,12.3% improved the NRI to 5.32% (95% CI [-0.13%; 12.06%] within the events, 0.24% (95% CI [0.10%; 0.36%] within the nonevents, and a total NRI of 0.055 (95% CI [0.001; 0.123]. Overall, the risk levels for individuals reclassified by tailored implementation of SCORE were more accurate.In our empirical example the presented approach successfully characterized subgroups of reclassified individuals that could be used to improve reclassification and reduce implementation burden. In particular when newly

  10. FDG-PET as a predictive biomarker for therapy with everolimus in metastatic renal cell cancer

    International Nuclear Information System (INIS)

    Chen, James L; Appelbaum, Daniel E; Kocherginsky, Masha; Cowey, Charles L; Kimryn Rathmell, Wendy; McDermott, David F; Stadler, Walter M

    2013-01-01

    The mTOR (mammalian target of rapamycin) inhibitor, everolimus, affects tumor growth by targeting cellular metabolic proliferation pathways and delays renal cell carcinoma (RCC) progression. Preclinical evidence suggests that baseline elevated tumor glucose metabolism as quantified by FDG-PET ([ 18 F] fluorodeoxy-glucose positron emission tomography) may predict antitumor activity. Metastatic RCC (mRCC) patients refractory to vascular endothelial growth factor (VEGF) pathway inhibition were treated with standard dose everolimus. FDG-PET scans were obtained at baseline and 2 weeks; serial computed tomography (CT) scans were obtained at baseline and every 8 weeks. Maximum standardized uptake value (SUVmax) of the most FDG avid lesion, average SUVmax of all measured lesions and their corresponding 2-week relative changes were examined for association with 8-week change in tumor size. A total of 63 patients were enrolled; 50 were evaluable for the primary endpoint of which 48 had both PET scans. Patient characteristics included the following: 36 (72%) clear cell histology and median age 59 (range: 37–80). Median pre- and 2-week treatment average SUVmax were 6.6 (1–17.9) and 4.2 (1–13.9), respectively. Response evaluation criteria in solid tumors (RECIST)-based measurements demonstrated an average change in tumor burden of 0.2% (−32.7% to 35.9%) at 8 weeks. Relative change in average SUVmax was the best predictor of change in tumor burden (all evaluable P = 0.01; clear cell subtype P = 0.02), with modest correlation. Baseline average SUVmax was correlated with overall survival and progression-free survival (PFS) (P = 0.023; 0.020), but not with change in tumor burden. Everolimus therapy decreased SUVs on follow-up PET scans in mRCC patients, but changes were only modestly correlated with changes in tumor size. Thus, clinical use of FDG-PET-based biomarkers is challenged by high variability. In this phase II trial, FDG-PET was explored as a predictive biomarker

  11. An etiologic prediction model incorporating biomarkers to predict the bladder cancer risk associated with occupational exposure to aromatic amines: a pilot study

    OpenAIRE

    Mastrangelo, Giuseppe; Carta, Angela; Arici, Cecilia; Pavanello, Sofia; Porru, Stefano

    2017-01-01

    Background No etiological prediction model incorporating biomarkers is available to predict bladder cancer risk associated with occupational exposure to aromatic amines. Methods Cases were 199 bladder cancer patients. Clinical, laboratory and genetic data were predictors in logistic regression models (full and short) in which the dependent variable was 1 for 15 patients with aromatic amines related bladder cancer and 0 otherwise. The receiver operating characteristics approach was adopted; th...

  12. Comparison of atria and CHA2DS2-vasc risk stratification schemes for the prediction of stroke in the individual patient with atrial fibrillation and the impact on treatment decisions

    NARCIS (Netherlands)

    Van Den Ham, Hendrika A.; Klungel, Olaf H.; Singer, Daniel E.; Leufkens, Hubert G.M.; Van Staa, Tjeerd P.

    2014-01-01

    Background: Atrial fibrillation (AF) increases the risk of ischaemic stroke and treatment with anticoagulants should be prescribed according to stroke risk. Objectives: To compare the predictive ability of the currently recommended CHA2DS2-VASc ischaemic stroke risk score with the new ATRIA stroke

  13. Magnetic Resonance Imaging-DRAGON score: 3-month outcome prediction after intravenous thrombolysis for anterior circulation stroke.

    Science.gov (United States)

    Turc, Guillaume; Apoil, Marion; Naggara, Olivier; Calvet, David; Lamy, Catherine; Tataru, Alina M; Méder, Jean-François; Mas, Jean-Louis; Baron, Jean-Claude; Oppenheim, Catherine; Touzé, Emmanuel

    2013-05-01

    The DRAGON score, which includes clinical and computed tomographic scan parameters, showed a high specificity to predict 3-month outcome in patients with acute ischemic stroke treated by intravenous tissue plasminogen activator. We adapted the score for patients undergoing MRI as the first-line diagnostic tool. We reviewed patients with consecutive anterior circulation ischemic stroke treated ≤ 4.5 hour by intravenous tissue plasminogen activator between 2003 and 2012 in our center, where MRI is systematically implemented as first-line diagnostic work-up. We derived the MRI-DRAGON score keeping all clinical parameters of computed tomography-DRAGON (age, initial National Institutes of Health Stroke Scale and glucose level, prestroke handicap, onset to treatment time), and considering the following radiological variables: proximal middle cerebral artery occlusion on MR angiography instead of hyperdense middle cerebral artery sign, and diffusion-weighted imaging Alberta Stroke Program Early Computed Tomography Score (DWI ASPECTS) ≤ 5 instead of early infarct signs on computed tomography. Poor 3-month outcome was defined as modified Rankin scale >2. We calculated c-statistics as a measure of predictive ability and performed an internal cross-validation. Two hundred twenty-eight patients were included. Poor outcome was observed in 98 (43%) patients and was significantly associated with all parameters of the MRI-DRAGON score in multivariate analysis, except for onset to treatment time (nonsignificant trend). The c-statistic was 0.83 (95% confidence interval, 0.78-0.88) for poor outcome prediction. All patients with a MRI-DRAGON score ≤ 2 (n=22) had a good outcome, whereas all patients with a score ≥ 8 (n=11) had a poor outcome. The MRI-DRAGON score is a simple tool to predict 3-month outcome in acute stroke patients screened by MRI then treated by intravenous tissue plasminogen activator and may help for therapeutic decision.

  14. Validation of the RRE-90 Scale to Predict Stroke Risk after Transient Symptoms with Infarction: A Prospective Cohort Study.

    Directory of Open Access Journals (Sweden)

    Bo Song

    Full Text Available The risk of stroke after a transient ischemic attack (TIA for patients with a positive diffusion-weighted image (DWI, i.e., transient symptoms with infarction (TSI, is much higher than for those with a negative DWI. The aim of this study was to validate the predictive value of a web-based recurrence risk estimator (RRE; http://www.nmr.mgh.harvard.edu/RRE/ of TSI.Data from the prospective hospital-based TIA database of the First Affiliated Hospital of Zhengzhou University were analyzed. The RRE and ABCD2 scores were calculated within 7 days of symptom onset. The predictive outcome was ischemic stroke occurrence at 90 days. The receiver-operating characteristics curves were plotted, and the predictive value of the two models was assessed by computing the C statistics.A total of 221 eligible patients were prospectively enrolled, of whom 46 (20.81% experienced a stroke within 90 days. The 90-day stroke risk in high-risk TSI patients (RRE ≥4 was 3.406-fold greater than in those at low risk (P <0.001. The C statistic of RRE (0.681; 95% confidence interval [CI], 0.592-0.771 was statistically higher than that of ABCD2 score (0.546; 95% CI, 0.454-0.638; Z = 2.115; P = 0.0344 at 90 days.The RRE score had a higher predictive value than the ABCD2 score for assessing the 90-day risk of stroke after TSI.

  15. Comparison of classification methods for voxel-based prediction of acute ischemic stroke outcome following intra-arterial intervention

    Science.gov (United States)

    Winder, Anthony J.; Siemonsen, Susanne; Flottmann, Fabian; Fiehler, Jens; Forkert, Nils D.

    2017-03-01

    Voxel-based tissue outcome prediction in acute ischemic stroke patients is highly relevant for both clinical routine and research. Previous research has shown that features extracted from baseline multi-parametric MRI datasets have a high predictive value and can be used for the training of classifiers, which can generate tissue outcome predictions for both intravenous and conservative treatments. However, with the recent advent and popularization of intra-arterial thrombectomy treatment, novel research specifically addressing the utility of predictive classi- fiers for thrombectomy intervention is necessary for a holistic understanding of current stroke treatment options. The aim of this work was to develop three clinically viable tissue outcome prediction models using approximate nearest-neighbor, generalized linear model, and random decision forest approaches and to evaluate the accuracy of predicting tissue outcome after intra-arterial treatment. Therefore, the three machine learning models were trained, evaluated, and compared using datasets of 42 acute ischemic stroke patients treated with intra-arterial thrombectomy. Classifier training utilized eight voxel-based features extracted from baseline MRI datasets and five global features. Evaluation of classifier-based predictions was performed via comparison to the known tissue outcome, which was determined in follow-up imaging, using the Dice coefficient and leave-on-patient-out cross validation. The random decision forest prediction model led to the best tissue outcome predictions with a mean Dice coefficient of 0.37. The approximate nearest-neighbor and generalized linear model performed equally suboptimally with average Dice coefficients of 0.28 and 0.27 respectively, suggesting that both non-linearity and machine learning are desirable properties of a classifier well-suited to the intra-arterial tissue outcome prediction problem.

  16. An overview of children as a special population-Relevance to predictive biomarkers

    International Nuclear Information System (INIS)

    Kimmel, Gary L.

    2005-01-01

    There has been an increasing focus on children as a special population in the fields of toxicology and epidemiology. At the same time, there has been considerable improvement in the technology for defining normal development and pathways of pathogenesis. Increased support of these areas has culminated in stronger research programs and greater professional involvement in addressing the specific challenges of applying new techniques and data to the improvement of children's health. Part of these challenges relates to the ever changing environment of the child. Not only does a child's anatomy, physiology, and metabolism change with time, but their lifestyle and awareness change as well. All of these can have a significant impact on a child's exposure and the potential of that exposure to have an effect on health and development. This paper will provide a brief overview of the susceptibility of the child relative to sensitive developmental life stages, the changing nature of exposure parameters during development, and how these factors can impact the relevance of predictive biomarkers of chemical toxicity in children

  17. Current and Future Applications of Biomedical Engineering for Proteomic Profiling: Predictive Biomarkers in Neuro-Traumatology

    Directory of Open Access Journals (Sweden)

    Mario Ganau

    2018-02-01

    Full Text Available This systematic review aims to summarize the impact of nanotechnology and biomedical engineering in defining clinically meaningful predictive biomarkers in patients with traumatic brain injury (TBI, a critical worldwide health problem with an estimated 10 billion people affected annually worldwide. Data were collected through a review of the existing English literature performed on Scopus, MEDLINE, MEDLINE in Process, EMBASE, and/or Cochrane Central Register of Controlled Trials. Only experimental articles revolving around the management of TBI, in which the role of new devices based on innovative discoveries coming from the field of nanotechnology and biomedical engineering were highlighted, have been included and analyzed in this study. Based on theresults gathered from this research on innovative methods for genomics, epigenomics, and proteomics, their future application in this field seems promising. Despite the outstanding technical challenges of identifying reliable biosignatures for TBI and the mixed nature of studies herein described (single cells proteomics, biofilms, sensors, etc., the clinical implementation of those discoveries will allow us to gain confidence in the use of advanced neuromonitoring modalities with a potential dramatic improvement in the management of those patients.

  18. Antioxidant defense parameters as predictive biomarkers for fermentative capacity of active dried wine yeast.

    Science.gov (United States)

    Gamero-Sandemetrio, Esther; Gómez-Pastor, Rocío; Matallana, Emilia

    2014-08-01

    The production of active dried yeast (ADY) is a common practice in industry for the maintenance of yeast starters and as a means of long term storage. The process, however, causes multiple cell injuries, with oxidative damage being one of the most important stresses. Consequentially, dehydration tolerance is a highly appreciated property in yeast for ADY production. In this study we analyzed the cellular redox environment in three Saccharomyces cerevisiae wine strains, which show markedly different fermentative capacities after dehydration. To measure/quantify the effect of dehydration on the S. cerevisiae strains, we used: (i) fluorescent probes; (ii) antioxidant enzyme activities; (ii) intracellular damage; (iii) antioxidant metabolites; and (iv) gene expression, to select a minimal set of biochemical parameters capable of predicting desiccation tolerance in wine yeasts. Our results show that naturally enhanced antioxidant defenses prevent oxidative damage after wine yeast biomass dehydration and improve fermentative capacity. Based on these results we chose four easily assayable parameters/biomarkers for the selection of industrial yeast strains of interest for ADY production: trehalose and glutathione levels, and glutathione reductase and catalase enzymatic activities. Yeast strains selected in accordance with this process display high levels of trehalose, low levels of oxidized glutathione, a high induction of glutathione reductase activity, as well as a high basal level and sufficient induction of catalase activity, which are properties inherent in superior ADY strains. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. The Role of BRCA2 Mutation Status as Diagnostic, Predictive, and Prognosis Biomarker for Pancreatic Cancer

    Directory of Open Access Journals (Sweden)

    Javier Martinez-Useros

    2016-01-01

    Full Text Available Pancreatic cancer is one of the deadliest cancers worldwide, and life expectancy after diagnosis is often short. Most pancreatic tumours appear sporadically and have been highly related to habits such as cigarette smoking, high alcohol intake, high carbohydrate, and sugar consumption. Other observational studies have suggested the association between pancreatic cancer and exposure to arsenic, lead, or cadmium. Aside from these factors, chronic pancreatitis and diabetes have also come to be considered as risk factors for these kinds of tumours. Studies have found that 10% of pancreatic cancer cases arise from an inherited syndrome related to some genetic alterations. One of these alterations includes mutation in BRCA2 gene. BRCA2 mutations impair DNA damage response and homologous recombination by direct regulation of RAD51. In light of these findings that link genetic factors to tumour development, DNA damage agents have been proposed as target therapies for pancreatic cancer patients carrying BRCA2 mutations. Some of these drugs include platinum-based agents and PARP inhibitors. However, the acquired resistance to PARP inhibitors has created a need for new chemotherapeutic strategies to target BRCA2. The present systematic review collects and analyses the role of BRCA2 alterations to be used in early diagnosis of an inherited syndrome associated with familiar cancer and as a prognostic and predictive biomarker for the management of pancreatic cancer patients.

  20. Validity of the performance-oriented mobility assessment in predicting fall of stroke survivors: a retrospective cohort study.

    Science.gov (United States)

    An, SeungHeon; Lee, YunBok; Lee, GyuChang

    2014-06-01

    Falling is one of the most common complications in stroke survivors. It is therefore important to evaluate the risk of falls. In this study, we investigated the usability of the performance-oriented mobility assessment (POMA) for predicting falls in stroke patients. The POMA examines the level of balance and mobility. Data were collected on the number of falls and physical functions from 72 stroke survivors. Physical functions were measured using the POMA balance subscale, One Leg Stand test (OLS), Sit To Stand test (STS), 10-m Walk Test (10WT), Fugl-Meyer assessment (FM), and Trunk Impairment Scale (TIS). Since the accuracy of the POMA balance subscale was moderate, the cutoff value used for predicting falls was 12.5 points (sensitivity: 72%; specificity: 74%), and the area under the curve was 0.78 (95% confidence interval: 0.66-0.91, p risk of falling increased by 0.304 times more than the group over 12.5 points. The POMA balance subscale is a valid tool for assessing the physical function and fall risk of stroke survivors.

  1. Taxane resistance in breast cancer: mechanisms, predictive biomarkers and circumvention strategies.

    Science.gov (United States)

    Murray, S; Briasoulis, E; Linardou, H; Bafaloukos, D; Papadimitriou, C

    2012-11-01

    prominent finding is that pharmaceutical down-regulation of HER-2 appears to reverse the taxane resistance. Currently no valid practical biomarkers exist that can predict resistance to the taxanes in breast cancer supporting the principle of individualized cancer therapy. The incorporation of several biomarker analyses into prospectively designed studies in this setting are needed. Copyright © 2012 Elsevier Ltd. All rights reserved.

  2. The ABCD2 score is better for stroke risk prediction after anterior circulation TIA compared to posterior circulation TIA.

    Science.gov (United States)

    Wang, Junjun; Wu, Jimin; Liu, Rongyi; Gao, Feng; Hu, Haitao; Yin, Xinzhen

    2015-01-01

    Transient ischemic attacks (TIAs) are divided into anterior and posterior circulation types (AC-TIA, PC-TIA, respectively). In the present study, we sought to evaluate the ABCD2 score for predicting stroke in either AC-TIA or PC-TIA. We prospectively studied 369 consecutive patients who presented with TIA between June 2009 and December 2012. The 7 d occurrence of stroke after TIA was recorded and correlated with the ABCD2 score with regards to AC-TIA or PC-TIA. Overall, 273 AC-TIA and 96 PC-TIA patients were recruited. Twenty-one patients with AC-TIA and seven with PC-TIA developed a stroke within the subsequent 7 d (7.7% vs. 7.3%, p = 0.899). The ABCD2 score had a higher predictive value of stroke occurrence in AC-TIA (the AUC was 0.790; 95% CI, 0.677-0.903) than in PC-TIA (the AUC was 0.535; 95% CI, 0.350-0.727) and the z-value of two receiver operating characteristic (ROC) curves was 2.24 (p = 0.025). AC-TIA resulted in a higher incidence of both unilateral weakness and speech disturbance and longer durations of the symptoms. Inversely, PC-TIA was associated with a higher incidence of diabetes mellitus (19.8% vs. 10.6%, p = 0.022). Evaluating each component of scores, age ≥ 60 yr (OR = 7.010, 95% CI 1.599-30.743), unilateral weakness (OR = 3.455, 95% CI 1.131-10.559), and blood pressure (OR = 9.652, 95% CI 2.202-42.308) were associated with stroke in AC-TIA, while in PC-TIA, diabetes mellitus (OR = 9.990, 95% CI 1.895-52.650) was associated with stroke. In our study, the ABCD2 score could predict the short-term risk of stroke after AC-TIA, but might have limitation for PC-TIA.

  3. Could infarct location predict the long-term functional outcome in childhood arterial ischemic stroke?

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    Mauricio López-Espejo

    Full Text Available ABSTRACT Objective: To explore the influence of infarct location on long-term functional outcome following a first-ever arterial ischemic stroke (AIS in non-neonate children. Method: The MRIs of 39 children with AIS (median age 5.38 years; 36% girls; mean follow-up time 5.87 years were prospectively evaluated. Infarct location was classified as the absence or presence of subcortical involvement. Functional outcome was measured using the modified Rankin scale (mRS for children after the follow-up assessment. We utilized multivariate logistic regression models to estimate the odds ratios (ORs for the outcome while adjusting for age, sex, infarct size and middle cerebral artery territory involvement (significance < 0.05. Results: Both infarcts ≥ 4% of total brain volume (OR 9.92; CI 1.76 – 55.9; p 0.009 and the presence of subcortical involvement (OR 8.36; CI 1.76 – 53.6; p 0.025 independently increased the risk of marked functional impairment (mRS 3 to 5. Conclusion: Infarct extension and location can help predict the extent of disability after childhood AIS.

  4. Thrombus length discrepancy on dual-phase CT can predict clinical outcome in acute ischemic stroke

    International Nuclear Information System (INIS)

    Park, Mina; Kim, Kyung-eun; Lee, Seung-Koo; Shin, Na-Young; Lim, Soo Mee; Song, Dongbeom; Heo, Ji Hoe; Kim, Jin Woo; Oh, Se Won

    2016-01-01

    The thrombus length may be overestimated on early arterial computed tomography angiography (CTA) depending on the collateral status. We evaluated the value of a grading system based on the thrombus length discrepancy on dual-phase CT in outcome prediction. Forty-eight acute ischemic stroke patients with M1 occlusion were included. Dual-phase CT protocol encompassed non-contrast enhanced CT, CTA with a bolus tracking technique, and delayed contrast enhanced CT (CECT) performed 40s after contrast injection. The thrombus length discrepancy between CTA and CECT was graded by using a three-point scale: G0 = no difference; G1 = no difference in thrombus length, but in attenuation distal to thrombus; G2 = difference in thrombus length. Univariate and multivariate analyses were performed to define independent predictors of poor clinical outcome at 3 months. The thrombus discrepancy grade showed significant linear relationships with both the collateral status (P = 0.008) and the presence of antegrade flow on DSA (P = 0.010) with good interobserver agreement (κ = 0.868). In a multivariate model, the presence of thrombus length discrepancy (G2) was an independent predictor of poor clinical outcome [odds ratio = 11.474 (1.350-97.547); P =0.025]. The presence of thrombus length discrepancy on dual-phase CT may be a useful predictor of unfavourable clinical outcome in acute M1 occlusion patients. (orig.)

  5. External validation of a biomarker and clinical prediction model for hospital mortality in acute respiratory distress syndrome.

    Science.gov (United States)

    Zhao, Zhiguo; Wickersham, Nancy; Kangelaris, Kirsten N; May, Addison K; Bernard, Gordon R; Matthay, Michael A; Calfee, Carolyn S; Koyama, Tatsuki; Ware, Lorraine B

    2017-08-01

    Mortality prediction in ARDS is important for prognostication and risk stratification. However, no prediction models have been independently validated. A combination of two biomarkers with age and APACHE III was superior in predicting mortality in the NHLBI ARDSNet ALVEOLI trial. We validated this prediction tool in two clinical trials and an observational cohort. The validation cohorts included 849 patients from the NHLBI ARDSNet Fluid and Catheter Treatment Trial (FACTT), 144 patients from a clinical trial of sivelestat for ARDS (STRIVE), and 545 ARDS patients from the VALID observational cohort study. To evaluate the performance of the prediction model, the area under the receiver operating characteristic curve (AUC), model discrimination, and calibration were assessed, and recalibration methods were applied. The biomarker/clinical prediction model performed well in all cohorts. Performance was better in the clinical trials with an AUC of 0.74 (95% CI 0.70-0.79) in FACTT, compared to 0.72 (95% CI 0.67-0.77) in VALID, a more heterogeneous observational cohort. The AUC was 0.73 (95% CI 0.70-0.76) when FACTT and VALID were combined. We validated a mortality prediction model for ARDS that includes age, APACHE III, surfactant protein D, and interleukin-8 in a variety of clinical settings. Although the model performance as measured by AUC was lower than in the original model derivation cohort, the biomarker/clinical model still performed well and may be useful for risk assessment for clinical trial enrollment, an issue of increasing importance as ARDS mortality declines, and better methods are needed for selection of the most severely ill patients for inclusion.

  6. BISAP, RANSON, lactate and others biomarkers in prediction of severe acute pancreatitis in a European cohort.

    Science.gov (United States)

    Valverde-López, Francisco; Matas-Cobos, Ana M; Alegría-Motte, Carlos; Jiménez-Rosales, Rita; Úbeda-Muñoz, Margarita; Redondo-Cerezo, Eduardo

    2017-09-01

    The study aims to assess and compare the predicting ability of some scores and biomarkers in acute pancreatitis. We prospectively collected data from 269 patients diagnosed of acute pancreatitis, admitted to Virgen de las Nieves University Hospital between June 2010 and June 2012. Blood urea nitrogen (BUN), C-reactive protein, and creatinine were measured on admission and after 48 h, lactate and bedside index for severity acute pancreatitis (BISAP) only on admission and RANSON within the first 48 h. Definitions from 2012 Atlanta Classification were used. Area under the curve (AUC) was calculated for each scoring system for predicting severe acute pancreatitis (SAP), mortality, and intensive care unit (ICU) admission, obtaining optimal cut-off values from the receiver operating characteristic curves. Eight (3%) patients died, 17 (6.3%) were classified as SAP, and 10 (3.7%) were admitted in ICU. BISAP was the best predictor on admission for SAP, mortality, and ICU admission with an AUC of 0.9 (95% CI 0.83-0.97); 0.97 (95% CI 0.95-0.99); and 0.89 (95% CI 0.79-0.99), respectively. After 48 h, BUN 48 h was the best predictor of SAP (AUC = 0.96 CI: 0.92-0.99); BUN 48 h and BISAP were the best predictors for mortality (AUC = 0.97 CI: 0.95-0.99) and creatinine 48 h for ICU admission (AUC = 0.96 CI: 0.92-0.99). Lactate showed an AUC of 0.79 (CI: 0.71-0.88), 0.87 (CI: 0.78-0.96), and 0.77 (CI: 0.67-0.87) for SAP, mortality, and ICU admission, respectively. All parameters were predictors for SAP, mortality, and ICU admission, but C-reactive protein on admission was only a significant predictor of SAP. Bedside index for severity acute pancreatitis is a good predictive system for SAP, mortality, and ICU admission, being useful for triaging patients for ICU management. Lactate could be useful for developing new scores. © 2017 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

  7. Predictive Potential of Twenty-Two Biochemical Biomarkers for Coronary Artery Disease in Type 2 Diabetes Mellitus

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    Edimar Cristiano Pereira

    2015-01-01

    Full Text Available We investigated the potential of a panel of 22 biomarkers to predict the presence of coronary artery disease (CAD in type 2 diabetes mellitus (DM2 patients. The study enrolled 96 DM2 patients with (n = 75 and without (n = 21 evidence of CAD. We assessed a biochemical profile that included 22 biomarkers: total cholesterol, LDL, HDL, LDL/HDL, triglycerides, glucose, glycated hemoglobin, fructosamine, homocysteine, cysteine, methionine, reduced glutathione, oxidized glutathione, reduced glutathione/oxidized glutathione, L-arginine, asymmetric dimethyl-L-arginine, symmetric dimethyl-L-arginine, asymmetric dimethyl-L-arginine/L-arginine, nitrate plus nitrite, S-nitrosothiols, nitrotyrosine, and n-acetyl-β-glucosaminidase. Prediction models were built using logistic regression models. We found that eight biomarkers (methionine, nitratate plus nitrite, n-acetyl-β-glucosaminidase, BMI, LDL, HDL, reduced glutathione, and L-arginine/asymmetric dimethyl-L-arginine along with gender and BMI were significantly associated with the odds of CAD in DM2. These preliminary findings support the notion that emerging biochemical markers might be used for CAD prediction in patients with DM2. Our findings warrant further investigation with large, well-designed studies.

  8. Role of the adverse outcome pathway framework in the validation of predictive biomarkers

    Science.gov (United States)

    Gene expression, enzyme activities, changes in endogenous metabolite or hormone titers, altered histology, etc. are widely used as biomarkers, but rarely, if ever, used for regulatory decision-making or to define management objectives. The disconnect between the measurements comm...

  9. [Collateral score based on CT perfusion can predict the prognosis of patients with anterior circulation ischemic stroke after thrombectomy].

    Science.gov (United States)

    Wang, Qingsong; Zhang, Sheng; Zhang, Meixia; Chen, Zhicai; Lou, Min

    2017-07-25

    To evaluate the value of collateral score based on CT perfusion (CTP-CS) in predicting the clinical outcome of patients with anterior circulation ischemic stroke after thrombectomy. Clinical data of acute ischemic stroke patients with anterior artery occlusion undergoing endovascular treatment in the Second Affiliated Hospital, Zhejiang University School of Medicine during October 2013 and October 2016 were retrospectively reviewed. Collateral scores were assessed based on CTP and digital subtraction angiography (DSA) images, respectively. And DSA-CS or CTP-CS 3-4 was defined as good collateral vessels. Good clinical outcome was defined as a modified Rankin Scale (mRS) ≤ 2 at 3 months after stroke. The binary logistic regression model was used to analyze the correlation between the collateral score and clinical outcome, and the receiver operating characteristic (ROC) curve was used to analyze the value of DSA-CS and CTP-CS in predicting the clinical outcome. Among 40 patients, 33 (82.5%) acquired recanalization and 16 (40.0%) got good outcome. Compared with poor outcome group, the collateral score (all P collateral vessels were higher in good outcome group (all P collateral vessels were independent factor of good outcome (CTP-CS: OR =48.404, 95% CI :1.373-1706.585, P Collateral scores based on CTP and DSA had good consistency ( κ =0.697, P <0.01), and ROC curve showed that the predictive value of CTP-CS and DSA-CS were comparable (both AUC=0.726, 95% CI :0.559-0.893, P <0.05). CTP-CS can predict the clinical outcome of patients with anterior circulation ischemic stroke after thrombectomy.

  10. Stroke Rehabilitation.

    Science.gov (United States)

    Belagaje, Samir R

    2017-02-01

    Rehabilitation is an important aspect of the continuum of care in stroke. With advances in the acute treatment of stroke, more patients will survive stroke with varying degrees of disability. Research in the past decade has expanded our understanding of the mechanisms underlying stroke recovery and has led to the development of new treatment modalities. This article reviews and summarizes the key concepts related to poststroke recovery. Good data now exist by which one can predict recovery, especially motor recovery, very soon after stroke onset. Recent trials have not demonstrated a clear benefit associated with very early initiation of rehabilitative therapy after stroke in terms of improvement in poststroke outcomes. However, growing evidence suggests that shorter and more frequent sessions of therapy can be safely started in the first 24 to 48 hours after a stroke. The optimal amount or dose of therapy for stroke remains undetermined, as more intensive treatments have not been associated with better outcomes compared to standard intensities of therapy. Poststroke depression adversely affects recovery across a variety of measures and is an important target for therapy. Additionally, the use of selective serotonin reuptake inhibitors (SSRIs) appears to benefit motor recovery through pleiotropic mechanisms beyond their antidepressant effect. Other pharmacologic approaches also appear to have a benefit in stroke rehabilitation. A comprehensive rehabilitation program is essential to optimize poststroke outcomes. Rehabilitation is a process that uses three major principles of recovery: adaptation, restitution, and neuroplasticity. Based on these principles, multiple different approaches, both pharmacologic and nonpharmacologic, exist to enhance rehabilitation. In addition to neurologists, a variety of health care professionals are involved in stroke rehabilitation. Successful rehabilitation involves understanding the natural history of stroke recovery and a

  11. Bayesian Nonparametric Estimation of Targeted Agent Effects on Biomarker Change to Predict Clinical Outcome

    Science.gov (United States)

    Graziani, Rebecca; Guindani, Michele; Thall, Peter F.

    2015-01-01

    Summary The effect of a targeted agent on a cancer patient's clinical outcome putatively is mediated through the agent's effect on one or more early biological events. This is motivated by pre-clinical experiments with cells or animals that identify such events, represented by binary or quantitative biomarkers. When evaluating targeted agents in humans, central questions are whether the distribution of a targeted biomarker changes following treatment, the nature and magnitude of this change, and whether it is associated with clinical outcome. Major difficulties in estimating these effects are that a biomarker's distribution may be complex, vary substantially between patients, and have complicated relationships with clinical outcomes. We present a probabilistically coherent framework for modeling and estimation in this setting, including a hierarchical Bayesian nonparametric mixture model for biomarkers that we use to define a functional profile of pre-versus-post treatment biomarker distribution change. The functional is similar to the receiver operating characteristic used in diagnostic testing. The hierarchical model yields clusters of individual patient biomarker profile functionals, and we use the profile as a covariate in a regression model for clinical outcome. The methodology is illustrated by analysis of a dataset from a clinical trial in prostate cancer using imatinib to target platelet-derived growth factor, with the clinical aim to improve progression-free survival time. PMID:25319212

  12. Ex vivo metabolic fingerprinting identifies biomarkers predictive of prostate cancer recurrence following radical prostatectomy.

    Science.gov (United States)

    Braadland, Peder R; Giskeødegård, Guro; Sandsmark, Elise; Bertilsson, Helena; Euceda, Leslie R; Hansen, Ailin F; Guldvik, Ingrid J; Selnæs, Kirsten M; Grytli, Helene H; Katz, Betina; Svindland, Aud; Bathen, Tone F; Eri, Lars M; Nygård, Ståle; Berge, Viktor; Taskén, Kristin A; Tessem, May-Britt

    2017-11-21

    Robust biomarkers that identify prostate cancer patients with high risk of recurrence will improve personalised cancer care. In this study, we investigated whether tissue metabolites detectable by high-resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS MRS) were associated with recurrence following radical prostatectomy. We performed a retrospective ex vivo study using HR-MAS MRS on tissue samples from 110 radical prostatectomy specimens obtained from three different Norwegian cohorts collected between 2002 and 2010. At the time of analysis, 50 patients had experienced prostate cancer recurrence. Associations between metabolites, clinicopathological variables, and recurrence-free survival were evaluated using Cox proportional hazards regression modelling, Kaplan-Meier survival analyses and concordance index (C-index). High intratumoural spermine and citrate concentrations were associated with longer recurrence-free survival, whereas high (total-choline+creatine)/spermine (tChoCre/Spm) and higher (total-choline+creatine)/citrate (tChoCre/Cit) ratios were associated with shorter time to recurrence. Spermine concentration and tChoCre/Spm were independently associated with recurrence in multivariate Cox proportional hazards modelling after adjusting for clinically relevant risk factors (C-index: 0.769; HR: 0.72; P=0.016 and C-index: 0.765; HR: 1.43; P=0.014, respectively). Spermine concentration and tChoCre/Spm ratio in prostatectomy specimens were independent prognostic markers of recurrence. These metabolites can be noninvasively measured in vivo and may thus offer predictive value to establish preoperative risk assessment nomograms.

  13. BIOMARKERS S100B AND NSE PREDICT OUTCOME IN HYPOTHERMIA-TREATED ENCEPHALOPATHIC NEWBORNS

    Science.gov (United States)

    Massaro, An N.; Chang, Taeun; Baumgart, Stephen; McCarter, Robert; Nelson, Karin B.; Glass, Penny

    2014-01-01

    Objective To evaluate if serum S100B protein and neuron specific enolase (NSE) measured during therapeutic hypothermia are predictive of neurodevelopmental outcome at 15 months in children with neonatal encephalopathy (NE). Design Prospective longitudinal cohort study Setting A level IV neonatal intensive care unit in a free-standing children’s hospital. Patients Term newborns with moderate to severe NE referred for therapeutic hypothermia during the study period. Interventions Serum NSE and S100B were measured at 0, 12, 24 and 72 hrs of hypothermia. Measurements and Main Reseults Of the 83 infants were enrolled, fifteen (18%) died in the newborn period. Survivors were evaluated by the Bayley Scales of Infant Development (BSID-II) at 15 months of age. Outcomes were assessed in 49/68 (72%) survivors at a mean age of 15.2±2.7 months. Neurodevelopmental outcome was classified by BSID-II Mental (MDI) and Psychomotor (PDI) Developmental Index scores, reflecting cognitive and motor outcomes respectively. Four-level outcome classifications were defined a priori: normal= MDI/PDI within 1SD (>85), mild= MDI/PDI <1SD (70–85), moderate/severe= MDI/PDI <2SD (<70), or died. Elevated serum S100B and NSE levels measured during hypothermia were associated with increasing outcome severity after controlling for baseline and soceioeconomic characteristics in ordinal regression models. Adjusted odds ratios for cognitive outcome were: S100B 2.5 (95% CI 1.3–4.8) and NSE 2.1 (1.2–3.6); for motor outcome: S100B 2.6 (1.2–5.6) and NSE 2.1 (1.2–3.6). Conclusions Serum S100B and NSE levels in babies with NE are associated with neurodevelopmental outcome at 15 months. These putative biomarkers of brain injury may help direct care during therapeutic hypothermia. PMID:24777302

  14. L-Dopa decarboxylase (DDC) constitutes an emerging biomarker in predicting patients' survival with stomach adenocarcinomas.

    Science.gov (United States)

    Florou, Dimitra; Papadopoulos, Iordanis N; Fragoulis, Emmanuel G; Scorilas, Andreas

    2013-02-01

    Stomach adenocarcinoma represents a major health problem and is regarded as the second commonest cause of cancer-associated mortality, universally, since it is still difficult to be perceived at a curable stage. Several lines of evidence have pointed out that the expression of L-Dopa decarboxylase (DDC) gene and/or protein becomes distinctively modulated in several human neuroendocrine neoplasms as well as adenocarcinomas. In order to elucidate the clinical role of DDC on primary gastric adenocarcinomas, we determined qualitatively and quantitatively the mRNA levels of the gene with regular PCR and real-time PCR by using the comparative threshold cycle method, correspondingly, and detected the expression of DDC protein by immunoblotting in cancerous and normal stomach tissue specimens. A statistically significant association was disclosed between DDC expression and gastric intestinal histotype as well as tumor localization at the distal third part of the stomach (p = 0.025 and p = 0.029, respectively). Univariate and multivariate analyses highlighted the powerful prognostic importance of DDC in relation to disease-free survival and overall survival of gastric cancer patients. According to Kaplan-Meier curves, the relative risk of relapse was found to be decreased in DDC-positive (p = 0.031) patients who, also, exhibited higher overall survival rates (p = 0.016) than those with DDC-negative tumors. This work is the first to shed light on the potential clinical usefulness of DDC, as an efficient tumor biomarker in gastric cancer. The provided evidence underlines the propitious predictive value of DDC expression in the survival of stomach adenocarcinoma patients.

  15. Prediction of motor outcomes and activities of daily living function using diffusion tensor tractography in acute hemiparetic stroke patients.

    Science.gov (United States)

    Imura, Takeshi; Nagasawa, Yuki; Inagawa, Tetsuji; Imada, Naoki; Izumi, Hiroaki; Emoto, Katsuya; Tani, Itaru; Yamasaki, Hiroyuki; Ota, Yuichiro; Oki, Shuichi; Maeda, Tadanori; Araki, Osamu

    2015-05-01

    [Purpose] The efficacy of diffusion tensor imaging in the prediction of motor outcomes and activities of daily living function remains unclear. We evaluated the most appropriate diffusion tensor parameters and methodology to determine whether the region of interest- or tractography-based method was more useful for predicting motor outcomes and activities of daily living function in stroke patients. [Subjects and Methods] Diffusion tensor imaging data within 10 days after stroke onset were collected and analyzed for 25 patients. The corticospinal tract was analyzed. Fractional anisotropy, number of fibers, and apparent diffusion coefficient were used as diffusion tensor parameters. Motor outcomes and activities of daily living function were evaluated on the same day as diffusion tensor imaging and at 1 month post-onset. [Results] The fractional anisotropy value of the affected corticospinal tract significantly correlated with the motor outcome and activities of daily living function within 10 days post-onset and at 1 month post-onset. Tthere were no significant correlations between other diffusion tensor parameters and motor outcomes or activities of daily living function. [Conclusion] The fractional anisotropy value of the affected corticospinal tract obtained using the tractography-based method was useful for predicting motor outcomes and activities of daily living function in stroke patients.

  16. DRAGON score predicts functional outcomes in acute ischemic stroke patients receiving both intravenous tissue plasminogen activator and endovascular therapy.

    Science.gov (United States)

    Wang, Arthur; Pednekar, Noorie; Lehrer, Rachel; Todo, Akira; Sahni, Ramandeep; Marks, Stephen; Stiefel, Michael F

    2017-01-01

    The DRAGON score, which includes clinical and computed tomographic (CT) scan parameters, predicts functional outcomes in ischemic stroke patients treated with intravenous tissue plasminogen activator (IV tPA). We assessed the utility of the DRAGON score in predicting functional outcome in stroke patients receiving both IV tPA and endovascular therapy. A retrospective chart review of patients treated at our institution from February 2009 to October 2015 was conducted. All patients with computed tomography angiography (CTA) proven large vessel occlusions (LVO) who underwent intravenous thrombolysis and endovascular therapy were included. Baseline DRAGON scores and modified Rankin Score (mRS) at the time of hospital discharge was calculated. Good outcome was defined as mRS ≤3. Fifty-eight patients with LVO of the anterior circulation were studied. The mean DRAGON score of patients on admission was 5.3 (range, 3-8). All patients received IV tPA and endovascular therapy. Multivariate analysis demonstrated that DRAGON scores ≥7 was associated with higher mRS ( P DRAGON scores ≤6. Patients with DRAGON scores of 7 and 8 on admission had a mortality rate of 3.8% and 40%, respectively. The DRAGON score can help predict better functional outcomes in ischemic stroke patients receiving both IV tPA and endovascular therapy. This data supports the use of the DRAGON score in selecting patients who could potentially benefit from more invasive therapies such as endovascular treatment. Larger prospective studies are warranted to further validate these results.

  17. The predictive capacity of hypersympathicotonia in post-stroke patients with III stage hypertension

    Directory of Open Access Journals (Sweden)

    I. N. Voloshyna

    2012-12-01

    Full Text Available The evaluation of neuropeptide Y plasma concentration and LF/ HF ratio in post-stroke hypertensive patients has been done. The prognostic significance of sympathetic nervous system activity markers for complications development was established.

  18. Evaluation of predictive factors influencing community reintegration in adult patients with stroke

    Directory of Open Access Journals (Sweden)

    Olajide Ayinla Olawale

    2018-01-01

    Full Text Available Objectives: Patients with stroke are faced with gait, balance, and fall difficulties which could impact on their community reintegration. In Nigeria, community reintegration after stroke has been understudied. The objective of this study was to evaluate the predictors of community reintegration in adult patients with stroke. Materials and Methods: Participants were 91 adult patients with stroke. Gait variables, balance self-efficacy, community balance/mobility, and fall self-efficacy were assessed using Rivermead Mobility Index, Activities-specific Balance Confidence Scale, Community Balance and Mobility Scale, and Falls Efficacy Scale-International respectively. Reintegration to Normal Living Index was used to assess satisfaction with community reintegration. Pearson Product-Moment Correlation Coefficient was used to determine the relationship between community reintegration and gait spatiotemporal variables, balance performance, and risk of fall. Multiple regression analysis was used to determine predictors of community reintegration (P ≤ 0.05. Results: There was significant positive relationship between community reintegration and cadence (r = 0.250, P = 0.017, functional mobility (r = 0.503, P = 0.001, balance self-efficacy (r = 0.608, P = 0.001, community balance/mobility (r = 0.586, P = 0.001, and duration of stroke (r = 0.220, P = 0.036. Stride time (r = −0.282, P = 0.073 and fall self-efficacy (r = 0.566, P = 0.001 were negatively correlated with community reintegration. Duration of stroke, balance self-efficacy, community balance/mobility, and fall self-efficacy (52.7% of the variance were the significant predictors of community reintegration. Conclusion: Community reintegration is influenced by cadence, functional mobility, balance self-efficacy, community balance/mobility, and duration of stroke. Hence, improving balance and mobility during rehabilitation is important in enhancing community reintegration in patients with stroke.

  19. Predictive biomarkers for type 2 of diabetes mellitus: Bridging the gap between systems research and personalized medicine.

    Science.gov (United States)

    Kraniotou, Christina; Karadima, Vasiliki; Bellos, George; Tsangaris, George Th

    2018-03-05

    The global incidence of metabolic disorders like type 2 diabetes mellitus (DM2) has assumed epidemic proportions, leading to adverse health and socio-economic impacts. It is therefore of critical importance the early diagnosis of DM2 patients and the detection of those at increased risk of disease. In this respect, Precision Medicine (PM) is an emerging approach that includes practices, tests, decisions and treatments adapted to the characteristics of each patient. With regard to DM2, PM manages a wealth of "omics" data (genomic, metabolic, proteomic, environmental, clinical and paraclinical) to increase the number of clinically validated biomarkers in order to identify patients in early stage even before the prediabetic phase. In this paper, we discuss the epidemic dimension of metabolic disorders like type 2 diabetes mellitus (DM2) and the urgent demand for novel biomarkers to reduce the incidence or even delay the onset of DM2. Recent research data produced by "multi-omics" technologies (genomics/epigenomics, transcriptomics, proteomics and metabolomics), suggest that many potential biomarkers might be helpful in the prediction and early diagnosis of DM2. Predictive, Preventive and Personalized Medicine (PPPM) manages and integrates these data to apply personalized, preventive, and therapeutic approaches. This is significant because there is an emerging need for establishing channels for communication and personalized consultation between systems research and precision medicine, as the medicine of the future. Copyright © 2018 Elsevier B.V. All rights reserved.

  20. A proteomic analysis identifies candidate early biomarkers to predict ovarian hyperstimulation syndrome in polycystic ovarian syndrome patients.

    Science.gov (United States)

    Wu, Lan; Sun, Yazhou; Wan, Jun; Luan, Ting; Cheng, Qing; Tan, Yong

    2017-07-01

    Ovarian hyperstimulation syndrome (OHSS) is a potentially life‑threatening, iatrogenic complication that occurs during assisted reproduction. Polycystic ovarian syndrome (PCOS) significantly increases the risk of OHSS during controlled ovarian stimulation. Therefore, a more effective early prediction technique is required in PCOS patients. Quantitative proteomic analysis of serum proteins indicates the potential diagnostic value for disease. In the present study, the authors revealed the differentially expressed proteins in OHSS patients with PCOS as new diagnostic biomarkers. The promising proteins obtained from liquid chromatography‑mass spectrometry were subjected to ELISA and western blotting assay for further confirmation. A total of 57 proteins were identified with significant difference, of which 29 proteins were upregulated and 28 proteins were downregulated in OHSS patients. Haptoglobin, fibrinogen and lipoprotein lipase were selected as candidate biomarkers. Receiver operating characteristic curve analysis demonstrated all three proteins may have potential as biomarkers to discriminate OHSS in PCOS patients. Haptoglobin, fibrinogen and lipoprotein lipase have never been reported as a predictive marker of OHSS in PCOS patients, and their potential roles in OHSS occurrence deserve further studies. The proteomic results reported in the present study may gain deeper insights into the pathophysiology of OHSS.

  1. Predictive Biomarkers of Gastroesophageal Reflux Disease and Barrett's Esophagus in World Trade Center Exposed Firefighters: a 15 Year Longitudinal Study.

    Science.gov (United States)

    Haider, Syed H; Kwon, Sophia; Lam, Rachel; Lee, Audrey K; Caraher, Erin J; Crowley, George; Zhang, Liqun; Schwartz, Theresa M; Zeig-Owens, Rachel; Liu, Mengling; Prezant, David J; Nolan, Anna

    2018-02-15

    Gastroesophageal reflux disease (GERD) and Barrett's Esophagus (BE), which are prevalent in the World Trade Center (WTC) exposed and general populations, negatively impact quality of life and cost of healthcare. GERD, a risk factor of BE, is linked to obstructive airways disease (OAD). We aim to identify serum biomarkers of GERD/BE, and assess the respiratory and clinical phenotype of a longitudinal cohort of never-smoking, male, WTC-exposed rescue workers presenting with pulmonary symptoms. Biomarkers collected soon after WTC-exposure were evaluated in optimized predictive models of GERD/BE. In the WTC-exposed cohort, the prevalence of BE is at least 6 times higher than in the general population. GERD/BE cases had similar lung function, D LCO , bronchodilator response and long-acting β-agonist use compared to controls. In confounder-adjusted regression models, TNF-α ≥ 6 pg/mL predicted both GERD and BE. GERD was also predicted by C-peptide ≥ 360 pg/mL, while BE was predicted by fractalkine ≥ 250 pg/mL and IP-10 ≥ 290 pg/mL. Finally, participants with GERD had significantly increased use of short-acting β-agonist compared to controls. Overall, biomarkers sampled prior to GERD/BE presentation showed strong predictive abilities of disease development. This study frames future investigations to further our understanding of aerodigestive pathology due to particulate matter exposure.

  2. Subtype classification for prediction of prognosis of breast cancer from a biomarker panel: correlations and indications

    Directory of Open Access Journals (Sweden)

    Chen C

    2014-02-01

    Full Text Available Chuang Chen,1 Jing-Ping Yuan,2,3 Wen Wei,1 Yi Tu,1 Feng Yao,1 Xue-Qin Yang,4 Jin-Zhong Sun,1 Sheng-Rong Sun,1 Yan Li2 1Department of Breast and Thyroid Surgery, Wuhan University, Renmin Hospital, Wuhan, 2Department of Oncology, Zhongnan Hospital of Wuhan University and Hubei Key Laboratory of Tumor Biological Behaviors and Hubei Cancer Clinical Study Center, Wuhan, 3Department of Pathology, The Central Hospital of Wuhan, Wuhan, 4Medical School of Jingchu University of Technology, Jingmen, People’s Republic of China Background: Hormone receptors, including the estrogen receptor and progesterone receptor, human epidermal growth factor receptor 2 (HER2, and other biomarkers like Ki67, epidermal growth factor receptor (EGFR, also known as HER1, the androgen receptor, and p53, are key molecules in breast cancer. This study evaluated the relationship between HER2 and hormone receptors and explored the additional prognostic value of Ki67, EGFR, the androgen receptor, and p53. Methods: Quantitative determination of HER2 and EGFR was performed in 240 invasive breast cancer tissue microarray specimens using quantum dot (QD-based nanotechnology. We identified two subtypes of HER2, ie, high total HER2 load (HTH2 and low total HER2 load (LTH2, and three subtypes of hormone receptor, ie, high hormone receptor (HHR, low hormone receptor (LHR, and no hormone receptor (NHR. Therefore, breast cancer patients could be divided into five subtypes according to HER2 and hormone receptor status. Ki67, p53, and the androgen receptor were determined by traditional immunohistochemistry techniques. The relationship between hormone receptors and HER2 was investigated and the additional value of Ki67, EGFR, the androgen receptor, and p53 for prediction of 5-year disease-free survival was assessed. Results: In all patients, quantitative determination showed a statistically significant (P<0.001 negative correlation between HER2 and the hormone receptors and a significant

  3. High urinary albumin/creatinine ratio at admission predicts poor functional outcome in patients with acute ischaemic stroke.

    Science.gov (United States)

    Watanabe, Yoko; Suda, Satoshi; Kanamaru, Takuya; Katsumata, Toshiya; Okubo, Seiji; Kaneko, Tomohiro; Mii, Akiko; Sakai, Yukinao; Katayama, Yasuo; Kimura, Kazumi; Tsuruoka, Shuichi

    2017-03-01

    Albuminuria and a low estimated glomerular filtration rate (eGFR) are widely recognized indices of kidney dysfunction and have been linked to cardiovascular events, including stroke. We evaluated albuminuria, measured using the urinary albumin/creatinine ratio (UACR), and the eGFR in the acute phase of ischaemic stroke, and investigated the clinical characteristics of ischaemic stroke patients with and those without kidney dysfunction. The study included 422 consecutive patients admitted between June 2010 and May 2012. General blood and urine examinations were performed at admission. Kidney dysfunction was defined as a low eGFR (high albuminuria (≥30 mg/g creatinine), or both. Neurological severity was evaluated using the National Institutes of Health Stroke Scale (NIHSS) at admission and the modified Rankin scale (mRS) at discharge. A poor outcome was defined as a mRS score of 3-5 or death. The impacts of the eGFR and UACR on outcomes at discharge were evaluated using multiple logistic regression analysis. Kidney dysfunction was diagnosed in 278 of the 422 patients (65.9%). The eGFR was significantly lower and UACR was significantly higher in patients with a poor outcome than in those with a good outcome. In multivariate analyses performed after adjusting for confounding factors, UACR >31.2 mg/g creatinine (OR, 2.58; 95% CI, 1.52-4.43; P = 0.0005) was independently associated with a poor outcome, while a low eGFR was not associated. A high UACR at admission may predict a poor outcome at discharge in patients with acute ischaemic stroke. © 2016 Asian Pacific Society of Nephrology.

  4. The P300 in middle cerebral artery strokes or hemorrhages: Outcome predictions and source localization.

    Science.gov (United States)

    Ehlers, Mana R; López Herrero, Carmen; Kastrup, Andreas; Hildebrandt, Helmut

    2015-08-01

    There are no reliable outcome predictors for severely impaired patients suffering from large infarctions or hemorrhages within the territory of the middle cerebral artery. This study investigated whether the amplitude of the event-related potential (ERP) component P300 predicts if a patient will be transferred to the next stage of rehabilitation (positive outcome) or to a nursing home (negative outcome). The second goal was to look for lesion locations determining the generation of the P300 amplitude. Forty-seven patients performed an auditory oddball task to elicit the P300 and were assessed with different scores for activities of daily living (ADL). Patients were divided in two groups according to their outcome. P300 amplitudes were compared between these groups controlling for age and gender. Post-hoc analyses were performed to analyse the relationship between P300 amplitude and neurological outcome scores. In addition, lesion overlaps were created to detect which lesion pattern affects P300 generation. Patients with a positive outcome showed higher P300 amplitudes at frontal electrode sites than those with a negative outcome. P300 amplitude correlated with ADL score difference. Lesions in the superior temporal gyrus, middle and inferior frontal and prefrontal regions led to visibly diminished P300 amplitudes. The findings suggest that an impairment of attention (P300 amplitude reduction) negatively influences successful neurological rehabilitation. Left superior temporal lobe and the left premotor/prefrontal areas are essential brain areas for the generation of the P300. P300 amplitude may be used as an outcome predictor for severely impaired patients suffering from middle cerebral artery strokes or hemorrhages. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  5. Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clustering

    Directory of Open Access Journals (Sweden)

    Sharma Animesh

    2007-01-01

    Full Text Available Abstract Background The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell tumor (SRBCT and thus often leads to misdiagnosis. Identification of biomarkers for distinguishing these cancers is a well studied problem. Existing methods typically evaluate each gene separately and do not take into account the nonlinear interaction between genes and the tools that are used to design the diagnostic prediction system. Consequently, more genes are usually identified as necessary for prediction. We propose a general scheme for finding a small set of biomarkers to design a diagnostic system for accurate classification of the cancer subgroups. We use multilayer networks with online gene selection ability and relational fuzzy clustering to identify a small set of biomarkers for accurate classification of the training and blind test cases of a well studied data set. Results Our method discerned just seven biomarkers that precisely categorized the four subgroups of cancer both in training and blind samples. For the same problem, others suggested 19–94 genes. These seven biomarkers include three novel genes (NAB2, LSP1 and EHD1 – not identified by others with distinct class-specific signatures and important role in cancer biology, including cellular proliferation, transendothelial migration and trafficking of MHC class antigens. Interestingly, NAB2 is downregulated in other tumors including Non-Hodgkin lymphoma and Neuroblastoma but we observed moderate to high upregulation in a few cases of Ewing sarcoma and Rabhdomyosarcoma, suggesting that NAB2 might be mutated in these tumors. These genes can discover the subgroups correctly with unsupervised learning, can differentiate non-SRBCT samples and they perform equally well with other machine learning tools including support vector machines. These biomarkers lead to four simple human interpretable

  6. Predicting efficacy of robot-aided rehabilitation in chronic stroke patients using an MRI-compatible robotic device.

    Science.gov (United States)

    Sergi, Fabrizio; Krebs, Hermano Igo; Groissier, Benjamin; Rykman, Avrielle; Guglielmelli, Eugenio; Volpe, Bruce T; Schaechter, Judith D

    2011-01-01

    We are investigating the neural correlates of motor recovery promoted by robot-mediated therapy in chronic stroke. This pilot study asked whether efficacy of robot-aided motor rehabilitation in chronic stroke could be predicted by a change in functional connectivity within the sensorimotor network in response to a bout of motor rehabilitation. To address this question, two stroke patients participated in a functional connectivity MRI study pre and post a 12-week robot-aided motor rehabilitation program. Functional connectivity was evaluated during three consecutive scans before the rehabilitation program: resting-state; point-to-point reaching movements executed by the paretic upper extremity (UE) using a newly developed MRI-compatible sensorized passive manipulandum; resting-state. A single resting-state scan was conducted after the rehabilitation program. Before the program, UE movement reduced functional connectivity between the ipsilesional and contralesional primary motor cortex. Reduced interhemispheric functional connectivity persisted during the second resting-state scan relative to the first and during the resting-state scan after the rehabilitation program. Greater reduction in interhemispheric functional connectivity during the resting-state was associated with greater gains in UE motor function induced by the 12-week robotic therapy program. These findings suggest that greater reduction in interhemispheric functional connectivity in response to a bout of motor rehabilitation may predict greater efficacy of the full rehabilitation program.

  7. Home blood pressure predicts stroke incidence among older adults with impaired physical function: the Ohasama study.

    Science.gov (United States)

    Murakami, Keiko; Asayama, Kei; Satoh, Michihiro; Hosaka, Miki; Matsuda, Ayako; Inoue, Ryusuke; Tsubota-Utsugi, Megumi; Murakami, Takahisa; Nomura, Kyoko; Kikuya, Masahiro; Metoki, Hirohito; Imai, Yutaka; Ohkubo, Takayoshi

    2017-12-01

    Several observational studies have found modifying effects of functional status on the association between conventional office blood pressure (BP) and adverse outcomes. We aimed to examine whether the association between higher BP and stroke was attenuated or inverted among older adults with impaired function using self-measured home BP measurements. We followed 501 Japanese community-dwelling adults aged at least 60 years (mean age, 68.6 years) with no history of stroke. Multivariate-adjusted hazard ratios for 1-SD increase in home BP and office BP measurements were calculated by the Cox proportional hazards model. Functional status was assessed by self-reported physical function. During a median follow-up of 11.5 years, first strokes were observed in 47 participants. Higher home SBP, but not office SBP, was significantly associated with increased risk of stroke among both 349 participants with normal physical function and 152 participants with impaired physical function [hazard ratio (95% confidence interval) per 14.4-mmHg increase: 1.74 (1.12-2.69) and 1.77 (1.06-2.94), respectively], with no significant interaction for physical function (P = 0.56). Higher home DBP, but not office DBP, was also significantly associated with increased risk of stroke (P ≤ 0.029) irrespective of physical function (all P > 0.05 for interaction). Neither home BP nor office BP was significantly associated with all-cause mortality irrespective of physical function. Higher home BP was associated with increased risk of stroke even among those with impaired physical function. Measurements of home BP would be useful for stroke prevention, even after physical function decline.

  8. Pediatric Stroke

    Science.gov (United States)

    ... and Patient Resources Home » Patients & Families » About Stroke » Pediatric Stroke » Introduction Introduction What is a Stroke? Ischemic Stroke Intracerebral Hemorrhage Subarachnoid Hemorrhage Pediatric Stroke Introduction Types of Stroke Diagnosis and Treatment ...

  9. Predicting the Grade of Disability 1 Year After Stroke Following Rehabilitation

    Directory of Open Access Journals (Sweden)

    Jau-Hong Lin

    2005-05-01

    Full Text Available The purpose of this study was to identify predictors of grades of disability at least 1 year after stroke rehabilitation therapy. We recruited stroke patients from the inpatient rehabilitation department of a university hospital. The degree of disability was graded using the disability evaluation at least 1 year after stroke onset. Functional ability was evaluated using the Functional Independence Measure instrument on admission, on discharge from the inpatient rehabilitation program, and at the 6-month follow-up visit after discharge. Major sociodemographic, medical, and rehabilitative factors were also collected during the hospitalization period. Of the 109 patients surveyed, 64 (58.7% had severe or very severe grades of disability. The correlates of severe or very severe disability in logistic regression analyses were bilaterally affected (odds ratio, OR, 10.8, impaired orientation (OR, 3.6, and poorer functional ability at discharge (OR, 7.6. Based on the significant predictors identified, the logistic regression model correctly classified severe or very severe disability in 68.0% of subjects. The higher frequency of severe or very severe disability in this study may have been due to the relatively more severely affected stroke patient population in the inpatient rehabilitation service and the use of unique disability evaluation criteria. These results may provide information useful in planning continuous rehabilitation care and setting relevant socio-welfare policies for stroke victims.

  10. A Contemporary Review of the Treatment Landscape and the Role of Predictive and Prognostic Biomarkers in Pancreatic Adenocarcinoma

    Directory of Open Access Journals (Sweden)

    Irene S. Yu

    2018-01-01

    Full Text Available Pancreatic cancer continues to represent one of the leading causes of cancer-related morbidity and mortality in the developed world. Over the past decade, novel systemic therapy combination regimens have contributed to clinically meaningful and statistically significant improvements in overall survival as compared to conventional monotherapy. However, the prognosis for most patients remains guarded secondary to the advanced stages of disease at presentation. There is growing consensus that outcomes can be further optimized with the use of predictive and prognostic biomarkers whereby the former can be enriching for patients who would benefit from therapies and the latter can inform decision-making regarding the need and timing of advanced care planning. One of the challenges of current biomarkers is the lack of standardization across clinical practices such that comparability between jurisdictions can be difficult or even impossible. This inconsistency can impede widespread implementation of their use. In this review article, we provide a comprehensive overview of the contemporary treatment options for pancreatic cancer and we offer some insights into the existing landscape and future directions of biomarker development for this disease.

  11. The Biomarker GlycA Is Associated with Chronic Inflammation and Predicts Long-Term Risk of Severe Infection.

    Science.gov (United States)

    Ritchie, Scott C; Würtz, Peter; Nath, Artika P; Abraham, Gad; Havulinna, Aki S; Fearnley, Liam G; Sarin, Antti-Pekka; Kangas, Antti J; Soininen, Pasi; Aalto, Kristiina; Seppälä, Ilkka; Raitoharju, Emma; Salmi, Marko; Maksimow, Mikael; Männistö, Satu; Kähönen, Mika; Juonala, Markus; Ripatti, Samuli; Lehtimäki, Terho; Jalkanen, Sirpa; Perola, Markus; Raitakari, Olli; Salomaa, Veikko; Ala-Korpela, Mika; Kettunen, Johannes; Inouye, Michael

    2015-10-28

    The biomarker glycoprotein acetylation (GlycA) has been shown to predict risk of cardiovascular disease and all-cause mortality. Here, we characterize biological processes associated with GlycA by leveraging population-based omics data and health records from >10,000 individuals. Our analyses show that GlycA levels are chronic within individuals for up to a decade. In apparently healthy individuals, elevated GlycA corresponded to elevation of myriad inflammatory cytokines, as well as a gene coexpression network indicative of increased neutrophil activity, suggesting that individuals with high GlycA may be in a state of chronic inflammatory response. Accordingly, analysis of infection-related hospitalization and death records showed that increased GlycA increased long-term risk of severe non-localized and respiratory infections, particularly septicaemia and pneumonia. In total, our work demonstrates that GlycA is a biomarker for chronic inflammation, neutrophil activity, and risk of future severe infection. It also illustrates the utility of leveraging multi-layered omics data and health records to elucidate the molecular and cellular processes associated with biomarkers. Copyright © 2015 Elsevier Inc. All rights reserved.

  12. C-reactive protein and homocysteine predict long-term mortality in young ischemic stroke patients.

    Science.gov (United States)

    Naess, Halvor; Nyland, Harald; Idicula, Titto; Waje-Andreassen, Ulrike

    2013-11-01

    We investigated the relationship between C-reactive protein (CRP) and homocysteine on follow-up and subsequent mortality in young ischemic stroke patients in a population-based study. Young ischemic stroke patients were followed-up on average 6 years after the index stroke. CRP and homocysteine levels were measured and risk factors were recorded, including myocardial infarction, diabetes mellitus, hypertension, smoking, alcoholism, and cancer. Stroke outcome was measured using the modified Rankin Scale score. Subsequent survival was obtained by examining the official population registry. Cox regression analyses were performed. In total, 198 patients were included in this study (82 [41%] women and 116 [59%] men). The mean age on follow-up was 47.8 years. In total, 36 (18.2%) patients died during the subsequent mean follow-up of 12.4 years. Cox regression analysis revealed that mortality was associated with CRP (hazard ratio [HR] 1.05; P=.001) and homocysteine levels (HR 1.04; P=.02) in patients without dissection. Kaplan-Meier curves grouped by dichotomized CRP (CRP≤1 v >1 mg/L) showed increasing separation between the survival curves, and likewise for dichotomized homocysteine (≤9 v >9 μg/L). There is an independent association between CRP and homocysteine levels obtained several years after ischemic stroke in young adults and subsequent mortality, even when adjusting for traditional risk factors. This association seems to continue for at least 12 years after the measurements. Copyright © 2013 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  13. Poor nutritional status on admission predicts poor outcomes after stroke: observational data from the FOOD trial.

    Science.gov (United States)

    2003-06-01

    Previous studies suggest that undernourished patients with acute stroke do badly. The data, however, are not robust. We aimed to reliably assess the importance of baseline nutritional status as an independent predictor of long-term outcome after stroke in a large prospective cohort enrolled in the Feed Or Ordinary Diet (FOOD) trial, a multicenter randomized trial evaluating various feeding policies. Patients admitted to hospital with a recent stroke were enrolled in the FOOD trial. Data on nutritional status and other clinical predictors of outcome were collected at trial entry. At 6 months, the coordinating center collected data on survival and functional status (modified Rankin Scale). Outcome assessment was done by researchers blinded to baseline assessments and treatment allocation. Between November 1996 and November 2001, 3012 patients were enrolled, and 2955 (98%) were followed up. Of the 275 undernourished patients, 102 (37%) were dead by final follow-up compared with only 445 (20%) of 2194 patients of normal nutritional status (odds ratio [OR], 2.32; 95% CI, 1.78 to 3.02). After adjustment for age, prestroke functional state, and stroke severity, this relationship, although weakened, still held (OR, 1.82; 95% CI, 1.34 to 2.47). Undernourished patients were more likely to develop pneumonia, other infections, and gastrointestinal bleeding during their hospital admission than other patients. These data provide reliable evidence that nutritional status early after stroke is independently associated with long-term outcome. It supports the rationale for the FOOD trial, which continues to recruit and aims to estimate the effect of different feeding regimes on outcome after stroke and thus determine whether the association observed in this study is likely to be causal.

  14. Analysis of Plasma Albumin, Vitamin D, and Apolipoproteins A and B as Predictive Coronary Risk Biomarkers in the REGICOR Study.

    Science.gov (United States)

    Vázquez-Oliva, Gabriel; Zamora, Alberto; Ramos, Rafel; Subirana, Isaac; Grau, María; Dégano, Irene R; Muñoz, Daniel; Fitó, Montserrat; Elosua, Roberto; Marrugat, Jaume

    2018-05-12

    New biomarkers could improve the predictive capacity of classic risk functions. The aims of this study were to determine the association between circulating levels of apolipoprotein A1 (apoA1), apolipoprotein B (apoB), albumin, and 25-OH-vitamin D and coronary events and to analyze whether these biomarkers improve the predictive capacity of the Framingham-REGICOR risk function. A case-cohort study was designed. From an initial cohort of 5404 individuals aged 35 to 74 years with a 5-year follow-up, all the participants who had a coronary event (n = 117) and a random group of the cohort (subcohort; n = 667) were selected. Finally, 105 cases and 651 individuals representative of the cohort with an available biological sample were included. The events of interest were angina, fatal and nonfatal myocardial infarction and coronary deaths. Case participants were older, had a higher proportion of men and cardiovascular risk factors, and showed higher levels of apoB and lower levels of apoA1, apoA1/apoB ratio, 25-OH-vitamin D and albumin than the subcohort. In multivariate analyses, plasma albumin concentration was the only biomarker independently associated with coronary events (HR, 0.73; P = .002). The inclusion of albumin in the risk function properly reclassified a significant proportion of individuals, especially in the intermediate risk group (net reclassification improvement, 32.3; P = .048). Plasma albumin levels are inversely associated with coronary risk and improve the predictive capacity of classic risk functions. Copyright © 2018 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

  15. Novel biomarkers in primary breast core biopsies to predict poor response to neoadjuvant chemotherapy and appearance of metastases.

    Science.gov (United States)

    Novell, Anna; Morales, Serafin; Valls, Joan; Panadés, Maria José; Salud, Antonieta; Iglesias, Edelmiro; Vilardell, Felip; Matias-Guiu, Xavier; Llombart-Cussac, Antonio

    2017-09-01

    Drug resistance has been one of the major obstacles limiting the success of cancer chemotherapy. In two thirds of breast cancer patients, large (>1cm) residual tumors are present after neoadjuvant chemotherapy (NCT). The residual tumor and involved nodes have been indicators of relapse and survival very important in breast cancer. The goal of this preliminary study was to assess the predictive significance of a panel of molecular biomarkers, related with the response to treatment or drug resistance to NCT, as determined on the diagnostic tumor. The expression of 22 proteins was examined using immunohistochemistry in tissue microarrays (TMA) from 115 patients of stage II-III breast cancer, treated with NCT. Among studied proteins, there are some that are anti-apoptotic, pro-proliferative, cancer stem cell markers and the Vitamin D Receptor. Other proteins are involved in the identification of molecular subtype, cell cycle regulation or DNA repair. Next, a predictive signature of poor response was generated from independent markers of predictive value. Tumors that expressed four or five conditions (biomarkers of chemoresistance with a determinated cutoff) were associated with a 9-fold increase in the chances of these patients of having a poor response to NCT. Additionally, we also found a worse prognostic signature, generated from independent markers of prognostic value. Tumors which expressed two or three conditions of worst prognostic, were associated with a 6-fold reduction in Distant Disease Free Survival. In conclusion, finding biomarkers of chemoresitance (ypTNM II-III) and metastases can become a stepping stone for future studies that will need to be assessed in a bigger scale.

  16. Very Low Cerebral Blood Volume Predicts Parenchymal Hematoma in Acute Ischemic Stroke

    DEFF Research Database (Denmark)

    Hermitte, Laure; Cho, Tae-Hee; Ozenne, Brice

    2013-01-01

    BACKGROUND AND PURPOSE: Parenchymal hematoma (PH) may worsen the outcome of patients with stroke. The aim of our study was to confirm the relationship between the volume of very low cerebral blood volume (CBV) and PH using a European multicenter database (I-KNOW). A secondary objective was to exp......BACKGROUND AND PURPOSE: Parenchymal hematoma (PH) may worsen the outcome of patients with stroke. The aim of our study was to confirm the relationship between the volume of very low cerebral blood volume (CBV) and PH using a European multicenter database (I-KNOW). A secondary objective...

  17. Innovative biomarkers for predicting type 2 diabetes mellitus: relevance to dietary management of frailty in older adults.

    Science.gov (United States)

    Ikwuobe, John; Bellary, Srikanth; Griffiths, Helen R

    2016-06-01

    Type 2 diabetes mellitus (T2DM) increases in prevalence in the elderly. There is evidence for significant muscle loss and accelerated cognitive impairment in older adults with T2DM; these comorbidities are critical features of frailty. In the early stages of T2DM, insulin sensitivity can be improved by a "healthy" diet. Management of insulin resistance by diet in people over 65 years of age should be carefully re-evaluated because of the risk for falling due to hypoglycaemia. To date, an optimal dietary programme for older adults with insulin resistance and T2DM has not been described. The use of biomarkers to identify those at risk for T2DM will enable clinicians to offer early dietary advice that will delay onset of disease and of frailty. Here we have used an in silico literature search for putative novel biomarkers of T2DM risk and frailty. We suggest that plasma bilirubin, plasma, urinary DPP4-positive microparticles and plasma pigment epithelium-derived factor merit further investigation as predictive biomarkers for T2DM and frailty risk in older adults. Bilirubin is screened routinely in clinical practice. Measurement of specific microparticle frequency in urine is less invasive than a blood sample so is a good choice for biomonitoring. Future studies should investigate whether early dietary changes, such as increased intake of whey protein and micronutrients that improve muscle function and insulin sensitivity, affect biomarkers and can reduce the longer term complication of frailty in people at risk for T2DM.

  18. A statistical approach to evaluate the performance of cardiac biomarkers in predicting death due to acute myocardial infarction: time-dependent ROC curve

    Science.gov (United States)

    Karaismailoğlu, Eda; Dikmen, Zeliha Günnur; Akbıyık, Filiz; Karaağaoğlu, Ahmet Ergun

    2018-04-30

    Background/aim: Myoglobin, cardiac troponin T, B-type natriuretic peptide (BNP), and creatine kinase isoenzyme MB (CK-MB) are frequently used biomarkers for evaluating risk of patients admitted to an emergency department with chest pain. Recently, time- dependent receiver operating characteristic (ROC) analysis has been used to evaluate the predictive power of biomarkers where disease status can change over time. We aimed to determine the best set of biomarkers that estimate cardiac death during follow-up time. We also obtained optimal cut-off values of these biomarkers, which differentiates between patients with and without risk of death. A web tool was developed to estimate time intervals in risk. Materials and methods: A total of 410 patients admitted to the emergency department with chest pain and shortness of breath were included. Cox regression analysis was used to determine an optimal set of biomarkers that can be used for estimating cardiac death and to combine the significant biomarkers. Time-dependent ROC analysis was performed for evaluating performances of significant biomarkers and a combined biomarker during 240 h. The bootstrap method was used to compare statistical significance and the Youden index was used to determine optimal cut-off values. Results : Myoglobin and BNP were significant by multivariate Cox regression analysis. Areas under the time-dependent ROC curves of myoglobin and BNP were about 0.80 during 240 h, and that of the combined biomarker (myoglobin + BNP) increased to 0.90 during the first 180 h. Conclusion: Although myoglobin is not clinically specific to a cardiac event, in our study both myoglobin and BNP were found to be statistically significant for estimating cardiac death. Using this combined biomarker may increase the power of prediction. Our web tool can be useful for evaluating the risk status of new patients and helping clinicians in making decisions.

  19. Predictive factors of subjective sleep quality and insomnia complaint in patients with stroke: implications for clinical practice

    Directory of Open Access Journals (Sweden)

    PATRICIA C. DA ROCHA

    2013-09-01

    Full Text Available The complaints regarding sleep problems have not been well identified after a stroke. The aim of this study was to investigate the predictive factors of sleep quality and insomnia complaints in patients with stroke. A total of 70 subjects, 40 patients (57 ± 7 years and 30 healthy controls (52 ± 6 years assessed by the Pittsburgh Sleep Quality Index (PSQI and the Sleep Habits Questionnaire took part in the study. The data were analyzed using the chi-square test, the Student's t-test and logistic regression analysis. On average, the patients showed poor sleep quality (patients: 6.3 ± 3.5; controls: 3.9 ± 2.2; p= 0.002 and insomnia complaint was the most prevalent (patients: 37.5%; controls: 6.7%; p= 0.007. The absence of insomnia complaint (OR= 0.120; 95%CI= 0.017-0.873; p= 0.036 and the decreased latency of sleep (OR= 0.120; 95%CI= 0.017-0.873; p= 0.036 were the protective factors of sleep quality. Female sex (OR= 11.098; 95%CI= 1.167-105.559; p= 0.036 and fragmented sleep (OR= 32.040; 95%CI= 3.236-317.261; p= 0.003 were the risk factors for insomnia complaint. We suggest that complaints of poor sleep quality and insomnia should be given priority assessment during clinical diagnosis of sleep disorders in stroke.

  20. On the assessment of the added value of new predictive biomarkers.

    Science.gov (United States)

    Chen, Weijie; Samuelson, Frank W; Gallas, Brandon D; Kang, Le; Sahiner, Berkman; Petrick, Nicholas

    2013-07-29

    The surge in biomarker development calls for research on statistical evaluation methodology to rigorously assess emerging biomarkers and classification models. Recently, several authors reported the puzzling observation that, in assessing the added value of new biomarkers to existing ones in a logistic regression model, statistical significance of new predictor variables does not necessarily translate into a statistically significant increase in the area under the ROC curve (AUC). Vickers et al. concluded that this inconsistency is because AUC "has vastly inferior statistical properties," i.e., it is extremely conservative. This statement is based on simulations that misuse the DeLong et al. method. Our purpose is to provide a fair comparison of the likelihood ratio (LR) test and the Wald test versus diagnostic accuracy (AUC) tests. We present a test to compare ideal AUCs of nested linear discriminant functions via an F test. We compare it with the LR test and the Wald test for the logistic regression model. The null hypotheses of these three tests are equivalent; however, the F test is an exact test whereas the LR test and the Wald test are asymptotic tests. Our simulation shows that the F test has the nominal type I error even with a small sample size. Our results also indicate that the LR test and the Wald test have inflated type I errors when the sample size is small, while the type I error converges to the nominal value asymptotically with increasing sample size as expected. We further show that the DeLong et al. method tests a different hypothesis and has the nominal type I error when it is used within its designed scope. Finally, we summarize the pros and cons of all four methods we consider in this paper. We show that there is nothing inherently less powerful or disagreeable about ROC analysis for showing the usefulness of new biomarkers or characterizing the performance of classification models. Each statistical method for assessing biomarkers and

  1. Uric acid predicts mortality and ischaemic stroke in subjects with diastolic dysfunction: the Tromsø Study 1994-2013.

    Science.gov (United States)

    Norvik, Jon V; Schirmer, Henrik; Ytrehus, Kirsti; Storhaug, Hilde M; Jenssen, Trond G; Eriksen, Bjørn O; Mathiesen, Ellisiv B; Løchen, Maja-Lisa; Wilsgaard, Tom; Solbu, Marit D

    2017-05-01

    To investigate whether serum uric acid predicts adverse outcomes in persons with indices of diastolic dysfunction in a general population. We performed a prospective cohort study among 1460 women and 1480 men from 1994 to 2013. Endpoints were all-cause mortality, incident myocardial infarction, and incident ischaemic stroke. We stratified the analyses by echocardiographic markers of diastolic dysfunction, and uric acid was the independent variable of interest. Hazard ratios (HR) were estimated per 59 μmol/L increase in baseline uric acid. Multivariable adjusted Cox proportional hazards models showed that uric acid predicted all-cause mortality in subjects with E/A ratio 1.5 (HR 1.51, 95% CI 1.09-2.09, P for interaction between E/A ratio category and uric acid = 0.02). Elevated uric acid increased mortality risk in persons with E-wave deceleration time 220 ms (HR 1.46, 95% CI 1.01-2.12 and HR 1.13, 95% CI 1.02-1.26, respectively; P for interaction = 0.04). Furthermore, in participants with isovolumetric relaxation time ≤60 ms, mortality risk was higher with increasing uric acid (HR 4.98, 95% CI 2.02-12.26, P for interaction = 0.004). Finally, elevated uric acid predicted ischaemic stroke in subjects with severely enlarged left atria (HR 1.62, 95% CI 1.03-2.53, P for interaction = 0.047). Increased uric acid was associated with higher all-cause mortality risk in subjects with echocardiographic indices of diastolic dysfunction, and with higher ischaemic stroke risk in persons with severely enlarged left atria.

  2. Validation of risk stratification schemes for predicting stroke and thromboembolism in patients with atrial fibrillation

    DEFF Research Database (Denmark)

    Olesen, Jonas Bjerring; Lip, Gregory Y H; Hansen, Morten Lock

    2011-01-01

    To evaluate the individual risk factors composing the CHADS(2) (Congestive heart failure, Hypertension, Age ≥ 75 years, Diabetes, previous Stroke) score and the CHA(2)DS(2)-VASc (CHA(2)DS(2)-Vascular disease, Age 65-74 years, Sex category) score and to calculate the capability of the schemes to p...

  3. Validation of risk stratification schemes for predicting stroke and thromboembolism in patients with atrial fibrillation

    DEFF Research Database (Denmark)

    Olesen, Jonas Bjerring; Lip, Gregory Y H; Hansen, Morten Lock

    2011-01-01

    Objectives To evaluate the individual risk factors composing the CHADS2 (Congestive heart failure, Hypertension, Age=75 years, Diabetes, previous Stroke) score and the CHA2DS2-VASc (CHA2DS2-Vascular disease, Age 65-74 years, Sex category) score and to calculate the capability of the schemes to pr...

  4. Predicting risk of cancer during HIV infection: the role of inflammatory and coagulation biomarkers.

    Science.gov (United States)

    Borges, Álvaro H; Silverberg, Michael J; Wentworth, Deborah; Grulich, Andrew E; Fätkenheuer, Gerd; Mitsuyasu, Ronald; Tambussi, Giuseppe; Sabin, Caroline A; Neaton, James D; Lundgren, Jens D

    2013-06-01

    To investigate the relationship between inflammatory [interleukin-6 (IL-6) and C-reactive protein (CRP)] and coagulation (D-dimer) biomarkers and cancer risk during HIV infection. A prospective cohort. HIV-infected patients on continuous antiretroviral therapy (ART) in the control arms of three randomized trials (N=5023) were included in an analysis of predictors of cancer (any type, infection-related or infection-unrelated). Hazard ratios for IL-6, CRP and D-dimer levels (log2-transformed) were calculated using Cox models stratified by trial and adjusted for demographics and CD4+ cell counts and adjusted also for all biomarkers simultaneously. To assess the possibility that biomarker levels were elevated at entry due to undiagnosed cancer, analyses were repeated excluding early cancer events (i.e. diagnosed during first 2 years of follow-up). During approximately 24,000 person-years of follow-up (PYFU), 172 patients developed cancer (70 infection-related; 102 infection-unrelated). The risk of developing cancer was associated with higher levels (per doubling) of IL-6 (hazard ratio 1.38, Passociated with cancer risk when all biomarkers were considered simultaneously. Results for infection-related and infection-unrelated cancers were similar to results for any cancer. Hazard ratios excluding 69 early cancer events were 1.31 (P=0.007), 1.14 (P=0.02) and 1.07 (P=0.49) for IL-6, CRP and D-dimer, respectively. Activated inflammation and coagulation pathways are associated with increased cancer risk during HIV infection. This association was stronger for IL-6 and persisted after excluding early cancer. Trials of interventions may be warranted to assess whether cancer risk can be reduced by lowering IL-6 levels in HIV-positive individuals.

  5. Presenting Symptoms and Dysphagia Screen Predict Outcome in Mild and Rapidly Improving Acute Ischemic Stroke Patients.

    Science.gov (United States)

    Gadodia, Gaurav; Rizk, Nibal; Camp, Deborah; Bryant, Katja; Zimmerman, Susan; Brasher, Cynthia; Connelly, Kerrin; Dunn, Joshua; Frankel, Michael; Ido, Moges Seymour; Lugtu, James; Nahab, Fadi

    2016-12-01

    There are limited data on which patients not treated with intravenous (IV) tissue-type plasminogen activator (tPA) due to mild and rapidly improving stroke symptoms (MaRISS) have unfavorable outcomes. Acute ischemic stroke (AIS) patients not treated with IV tPA due to MaRISS from January 1, 2009 to December 31, 2013 were identified as part of the Georgia Coverdell Acute Stroke Registry. Multivariable regression analysis was used to identify factors associated with a lower likelihood of favorable outcome, defined as discharge to home. There were 1614 AIS patients who did not receive IV tPA due to MaRISS (median National Institutes of Health stroke scale [NIHSS] 1], of which 305 (19%) did not have a favorable outcome. Factors associated with lower likelihood of favorable outcome included Medicare insurance status (odds ratio [OR]: .53, 95% confidence interval [CI]: .34-.84), arrival by emergency medical services (OR: .46, 95% CI: .29-.73), increasing NIHSS score (per unit OR: .89, 95% CI: .84-.93), weakness as the presenting symptom (OR: .50, 95% CI: .30-.84), and a failed dysphagia screen (OR: .43, 95% CI: .23-.80). During the study period, dysphagia screen identify a subgroup of patients who are more likely to have an unfavorable outcome. Whether IV tPA treatment can improve the outcome in this subgroup of patients needs to be evaluated in a randomized placebo-controlled trial. Copyright © 2016 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  6. The potential biomarkers in predicting pathologic response of breast cancer to three different chemotherapy regimens: a case control study

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    Xu Chaoyang

    2009-07-01

    Full Text Available Abstract Background Preoperative chemotherapy (PCT has become the standard of care in locally advanced breast cancer. The identification of patient-specific tumor characteristics that can improve the ability to predict response to therapy would help optimize treatment, improve treatment outcomes, and avoid unnecessary exposure to potential toxicities. This study is to determine whether selected biomarkers could predict pathologic response (PR of breast tumors to three different PCT regimens, and to identify a subset of patients who would benefit from a given type of treatment. Methods 118 patients with primary breast tumor were identified and three PCT regimens including DEC (docetaxel+epirubicin+cyclophosphamide, VFC (vinorelbine/vincristine+5-fluorouracil+cyclophosphamide and EFC (epirubicin+5-fluorouracil+cyclophosphamide were investigated. Expression of steroid receptors, HER2, P-gp, MRP, GST-pi and Topo-II was evaluated by immunohistochemical scoring on tumor tissues obtained before and after PCT. The PR of breast carcinoma was graded according to Sataloff's classification. Chi square test, logistic regression and Cochran-Mantel-Haenszel assay were performed to determine the association between biomarkers and PR, as well as the effectiveness of each regimen on induction of PR. Results There was a clear-cut correlation between the expression of ER and decreased PR to PCT in all three different regimens (p p Conclusion ER is an independent predictive factor for PR to PCT regimens including DEC, VFC and EFC in primary breast tumors, while HER2 is only predictive for DEC regimen. Expression of PgR, Topo-II, P-gp, MRP and GST-pi are not predictive for PR to any PCT regimens investigated. Results obtained in this clinical study may be helpful for the selection of appropriate treatments for breast cancer patients.

  7. The application of SHERPA (Systematic Human Error Reduction and Prediction Approach) in the development of compensatory cognitive rehabilitation strategies for stroke patients with left and right brain damage.

    Science.gov (United States)

    Hughes, Charmayne M L; Baber, Chris; Bienkiewicz, Marta; Worthington, Andrew; Hazell, Alexa; Hermsdörfer, Joachim

    2015-01-01

    Approximately 33% of stroke patients have difficulty performing activities of daily living, often committing errors during the planning and execution of such activities. The objective of this study was to evaluate the ability of the human error identification (HEI) technique SHERPA (Systematic Human Error Reduction and Prediction Approach) to predict errors during the performance of daily activities in stroke patients with left and right hemisphere lesions. Using SHERPA we successfully predicted 36 of the 38 observed errors, with analysis indicating that the proportion of predicted and observed errors was similar for all sub-tasks and severity levels. HEI results were used to develop compensatory cognitive strategies that clinicians could employ to reduce or prevent errors from occurring. This study provides evidence for the reliability and validity of SHERPA in the design of cognitive rehabilitation strategies in stroke populations.

  8. Prediction of hemorrhagic transformation in acute ischemic stroke using permeability surface of CT perfusion

    International Nuclear Information System (INIS)

    Xiong Bing; Chen Weijian; Fufengli

    2012-01-01

    Objective: To investigate the value of permeability surface (PS) in predicting hemorrhagic transformation (HT) in acute ischernic stroke (AIS) using CT perfusion (CTP). Methods: The study included 31 consecutive patients who presented symptoms suggestive of an AIS for 3-9 h. All patients underwent CT examination (noncontrast CT, CTP). HT was determined by follow-up CT images. According to presence of HT, the AIS was divided into HT group (PS HT , 11 patients) and non-HT group (PS No-HT , 20 patients). PS, cerebral blood flow (CBF), cerebral blood volume (CBV) and mean transit time (MTT) on both sides of brains were measured.The relative PS (rPS), relative CBF (rCBF), relative CBV (rCBV) and relative MTT(rMTT) were obtained by calculating the ratio of the values of bilateral regions. The rPS between PS HT and PS No-HT was compared with an exact Wilcoxon signed-rank test. The rCBF, rCBV, rMTT and the PS of the ischemic side between PS HT and PS No-HT were compared with independent-sample t test. Meanwhile, Spearman rank correlation analysis was conducted to analyze the relationship between the CTP parameters and HT. Results: The PS value of ischemic side was (1.61 ±0.77) ml · min -1 · 100 g -1 for the PS HT group,and the value was (0.91 ± 0.49) ml · min -1 · 100 g -1 for the PS No-HT group. For the PS HT group, rPS, rCBF, rCBV, rMTT were 2.76 ±0.78, 0.32 ±0.18, 0.66 ±0.31, 2.67 ±0.71, and for the PS No-HT group, rPS, rCBF, rCBV, rMTT were 1.35 ±0.19, 0.50±0.21, 0.91 ±0.28, 2.62 ± 1.31. Compared with PS No-HT ,PS HT had higher rPS and PS value,and there were significant statistical differences (U=0.000, t=3.070, P<0.01). But rCBF and rCBV values were lower in the PS HT group compared to the PS No-HT group, and there were significant statistical differences (t rCBF =2.343, t rCBV =2.210, P<0.05). There was no significant statistical difference in rMTT between the two groups (t=0.118, P>0.05). Significant positive correlations were detected between the r

  9. Pre-operative Carotid Plaque Echolucency Assessment has no Predictive Value for Long-Term Risk of Stroke or Cardiovascular Death in Patients Undergoing Carotid Endarterectomy.

    Science.gov (United States)

    de Waard, D; de Borst, G J; Bulbulia, R; Pan, H; Halliday, A

    2017-08-01

    In patients with carotid stenosis receiving medical treatment, carotid plaque echolucency has been thought to predict risk of future stroke and of other cardiovascular events. This study evaluated the prognostic value of pre-operative plaque echolucency for future stroke and cardiovascular death in patients undergoing carotid endarterectomy in the first Asymptomatic Carotid Surgery Trial (ACST-1). In ACST-1, 1832/3120 patients underwent carotid endarterectomy (CEA), of whom 894 had visual echolucency assessment according to the Gray-Weale classification. During follow-up patients were monitored both for peri-procedural (i.e. within 30 days) death, stroke, or MI, and for long-term risk of stroke or cardiovascular death. Unconditional maximum likelihood estimation was used to calculate odds ratios of peri-procedural risk and Kaplan-Meier statistics with log-rank test were used to compare cumulative long-term risks. Of 894 operated patients in whom echolucency was assessed, 458 plaques (51%) were rated as echolucent and peri-procedural risk of death/stroke/MI in these patients was non-significantly higher when compared with patients with non-echolucent plaques (OR 1.48 [95% CI 0.76-2.88], p = .241). No differences were found in the 10 year risk of any stroke (30/447 [11.6%] vs. 29/433 [11.0%], p = .900) or cardiovascular (non-stroke) death (85/447 [27.9%] vs. 93/433 [32.1%], p = .301). In ACST-1, carotid plaque echolucency assessment in patients undergoing CEA offered no predictive value with regard to peri-operative or long-term stroke risk or of cardiovascular (non-stroke) death. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  10. Development of the Stroke-unit Discharge Guideline: choice of assessment instruments for prediction in the subacute phase post-stroke

    NARCIS (Netherlands)

    Meijer, Ronald; van Limbeek, Jacques; de Haan, Rob

    2006-01-01

    The purpose of this paper is to present the design of an evidence-based dataset of assessment instruments for the prognostic factors of the Stroke-unit Discharge Guideline (SDG), a consensus based guideline for the decision of the discharge destination from the hospital stroke unit. In our

  11. Development of the Stroke-unit Discharge Guideline: choice of assessment instruments for prediction in the subacute phase post-stroke.

    NARCIS (Netherlands)

    Meijer, R.; Limbeek, J. van; Haan, R. de

    2006-01-01

    The purpose of this paper is to present the design of an evidence-based dataset of assessment instruments for the prognostic factors of the Stroke-unit Discharge Guideline (SDG), a consensus based guideline for the decision of the discharge destination from the hospital stroke unit. In our

  12. Cutoff value of pharyngeal residue in prognosis prediction after neuromuscular electrical stimulation therapy for Dysphagia in subacute stroke patients.

    Science.gov (United States)

    Park, Jeong Mee; Yong, Sang Yeol; Kim, Ji Hyun; Jung, Hong Sun; Chang, Sei Jin; Kim, Ki Young; Kim, Hee

    2014-10-01

    To determine the cutoff value of the pharyngeal residue for predicting reduction of aspiration, by measuring the residue of valleculae and pyriformis sinuses through videofluoroscopic swallowing studies (VFSS) after treatment with neuromuscular electrical stimulator (VitalStim) in stroke patients with dysphagia. VFSS was conducted on first-time stroke patients before and after the VitalStim therapy. The results were analyzed for comparison of the pharyngeal residue in the improved group and the non-improved group. A total of 59 patients concluded the test, in which 42 patients improved well enough to change the dietary methods while 17 did not improve sufficiently. Remnant area to total area (R/T) ratios of the valleculae before treatment in the improved group were 0.120, 0.177, and 0.101 for solid, soft, and liquid foods, respectively, whereas the ratios for the non-improved group were 0.365, 0.396, and 0.281, respectively. The ratios of the pyriformis sinuses were 0.126, 0.159, and 0.121 for the improved group and 0.315, 0.338, and 0.244 for the non-improved group. The R/T ratios of valleculae and pyriformis sinus were significantly lower in the improved group than the non-improved group in all food types before treatment. The R/T ratio cutoff values were 0.267, 0.250, and 0.185 at valleculae and 0.228, 0.218, and 0.185 at pyriformis sinuses. In dysphagia after stroke, less pharyngeal residue before treatment serves as a factor for predicting greater improvement after VitalStim treatment.

  13. Whole-brain perfusion CT using a toggling table technique to predict final infarct volume in acute ischemic stroke.

    Science.gov (United States)

    Schrader, I; Wilk, D; Jansen, O; Riedel, C

    2013-09-01

    To evaluate how accurately final infarct volume in acute ischemic stroke can be predicted with perfusion CT (PCT) using a 64-MDCT unit and the toggling table technique. Retrospective analysis of 89 patients with acute ischemic stroke who underwent CCT, CT angiography (CTA) and PCT using the "toggling table" technique within the first three hours after symptom onset. In patients with successful thrombolytic therapy (n = 48) and in those without effective thrombolytic therapy (n = 41), the infarct volume and the volume of the penumbra on PCT were compared to the infarct size on follow-up images (CT or MRI) performed within 8 days. The feasibility of complete infarct volume prediction by 8 cm cranio-caudal coverage was evaluated. The correlation between the volume of hypoperfusion on PCT defined by cerebral blood volume reduction and final infarct volume was strongest in patients with successful thrombolytic therapy with underestimation of the definite infarct volume by 8.5 ml on average. The CBV map had the greatest prognostic value. In patients without successful thrombolytic therapy, the final infarct volume was overestimated by 12.1 ml compared to the MTT map on PCT. All infarcts were detected completely. There were no false-positive or false-negative results. Using PCT and the "toggling table" technique in acute stroke patients is helpful for the rapid and accurate quantification of the minimal final infarct and is therefore a prognostic parameter which has to be evaluated in further studies to assess its impact on therapeutic decision. ▶ Using PCT and the “toggling table technique” allows accurate quantification of the infarct core and penumbra. ▶ It is possible to record dynamic perfusion parameters quickly and easily of almost the entire supratentorial brain volume on a 64-slice MDCT unit. ▶ The technique allows identification of those patients who could profit from thrombolytic therapy outside the established time intervals. © Georg Thieme Verlag

  14. Logical Analysis of Data (LAD model for the early diagnosis of acute ischemic stroke

    Directory of Open Access Journals (Sweden)

    Hoehn Gerard

    2008-07-01

    Full Text Available Abstract Background Strokes are a leading cause of morbidity and the first cause of adult disability in the United States. Currently, no biomarkers are being used clinically to diagnose acute ischemic stroke. A diagnostic test using a blood sample from a patient would potentially be beneficial in treating the disease. Results A classification approach is described for differentiating between proteomic samples of stroke patients and controls, and a second novel predictive model is developed for predicting the severity of stroke as measured by the National Institutes of Health Stroke Scale (NIHSS. The models were constructed by applying the Logical Analysis of Data (LAD methodology to the mass peak profiles of 48 stroke patients and 32 controls. The classification model was shown to have an accuracy of 75% when tested on an independent validation set of 35 stroke patients and 25 controls, while the predictive model exhibited superior performance when compared to alternative algorithms. In spite of their high accuracy, both models are extremely simple and were developed using a common set consisting of only 3 peaks. Conclusion We have successfully identified 3 biomarkers that can detect ischemic stroke with an accuracy of 75%. The performance of the classification model on the validation set and on cross-validation does not deteriorate significantly when compared to that on the training set, indicating the robustness of the model. As in the case of the LAD classification model, the results of the predictive model validate the function constructed on our support-set for approximating the severity scores of stroke patients. The correlation and root mean absolute error of the LAD predictive model are consistently superior to those of the other algorithms used (Support vector machines, C4.5 decision trees, Logistic regression and Multilayer perceptron.

  15. Inflammatory Biomarkers Predict Airflow Obstruction After Exposure to World Trade Center Dust

    Science.gov (United States)

    Nolan, Anna; Naveed, Bushra; Comfort, Ashley L.; Ferrier, Natalia; Hall, Charles B.; Kwon, Sophia; Kasturiarachchi, Kusali J.; Cohen, Hillel W.; Zeig-Owens, Rachel; Glaser, Michelle S.; Webber, Mayris P.; Aldrich, Thomas K.; Rom, William N.; Kelly, Kerry; Prezant, David J.

    2012-01-01

    Background: The World Trade Center (WTC) collapse on September 11, 2001, produced airflow obstruction in a majority of firefighters receiving subspecialty pulmonary evaluation (SPE) within 6.5 years post-September 11, 2001. Methods: In a cohort of 801 never smokers with normal pre-September 11, 2001, FEV1, we correlated inflammatory biomarkers and CBC counts at monitoring entry within 6 months of September 11, 2001, with a median FEV1 at SPE (34 months; interquartile range, 25-57). Cases of airflow obstruction had FEV1 less than the lower limit of normal (LLN) (100 of 801; 70 of 100 had serum), whereas control subjects had FEV1 greater than or equal to LLN (153 of 801; 124 of 153 had serum). Results: From monitoring entry to SPE years later, FEV1 declined 12% in cases and increased 3% in control subjects. Case subjects had elevated serum macrophage derived chemokine (MDC), granulocyte-macrophage colony-stimulating factor (GM-CSF), granulocyte colony-stimulating factor, and interferon inducible protein-10 levels. Elevated GM-CSF and MDC increased the risk for subsequent FEV1 less than LLN by 2.5-fold (95% CI, 1.2-5.3) and 3.0-fold (95% CI, 1.4-6.1) in a logistic model adjusted for exposure, BMI, age on September 11, 2001, and polymorphonuclear neutrophils. The model had sensitivity of 38% (95% CI, 27-51) and specificity of 88% (95% CI, 80-93). Conclusions: Inflammatory biomarkers can be risk factors for airflow obstruction following dust and smoke exposure. Elevated serum GM-CSF and MDC levels soon after WTC exposure were associated with increased risk of airflow obstruction in subsequent years. Biomarkers of inflammation may help identify pathways producing obstruction after irritant exposure. PMID:21998260

  16. The potential role for use of mitochondrial DNA copy number as predictive biomarker in presbycusis.

    Science.gov (United States)

    Falah, Masoumeh; Houshmand, Massoud; Najafi, Mohammad; Balali, Maryam; Mahmoudian, Saeid; Asghari, Alimohamad; Emamdjomeh, Hessamaldin; Farhadi, Mohammad

    2016-01-01

    Age-related hearing impairment, or presbycusis, is the most common communication disorder and neurodegenerative disease in the elderly. Its prevalence is expected to increase, due to the trend of growth of the elderly population. The current diagnostic test for detection of presbycusis is implemented after there has been a change in hearing sensitivity. Identification of a pre-diagnostic biomarker would raise the possibility of preserving hearing sensitivity before damage occurs. Mitochondrial dysfunction, including the production of reactive oxygen species and induction of expression of apoptotic genes, participates in the progression of presbycusis. Mitochondrial DNA sequence variation has a critical role in presbycusis. However, the nature of the relationship between mitochondrial DNA copy number, an important biomarker in many other diseases, and presbycusis is undetermined. Fifty-four subjects with presbycusis and 29 healthy controls were selected after ear, nose, throat examination and pure-tone audiometry. DNA was extracted from peripheral blood samples. The copy number of mitochondrial DNA relative to the nuclear genome was measured by quantitative real-time polymerase chain reaction. Subjects with presbycusis had a lower median mitochondrial DNA copy number than healthy subjects and the difference was statistically significant ( P =0.007). Mitochondrial DNA copy number was also significantly associated with degree of hearing impairment ( P =0.025) and audiogram configuration ( P =0.022). The findings of this study suggest that lower mitochondrial DNA copy number is responsible for presbycusis through alteration of mitochondrial function. Moreover, the significant association of mitochondrial DNA copy number in peripheral blood samples with the degree of hearing impairment and audiogram configuration has potential for use as a standard test for presbycusis, providing the possibility of the development of an easy-to-use biomarker for the early detection of

  17. Improving the Prediction of Spontaneous and Post-thrombolytic Recanalization in Ischemic Stroke Patients.

    Science.gov (United States)

    Vanacker, Peter; Lambrou, Dimitris; Eskandari, Ashraf; Ntaios, George; Cras, Patrick; Maeder, Philippe; Meuli, Reto; Michel, Patrik

    2015-08-01

    Endovascular treatment for acute ischemic stroke patients was recently shown to improve recanalization rates and clinical outcome in a well-defined study population. Intravenous thrombolysis (IVT) alone is insufficiently effective to recanalize in certain patients or of little value in others. Accordingly, we aimed at identifying predictors of recanalization in patients treated with or without IVT. In the observational Acute Stroke Registry and Analysis of Lausanne (ASTRAL) registry, we selected those stroke patients (1) with an arterial occlusion on computed tomography angiography (CTA) imaging, (2) who had an arterial patency assessment at 24 hours (CTA/magnetic resonance angiography/transcranial Doppler), and (3) who were treated with IVT or had no revascularization treatment. Based on 2 separate logistic regression analyses, predictors of spontaneous and post-thrombolytic recanalization were generated. Partial or complete recanalization was achieved in 121 of 210 (58%) thrombolyzed patients. Recanalization was associated with atrial fibrillation (odds ratio , 1.6; 95% confidence interval, 1.2-3.0) and absence of early ischemic changes on CT (1.1, 1.1-1.2) and inversely correlated with the presence of a significant extracranial (EC) stenosis or occlusion (.6, .3-.9). In nonthrombolyzed patients, partial or complete recanalization was significantly less frequent (37%, P < .01). The recanalization was independently associated with a history of hypercholesterolemia (2.6, 1.2-5.6) and the proximal site of the intracranial occlusion (2.5, 1.2-5.4), and inversely correlated with a decreased level of consciousness (.3, .1-.8), and EC (.3, .1-.6) and basilar artery pathology (.1, .0-.6). Various clinical findings, cardiovascular risk factors, and arterial pathology on acute CTA-based imaging are moderately associated with spontaneous and post-thrombolytic arterial recanalization at 24 hours. If confirmed in other studies, this information may influence patient selection

  18. The potential role for use of mitochondrial DNA copy number as predictive biomarker in presbycusis

    Directory of Open Access Journals (Sweden)

    Falah M

    2016-10-01

    Full Text Available Masoumeh Falah,1,2 Massoud Houshmand,3 Mohammad Najafi,2 Maryam Balali,1 Saeid Mahmoudian,1 Alimohamad Asghari,4 Hessamaldin Emamdjomeh,1 Mohammad Farhadi1 1ENT and Head & Neck Research Center and Department, Iran University of Medical Sciences, Tehran, Iran; 2Cellular and Molecular Research Center, Biochemistry Department, Iran University of Medical Sciences, Tehran, Iran; 3Department of Medical Genetics, National Institute for Genetic Engineering and Biotechnology, Tehran, Iran; 4Skull base research center, Iran University of Medical Sciences, Tehran, Iran Objectives: Age-related hearing impairment, or presbycusis, is the most common communication disorder and neurodegenerative disease in the elderly. Its prevalence is expected to increase, due to the trend of growth of the elderly population. The current diagnostic test for detection of presbycusis is implemented after there has been a change in hearing sensitivity. Identification of a pre-diagnostic biomarker would raise the possibility of preserving hearing sensitivity before damage occurs. Mitochondrial dysfunction, including the production of reactive oxygen species and induction of expression of apoptotic genes, participates in the progression of presbycusis. Mitochondrial DNA sequence variation has a critical role in presbycusis. However, the nature of the relationship between mitochondrial DNA copy number, an important biomarker in many other diseases, and presbycusis is undetermined.Methods: Fifty-four subjects with presbycusis and 29 healthy controls were selected after ear, nose, throat examination and pure-tone audiometry. DNA was extracted from peripheral blood samples. The copy number of mitochondrial DNA relative to the nuclear genome was measured by quantitative real-time polymerase chain reaction.Results: Subjects with presbycusis had a lower median mitochondrial DNA copy number than healthy subjects and the difference was statistically significant (P=0.007. Mitochondrial DNA

  19. Early menopause predicts future coronary heart disease and stroke: the Multi-Ethnic Study of Atherosclerosis.

    Science.gov (United States)

    Wellons, Melissa; Ouyang, Pamela; Schreiner, Pamela J; Herrington, David M; Vaidya, Dhananjay

    2012-10-01

    Cardiovascular disease is the number one killer of women. Identifying women at risk of cardiovascular disease has tremendous public health importance. Early menopause is associated with increased cardiovascular disease events in some predominantly white populations, but not consistently. Our objective was to determine if self-reported early menopause (menopause at an age menopause (either natural menopause or surgical removal of ovaries at an age menopause. In survival curves, women with early menopause had worse coronary heart disease and stroke-free survival (log rank P = 0.008 and P = 0.0158). In models adjusted for age, race/ethnicity, Multi-ethnic Study Atherosclerosis site, and traditional cardiovascular disease risk factors, this risk for coronary heart disease and stroke remained (hazard ratio, 2.08; 95% CI, 1.17-3.70; and hazard ratio, 2.19; 95% CI, 1.11-4.32, respectively). Early menopause is positively associated with coronary heart disease and stroke in a multiethnic cohort, independent of traditional cardiovascular disease risk factors.

  20. Prediction of early neurological deterioration using diffusion- and perfusion-weighted imaging in hyperacute middle cerebral artery ischemic stroke.

    Science.gov (United States)

    Arenillas, Juan F; Rovira, Alex; Molina, Carlos A; Grivé, Elisenda; Montaner, Joan; Alvarez-Sabín, José

    2002-09-01

    Early neurological deterioration (END) occurs in approximately one third of all ischemic stroke patients and is associated with a poor outcome. Our study sought to assess the value of ultra-early MRI in the prediction of END in stroke patients. Between August 1999 and November 2001, 38 stroke patients with a proven middle cerebral artery (MCA) or intracranial internal carotid artery (ICA) occlusion on MR angiography underwent perfusion-weighted imaging (PWI) and diffusion-weighted imaging (DWI) within 6 hours after onset, and 30 fulfilled all inclusion criteria. Control DWI and MR angiography were performed between days 3 and 5. Cranial CT was performed to rule out hemorrhagic transformation. Vascular risk factors, temperature, blood pressure, glycemia, and blood count were assessed on admission. National Institutes of Health Stroke Scale (NIHSS) scores were obtained at baseline and at 6, 12, 24, and 48 hours. At the same time points, transcranial Doppler (TCD) examinations were conducted to assess arterial recanalization. END was defined as an increase in the NIHSS score >4. A logistic regression model was applied to detect independent predictors of END. The Kruskal-Wallis test was used to evaluate the relationship between infarct growth and duration of vessel occlusion. Initial MR angiography showed an occlusion of intracranial ICA in 7 patients (23.3%), of proximal MCA in 14 (46.6%), and of distal MCA in the remaining 9 (30%). A PWI-DWI mismatch >20% was observed in 28 patients (93.3%). END occurred in 7 patients (23.3%). Baseline NIHSS score (P=0.05), proximal site of occlusion (P=0.002), initial DWI (P=0.002) and PWI (P=0.003) volumes, and reduced PWI-DWI mismatch (P=0.038) were associated with END in the univariate analysis. Only hyperacute DWI volume remained as a predictor of END when a logistic regression model was applied (odds ratio, 11.5; 95% CI, 2.31 to 57.10; P=0.0028). A receiver operator characteristic curve identified a cutoff point of DWI >89 cm(3

  1. DI/LC-MS/MS-Based Metabolic Profiling for Identification of Early Predictive Serum Biomarkers of Metritis in Transition Dairy Cows.

    Science.gov (United States)

    Zhang, Guanshi; Deng, Qilan; Mandal, Rupasri; Wishart, David S; Ametaj, Burim N

    2017-09-27

    The objectives of this study were to evaluate alterations of metabolites in the blood of dairy cows before, during, and after diagnosis of metritis and identify predictive serum metabolite biomarkers for metritis. DI/LC-MS/MS was used to analyze serum samples collected from both healthy and metritic cows during -8, -4, disease diagnosis, +4, and +8 wks relative to parturition. Results indicated that cows with metritis experienced altered concentrations of serum amino acids, glycerophospholipids, sphingolipids, acylcarnitines, and biogenic amines during the entire experimental period. Moreover, two sets of predictive biomarker models and one set of diagnostic biomarker models for metritis were developed, and all of them showed high sensitivity and specificity (e.g., high AUC values by the ROC curve evaluation), which indicate that serum metabolites identified have pretty accurate predictive, diagnostic, and prognostic abilities for metritis in transition dairy cows.

  2. Stroke-Related Translational Research

    Science.gov (United States)

    Caplan, Louis R.; Arenillas, Juan; Cramer, Steven C.; Joutel, Anne; Lo, Eng H.; Meschia, James; Savitz, Sean; Tournier-Lasserve, Elizabeth

    2013-01-01

    Stroke-related translational research is multifaceted. Herein, we highlight genome-wide association studies and genetic studies of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, COL4A1 mutations, and cerebral cavernous malformations; advances in molecular biology and biomarkers; newer brain imaging research; and recovery from stroke emphasizing cell-based and other rehabilitative modalities. PMID:21555605

  3. Predictive value of vertebral artery extracranial color-coded duplex sonography for ischemic stroke-related vertigo.

    Science.gov (United States)

    Liou, Li-Min; Lin, Hsiu-Fen; Huang, I-Fang; Chang, Yang-Pei; Lin, Ruey-Tay; Lai, Chiou-Lian

    2013-12-01

    Vertigo can be a major presentation of posterior circulation stroke and can be easily misdiagnosed because of its complicated presentation. We thus prospectively assessed the predictive value of vertebral artery extracranial color-coded duplex sonography (ECCS) for the prediction of ischemic stroke-related vertigo. The inclusion criteria were: (1) a sensation of whirling (vertigo); (2) intractable vertigo for more than 1 hour despite appropriate treatment; and (3) those who could complete cranial magnetic resonance imaging (MRI) and vertebral artery (V2 segment) ECCS studies. Eventually, 76 consecutive participants with vertigo were enrolled from Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung, Taiwan between August 2010 and August 2011. Demographic data, neurological symptoms, neurologic examinations, and V2 ECCS were assessed. We chose the parameters of peak systolic velocity (PSV), end diastolic velocity (EDV), PSV/EDV, mean velocity (MV), resistance index (RI), and pulsatility index (PI) to represent the hemodynamics. Values from both sides of V2 segments were averaged. We then calculated the average RI (aRI), average PI (aPI), average PSV (aPSV)/EDV, and average (aMV). Axial and coronal diffusion-weighted MRI findings determined the existence of acute ischemic stroke. We grouped and analyzed participants in two ways (way I and way II analyses) based on the diffusion-weighted MRI findings (to determine whether there was acute stroke) and neurological examinations. Using way I analysis, the "MRI (+)" group had significantly higher impedance (aRI, aPI, and aPSV/EDV ratio) and lower velocity (aPSV, aEDV, and aMV(PSV + EDV/2)), compared to the "MRI (-)" group. The cutoff value/sensitivity/specificity of aPSV, aEDV, aMV, aPI, aRI, and aPSV/EDV between the MRI (+) and MRI (-) groups were 41.15/61.5/66.0 (p = 0.0101), 14.55/69.2/72.0 (p = 0.0003), 29.10/92.1/38.0 (p = 0.0013), 1.07/76.9/64.0 (p = 0.0066), 0.62/76.9/64.0 (p = 0.0076), and 2.69/80.8/66.0 (p = 0

  4. Body configuration at first stepping-foot contact predicts backward balance recovery capacity in people with chronic stroke.

    Science.gov (United States)

    de Kam, Digna; Roelofs, Jolanda M B; Geurts, Alexander C H; Weerdesteyn, Vivian

    2018-01-01

    To determine the predictive value of leg and trunk inclination angles at stepping-foot contact for the capacity to recover from a backward balance perturbation with a single step in people after stroke. Twenty-four chronic stroke survivors and 21 healthy controls were included in a cross-sectional study. We studied reactive stepping responses by subjecting participants to multidirectional stance perturbations at different intensities on a translating platform. In this paper we focus on backward perturbations. Participants were instructed to recover from the perturbations with maximally one step. A trial was classified as 'success' if balance was restored according to this instruction. We recorded full-body kinematics and computed: 1) body configuration parameters at first stepping-foot contact (leg and trunk inclination angles) and 2) spatiotemporal step parameters (step onset, step length, step duration and step velocity). We identified predictors of balance recovery capacity using a stepwise logistic regression. Perturbation intensity was also included as a predictor. The model with spatiotemporal parameters (perturbation intensity, step length and step duration) could correctly classify 85% of the trials as success or fail (Nagelkerke R2 = 0.61). In the body configuration model (Nagelkerke R2 = 0.71), perturbation intensity and leg and trunk angles correctly classified the outcome of 86% of the recovery attempts. The goodness of fit was significantly higher for the body configuration model compared to the model with spatiotemporal variables (pmodel. Body configuration at stepping-foot contact is a valid and clinically feasible indicator of backward fall risk in stroke survivors, given its potential to be derived from a single sagittal screenshot.

  5. Adjustment of Serum HE4 to reduced Glomerular filtration and its use in Biomarker-based prediction of deep Myometrial invasion in endometrial cancer

    DEFF Research Database (Denmark)

    Chovanec, Josef; Selingerova, Iveta; Greplova, Kristina

    2017-01-01

    Background: We investigated the efficacy of circulating biomarkers together with histological grade and age to predict deep myometrial invasion (dMI) in endometrial cancer patients. Methods: HE4ren was developed adjusting HE4 serum levels towards decreased glomerular filtration rate as quantified...... levels to reduced eGFR that enables quantification of time-dependent changes in HE4 production and elimination irrespective of age and renal function in women. Utilizing HE4ren improves performance of biomarker-based models for prediction of dMI in endometrial cancer patients....

  6. An etiologic prediction model incorporating biomarkers to predict the bladder cancer risk associated with occupational exposure to aromatic amines: a pilot study.

    Science.gov (United States)

    Mastrangelo, Giuseppe; Carta, Angela; Arici, Cecilia; Pavanello, Sofia; Porru, Stefano

    2017-01-01

    No etiological prediction model incorporating biomarkers is available to predict bladder cancer risk associated with occupational exposure to aromatic amines. Cases were 199 bladder cancer patients. Clinical, laboratory and genetic data were predictors in logistic regression models (full and short) in which the dependent variable was 1 for 15 patients with aromatic amines related bladder cancer and 0 otherwise. The receiver operating characteristics approach was adopted; the area under the curve was used to evaluate discriminatory ability of models. Area under the curve was 0.93 for the full model (including age, smoking and coffee habits, DNA adducts, 12 genotypes) and 0.86 for the short model (including smoking, DNA adducts, 3 genotypes). Using the "best cut-off" of predicted probability of a positive outcome, percentage of cases correctly classified was 92% (full model) against 75% (short model). Cancers classified as "positive outcome" are those to be referred for evaluation by an occupational physician for etiological diagnosis; these patients were 28 (full model) or 60 (short model). Using 3 genotypes instead of 12 can double the number of patients with suspect of aromatic amine related cancer, thus increasing costs of etiologic appraisal. Integrating clinical, laboratory and genetic factors, we developed the first etiologic prediction model for aromatic amine related bladder cancer. Discriminatory ability was excellent, particularly for the full model, allowing individualized predictions. Validation of our model in external populations is essential for practical use in the clinical setting.

  7. A genomic biomarker signature can predict skin sensitizers using a cell-based in vitro alternative to animal tests

    Directory of Open Access Journals (Sweden)

    Albrekt Ann-Sofie

    2011-08-01

    Full Text Available Abstract Background Allergic contact dermatitis is an inflammatory skin disease that affects a significant proportion of the population. This disease is caused by an adverse immune response towards chemical haptens, and leads to a substantial economic burden for society. Current test of sensitizing chemicals rely on animal experimentation. New legislations on the registration and use of chemicals within pharmaceutical and cosmetic industries have stimulated significant research efforts to develop alternative, human cell-based assays for the prediction of sensitization. The aim is to replace animal experiments with in vitro tests displaying a higher predictive power. Results We have developed a novel cell-based assay for the prediction of sensitizing chemicals. By analyzing the transcriptome of the human cell line MUTZ-3 after 24 h stimulation, using 20 different sensitizing chemicals, 20 non-sensitizing chemicals and vehicle controls, we have identified a biomarker signature of 200 genes with potent discriminatory ability. Using a Support Vector Machine for supervised classification, the prediction performance of the assay revealed an area under the ROC curve of 0.98. In addition, categorizing the chemicals according to the LLNA assay, this gene signature could also predict sensitizing potency. The identified markers are involved in biological pathways with immunological relevant functions, which can shed light on the process of human sensitization. Conclusions A gene signature predicting sensitization, using a human cell line in vitro, has been identified. This simple and robust cell-based assay has the potential to completely replace or drastically reduce the utilization of test systems based on experimental animals. Being based on human biology, the assay is proposed to be more accurate for predicting sensitization in humans, than the traditional animal-based tests.

  8. A genomic biomarker signature can predict skin sensitizers using a cell-based in vitro alternative to animal tests

    Science.gov (United States)

    2011-01-01

    Background Allergic contact dermatitis is an inflammatory skin disease that affects a significant proportion of the population. This disease is caused by an adverse immune response towards chemical haptens, and leads to a substantial economic burden for society. Current test of sensitizing chemicals rely on animal experimentation. New legislations on the registration and use of chemicals within pharmaceutical and cosmetic industries have stimulated significant research efforts to develop alternative, human cell-based assays for the prediction of sensitization. The aim is to replace animal experiments with in vitro tests displaying a higher predictive power. Results We have developed a novel cell-based assay for the prediction of sensitizing chemicals. By analyzing the transcriptome of the human cell line MUTZ-3 after 24 h stimulation, using 20 different sensitizing chemicals, 20 non-sensitizing chemicals and vehicle controls, we have identified a biomarker signature of 200 genes with potent discriminatory ability. Using a Support Vector Machine for supervised classification, the prediction performance of the assay revealed an area under the ROC curve of 0.98. In addition, categorizing the chemicals according to the LLNA assay, this gene signature could also predict sensitizing potency. The identified markers are involved in biological pathways with immunological relevant functions, which can shed light on the process of human sensitization. Conclusions A gene signature predicting sensitization, using a human cell line in vitro, has been identified. This simple and robust cell-based assay has the potential to completely replace or drastically reduce the utilization of test systems based on experimental animals. Being based on human biology, the assay is proposed to be more accurate for predicting sensitization in humans, than the traditional animal-based tests. PMID:21824406

  9. CT image biomarkers to improve patient-specific prediction of radiation-induced xerostomia and sticky saliva.

    Science.gov (United States)

    van Dijk, Lisanne V; Brouwer, Charlotte L; van der Schaaf, Arjen; Burgerhof, Johannes G M; Beukinga, Roelof J; Langendijk, Johannes A; Sijtsema, Nanna M; Steenbakkers, Roel J H M

    2017-02-01

    Current models for the prediction of late patient-rated moderate-to-severe xerostomia (XER 12m ) and sticky saliva (STIC 12m ) after radiotherapy are based on dose-volume parameters and baseline xerostomia (XER base ) or sticky saliva (STIC base ) scores. The purpose is to improve prediction of XER 12m and STIC 12m with patient-specific characteristics, based on CT image biomarkers (IBMs). Planning CT-scans and patient-rated outcome measures were prospectively collected for 249 head and neck cancer patients treated with definitive radiotherapy with or without systemic treatment. The potential IBMs represent geometric, CT intensity and textural characteristics of the parotid and submandibular glands. Lasso regularisation was used to create multivariable logistic regression models, which were internally validated by bootstrapping. The prediction of XER 12m could be improved significantly by adding the IBM "Short Run Emphasis" (SRE), which quantifies heterogeneity of parotid tissue, to a model with mean contra-lateral parotid gland dose and XER base . For STIC 12m , the IBM maximum CT intensity of the submandibular gland was selected in addition to STIC base and mean dose to submandibular glands. Prediction of XER 12m and STIC 12m was improved by including IBMs representing heterogeneity and density of the salivary glands, respectively. These IBMs could guide additional research to the patient-specific response of healthy tissue to radiation dose. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  10. An integrated model supporting histological and biometric responses as predictive biomarkers of fish health status

    Science.gov (United States)

    Torres Junior, Audalio Rebelo; Sousa, Débora Batista Pinheiro; Neta, Raimunda Nonata Fortes Carvalho

    2014-10-01

    In this work, an experimental system of histological (branchial lesions) biomarkers and biometric data in catfish (Sciades herzbergii) was modeled. The fish were sampled along known pollution areas (S1) and from environmental protect areas (S2) in São Marcos' Bay, Brazil. Gills were fixed in 10% formalin and usual histological techniques were used in the first gill arch right. The lesions were observed by light microscopy. There were no histopathological changes in animals captured at reference site (S1). However, in the catfish collected in the potentially contaminated area (S2) was observed several branchial lesions, such as lifting of the lamellar epithelium, fusion of some secondary lamellae, hypertrophy of epithelial cells and lamellar aneurysm. The analysis using the biometric data showed significant differences, being highest in fish analyzed in the reference area. This approach revealed spatial differences related with biometric patterns and morphological modifications of catfish.

  11. An integrated model supporting histological and biometric responses as predictive biomarkers of fish health status

    International Nuclear Information System (INIS)

    Torres Junior, Audalio Rebelo; Sousa, Débora Batista Pinheiro; Neta, Raimunda Nonata Fortes Carvalho

    2014-01-01

    In this work, an experimental system of histological (branchial lesions) biomarkers and biometric data in catfish (Sciades herzbergii) was modeled. The fish were sampled along known pollution areas (S1) and from environmental protect areas (S2) in São Marcos' Bay, Brazil. Gills were fixed in 10% formalin and usual histological techniques were used in the first gill arch right. The lesions were observed by light microscopy. There were no histopathological changes in animals captured at reference site (S1). However, in the catfish collected in the potentially contaminated area (S2) was observed several branchial lesions, such as lifting of the lamellar epithelium, fusion of some secondary lamellae, hypertrophy of epithelial cells and lamellar aneurysm. The analysis using the biometric data showed significant differences, being highest in fish analyzed in the reference area. This approach revealed spatial differences related with biometric patterns and morphological modifications of catfish

  12. An integrated model supporting histological and biometric responses as predictive biomarkers of fish health status

    Energy Technology Data Exchange (ETDEWEB)

    Torres Junior, Audalio Rebelo [Department of Oceanography and Limnology, Federal University of Maranhão (Brazil); Sousa, Débora Batista Pinheiro [Postgraduate Program of Aquatic Resources and Fishery (PPGRAP/UEMA), State University of Maranhão (Brazil); Neta, Raimunda Nonata Fortes Carvalho [Department of Chemistry and Biology, State University of Maranhão (Brazil)

    2014-10-06

    In this work, an experimental system of histological (branchial lesions) biomarkers and biometric data in catfish (Sciades herzbergii) was modeled. The fish were sampled along known pollution areas (S1) and from environmental protect areas (S2) in São Marcos' Bay, Brazil. Gills were fixed in 10% formalin and usual histological techniques were used in the first gill arch right. The lesions were observed by light microscopy. There were no histopathological changes in animals captured at reference site (S1). However, in the catfish collected in the potentially contaminated area (S2) was observed several branchial lesions, such as lifting of the lamellar epithelium, fusion of some secondary lamellae, hypertrophy of epithelial cells and lamellar aneurysm. The analysis using the biometric data showed significant differences, being highest in fish analyzed in the reference area. This approach revealed spatial differences related with biometric patterns and morphological modifications of catfish.

  13. The potential use of biomarkers in predicting contrast-induced acute kidney injury

    Directory of Open Access Journals (Sweden)

    Andreucci M

    2016-09-01

    Full Text Available Michele Andreucci,1 Teresa Faga,1 Eleonora Riccio,2 Massimo Sabbatini,2 Antonio Pisani,2 Ashour Michael,1 1Department of Health Sciences, University “Magna Graecia” of Catanzaro, Catanzaro, 2Department of Public Health, University of Naples Federico II, Naples, Italy Abstract: Contrast-induced acute kidney injury (CI-AKI is a problem associated with the use of iodinated contrast media, causing kidney dysfunction in patients with preexisting renal failure. It accounts for 12% of all hospital-acquired kidney failure and increases the length of hospitalization, a situation that is worsening with increasing numbers of patients with comorbidities, including those requiring cardiovascular interventional procedures. So far, its diagnosis has relied upon the rise in creatinine levels, which is a late marker of kidney damage and is believed to be inadequate. Therefore, there is an urgent need for biomarkers that can detect CI-AKI sooner and more reliably. In recent years, many new biomarkers have been characterized for AKI, and these are discussed particularly with their use in known CI-AKI models and studies and include neutrophil gelatinase-associated lipocalin, cystatin C (Cys-C, kidney injury molecule-1, interleukin-18, N-acetyl-β-d-glucosaminidase, and L-type fatty acid-binding protein (L-FABP. The potential of miRNA and metabolomic technology is also mentioned. Early detection of CI-AKI may lead to early intervention and therefore improve patient outcome, and in future any one or a combination of several of these markers together with development in technology for their analysis may prove effective in this respect. Keywords: radiocontrast media, acute renal failure, markers, renal injury

  14. Permeability Surface of Deep Middle Cerebral Artery Territory on Computed Tomographic Perfusion Predicts Hemorrhagic Transformation After Stroke.

    Science.gov (United States)

    Li, Qiao; Gao, Xinyi; Yao, Zhenwei; Feng, Xiaoyuan; He, Huijin; Xue, Jing; Gao, Peiyi; Yang, Lumeng; Cheng, Xin; Chen, Weijian; Yang, Yunjun

    2017-09-01

    Permeability surface (PS) on computed tomographic perfusion reflects blood-brain barrier permeability and is related to hemorrhagic transformation (HT). HT of deep middle cerebral artery (MCA) territory can occur after recanalization of proximal large-vessel occlusion. We aimed to determine the relationship between HT and PS of deep MCA territory. We retrospectively reviewed 70 consecutive acute ischemic stroke patients presenting with occlusion of the distal internal carotid artery or M1 segment of the MCA. All patients underwent computed tomographic perfusion within 6 hours after symptom onset. Computed tomographic perfusion data were postprocessed to generate maps of different perfusion parameters. Risk factors were identified for increased deep MCA territory PS. Receiver operating characteristic curve analysis was performed to calculate the optimal PS threshold to predict HT of deep MCA territory. Increased PS was associated with HT of deep MCA territory. After adjustments for age, sex, onset time to computed tomographic perfusion, and baseline National Institutes of Health Stroke Scale, poor collateral status (odds ratio, 7.8; 95% confidence interval, 1.67-37.14; P =0.009) and proximal MCA-M1 occlusion (odds ratio, 4.12; 95% confidence interval, 1.03-16.52; P =0.045) were independently associated with increased deep MCA territory PS. Relative PS most accurately predicted HT of deep MCA territory (area under curve, 0.94; optimal threshold, 2.89). Increased PS can predict HT of deep MCA territory after recanalization therapy for cerebral proximal large-vessel occlusion. Proximal MCA-M1 complete occlusion and distal internal carotid artery occlusion in conjunction with poor collaterals elevate deep MCA territory PS. © 2017 American Heart Association, Inc.

  15. Manual physical balance assistance of therapists during gait training of stroke survivors: characteristics and predicting the timing.

    Science.gov (United States)

    Haarman, Juliet A M; Maartens, Erik; van der Kooij, Herman; Buurke, Jaap H; Reenalda, Jasper; Rietman, Johan S

    2017-12-02

    During gait training, physical therapists continuously supervise stroke survivors and provide physical support to their pelvis when they judge that the patient is unable to keep his balance. This paper is the first in providing quantitative data about the corrective forces that therapists use during gait training. It is assumed that changes in the acceleration of a patient's COM are a good predictor for therapeutic balance assistance during the training sessions Therefore, this paper provides a method that predicts the timing of therapeutic balance assistance, based on acceleration data of the sacrum. Eight sub-acute stroke survivors and seven therapists were included in this study. Patients were asked to perform straight line walking as well as slalom walking in a conventional training setting. Acceleration of the sacrum was captured by an Inertial Magnetic Measurement Unit. Balance-assisting corrective forces applied by the therapist were collected from two force sensors positioned on both sides of the patient's hips. Measures to characterize the therapeutic balance assistance were the amount of force, duration, impulse and the anatomical plane in which the assistance took place. Based on the acceleration data of the sacrum, an algorithm was developed to predict therapeutic balance assistance. To validate the developed algorithm, the predicted events of balance assistance by the algorithm were compared with the actual provided therapeutic assistance. The algorithm was able to predict the actual therapeutic assistance with a Positive Predictive Value of 87% and a True Positive Rate of 81%. Assistance mainly took place over the medio-lateral axis and corrective forces of about 2% of the patient's body weight (15.9 N (11), median (IQR)) were provided by therapists in this plane. Median duration of balance assistance was 1.1 s (0.6) (median (IQR)) and median impulse was 9.4Ns (8.2) (median (IQR)). Although therapists were specifically instructed to aim for the

  16. Advancing stroke genomic research in the age of Trans-Omics big data science: Emerging priorities and opportunities.

    Science.gov (United States)

    Owolabi, Mayowa; Peprah, Emmanuel; Xu, Huichun; Akinyemi, Rufus; Tiwari, Hemant K; Irvin, Marguerite R; Wahab, Kolawole Wasiu; Arnett, Donna K; Ovbiagele, Bruce

    2017-11-15

    We systematically reviewed the genetic variants associated with stroke in genome-wide association studies (GWAS) and examined the emerging priorities and opportunities for rapidly advancing stroke research in the era of Trans-Omics science. Using the PRISMA guideline, we searched PubMed and NHGRI- EBI GWAS catalog for stroke studies from 2007 till May 2017. We included 31 studies. The major challenge is that the few validated variants could not account for the full genetic risk of stroke and have not been translated for clinical use. None of the studies included continental Africans. Genomic study of stroke among Africans presents a unique opportunity for the discovery, validation, functional annotation, Trans-Omics study and translation of genomic determinants of stroke with implications for global populations. This is because all humans originated from Africa, a continent with a unique genomic architecture and a distinctive epidemiology of stroke; as well as substantially higher heritability and resolution of fine mapping of stroke genes. Understanding the genomic determinants of stroke and the corresponding molecular mechanisms will revolutionize the development of a new set of precise biomarkers for stroke prediction, diagnosis and prognostic estimates as well as personalized interventions for reducing the global burden of stroke. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Predicting the disease of Alzheimer with SNP biomarkers and clinical data using data mining classification approach: decision tree.

    Science.gov (United States)

    Erdoğan, Onur; Aydin Son, Yeşim

    2014-01-01

    Single Nucleotide Polymorphisms (SNPs) are the most common genomic variations where only a single nucleotide differs between individuals. Individual SNPs and SNP profiles associated with diseases can be utilized as biological markers. But there is a need to determine the SNP subsets and patients' clinical data which is informative for the diagnosis. Data mining approaches have the highest potential for extracting the knowledge from genomic datasets and selecting the representative SNPs as well as most effective and informative clinical features for the clinical diagnosis of the diseases. In this study, we have applied one of the widely used data mining classification methodology: "decision tree" for associating the SNP biomarkers and significant clinical data with the Alzheimer's disease (AD), which is the most common form of "dementia". Different tree construction parameters have been compared for the optimization, and the most accurate tree for predicting the AD is presented.

  18. Endothelial dysfunction, vascular disease and stroke: the ARTICO study.

    Science.gov (United States)

    Roquer, J; Segura, T; Serena, J; Castillo, J

    2009-01-01

    Endothelial dysfunction is a fundamental step in the atherosclerotic disease process. Its presence is a risk factor for the development of clinical events, and may represent a marker of atherothrombotic burden. Also, endothelial dysfunction contributes to enhanced plaque vulnerability, may trigger plaque rupture, and favors thrombus formation. The assessment of endothelial vasomotion is a useful marker of atherosclerotic vascular disease. There are different methods to assess endothelial function: endothelium-dependent vasodilatation brachial flow-mediated dilation, cerebrovascular reactivity to L-arginine, and the determination of some biomarkers such as microalbuminuria, platelet function, and C-reactive protein. Endothelial dysfunction has been observed in stroke patients and has been related to stroke physiopathology, stroke subtypes, clinical severity and outcome. Resting ankle-brachial index (ABI) is also considered an indicator of generalized atherosclerosis, and a low ABI is associated with an increase in stroke incidence in the elderly. Despite all these data, there are no studies analyzing the predictive value of ABI for new cardiovascular events in patients after suffering an acute ischemic stroke. ARTICO is an ongoing prospective, observational, multicenter study being performed in 50 Spanish hospitals. The aim of the ARTICO study is to evaluate the prognostic value of a pathological ABI (ARTICO study will increase the knowledge of patient outcome after ischemic stroke and may help to improve our ability to detect patients at high risk of stroke recurrence or major cardiovascular events. (c) 2009 S. Karger AG, Basel.

  19. Innovative methods for the identification of predictive biomarker signatures in oncology: Application to bevacizumab

    Directory of Open Access Journals (Sweden)

    Paul Delmar

    2017-03-01

    Full Text Available Current methods for subgroup analyses of data collected from randomized clinical trials (RCTs may lead to false-positives from multiple testing, lack power to detect moderate but clinically meaningful differences, or be too simplistic in characterizing patients who may benefit from treatment. Herein, we present a general procedure based on a set of newly developed statistical methods for the identification and evaluation of complex multivariate predictors of treatment effect. Furthermore, we implemented this procedure to identify a subgroup of patients who may receive the largest benefit from bevacizumab treatment using a panel of 10 biomarkers measured at baseline in patients enrolled on two RCTs investigating bevacizumab in metastatic breast cancer. Data were collected from patients with human epidermal growth factor receptor 2 (HER2-negative (AVADO and HER2-positive (AVEREL metastatic breast cancer. We first developed a classification rule based on an estimated individual scoring system, using data from the AVADO study only. The classification rule takes into consideration a panel of biomarkers, including vascular endothelial growth factor (VEGF-A. We then classified the patients in the independent AVEREL study into patient groups according to “promising” or “not-promising” treatment benefit based on this rule and conducted a statistical analysis within these subgroups to compute point estimates, confidence intervals, and p-values for treatment effect and its interaction. In the group with promising treatment benefit in the AVEREL study, the estimated hazard ratio of bevacizumab versus placebo for progression-free survival was 0.687 (95% confidence interval [CI]: 0.462–1.024, p = 0.065, while in the not-promising group the hazard ratio (HR was 1.152 (95% CI: 0.526–2.524, p = 0.723. Using the median level of VEGF-A from the AVEREL study to divide the study population, then the HR becomes 0.711 (95% CI: 0.435–1.163, p = 0

  20. Microparticles provide a novel biomarker to predict severe clinical outcomes of dengue virus infection.

    Science.gov (United States)

    Punyadee, Nuntaya; Mairiang, Dumrong; Thiemmeca, Somchai; Komoltri, Chulaluk; Pan-Ngum, Wirichada; Chomanee, Nusara; Charngkaew, Komgrid; Tangthawornchaikul, Nattaya; Limpitikul, Wannee; Vasanawathana, Sirijitt; Malasit, Prida; Avirutnan, Panisadee

    2015-02-01

    Shedding of microparticles (MPs) is a consequence of apoptotic cell death and cellular activation. Low levels of circulating MPs in blood help maintain homeostasis, whereas increased MP generation is linked to many pathological conditions. Herein, we investigated the role of MPs in dengue virus (DENV) infection. Infection of various susceptible cells by DENV led to apoptotic death and MP release. These MPs harbored a viral envelope protein and a nonstructural protein 1 (NS1) on their surfaces. Ex vivo analysis of clinical specimens from patients with infections of different degrees of severity at multiple time points revealed that MPs generated from erythrocytes and platelets are two major MP populations in the circulation of DENV-infected patients. Elevated levels of red blood cell-derived MPs (RMPs) directly correlated with DENV disease severity, whereas a significant decrease in platelet-derived MPs was associated with a bleeding tendency. Removal by mononuclear cells of complement-opsonized NS1-anti-NS1 immune complexes bound to erythrocytes via complement receptor type 1 triggered MP shedding in vitro, a process that could explain the increased levels of RMPs in severe dengue. These findings point to the multiple roles of MPs in dengue pathogenesis. They offer a potential novel biomarker candidate capable of differentiating dengue fever from the more serious dengue hemorrhagic fever. Dengue is the most important mosquito-transmitted viral disease in the world. No vaccines or specific treatments are available. Rapid diagnosis and immediate treatment are the keys to achieve a positive outcome. Dengue virus (DENV) infection, like some other medical conditions, changes the level and composition of microparticles (MPs), tiny bag-like structures which are normally present at low levels in the blood of healthy individuals. This study investigated how MPs in culture and patients' blood are changed in response to DENV infection. Infection of cells led to programmed

  1. Predictive value of the National Institutes of Health Stroke Scale and the Mini-Mental State Examination for neurologic outcome after coronary artery bypass graft surgery.

    Science.gov (United States)

    Nussmeier, Nancy A; Miao, Yinghui; Roach, Gary W; Wolman, Richard L; Mora-Mangano, Christina; Fox, Mark; Szekely, Andrea; Tommasino, Concezione; Schwann, Nanette M; Mangano, Dennis T

    2010-04-01

    We intended to define the role of the National Institutes of Health Stroke Scale and the Mini-Mental State Examination in identifying adverse neurologic outcomes in a large international sample of patients undergoing cardiac surgery. We evaluated 4707 patients undergoing cardiac surgery with cardiopulmonary bypass at 72 centers in 17 countries between November 1996 and June 2000. Prespecified overt neurologic outcomes were categorized as type I (clinically diagnosed stroke, transient ischemic attack, encephalopathy, or coma) or type II (deterioration of intellectual function). The National Institutes of Health Stroke Scale and Mini-Mental State Examination were administered preoperatively and on postoperative day 3, 4, or 5. Receiver operating characteristic curves were plotted to determine the predictive value of worsening in National Institutes of Health Stroke Scale and Mini-Mental State Examination scores with respect to type I and II outcomes. The receiver operating characteristic area under the curve for changes in National Institutes of Health Stroke Scale score (n = 4620) was 0.89 for type I outcomes and 0.66 for type II outcomes. A 1-point worsening in National Institutes of Health Stroke Scale score provided excellent discrimination (86% specificity; 84% sensitivity) of type I outcomes. The receiver operating characteristic area under the curve for changes in Mini-Mental State Examination score (n = 4707) was 0.75 for type I outcomes and 0.71 for type II outcomes. A 2-point worsening in Mini-Mental State Examination score provided only fair discrimination (73% specificity; 62% sensitivity) of type II outcomes. We used baseline controls and postoperative worsening in National Institutes of Health Stroke Scale and Mini-Mental State Examination scores to predict both serious adverse neurologic outcome and deterioration of intellectual function. Our findings provide the only reference for evaluating these tests that are used in cardiac surgical clinical

  2. Evaluation of interleukin-6 and serotonin as biomarkers to predict response to fluoxetine.

    Science.gov (United States)

    Manoharan, Aarthi; Rajkumar, Ravi Philip; Shewade, Deepak Gopal; Sundaram, Rajan; Muthuramalingam, Avin; Paul, Abialbon

    2016-05-01

    Only 30% of major depressive disorder (MDD) patients achieve complete remission with a serotonergic antidepressant (selective serotonin reuptake inhibitor). We investigated the potential of serotonin (5-HT) and interleukin-6 (IL-6) to serve as functional biomarkers of fluoxetine response. Serum IL-6 and 5-HT were measured in 73 MDD patients (39 responders and 34 non-responders) pre- and 6 weeks post-treatment and in 44 normal controls with ELISA. Fluoxetine and norfluoxetine were measured using LC MS/MS. IL-6 levels were significantly higher in MDD patients when compared with controls (p Fluoxetine and norfluoxetine concentrations were not significantly different in responders and non-responders, and there was no correlation between fluoxetine concentrations and percentage reduction in 5-HT from week 0 to 6. 5-HT and IL-6 may not serve as useful markers of response to fluoxetine because of inconsistent results across different studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  3. IL-10 and socs3 Are Predictive Biomarkers of Dengue Hemorrhagic Fever

    Directory of Open Access Journals (Sweden)

    Lilian Karem Flores-Mendoza

    2017-01-01

    Full Text Available Background. Cytokines play important roles in the physiopathology of dengue infection; therefore, the suppressors of cytokine signaling (socs that control the type and timing of cytokine functions could be involved in the origin of immune alterations in dengue. Objective. To explore the association of cytokine and socs levels with disease severity in dengue patients. Methods. Blood samples of 48 patients with confirmed dengue infection were analyzed. Amounts of interleukins IL-2, IL-4, IL-6, and IL-10, interferon- (IFN- γ, and tumor necrosis factor- (TNF- α were quantified by flow cytometry, and the relative expression of socs1 and socs3 mRNA was quantified by real-time RT-PCR. Results. Increased levels of IL-10 and socs3 and lower expression of socs1 were found in patients with dengue hemorrhagic fever (DHF with respect to those with dengue fever (DF (p199.8-fold, socs1 (134 pg/ml have the highest sensitivity and specificity to discriminate between DF and DHF. Conclusion. Simultaneous changes in IL-10 and socs1/socs3 could be used as prognostic biomarkers of dengue severity.

  4. Adipose tissue and muscle attenuation as novel biomarkers predicting mortality in patients with extremity sarcomas

    International Nuclear Information System (INIS)

    Veld, Joyce; Vossen, Josephina A.; Torriani, Martin; Bredella, Miriam A.; De Amorim Bernstein, Karen; Halpern, Elkan F.

    2016-01-01

    To assess CT-attenuation of abdominal adipose tissue and psoas muscle as predictors of mortality in patients with sarcomas of the extremities. Our study was IRB approved and HIPAA compliant. The study group comprised 135 patients with history of extremity sarcoma (mean age: 53 ± 17 years) who underwent whole body PET/CT. Abdominal subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and psoas muscle attenuation (HU) was assessed on non-contrast, attenuation-correction CT. Clinical information including survival, tumour stage, sarcoma type, therapy and pre-existing comorbidities were recorded. Cox proportional hazard models were used to determine longitudinal associations between adipose tissue and muscle attenuation and mortality. There were 47 deaths over a mean follow-up period of 20 ± 17 months. Higher SAT and lower psoas attenuation were associated with increased mortality (p = 0.03 and p = 0.005, respectively), which remained significant after adjustment for age, BMI, sex, tumor stage, therapy, and comorbidities (p = 0.002 and p = 0.02, respectively). VAT attenuation was not associated with mortality. Attenuation of SAT and psoas muscle, assessed on non-contrast CT, are predictors of mortality in patients with extremity sarcomas, independent of other established prognostic factors, suggesting that adipose tissue and muscle attenuation could serve as novel biomarkers for mortality in patients with sarcomas. (orig.)

  5. Adipose tissue and muscle attenuation as novel biomarkers predicting mortality in patients with extremity sarcomas

    Energy Technology Data Exchange (ETDEWEB)

    Veld, Joyce; Vossen, Josephina A.; Torriani, Martin; Bredella, Miriam A. [Massachusetts General Hospital and Harvard Medical School, Division of Musculoskeletal Imaging and Intervention, Department of Radiology, Boston, MA (United States); De Amorim Bernstein, Karen [Massachusetts General Hospital and Harvard Medical School, Department of Radiation Oncology, Francis H Burr Proton Therapy Center, Boston, MA (United States); Halpern, Elkan F. [Massachusetts General Hospital and Harvard Medical School, Institute of Technology Assessment, Boston, MA (United States)

    2016-12-15

    To assess CT-attenuation of abdominal adipose tissue and psoas muscle as predictors of mortality in patients with sarcomas of the extremities. Our study was IRB approved and HIPAA compliant. The study group comprised 135 patients with history of extremity sarcoma (mean age: 53 ± 17 years) who underwent whole body PET/CT. Abdominal subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and psoas muscle attenuation (HU) was assessed on non-contrast, attenuation-correction CT. Clinical information including survival, tumour stage, sarcoma type, therapy and pre-existing comorbidities were recorded. Cox proportional hazard models were used to determine longitudinal associations between adipose tissue and muscle attenuation and mortality. There were 47 deaths over a mean follow-up period of 20 ± 17 months. Higher SAT and lower psoas attenuation were associated with increased mortality (p = 0.03 and p = 0.005, respectively), which remained significant after adjustment for age, BMI, sex, tumor stage, therapy, and comorbidities (p = 0.002 and p = 0.02, respectively). VAT attenuation was not associated with mortality. Attenuation of SAT and psoas muscle, assessed on non-contrast CT, are predictors of mortality in patients with extremity sarcomas, independent of other established prognostic factors, suggesting that adipose tissue and muscle attenuation could serve as novel biomarkers for mortality in patients with sarcomas. (orig.)

  6. Ciculating miRNA-21 as a Biomarker Predicts Polycystic Ovary Syndrome (PCOS) in Patients.

    Science.gov (United States)

    Jiang, Liyan; Li, Wei; Wu, Minmin; Cao, Sifan

    2015-01-01

    Polycystic ovary syndrome (PCOS) is characterized by hyperandrogenism, hyperinsulinemia, and infertility. In PCOS, abnormal regulation of relevant genes is required for follicular development. By binding to the 3' untranslated region (3'URT), microRNAs (miRNAs) are widely involved in posttranscriptional gene regulation. However, few studies have been conducted on circulating miRNA expression in PCOS. This study aims to describe altered expression of circulating miR-21 in PCOS. The expression of serum miRNAs of PCOS patients were explored using the TaqMan Low Density Array followed by individual quantitative reverse transcription polymerase chain reaction assays. The protein level of LATS1 was determined using Western blot. To validate whether miR-21 targeted LATS1, the luciferase assay was applied. In comparison with normal subjects, the circulating level of miRNA-21 was significantly enhanced in PCOS patients. In PCOS patients, the expression levels of MST1/2, LATS1/2, TAZ were much lower than the control subjects. Luciferase reporter assay revealed that LATS1 was a downstream target of miR-21. In comparison with normal subjects, serum miR-21 is obviously increased in PCOS patients. Through targeting LATS1, miR-21 could prompt PCOS progression and could act as a novel non-invasive biomarker for diagnosis of PCOS.

  7. Validation of risk stratification schemes for predicting stroke and thromboembolism in patients with atrial fibrillation: nationwide cohort study.

    Science.gov (United States)

    Olesen, Jonas Bjerring; Lip, Gregory Y H; Hansen, Morten Lock; Hansen, Peter Riis; Tolstrup, Janne Schurmann; Lindhardsen, Jesper; Selmer, Christian; Ahlehoff, Ole; Olsen, Anne-Marie Schjerning; Gislason, Gunnar Hilmar; Torp-Pedersen, Christian

    2011-01-31

    To evaluate the individual risk factors composing the CHADS(2) (Congestive heart failure, Hypertension, Age ≥ 75 years, Diabetes, previous Stroke) score and the CHA(2)DS(2)-VASc (CHA(2)DS(2)-Vascular disease, Age 65-74 years, Sex category) score and to calculate the capability of the schemes to predict thromboembolism. Registry based cohort study. Nationwide data on patients admitted to hospital with atrial fibrillation. Population All patients with atrial fibrillation not treated with vitamin K antagonists in Denmark in the period 1997-2006. Stroke and thromboembolism. Of 121,280 patients with non-valvular atrial fibrillation, 73,538 (60.6%) fulfilled the study inclusion criteria. In patients at "low risk" (score = 0), the rate of thromboembolism per 100 person years was 1.67 (95% confidence interval 1.47 to 1.89) with CHADS(2) and 0.78 (0.58 to 1.04) with CHA(2)DS(2)-VASc at one year's follow-up. In patients at "intermediate risk" (score = 1), this rate was 4.75 (4.45 to 5.07) with CHADS(2) and 2.01 (1.70 to 2.36) with CHA(2)DS(2)-VASc. The rate of thromboembolism depended on the individual risk factors composing the scores, and both schemes underestimated the risk associated with previous thromboembolic events. When patients were categorised into low, intermediate, and high risk groups, C statistics at 10 years' follow-up were 0.812 (0.796 to 0.827) with CHADS(2) and 0.888 (0.875 to 0.900) with CHA(2)DS(2)-VASc. The risk associated with a specific risk stratification score depended on the risk factors composing the score. CHA(2)DS(2)-VASc performed better than CHADS(2) in predicting patients at high risk, and those categorised as low risk by CHA(2)DS(2)-VASc were truly at low risk for thromboembolism.

  8. Multiphasic perfusion CT in acute middle cerebral artery ischemic stroke: prediction of final infarct volume and correlation with clinical outcome

    International Nuclear Information System (INIS)

    Yi, Chin A; Na, Dong Gyu; Ryoo, Jae Wook; Moon, Chan Hong; Byun, Hong Sik; Roh, Hong Gee; Moon, Won Jin; Lee, Kwang Ho; Lee, Soo Joo

    2002-01-01

    To assess the utility of multiphasic perfusion CT in the prediction of final infarct volume, and the relationship between lesion volume revealed by CT imaging and clinical outcome in acute ischemic stroke patients who have not undergone thrombolytic therapy. Thirty-five patients underwent multiphasic perfusion CT within six hours of stroke onset. After baseline unenhanced helical CT scanning, contrast-enhanced CT scans were obtained 20, 34, 48, and 62 secs after the injection of 90 mL contrast medium at a rate of 3 mL/sec. CT peak and total perfusion maps were obtained from serial CT images, and the initial lesion volumes revealed by CT were compared with final infarct volumes and clinical scores. Overall, the lesion volumes seen on CT peak perfusion maps correlated most strongly with final infarct volumes (R2=0.819, p<0.001, slope of regression line=1.016), but individual data showed that they were less than final infarct volume in 31.4% of patients. In those who showed early clinical improvement (n=6), final infarct volume tended to be overestimated by CT peak perfusion mapping and only on total perfusion maps was there significant correlation between lesion volume and final infarct volume (R2=0.854, p=0.008). The lesion volumes depicted by CT maps showed moderate correlation with baseline clinical scores and clinical outcomes (R=0.445-0.706, p≤0.007). CT peak perfusion maps demonstrate strong correlation between lesion volume and final infarct volume, and accurately predict final infarct volume in about two-thirds of the 35 patients. The lesion volume seen on CT maps shows moderate correlation with clinical outcome

  9. Prediction of infarction and reperfusion in stroke by flow- and volume-weighted collateral signal in MR angiography.

    Science.gov (United States)

    Ernst, M; Forkert, N D; Brehmer, L; Thomalla, G; Siemonsen, S; Fiehler, J; Kemmling, A

    2015-02-01

    In proximal anterior circulation occlusive strokes, collateral flow is essential for good outcome. Collateralized vessel intensity in TOF- and contrast-enhanced MRA is variable due to different acquisition methods. Our purpose was to quantify collateral supply by using flow-weighted signal in TOF-MRA and blood volume-weighted signal in contrast-enhanced MRA to determine each predictive contribution to tissue infarction and reperfusion. Consecutively (2009-2013), 44 stroke patients with acute proximal anterior circulation occlusion met the inclusion criteria with TOF- and contrast-enhanced MRA and penumbral imaging. Collateralized vessels in the ischemic hemisphere were assessed by TOF- and contrast-enhanced MRA using 2 methods: 1) visual 3-point collateral scoring, and 2) collateral signal quantification by an arterial atlas-based collateral index. Collateral measures were tested by receiver operating characteristic curve and logistic regression against 2 imaging end points of tissue-outcome: final infarct volume and percentage of penumbra saved. Visual collateral scores on contrast-enhanced MRA but not TOF were significantly higher in patients with good outcome. Visual collateral scoring on contrast-enhanced MRA was the best rater-based discriminator for final infarct volume 50% (area under the curve, 0.67; P = .04). Atlas-based collateral index of contrast-enhanced MRA was the overall best independent discriminator for final infarct volume of collateral index combining the signal of TOF- and contrast-enhanced MRA was the overall best discriminator for effective reperfusion (percentage of penumbra saved >50%; area under the curve, 0.89; P collateral assessment, TOF- and contrast-enhanced MRA both contain predictive signal information for penumbral reperfusion. This could improve risk stratification in further studies. © 2015 by American Journal of Neuroradiology.

  10. Collateral circulation on perfusion-computed tomography-source images predicts the response to stroke intravenous thrombolysis.

    Science.gov (United States)

    Calleja, A I; Cortijo, E; García-Bermejo, P; Gómez, R D; Pérez-Fernández, S; Del Monte, J M; Muñoz, M F; Fernández-Herranz, R; Arenillas, J F

    2013-05-01

    Perfusion-computed tomography-source images (PCT-SI) may allow a dynamic assessment of leptomeningeal collateral arteries (LMC) filling and emptying in middle cerebral artery (MCA) ischaemic stroke. We described a regional LMC scale on PCT-SI and hypothesized that a higher collateral score would predict a better response to intravenous (iv) thrombolysis. We studied consecutive ischaemic stroke patients with an acute MCA occlusion documented by transcranial Doppler/transcranial color-coded duplex, treated with iv thrombolysis who underwent PCT prior to treatment. Readers evaluated PCT-SI in a blinded fashion to assess LMC within the hypoperfused MCA territory. LMC scored as follows: 0, absence of vessels; 1, collateral supply filling ≤ 50%; 2, between> 50% and < 100%; 3, equal or more prominent when compared with the unaffected hemisphere. The scale was divided into good (scores 2-3) vs. poor (scores 0-1) collaterals. The predetermined primary end-point was a good 3-month functional outcome, while early neurological recovery, transcranial duplex-assessed 24-h MCA recanalization, 24-h hypodensity volume and hemorrhagic transformation were considered secondary end-points. Fifty-four patients were included (55.5% women, median NIHSS 10), and 4-13-23-14 patients had LMC score (LMCs) of 0-1-2-3, respectively. The probability of a good long-term outcome augmented gradually with increasing LMCs: (0) 0%; (1) 15.4%; (2) 65.2%; (3) 64.3%, P = 0.004. Good-LMCs was independently associated with a good outcome [OR 21.02 (95% CI 2.23-197.75), P = 0.008]. Patients with good LMCs had better early neurological recovery (P = 0.001), smaller hypodensity volumes (P < 0.001) and a clear trend towards a higher recanalization rate. A higher degree of LMC assessed by PCT-SI predicts good response to iv thrombolysis in MCA ischaemic stroke patients. © 2012 The Author(s) European Journal of Neurology © 2012 EFNS.

  11. Self-perceived quality of life predicts mortality risk better than a multi-biomarker panel, but the combination of both does best

    Directory of Open Access Journals (Sweden)

    Nauck Matthias

    2011-07-01

    Full Text Available Abstract Background Associations between measures of subjective health and mortality risk have previously been shown. We assessed the impact and comparative predictive performance of a multi-biomarker panel on this association. Methods Data from 4,261 individuals aged 20-79 years recruited for the population-based Study of Health in Pomerania was used. During an average 9.7 year follow-up, 456 deaths (10.7% occurred. Subjective health was assessed by SF-12 derived physical (PCS-12 and mental component summaries (MCS-12, and a single-item self-rated health (SRH question. We implemented Cox proportional-hazards regression models to investigate the association of subjective health with mortality and to assess the impact of a combination of 10 biomarkers on this association. Variable selection procedures were used to identify a parsimonious set of subjective health measures and biomarkers, whose predictive ability was compared using receiver operating characteristic (ROC curves, C-statistics, and reclassification methods. Results In age- and gender-adjusted Cox models, poor SRH (hazard ratio (HR, 2.07; 95% CI, 1.34-3.20 and low PCS-12 scores (lowest vs. highest quartile: HR, 1.75; 95% CI, 1.31-2.33 were significantly associated with increased risk of all-cause mortality; an association independent of various covariates and biomarkers. Furthermore, selected subjective health measures yielded a significantly higher C-statistic (0.883 compared to the selected biomarker panel (0.872, whereas a combined assessment showed the highest C-statistic (0.887 with a highly significant integrated discrimination improvement of 1.5% (p Conclusion Adding biomarker information did not affect the association of subjective health measures with mortality, but significantly improved risk stratification. Thus, a combined assessment of self-reported subjective health and measured biomarkers may be useful to identify high-risk individuals for intensified monitoring.

  12. Cancer predictive value of cytogenetic markers used in occupational health surveillance programs. A report from an ongoing study by the European Study Group on Cytogenetic Biomarkers and Health

    Energy Technology Data Exchange (ETDEWEB)

    Hagmar, Lars; Stroemberg, Ulf; Mikoczy, Zoli; Tinnerberg, Hakan; Skerfving, Staffan [Department of Occupational and Environmental Medicine, Lund University, S-221 85 Lund (Sweden); Bonassi, Stefano; Lando, Cecilia [Department of Environmental Epidemiology, Istituto Nazionale per la Ricerca sul Cancro, Viale Benedetto XV, I-1016132 Genoa (Italy); Hansteen, Inger-Lise [Department of Occupational Medicine, Telemark Central Hospital, N-3710 Skien (Norway); Montagud, Alicia Huici [Centro Nacional de Condiciones de Trabajo, Instituto Nacional de Seguridad e Higiene en el Trabajo, Dulcet 2-10, ES-08034 Barcelona (Spain); Knudsen, Lisbeth [National Institute of Occupational Health, Lersoe Parkalle 105, DK-2100 Copenhagen (Denmark); Norppa, Hannu [Finnish Institute of Occupational Health, Topeliuksekatu 41 aA, FIN-00250 Helsinki (Finland); Reuterwall, Christina [National Institute of Work Life, S-171 84 Solna (Sweden); Broegger, Anton [Norwegian Radium Hospital, Oslo (Norway); Forni, Alessandra [Istituto di Medicina del Lavoro Clinica del Lavoro `L. Devoto`, Milan (Italy); Hoegstedt, Benkt [Department of Occupational Medicine, Central Hospital, Halmstad (Sweden); Lambert, Bo [Department of Environmental Medicine, Centre for Nutrition and Toxicology, Karolinska Institute, Stockholm (Sweden); Mitelman, Felix [Department of Clinical Genetics, Lund University, Lund (Sweden); Nordenson, Ingrid [National Institute of Work Life, Umea (Sweden); Salomaa, Sisko [Finnish Center for Radiation and Nuclear Safety, Helsinki (Finland)

    1998-09-20

    The cytogenetic endpoints in peripheral blood lymphocytes: chromosomal aberrations (CA), sister chromatid exchange (SCE) and micronuclei (MN) are established biomarkers of exposure for mutagens or carcinogens in the work environment. However, it is not clear whether these biomarkers also may serve as biomarkers for genotoxic effects which will result in an enhanced cancer risk. In order to assess this problem, Nordic and Italian cohorts were established, and preliminary results from these two studies indicated a predictive value of CA frequency for cancer risk, whereas no such associations were observed for SCE or MN. A collaborative study between the Nordic and Italian research groups, will enable a more thorough evaluation of the cancer predictivity of the cytogenetic endpoints. We here report on the establishment of a joint data base comprising 5271 subjects, examined 1965-1988 for at least one cytogenetic biomarker. Totally, 3540 subjects had been examined for CA, 2702 for SCE and 1496 for MN. These cohorts have been followed-up with respect to subsequent cancer mortality or cancer incidence, and the expected values have been calculated from rates derived from the general populations in each country. Stratified cohort analyses will be performed with respect to the levels of the cytogenetic biomarkers. The importance of potential effect modifiers such as gender, age at test, and time since test, will be evaluated using Poisson regression models. The remaining two potential effect modifiers, occupational exposures and smoking, will be assessed in a case-referent study within the study base

  13. Cancer predictive value of cytogenetic markers used in occupational health surveillance programs. A report from an ongoing study by the European Study Group on Cytogenetic Biomarkers and Health

    International Nuclear Information System (INIS)

    Hagmar, Lars; Stroemberg, Ulf; Mikoczy, Zoli; Tinnerberg, Hakan; Skerfving, Staffan; Bonassi, Stefano; Lando, Cecilia; Hansteen, Inger-Lise; Montagud, Alicia Huici; Knudsen, Lisbeth; Norppa, Hannu; Reuterwall, Christina; Broegger, Anton; Forni, Alessandra; Hoegstedt, Benkt; Lambert, Bo; Mitelman, Felix; Nordenson, Ingrid; Salomaa, Sisko

    1998-01-01

    The cytogenetic endpoints in peripheral blood lymphocytes: chromosomal aberrations (CA), sister chromatid exchange (SCE) and micronuclei (MN) are established biomarkers of exposure for mutagens or carcinogens in the work environment. However, it is not clear whether these biomarkers also may serve as biomarkers for genotoxic effects which will result in an enhanced cancer risk. In order to assess this problem, Nordic and Italian cohorts were established, and preliminary results from these two studies indicated a predictive value of CA frequency for cancer risk, whereas no such associations were observed for SCE or MN. A collaborative study between the Nordic and Italian research groups, will enable a more thorough evaluation of the cancer predictivity of the cytogenetic endpoints. We here report on the establishment of a joint data base comprising 5271 subjects, examined 1965-1988 for at least one cytogenetic biomarker. Totally, 3540 subjects had been examined for CA, 2702 for SCE and 1496 for MN. These cohorts have been followed-up with respect to subsequent cancer mortality or cancer incidence, and the expected values have been calculated from rates derived from the general populations in each country. Stratified cohort analyses will be performed with respect to the levels of the cytogenetic biomarkers. The importance of potential effect modifiers such as gender, age at test, and time since test, will be evaluated using Poisson regression models. The remaining two potential effect modifiers, occupational exposures and smoking, will be assessed in a case-referent study within the study base

  14. A study on the influence of corona on currents and electromagnetic fields predicted by a nonlinear lightning return-stroke model

    Science.gov (United States)

    De Conti, Alberto; Silveira, Fernando H.; Visacro, Silvério

    2014-05-01

    This paper investigates the influence of corona on currents and electromagnetic fields predicted by a return-stroke model that represents the lightning channel as a nonuniform transmission line with time-varying (nonlinear) resistance. The corona model used in this paper allows the calculation of corona currents as a function of the radial electric field in the vicinity of the channel. A parametric study is presented to investigate the influence of corona parameters, such as the breakdown electric field and the critical electric field for the stable propagation of streamers, on predicted currents and electromagnetic fields. The results show that, regardless of the assumed corona parameters, the incorporation of corona into the nonuniform and nonlinear transmission line model under investigation modifies the model predictions so that they consistently reproduce most of the typical features of experimentally observed lightning electromagnetic fields and return-stroke speed profiles. In particular, it is shown that the proposed model leads to close vertical electric fields presenting waveforms, amplitudes, and decay with distance in good agreement with dart leader electric field changes measured in triggered lightning experiments. A comparison with popular engineering return-stroke models further confirms the model's ability to predict consistent electric field waveforms in the close vicinity of the channel. Some differences observed in the field amplitudes calculated with the different models can be related to the fact that current distortion, while present in the proposed model, is ultimately neglected in the considered engineering return-stroke models.

  15. Stroke Treatments

    Science.gov (United States)

    ... Stroke Association.org Professionals for Stroke Association.org Shop for Stroke Association.org Support for Stroke Association. ... works by dissolving the clot and improving blood flow to the part of the brain being deprived ...

  16. Molecular Profiling of Refractory Adrenocortical Cancers and Predictive Biomarkers to Therapy

    Directory of Open Access Journals (Sweden)

    Sherri Z. Millis

    2015-01-01

    Full Text Available Purpose Current first-line chemotherapy for patients with metastatic adrenocortical cancer (ACC includes doxorubicin, etoposide, cisplatin, and mitotane with a reported response rate of only 23.2%. New therapeutic leads for patients with refractory tumors are needed; there is no standard second-line treatment. Methods Samples from 135 ACC tumors were analyzed by immunohistochemistry, in situ hybridization (FISH or CISH, and/or gene sequencing at a single commercial reference laboratory (Caris Life Sciences to identify markers associated with drug sensitivity and resistance. Results Overexpression of proteins related to demonstrated chemotherapy sensitivity or resistance included topoisomerase 1, progesterone receptor, and topoisomerase 2-alpha in 46%, 63%, and 42% of cases, respectively. Loss of excision repair cross-complementary group 1 (ERCC1, phosophatase and tensin homolog, O(6-methylguanine-methyltransferase, and ribonucleotide reductase M1 (RRM1 was identified in 56%, 59%, 71%, and 58% of cases, respectively. Other aberrations included overexpression of programmed death-ligand 1 or programmed cell death protein 1 tumor-infiltrating lymphocytes in >40% of cases. In all, 35% of cases had a mutation in the canonical Wnt signaling pathway (either CTNNB1 or APC and 48% had a mutation in TP53. No other genomic alterations were identified. Conclusion Biomarker alterations in ACC may be used to direct therapies, including recommendations for and potential resistance of some patients to traditional chemotherapies, which may explain the low response rate in the unselected population. Limited outcomes data support the use of mitotane and platinum therapies for patients with low levels of the proteins RRM1 and ERCC1.

  17. Identification of CREB3L1 as a Biomarker Predicting Doxorubicin Treatment Outcome.

    Directory of Open Access Journals (Sweden)

    Bray Denard

    Full Text Available Doxorubicin has been shown to inhibit proliferation of cancer cells through proteolytic activation of CREB3L1 (cAMP response element binding protein 3-like 1, a transcription factor synthesized as a membrane-bound precursor. Upon doxorubicin treatment, CREB3L1 is cleaved so that the N-terminal domain of the protein can reach the nucleus where it activates transcription of genes that inhibit cell proliferation. These results suggest that the level of CREB3L1 in cancer cells may determine their sensitivity to doxorubicin.Mice transplanted with 6 lines of renal cell carcinoma (RCC were injected with doxorubicin to observe the effect of the chemotherapy on tumor growth. Immunohistochemistry and bioinformatics analyses were performed to compare CREB3L1 levels in types of cancer known to respond to doxorubicin versus those resistant to doxorubicin.Higher levels of CREB3L1 protein are correlated with increased doxorubicin sensitivity of xenograft RCC tumors (p = 0.017 by Pearson analysis. From patient tumor biopsies we analyzed, CREB3L1 was expressed in 19% of RCC, which is generally resistant to doxorubicin, but in 70% of diffuse large B-cell lymphoma that is sensitive to doxorubicin. Doxorubicin is used as the standard treatment for cancers that express the highest levels of CREB3L1 such as osteosarcoma and malignant fibrous histiocytoma but is not generally used to treat those that express the lowest levels of CREB3L1 such as RCC.Identification of CREB3L1 as the biomarker for doxorubicin sensitivity may markedly improve the doxorubicin response rate by applying doxorubicin only to patients with cancers expressing CREB3L1.

  18. Biomarkers improve mortality prediction by prognostic scales in community-acquired pneumonia.

    Science.gov (United States)

    Menéndez, R; Martínez, R; Reyes, S; Mensa, J; Filella, X; Marcos, M A; Martínez, A; Esquinas, C; Ramirez, P; Torres, A

    2009-07-01

    Prognostic scales provide a useful tool to predict mortality in community-acquired pneumonia (CAP). However, the inflammatory response of the host, crucial in resolution and outcome, is not included in the prognostic scales. The aim of this study was to investigate whether information about the initial inflammatory cytokine profile and markers increases the accuracy of prognostic scales to predict 30-day mortality. To this aim, a prospective cohort study in two tertiary care hospitals was designed. Procalcitonin (PCT), C-reactive protein (CRP) and the systemic cytokines tumour necrosis factor alpha (TNFalpha) and interleukins IL6, IL8 and IL10 were measured at admission. Initial severity was assessed by PSI (Pneumonia Severity Index), CURB65 (Confusion, Urea nitrogen, Respiratory rate, Blood pressure, > or = 65 years of age) and CRB65 (Confusion, Respiratory rate, Blood pressure, > or = 65 years of age) scales. A total of 453 hospitalised CAP patients were included. The 36 patients who died (7.8%) had significantly increased levels of IL6, IL8, PCT and CRP. In regression logistic analyses, high levels of CRP and IL6 showed an independent predictive value for predicting 30-day mortality, after adjustment for prognostic scales. Adding CRP to PSI significantly increased the area under the receiver operating characteristic curve (AUC) from 0.80 to 0.85, that of CURB65 from 0.82 to 0.85 and that of CRB65 from 0.79 to 0.85. Adding IL6 or PCT values to CRP did not significantly increase the AUC of any scale. When using two scales (PSI and CURB65/CRB65) and CRP simultaneously the AUC was 0.88. Adding CRP levels to PSI, CURB65 and CRB65 scales improves the 30-day mortality prediction. The highest predictive value is reached with a combination of two scales and CRP. Further validation of that improvement is needed.

  19. A three-protein biomarker panel assessed in diagnostic tissue predicts death from prostate cancer for men with localized disease

    International Nuclear Information System (INIS)

    Severi, Gianluca; FitzGerald, Liesel M; Muller, David C; Pedersen, John; Longano, Anthony; Southey, Melissa C; Hopper, John L; English, Dallas R; Giles, Graham G; Mills, John

    2014-01-01

    Only a minority of prostate cancers lead to death. Because no tissue biomarkers of aggressiveness other than Gleason score are available at diagnosis, many nonlethal cancers are treated aggressively. We evaluated whether a panel of biomarkers, associated with a range of disease outcomes in previous studies, could predict death from prostate cancer for men with localized disease. Using a case-only design, subjects were identified from three Australian epidemiological studies. Men who had died of their disease, “cases” (N = 83), were matched to “referents” (N = 232), those who had not died of prostate cancer, using incidence density sampling. Diagnostic tissue was retrieved to assess expression of AZGP1, MUC1, NKX3.1, p53, and PTEN by semiquantitative immunohistochemistry (IHC). Poisson regression was used to estimate mortality rate ratios (MRRs) adjusted for age, Gleason score, and stage and to estimate survival probabilities. Expression of MUC1 and p53 was associated with increased mortality (MRR 2.51, 95% CI 1.14–5.54, P = 0.02 and 3.08, 95% CI 1.41–6.95, P = 0.005, respectively), whereas AZGP1 expression was associated with decreased mortality (MRR 0.44, 95% CI 0.20–0.96, P = 0.04). Analyzing all markers under a combined model indicated that the three markers were independent predictors of prostate cancer death and survival. For men with localized disease at diagnosis, assessment of AZGP1, MUC1, and p53 expression in diagnostic tissue by IHC could potentially improve estimates of risk of dying from prostate cancer based only on Gleason score and clinical stage

  20. Development and validation of a Luminex assay for detection of a predictive biomarker for PROSTVAC-VF therapy

    Science.gov (United States)

    Lucas, Julie L.; Tacheny, Erin A.; Ferris, Allison; Galusha, Michelle; Srivastava, Apurva K.; Ganguly, Aniruddha; Williams, P. Mickey; Sachs, Michael C.; Thurin, Magdalena; Tricoli, James V.; Ricker, Winnie; Gildersleeve, Jeffrey C.

    2017-01-01

    Cancer therapies can provide substantially improved survival in some patients while other seemingly similar patients receive little or no benefit. Strategies to identify patients likely to respond well to a given therapy could significantly improve health care outcomes by maximizing clinical benefits while reducing toxicities and adverse effects. Using a glycan microarray assay, we recently reported that pretreatment serum levels of IgM specific to blood group A trisaccharide (BG-Atri) correlate positively with overall survival of cancer patients on PROSTVAC-VF therapy. The results suggested anti-BG-Atri IgM measured prior to treatment could serve as a biomarker for identifying patients likely to benefit from PROSTVAC-VF. For continued development and clinical application of serum IgM specific to BG-Atri as a predictive biomarker, a clinical assay was needed. In this study, we developed and validated a Luminex-based clinical assay for measuring serum IgM specific to BG-Atri. IgM levels were measured with the Luminex assay and compared to levels measured using the microarray for 126 healthy individuals and 77 prostate cancer patients. This assay provided reproducible and consistent results with low %CVs, and tolerance ranges were established for the assay. IgM levels measured using the Luminex assay were found to be highly correlated to the microarray results with R values of 0.93–0.95. This assay is a Laboratory Developed Test (LDT) and is suitable for evaluating thousands of serum samples in CLIA certified laboratories that have validated the assay. In addition, the study demonstrates that discoveries made using neoglycoprotein-based microarrays can be readily migrated to a clinical assay. PMID:28771597

  1. Frequencies of circulating B- and T-lymphocytes as indicators for stroke outcomes

    Directory of Open Access Journals (Sweden)

    Wang Y

    2017-10-01

    Full Text Available Yanling Wang,1 Jihong Liu,1 Xuemei Wang,1 Zongjian Liu,2 Fengwu Li,1 Fenghua Chen,3 Xiaokun Geng,1 Zhili Ji,2 Huishan Du,1 Xiaoming Hu1,3 1Department of Neurology, China-America Institute of Neuroscience, 2Central Laboratory, Beijing Luhe Hospital, Capital Medical University, Beijing, People’s Republic of China; 3Department of Neurology, Pittsburgh Institute of Brain Disorders and Recovery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA Background: Stroke has high mortality and morbidity. Biomarkers are required for to predict stroke outcomes, which could help clinicians to provide rationale approaches for patient management. The dynamic changes in circulating immune cells have been reported in stroke patients and animal models of stroke.Aim: The aim of this study was to explore biomarkers to predict stroke outcomes by investigating the relationship between the frequencies of circulating immune cells and stroke outcomes.Methods: In all, 50 acute ischemic stroke (AIS patients were enrolled. Their blood samples were collected upon hospital admission and on day 1 and day 7 after stroke, and the leukocyte subsets were analyzed by flow cytometry. The dynamic changes in some types of immune cells in the AIS course and their correlation with clinical parameters were analyzed. Blood samples from 123 age- and gender-matched healthy subjects were used as controls.Results: The proportions of T-lymphocytes and NK cells in stroke patients were significantly lower than in healthy controls. The frequencies of B- and T-lymphocytes were negatively correlated with stroke severity at onset, including neurological deficits as assessed by National Institutes of Health Stroke Scale (NIHSS, and infarct volume as measured by the diffusion-weighted images (DWIs of magnetic resonance (MR. Logistic regression analysis showed that modified Rankin scale (mRs scores, a score system for the long-term neurological dysfunctions, were negatively correlated

  2. Proteomic biomarkers predicting lymph node involvement in serum of cervical cancer patients. Limitations of SELDI-TOF MS

    Directory of Open Access Journals (Sweden)

    Van Gorp Toon

    2012-06-01

    Full Text Available Abstract Background Lymph node status is not part of the staging system for cervical cancer, but provides important information for prognosis and treatment. We investigated whether lymph node status can be predicted with proteomic profiling. Material & methods Serum samples of 60 cervical cancer patients (FIGO I/II were obtained before primary treatment. Samples were run through a HPLC depletion column, eliminating the 14 most abundant proteins ubiquitously present in serum. Unbound fractions were concentrated with spin filters. Fractions were spotted onto CM10 and IMAC30 surfaces and analyzed with surface-enhanced laser desorption time of flight (SELDI-TOF mass spectrometry (MS. Unsupervised peak detection and peak clustering was performed using MASDA software. Leave-one-out (LOO validation for weighted Least Squares Support Vector Machines (LSSVM was used for prediction of lymph node involvement. Other outcomes were histological type, lymphvascular space involvement (LVSI and recurrent disease. Results LSSVM models were able to determine LN status with a LOO area under the receiver operating characteristics curve (AUC of 0.95, based on peaks with m/z values 2,698.9, 3,953.2, and 15,254.8. Furthermore, we were able to predict LVSI (AUC 0.81, to predict recurrence (AUC 0.92, and to differentiate between squamous carcinomas and adenocarcinomas (AUC 0.88, between squamous and adenosquamous carcinomas (AUC 0.85, and between adenocarcinomas and adenosquamous carcinomas (AUC 0.94. Conclusions Potential markers related with lymph node involvement were detected, and protein/peptide profiling support differentiation between various subtypes of cervical cancer. However, identification of the potential biomarkers was hampered by the technical limitations of SELDI-TOF MS.

  3. Prediction of early recurrent thromboembolic event and major bleeding in patients with acute stroke and atrial fibrillation by a risk stratification schema: the ALESSA score study

    OpenAIRE

    Paciaroni, Maurizio; Agnelli, Giancarlo; Caso, Valeria; Tsivgoulis, Georgios; Furie, Karen L; Tadi, Prasanna; Becattini, Cecilia; Falocci, Nicola; Zedde, Marialuisa; Abdul-Rahim, Azmil H.; Lees, Kennedy R.; Alberti, Andrea; Venti, Michele; Acciarresi, Monica; D'Amore, Cataldo

    2017-01-01

    Background and Purposes—This study was designed to derive and validate a score to predict early ischemic events and major bleedings after an acute ischemic stroke in patients with atrial fibrillation.\\ud \\ud Methods—The derivation cohort consisted of 854 patients with acute ischemic stroke and atrial fibrillation included in prospective series between January 2012 and March 2014. Older age (hazard ratio 1.06 for each additional year; 95% confidence interval, 1.00–1.11) and severe atrial enlar...

  4. Application of cardiovascular disease risk prediction models and the relevance of novel biomarkers to risk stratification in Asian Indians.

    Science.gov (United States)

    Kanjilal, S; Rao, V S; Mukherjee, M; Natesha, B K; Renuka, K S; Sibi, K; Iyengar, S S; Kakkar, Vijay V

    2008-01-01

    The increasing pressure on health resources has led to the emergence of risk assessment as an essential tool in the management of cardiovascular disease (CVD). Concern exists regarding the validity of their generalization to all populations. Existing risk scoring models do not incorporate emerging 'novel' risk factors. In this context, the aim of the study was to examine the relevance of British, European, and Framingham predictive CVD risk scores to the asymptomatic high risk Indian population. Blood samples drawn from the participants were analyzed for various 'traditional' and 'novel' biomarkers, and their CVD risk factor profiling was also done. The Framingham model defined only 5% of the study cohort to be at high risk, which appears to be an underestimation of CVD risk in this genetically predisposed population. These subjects at high risk had significantly elevated levels of lipid, pro-inflammatory, pro-thrombotic, and serological markers. It is more relevant to develop risk predictive scores for application to the Indian population. This study substantiates the argument that alternative approaches to risk stratification are required in order to make them more adaptable and applicable to different populations with varying risk factor and disease patterns.

  5. Predicting prostate biopsy outcome: prostate health index (phi) and prostate cancer antigen 3 (PCA3) are useful biomarkers.

    Science.gov (United States)

    Ferro, Matteo; Bruzzese, Dario; Perdonà, Sisto; Mazzarella, Claudia; Marino, Ada; Sorrentino, Alessandra; Di Carlo, Angelina; Autorino, Riccardo; Di Lorenzo, Giuseppe; Buonerba, Carlo; Altieri, Vincenzo; Mariano, Angela; Macchia, Vincenzo; Terracciano, Daniela

    2012-08-16

    Indication for prostate biopsy is presently mainly based on prostate-specific antigen (PSA) serum levels and digital-rectal examination (DRE). In view of the unsatisfactory accuracy of these two diagnostic exams, research has focused on novel markers to improve pre-biopsy prostate cancer detection, such as phi and PCA3. The purpose of this prospective study was to assess the diagnostic accuracy of phi and PCA3 for prostate cancer using biopsy as gold standard. Phi index (Beckman coulter immunoassay), PCA3 score (Progensa PCA3 assay) and other established biomarkers (tPSA, fPSA and %fPSA) were assessed before a 18-core prostate biopsy in a group of 251 subjects at their first biopsy. Values of %p2PSA and phi were significantly higher in patients with PCa compared with PCa-negative group (pphi and PCA3 are predictive of malignancy. In conclusion, %p2PSA, phi and PCA3 may predict a diagnosis of PCa in men undergoing their first prostate biopsy. PCA3 score is more useful in discriminating between HGPIN and non-cancer. Copyright © 2012 Elsevier B.V. All rights reserved.

  6. Inflammation biomarkers and mortality prediction in patients with type 2 diabetes (ZODIAC-27)

    NARCIS (Netherlands)

    Landman, Gijs W. D.; Kleefstra, Nanne; Groenier, Klaas H.; Bakker, Stephan J. L.; Groeneveld, Geert H.; Bilo, Henk J. G.; van Hateren, Kornelis J. J.

    Background: C-reactive protein (CRP), procalcitonin (PCT) and pro-adrenomedullin (MR-proADM) are inflammation markers associated with long-term mortality risk. We compared the associations and predictive capacities of CRP, PCT and MR-proADM with cardiovascular and all-cause mortality in patients

  7. Registration of acute stroke

    DEFF Research Database (Denmark)

    Wildenschild, Cathrine; Mehnert, Frank; Thomsen, Reimar Wernich

    2014-01-01

    BACKGROUND: The validity of the registration of patients in stroke-specific registries has seldom been investigated, nor compared with administrative hospital discharge registries. The objective of this study was to examine the validity of the registration of patients in a stroke-specific registry...... (The Danish Stroke Registry [DSR]) and a hospital discharge registry (The Danish National Patient Registry [DNRP]). METHODS: Assuming that all patients with stroke were registered in either the DSR, DNRP or both, we first identified a sample of 75 patients registered with stroke in 2009; 25 patients...... in the DSR, 25 patients in the DNRP, and 25 patients registered in both data sources. Using the medical record as a gold standard, we then estimated the sensitivity and positive predictive value of a stroke diagnosis in the DSR and the DNRP. Secondly, we reviewed 160 medical records for all potential stroke...

  8. Enlarged pulmonary artery is predicted by vascular injury biomarkers and is associated with WTC-Lung Injury in exposed fire fighters: a case–control study

    Science.gov (United States)

    Schenck, Edward J; Echevarria, Ghislaine C; Girvin, Francis G; Kwon, Sophia; Comfort, Ashley L; Rom, William N; Prezant, David J; Weiden, Michael D; Nolan, Anna

    2014-01-01

    Objectives We hypothesise that there is an association between an elevated pulmonary artery/aorta (PA/A) and World Trade Center-Lung Injury (WTC-LI). We assessed if serum vascular disease biomarkers were predictive of an elevated PA/A. Design Retrospective case-cohort analysis of thoracic CT scans of WTC-exposed firefighters who were symptomatic between 9/12/2001 and 3/10/2008. Quantification of vascular-associated biomarkers from serum collected within 200 days of exposure. Setting Urban tertiary care centre and occupational healthcare centre. Participants Male never-smoking firefighters with accurate pre-9/11 forced expiratory volume in 1 s (FEV1) ≥75%, serum sampled ≤200 days of exposure was the baseline cohort (n=801). A subcohort (n=97) with available CT scans and serum biomarkers was identified. WTC-LI was defined as FEV1≤77% at the subspecialty pulmonary evaluation (n=34) and compared with controls (n=63) to determine the associated PA/A ratio. The subcohort was restratified based on PA/A≥0.92 (n=38) and PA/A<0.92(n=59) to determine serum vascular biomarkers that were predictive of this vasculopathy. Outcome measures The primary outcome of this study was to identify a PA/A ratio in a cohort of individuals exposed to WTC dust that was associated with WTC-LI. The secondary outcome was to identify serum biomarkers predictive of the PA/A ratio using logistic regression. Results PA/A≥0.92 was associated with WTC-LI, OR of 4.02 (95% CI 1.21 to 13.41; p=0.023) when adjusted for exposure, body mass index and age at CT. Elevated macrophage derived chemokine and soluble endothelial selectin were predictive of PA/A≥0.92, (OR, 95% CI 2.08, 1.05 to 4.11, p=0.036; 1.33, 1.06 to 1.68, p=0.016, respectively), while the increased total plasminogen activator inhibitor 1 was predictive of not having PA/A≥0.92 (OR 0.88, 0.79 to 0.98; p=0.024). Conclusions Elevated PA/A was associated with WTC-LI. Development of an elevated PA/A was predicted by biomarkers of

  9. Blood biomarkers are helpful in the prediction of response to chemoradiation in rectal cancer: A prospective, hypothesis driven study on patients with locally advanced rectal cancer

    International Nuclear Information System (INIS)

    Buijsen, Jeroen; Stiphout, Ruud G. van; Menheere, Paul P.C.A.; Lammering, Guido; Lambin, Philippe

    2014-01-01

    Purpose/objective: Chemoradiation (CRT) has been shown to lead to downsizing of an important portion of rectal cancers. In order to tailor treatment at an earlier stage during treatment, predictive models are being developed. Adding blood biomarkers may be attractive for prediction, as they can be collected very easily and determined with excellent reproducibility in clinical practice. The hypothesis of this study was that blood biomarkers related to tumor load, hypoxia and inflammation can help to predict response to CRT in rectal cancer. Material/methods: 295 patients with locally advanced rectal cancer who were planned to undergo CRT were prospectively entered into a biobank protocol ( (NCT01067872)). Blood samples were drawn before start of CRT. Nine biomarkers were selected, based on a previously defined hypothesis, and measured in a standardized way by a certified lab: CEA, CA19-9, LDH, CRP, IL-6, IL-8, CA IX, osteopontin and 25-OH-vitamin D. Outcome was analyzed in two ways: pCR vs. non-pCR and responders (defined as ypT0-2N0) vs. non-responders (all other ypTN stages). Results: 276 patients could be analyzed. 20.7% developed a pCR and 47.1% were classified as responders. In univariate analysis CEA (p = 0.001) and osteopontin (p = 0.012) were significant predictors for pCR. Taking response as outcome CEA (p < 0.001), IL-8 (p < 0.001) and osteopontin (p = 0.004) were significant predictors. In multivariate analysis CEA was the strongest predictor for pCR (OR 0.92, p = 0.019) and CEA and IL-8 predicted for response (OR 0.97, p = 0.029 and OR 0.94, p = 0.036). The model based on biomarkers only had an AUC of 0.65 for pCR and 0.68 for response; the strongest model included clinical data, PET-data and biomarkers and had an AUC of 0.81 for pCR and 0.78 for response. Conclusion: CEA and IL-8 were identified as predictive biomarkers for tumor response and PCR after CRT in rectal cancer. Incorporation of these blood biomarkers leads to an additional accuracy of

  10. Prediction of Tissue Outcome and Assessment of Treatment Effect in Acute Ischemic Stroke Using Deep Learning

    DEFF Research Database (Denmark)

    Nielsen, Anne; Hansen, Mikkel Bo; Tietze, Anna

    2018-01-01

    of automatically identifying and combining acute imaging features to accurately predict final lesion volume. METHODS: Using acute magnetic resonance imaging, we developed and trained a deep convolutional neural network (CNNdeep) to predict final imaging outcome. A total of 222 patients were included, of which 187...

  11. A lower baseline glomerular filtration rate predicts high mortality and newly cerebrovascular accidents in acute ischemic stroke patients.

    Science.gov (United States)

    Dong, Kai; Huang, Xiaoqin; Zhang, Qian; Yu, Zhipeng; Ding, Jianping; Song, Haiqing

    2017-02-01

    Chronic kidney disease (CKD) is gradually recognized as an independent risk factor for cardiovascular and cardio-/cerebrovascular disease. This study aimed to examine the association of the estimated glomerular filtration rate (eGFR) and clinical outcomes at 3 months after the onset of ischemic stroke in a hospitalized Chinese population.Totally, 972 patients with acute ischemic stroke were enrolled into this study. Modified of Diet in Renal Disease (MDRD) equations were used to calculate eGFR and define CKD. The site and degree of the stenosis were examined. Patients were followed-up for 3 months. Endpoint events included all-cause death and newly ischemic events. The multivariate logistic model was used to determine the association between renal dysfunction and patients' outcomes.Of all patients, 130 patients (13.4%) had reduced eGFR (<60 mL/min/1.73 m), and 556 patients had a normal eGFR (≥90 mL/min/1.73 m). A total of 694 patients suffered from cerebral artery stenosis, in which 293 patients only had intracranial artery stenosis (ICAS), 110 only with extracranial carotid atherosclerotic stenosis (ECAS), and 301 with both ICAS and ECAS. The patients with eGFR <60 mL/min/1.73m had a higher proportion of death and newly ischemic events compared with those with a relatively normal eGFR. Multivariate analysis revealed that a baseline eGFR <60 mL/min/1.73 m increased the risk of mortality by 3.089-fold and newly ischemic events by 4.067-fold. In further analysis, a reduced eGFR was associated with increased rates of mortality and newly events both in ICAS patients and ECAS patients. However, only an increased risk of newly events was found as the degree of renal function deteriorated in ICAS patients (odds ratio = 8.169, 95% confidence interval = 2.445-14.127).A low baseline eGFR predicted a high mortality and newly ischemic events at 3 months in ischemic stroke patients. A low baseline eGFR was also a strong independent predictor for newly

  12. Predictive Biomarkers in Colorectal Cancer: From the Single Therapeutic Target to a Plethora of Options

    Directory of Open Access Journals (Sweden)

    Daniela Rodrigues

    2016-01-01

    Full Text Available Colorectal cancer (CRC is one of the most frequent cancers and is a leading cause of cancer death worldwide. Treatments used for CRC may include some combination of surgery, radiation therapy, chemotherapy, and targeted therapy. The current standard drugs used in chemotherapy are 5-fluorouracil and leucovorin in combination with irinotecan and/or oxaliplatin. Most recently, biologic agents have been proven to have therapeutic benefits in metastatic CRC alone or in association with standard chemotherapy. However, patients present different treatment responses, in terms of efficacy and toxicity; therefore, it is important to identify biological markers that can predict the response to therapy and help select patients that would benefit from specific regimens. In this paper, authors review CRC genetic markers that could be useful in predicting the sensitivity/resistance to chemotherapy.

  13. The value of diffusion-weighted imaging for prediction of lasting deficit in acute stroke: an analysis of 134 patients with acute neurologic deficits

    International Nuclear Information System (INIS)

    Wiener, J.I.; King, J.T. Jr.; Moore, J.R.; Lewin, J.S.

    2001-01-01

    Acute stroke is one of the three major causes of death and disability in the United States. Now that new, and possibly effective therapy is becoming available, accurate, rapid diagnosis is important to provide timely treatment, while avoiding the risk of complications from unnecessary intervention. Our objective was to test the hypothesis that use of echo-planar (EPI) diffusion-weighted imaging (DWI) is more accurate than conventional T 2 weighted MRI in predicting progression to stroke in patients with acute ischemic neurologic deficits. We studied 134 patients presenting with acute neurologic deficits to a community hospital emergency room with both conventional MRI and DWI within 72 h of the onset of the acute deficit. We found DWI significantly more sensitive to permanent neurologic deficit at discharge (sensitivity 0.81) than conventional MRI (sensitivity 0.41). When available, DWI should be considered for routine use in patients being imaged for acute stroke. (orig.)

  14. Cancer predictive value of cytogenetic markers used in occupational health surveillance programs: a report from an ongoing study by the European Study Group on Cytogenetic Biomarkers and Health

    DEFF Research Database (Denmark)

    Hagmar, L; Bonassi, S; Strömberg, U

    1998-01-01

    cytogenetic biomarker. Totally, 3540 subjects had been examined for CA, 2702 for SCE and 1496 for MN. These cohorts have been followed-up with respect to subsequent cancer mortality or cancer incidence, and the expected values have been calculated from rates derived from the general populations in each...... as biomarkers for genotoxic effects which will result in an enhanced cancer risk. In order to assess this problem, Nordic and Italian cohorts were established, and preliminary results from these two studies indicated a predictive value of CA frequency for cancer risk, whereas no such associations were observed...... country. Stratified cohort analyses will be performed with respect to the levels of the cytogenetic biomarkers. The importance of potential effect modifiers such as gender, age at test, and time since test, will be evaluated using Poisson regression models. The remaining two potential effect modifiers...

  15. Utility of combinations of biomarkers, cognitive markers, and risk factors to predict conversion from mild cognitive impairment to Alzheimer disease in patients in the Alzheimer's disease neuroimaging initiative.

    Science.gov (United States)

    Gomar, Jesus J; Bobes-Bascaran, Maria T; Conejero-Goldberg, Concepcion; Davies, Peter; Goldberg, Terry E

    2011-09-01

    Biomarkers have become increasingly important in understanding neurodegenerative processes associated with Alzheimer disease. Markers include regional brain volumes, cerebrospinal fluid measures of pathological Aβ1-42 and total tau, cognitive measures, and individual risk factors. To determine the discriminative utility of different classes of biomarkers and cognitive markers by examining their ability to predict a change in diagnostic status from mild cognitive impairment to Alzheimer disease. Longitudinal study. We analyzed the Alzheimer's Disease Neuroimaging Initiative database to study patients with mild cognitive impairment who converted to Alzheimer disease (n = 116) and those who did not convert (n = 204) within a 2-year period. We determined the predictive utility of 25 variables from all classes of markers, biomarkers, and risk factors in a series of logistic regression models and effect size analyses. The Alzheimer's Disease Neuroimaging Initiative public database. Primary outcome measures were odds ratios, pseudo- R(2)s, and effect sizes. In comprehensive stepwise logistic regression models that thus included variables from all classes of markers, the following baseline variables predicted conversion within a 2-year period: 2 measures of delayed verbal memory and middle temporal lobe cortical thickness. In an effect size analysis that examined rates of decline, change scores for biomarkers were modest for 2 years, but a change in an everyday functional activities measure (Functional Assessment Questionnaire) was considerably larger. Decline in scores on the Functional Assessment Questionnaire and Trail Making Test, part B, accounted for approximately 50% of the predictive variance in conversion from mild cognitive impairment to Alzheimer disease. Cognitive markers at baseline were more robust predictors of conversion than most biomarkers. Longitudinal analyses suggested that conversion appeared to be driven less by changes in the neurobiologic

  16. Admission biomarkers of trauma-induced secondary cardiac injury predict adverse cardiac events and are associated with plasma catecholamine levels.

    Science.gov (United States)

    Naganathar, Sriveena; De'Ath, Henry D; Wall, Johanna; Brohi, Karim

    2015-07-01

    Secondary cardiac injury and dysfunction may be important contributors to poor outcomes in trauma patients, but the pathophysiology and clinical impact remain unclear. Early elevations in cardiac injury markers have been associated with the development of adverse cardiac events (ACEs), prolonged intensive care unit stays, and increased mortality. Studies of preinjury β-blocker use suggest a potential protective effect in critically ill trauma patients. This study aimed to prospectively examine the association of early biomarker evidence of trauma-induced secondary cardiac injury (TISCI) and ACEs and to examine the potential contribution of circulating catecholamines to its pathophysiology. Injured patients who met the study criteria were recruited at a single major trauma center. A blood sample was collected immediately on arrival. Serum epinephrine (E), norepinephrine (NE), and cardiac biomarkers including heart-related fatty acid binding protein (H-FABP) were assayed. Data were prospectively collected on ACEs. Of 300 patients recruited, 38 (13%) developed an ACE and had increased mortality (19% vs. 9%, p = 0.01) and longer intensive care unit stays (13 days, p < 0.001). H-FABP was elevated on admission in 56% of the patients, predicted the development of ACE, and was associated with higher mortality (14% vs. 5%, p = 0.01). Admission E and NE levels were strongly associated with elevations in H-FABP and ACEs (E, 274.0 pg/mL vs. 622.5 pg/mL, p < 0.001; NE, 1,063.2 pg/mL vs. 2,032.6 pg/mL, p < 0.001). Catecholamine effect on the development of TISCI or ACEs was not statistically independent of injury severity or depth of shock. Admission levels of H-FABP predict the development of ACEs and may be useful for prognosis and stratification of trauma patients. The development of TISCI and ACEs was associated with high admission levels of catecholamines, but their role in pathogenesis remains unclear. Clinical trials of adrenergic blockade may have the potential to

  17. Evaluation of different biomarkers to predict individual radiosensitivity in an inter-laboratory comparison--lessons for future studies.

    Directory of Open Access Journals (Sweden)

    Burkhard Greve

    Full Text Available Radiotherapy is a powerful cure for several types of solid tumours, but its application is often limited because of severe side effects in individual patients. With the aim to find biomarkers capable of predicting normal tissue side reactions we analysed the radiation responses of cells from individual head and neck tumour and breast cancer patients of different clinical radiosensitivity in a multicentric study. Multiple parameters of cellular radiosensitivity were analysed in coded samples of peripheral blood lymphocytes (PBLs and derived lymphoblastoid cell lines (LCLs from 15 clinical radio-hypersensitive tumour patients and compared to age- and sex-matched non-radiosensitive patient controls and 15 lymphoblastoid cell lines from age- and sex- matched healthy controls of the KORA study. Experimental parameters included ionizing radiation (IR-induced cell death (AnnexinV, induction and repair of DNA strand breaks (Comet assay, induction of yH2AX foci (as a result of DNA double strand breaks, and whole genome expression analyses. Considerable inter-individual differences in IR-induced DNA strand breaks and their repair and/or cell death could be detected in primary and immortalised cells with the applied assays. The group of clinically radiosensitive patients was not unequivocally distinguishable from normal responding patients nor were individual overreacting patients in the test system unambiguously identified by two different laboratories. Thus, the in vitro test systems investigated here seem not to be appropriate for a general prediction of clinical reactions during or after radiotherapy due to the experimental variability compared to the small effect of radiation sensitivity. Genome-wide expression analysis however revealed a set of 67 marker genes which were differentially induced 6 h after in vitro-irradiation in lymphocytes from radio-hypersensitive and non-radiosensitive patients. These results warrant future validation in larger

  18. Predicting final extent of ischemic infarction using artificial neural network analysis of multi-parametric MRI in patients with stroke.

    Directory of Open Access Journals (Sweden)

    Hassan Bagher-Ebadian

    Full Text Available In hemispheric ischemic stroke, the final size of the ischemic lesion is the most important correlate of clinical functional outcome. Using a set of acute-phase MR images (Diffusion-weighted--DWI, T(1-weighted--T1WI, T(2-weighted--T2WI, and proton density weighted--PDWI for inputs, and the chronic T2WI at 3 months as an outcome measure, an Artificial Neural Network (ANN was trained to predict the 3-month outcome in the form of a voxel-by-voxel forecast of the chronic T2WI. The ANN was trained and tested using 12 subjects (with 83 slices and 140218 voxels using a leave-one-out cross-validation method with calculation of the Area Under the Receiver Operator Characteristic Curve (AUROC for training, testing and optimization of the ANN. After training and optimization, the ANN produced maps of predicted outcome that were well correlated (r = 0.80, p<0.0001 with the T2WI at 3 months for all 12 patients. This result implies that the trained ANN can provide an estimate of 3-month ischemic lesion on T2WI in a stable and accurate manner (AUROC = 0.89.

  19. Prediction of infarction development after endovascular stroke therapy with dual-energy computed tomography.

    Science.gov (United States)

    Djurdjevic, Tanja; Rehwald, Rafael; Knoflach, Michael; Matosevic, Benjamin; Kiechl, Stefan; Gizewski, Elke Ruth; Glodny, Bernhard; Grams, Astrid Ellen

    2017-03-01

    After intraarterial recanalisation (IAR), the haemorrhage and the blood-brain barrier (BBB) disruption can be distinguished using dual-energy computed tomography (DECT). The aim of the present study was to investigate whether future infarction development can be predicted from DECT. DECT scans of 20 patients showing 45 BBB disrupted areas after IAR were assessed and compared with follow-up examinations. Receiver operator characteristic (ROC) analyses using densities from the iodine map (IM) and virtual non-contrast (VNC) were performed. Future infarction areas are denser than future non-infarction areas on IM series (23.44 ± 24.86 vs. 5.77 ± 2.77; p VNC series (29.71 ± 3.33 vs. 35.33 ± 3.50; p 17.13 HU; p VNC series allowed prediction of infarction volume. Future infarction development after IAR can be reliably predicted with the IM series. The prediction of haemorrhages and of infarction size is less reliable. • The IM series (DECT) can predict future infarction development after IAR. • Later haemorrhages can be predicted using the IM and the BW series. • The volume of definable hypodense areas in VNC correlates with infarction volume.

  20. Prediction of infarction development after endovascular stroke therapy with dual-energy computed tomography

    International Nuclear Information System (INIS)

    Djurdjevic, Tanja; Gizewski, Elke Ruth; Grams, Astrid Ellen; Rehwald, Rafael; Glodny, Bernhard; Knoflach, Michael; Matosevic, Benjamin; Kiechl, Stefan

    2017-01-01

    After intraarterial recanalisation (IAR), the haemorrhage and the blood-brain barrier (BBB) disruption can be distinguished using dual-energy computed tomography (DECT). The aim of the present study was to investigate whether future infarction development can be predicted from DECT. DECT scans of 20 patients showing 45 BBB disrupted areas after IAR were assessed and compared with follow-up examinations. Receiver operator characteristic (ROC) analyses using densities from the iodine map (IM) and virtual non-contrast (VNC) were performed. Future infarction areas are denser than future non-infarction areas on IM series (23.44 ± 24.86 vs. 5.77 ± 2.77; p < 0.0001) and more hypodense on VNC series (29.71 ± 3.33 vs. 35.33 ± 3.50; p < 0.0001). ROC analyses for the IM series showed an area under the curve (AUC) of 0.99 (cut-off: <9.97 HU; p < 0.05; sensitivity 91.18 %; specificity 100.00 %; accuracy 0.93) for the prediction of future infarctions. The AUC for the prediction of haemorrhagic infarctions was 0.78 (cut-off >17.13 HU; p < 0.05; sensitivity 90.00 %; specificity 62.86 %; accuracy 0.69). The VNC series allowed prediction of infarction volume. Future infarction development after IAR can be reliably predicted with the IM series. The prediction of haemorrhages and of infarction size is less reliable. (orig.)

  1. Prediction of infarction development after endovascular stroke therapy with dual-energy computed tomography

    Energy Technology Data Exchange (ETDEWEB)

    Djurdjevic, Tanja; Gizewski, Elke Ruth; Grams, Astrid Ellen [Medical University of Innsbruck, Department of Neuroradiology, Innsbruck (Austria); Rehwald, Rafael; Glodny, Bernhard [Medical University of Innsbruck, Department of Radiology, Innsbruck (Austria); Knoflach, Michael; Matosevic, Benjamin; Kiechl, Stefan [Medical University of Innsbruck, Department of Neurology, Innsbruck (Austria)

    2017-03-15

    After intraarterial recanalisation (IAR), the haemorrhage and the blood-brain barrier (BBB) disruption can be distinguished using dual-energy computed tomography (DECT). The aim of the present study was to investigate whether future infarction development can be predicted from DECT. DECT scans of 20 patients showing 45 BBB disrupted areas after IAR were assessed and compared with follow-up examinations. Receiver operator characteristic (ROC) analyses using densities from the iodine map (IM) and virtual non-contrast (VNC) were performed. Future infarction areas are denser than future non-infarction areas on IM series (23.44 ± 24.86 vs. 5.77 ± 2.77; p < 0.0001) and more hypodense on VNC series (29.71 ± 3.33 vs. 35.33 ± 3.50; p < 0.0001). ROC analyses for the IM series showed an area under the curve (AUC) of 0.99 (cut-off: <9.97 HU; p < 0.05; sensitivity 91.18 %; specificity 100.00 %; accuracy 0.93) for the prediction of future infarctions. The AUC for the prediction of haemorrhagic infarctions was 0.78 (cut-off >17.13 HU; p < 0.05; sensitivity 90.00 %; specificity 62.86 %; accuracy 0.69). The VNC series allowed prediction of infarction volume. Future infarction development after IAR can be reliably predicted with the IM series. The prediction of haemorrhages and of infarction size is less reliable. (orig.)

  2. Decorin in human oral cancer: A promising predictive biomarker of S-1 neoadjuvant chemosensitivity

    International Nuclear Information System (INIS)

    Kasamatsu, Atsushi; Uzawa, Katsuhiro; Minakawa, Yasuyuki; Ishige, Shunsaku; Kasama, Hiroki; Endo-Sakamoto, Yosuke; Ogawara, Katsunori; Shiiba, Masashi; Takiguchi, Yuichi; Tanzawa, Hideki

    2015-01-01

    Highlights: • DCN is significantly up-regulated in chemoresistant cancer cell lines. • DCN is a key regulator for chemoresistant mechanisms in vitro and in vivo. • DCN predicts the clinical responses to S-1 NAC for patients with oral cancer. - Abstract: We reported previously that decorin (DCN) is significantly up-regulated in chemoresistant cancer cell lines. DCN is a small leucine-rich proteoglycan that exists and functions in stromal and epithelial cells. Accumulating evidence suggests that DCN affects the biology of several types of cancer by directly/indirectly targeting the signaling molecules involved in cell growth, survival, metastasis, and angiogenesis, however, the molecular mechanisms of DCN in chemoresistance and its clinical relevance are still unknown. Here we assumed that DCN silencing cells increase chemosusceptibility to S-1, consisted of tegafur, prodrug of 5-fluorouracil. We first established DCN knockdown transfectants derived from oral cancer cells for following experiments including chemosusceptibility assay to S-1. In addition to the in vitro data, DCN knockdown zenografting tumors in nude mice demonstrate decreasing cell proliferation and increasing apoptosis with dephosphorylation of AKT after S-1 chemotherapy. We also investigated whether DCN expression predicts the clinical responses of neoadjuvant chemotherapy (NAC) using S-1 (S-1 NAC) for oral cancer patients. Immunohistochemistry data in the preoperative biopsy samples was analyzed to determine the cut-off point for status of DCN expression by receiver operating curve analysis. Interestingly, low DCN expression was observed in five (83%) of six cases with complete responses to S-1 NAC, and in one (10%) case of 10 cases with stable/progressive disease, indicating that S-1 chemosensitivity is dramatically effective in oral cancer patients with low DCN expression compared with high DCN expression. Our findings suggest that DCN is a key regulator for chemoresistant mechanisms, and

  3. Interleukin-6 and procalcitonin as biomarkers in mortality prediction of hospitalized patients with community acquired pneumonia

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    Ilija Andrijevic

    2014-01-01

    Full Text Available Introduction: Community acquired pneumonia (CAP may present as life-threatening infection with uncertain progression and outcome of treatment. Primary aim of the trial was determination of the cut-off value of serum interleukin-6 (IL-6 and procalcitonin (PCT above which, 30-day mortality in hospitalized patients with CAP, could be predicted with high sensitivity and specificity. We investigated correlation between serum levels of IL-6 and PCT at admission and available scoring systems of CAP (pneumonia severity index-PSI, modified early warning score-MEWS and (Confusion, Urea nitrogen, respiratory rate, Blood pressure, ≥65 years of age-CURB65. Methods: This was prospective, non-randomized trial which included 101 patients with diagnosed CAP. PSI, MEWS and CURB65 were assessed on first day of hospitalization. IL-6 and PCT were also sampled on the first day of hospitalization. Results: Based on ROC curve analysis (AUC ± SE = 0.934 ± 0.035; 95%CI(0.864-1.0; P = 0.000 hospitalized CAP patients with elevated IL-6 level have 93.4% higher risk level for lethal outcome. Cut-off value of 20.2 pg/ml IL-6 shows sensitivity of 84% and specificity of 87% in mortality prediction. ROC curve analysis confirmed significant role of procalcitonin as a mortality predictor in CAP patients (AUC ± SE = 0.667 ± 0.062; 95%CI(0.546-0.789; P = 0.012. Patients with elevated PCT level have 66.7% higher risk level for lethal outcome. As a predictor of mortality at the cut-off value of 2.56 ng/ml PCT shows sensitivity of 76% and specificity of 61.8%. Conclusions: Both IL-6 and PCI are significant for prediction of 30-day mortality in hospitalized patients with CAP. Serum levels of IL6 correlate with major CAP scoring systems.

  4. Degradation Rate of 5-Fluorouracil in Metastatic Colorectal Cancer: A New Predictive Outcome Biomarker?

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    Andrea Botticelli

    Full Text Available 5-FU based chemotherapy is the most common first line regimen used for metastatic colorectal cancer (mCRC. Identification of predictive markers of response to chemotherapy is a challenging approach for drug selection. The present study analyzes the predictive role of 5-FU degradation rate (5-FUDR and genetic polymorphisms (MTHFR, TSER, DPYD on survival.Genetic polymorphisms of MTHFR, TSER and DPYD, and the 5-FUDR of homogenous patients with mCRC were retrospectively studied. Genetic markers and the 5-FUDR were correlated with clinical outcome.133 patients affected by mCRC, treated with fluoropyrimidine-based chemotherapy from 2009 to 2014, were evaluated. Patients were classified into three metabolic classes, according to normal distribution of 5-FUDR in more than 1000 patients, as previously published: poor-metabolizer (PM with 5-FU-DR ≤ 0,85 ng/ml/106 cells/min (8 pts; normal metabolizer with 0,85 < 5-FU-DR < 2,2 ng/ml/106 cells/min (119 pts; ultra-rapid metabolizer (UM with 5-FU-DR ≥ 2,2 ng/ml/106 cells/min (6 pts. PM and UM groups showed a longer PFS respect to normal metabolizer group (14.5 and 11 months respectively vs 8 months; p = 0.029. A higher G3-4 toxicity rate was observed in PM and UM, respect to normal metabolizer (50% in both PM and UM vs 18%; p = 0.019. No significant associations between genes polymorphisms and outcomes or toxicities were observed.5-FUDR seems to be significantly involved in predicting survival of patients who underwent 5-FU based CHT for mCRC. Although our findings require confirmation in large prospective studies, they reinforce the concept that individual genetic variation may allow personalized selection of chemotherapy to optimize clinical outcomes.

  5. Decorin in human oral cancer: A promising predictive biomarker of S-1 neoadjuvant chemosensitivity

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    Kasamatsu, Atsushi, E-mail: kasamatsua@faculty.chiba-u.jp [Department of Oral Science, Graduate School of Medicine, Chiba University, Chiba 260-8670 (Japan); Department of Dentistry and Oral–Maxillofacial Surgery, Chiba University Hospital, Chiba 260-8670 (Japan); Uzawa, Katsuhiro, E-mail: uzawak@faculty.chiba-u.jp [Department of Oral Science, Graduate School of Medicine, Chiba University, Chiba 260-8670 (Japan); Department of Dentistry and Oral–Maxillofacial Surgery, Chiba University Hospital, Chiba 260-8670 (Japan); Minakawa, Yasuyuki; Ishige, Shunsaku; Kasama, Hiroki [Department of Oral Science, Graduate School of Medicine, Chiba University, Chiba 260-8670 (Japan); Endo-Sakamoto, Yosuke; Ogawara, Katsunori [Department of Dentistry and Oral–Maxillofacial Surgery, Chiba University Hospital, Chiba 260-8670 (Japan); Shiiba, Masashi; Takiguchi, Yuichi [Medical Oncology, Graduate School of Medicine, Chiba University, Chiba 260-8670 (Japan); Tanzawa, Hideki [Department of Oral Science, Graduate School of Medicine, Chiba University, Chiba 260-8670 (Japan); Department of Dentistry and Oral–Maxillofacial Surgery, Chiba University Hospital, Chiba 260-8670 (Japan)

    2015-01-30

    Highlights: • DCN is significantly up-regulated in chemoresistant cancer cell lines. • DCN is a key regulator for chemoresistant mechanisms in vitro and in vivo. • DCN predicts the clinical responses to S-1 NAC for patients with oral cancer. - Abstract: We reported previously that decorin (DCN) is significantly up-regulated in chemoresistant cancer cell lines. DCN is a small leucine-rich proteoglycan that exists and functions in stromal and epithelial cells. Accumulating evidence suggests that DCN affects the biology of several types of cancer by directly/indirectly targeting the signaling molecules involved in cell growth, survival, metastasis, and angiogenesis, however, the molecular mechanisms of DCN in chemoresistance and its clinical relevance are still unknown. Here we assumed that DCN silencing cells increase chemosusceptibility to S-1, consisted of tegafur, prodrug of 5-fluorouracil. We first established DCN knockdown transfectants derived from oral cancer cells for following experiments including chemosusceptibility assay to S-1. In addition to the in vitro data, DCN knockdown zenografting tumors in nude mice demonstrate decreasing cell proliferation and increasing apoptosis with dephosphorylation of AKT after S-1 chemotherapy. We also investigated whether DCN expression predicts the clinical responses of neoadjuvant chemotherapy (NAC) using S-1 (S-1 NAC) for oral cancer patients. Immunohistochemistry data in the preoperative biopsy samples was analyzed to determine the cut-off point for status of DCN expression by receiver operating curve analysis. Interestingly, low DCN expression was observed in five (83%) of six cases with complete responses to S-1 NAC, and in one (10%) case of 10 cases with stable/progressive disease, indicating that S-1 chemosensitivity is dramatically effective in oral cancer patients with low DCN expression compared with high DCN expression. Our findings suggest that DCN is a key regulator for chemoresistant mechanisms, and

  6. ULK1: a promising biomarker in predicting poor prognosis and therapeutic response in human nasopharygeal carcinoma.

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    Miao Yun

    Full Text Available Plenty of studies have established that dysregulation of autophagy plays an essential role in cancer progression. The autophagy-related proteins have been reported to be closely associated with human cancer patients' prognosis. We explored the expression dynamics and prognostic value of autophagy-related protein ULK1 by immunochemistry (IHC method in two independent cohorts of nasopharygeal carcinoma (NPC cases. The X-tile program was applied to determine the optimal cut-off value in the training cohort. This derived cutoff value was then subjected to analysis the association of ULK1 expression with patients' clinical characteristics and survival outcome in the validation cohort and overall cases. High ULK1 expression was closely associated with aggressive clinical feature of NPC patients. Furthermore, high expression of ULK1 was observed more frequently in therapeutic resistant group than that in therapeutic effective group. Our univariate and multivariate analysis also showed that higher ULK1 expression predicted inferior disease-specific survival (DSS (P<0.05. Consequently, a new clinicopathologic prognostic model with 3 poor prognostic factors (ie, ULK1 expression, overall clinical stage and therapeutic response could significantly stratify risk (low, intermediate and high for DSS in NPC patients (P<0.001. These findings provide evidence that, the examination of ULK1 expression by IHC method, could serve as an effective additional tool for predicting therapeutic response and patients' survival outcome in NPC patients.

  7. Thrombolysis with Intravenous Tissue Plasminogen Activator (rt-PA) Predicts Favorable Discharge Disposition in Patients with Acute Ischemic Stroke

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    Ifejika-Jones, Nneka L.; Harun, Nusrat; Mohammed-Rajput, Nareesa A.; Noser, Elizabeth A.; Grotta, James C.

    2011-01-01

    Background and Purpose Acute ischemic stroke patients receiving IV tissue plasminogen activator (rt-PA) within 3 hours of symptom onset are 30% more likely to have minimal disability at three months. During hospitalization, short-term disability is subjectively measured by discharge disposition, whether to home, Inpatient Rehabilitation (IR), Skilled Nursing Facility (SNF) or Subacute Care (Sub). There are no studies assessing the role of rt-PA use as a predictor of post-stroke disposition. Methods Retrospective analysis of all ischemic stroke patients admitted to the University of Texas Houston Medical School (UTHMS) Stroke Service between Jan 2004 and Oct 2009. Baseline demographics and National Institute of Health Stroke Scale (NIHSS) score were collected. Cerebrovascular disease risk factors were used for risk stratification. Results Home vs. IR, SNF, Sub Of 2225 acute ischemic stroke patients, 1019 were discharged home, 1206 to another level of care. Patients who received rt-PA therapy were 1.9 times more likely to be discharged home (P = stroke patients, 719 patients were discharged to acute IR, 371 were discharged to SNF, 116 to Sub. There were no differences in disposition between patients who received rt-PA therapy. Conclusions Stroke patients who receive IV rt-PA for acute ischemic stroke are more 1.9 times more likely to be discharged directly home after hospitalization. This study is limited by its retrospective nature and the undetermined role of psychosocial factors related to discharge. PMID:21293014

  8. Prognostic value of serum thioredoxin levels in ischemic stroke.

    Science.gov (United States)

    Yu, Tieer; Zhang, Wanli; Lin, Yuanshao; Li, Qian; Xue, Jie; Cai, Zhengyi; Cheng, Yifan; Shao, Bei

    2017-11-01

    Thioredoxin (Trx) is one of significant antioxidative molecules to diminish oxidative stress. Current evidence suggests that Trx is a potent antioxidant with cytoprotective functions. The aim of our study was to investigate specifically the association between serum Trx levels and acute ischemic stroke (AIS) patients. 198 AIS patients and 75 controls were enrolled to the study. Serum Trx levels were measured using an enzyme-linked immunosorbent assay (ELISA). Stroke severity was assessed with the National Institutes of Health Stroke Scale (NIHSS) score on admission. Clinical endpoint was functional outcome measured by Barthel Index (BI) 3 months after admission. Multivariate binary logistic regression analyses were performed to identify predictors. We found that serum Trx levels were significantly increased in patients as compared to controls. Serum Trx was an independent biomarker to predict ischemic stroke (OR, 1.264; 95% CI, 1.04-1.537; P = 0.019). In addition, there was a negative correlation between NIHSS score at admission and serum Trx levels in cardioembolic stroke patients (r = -0.422; P = 0.013). Furthermore, higher serum Trx levels in AIS patients were associated with favorable functional outcome. Serum Trx was an independent predictor for the functional outcome (OR, 0.862; 95% CI, 0.75-0.991; P = 0.037). Serum Trx might be as a biomarker of cardioembolic stroke severity. Increased serum Trx levels could be a useful tool to predict good prognosis in patients with AIS.

  9. Prediction of Small for Gestational Age Infants in Healthy Nulliparous Women Using Clinical and Ultrasound Risk Factors Combined with Early Pregnancy Biomarkers.

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    Lesley M E McCowan

    Full Text Available Most small for gestational age pregnancies are unrecognised before birth, resulting in substantial avoidable perinatal mortality and morbidity. Our objective was to develop multivariable prediction models for small for gestational age combining clinical risk factors and biomarkers at 15±1 weeks' with ultrasound parameters at 20±1 weeks' gestation.Data from 5606 participants in the Screening for Pregnancy Endpoints (SCOPE cohort study were divided into Training (n = 3735 and Validation datasets (n = 1871. The primary outcomes were All-SGA (small for gestational age with birthweight <10th customised centile, Normotensive-SGA (small for gestational age with a normotensive mother and Hypertensive-SGA (small for gestational age with an hypertensive mother. The comparison group comprised women without the respective small for gestational age phenotype. Multivariable analysis was performed using stepwise logistic regression beginning with clinical variables, and subsequent additions of biomarker and then ultrasound (biometry and Doppler variables. Model performance was assessed in Training and Validation datasets by calculating area under the curve.633 (11.2% infants were All-SGA, 465(8.2% Normotensive-SGA and 168 (3% Hypertensive-SGA. Area under the curve (95% Confidence Intervals for All-SGA using 15±1 weeks' clinical variables, 15±1 weeks' clinical+ biomarker variables and clinical + biomarkers + biometry /Doppler at 20±1 weeks' were: 0.63 (0.59-0.67, 0.64 (0.60-0.68 and 0.69 (0.66-0.73 respectively in the Validation dataset; Normotensive-SGA results were similar: 0.61 (0.57-0.66, 0.61 (0.56-0.66 and 0.68 (0.64-0.73 with small increases in performance in the Training datasets. Area under the curve (95% Confidence Intervals for Hypertensive-SGA were: 0.76 (0.70-0.82, 0.80 (0.75-0.86 and 0.84 (0.78-0.89 with minimal change in the Training datasets.Models for prediction of small for gestational age, which combine biomarkers, clinical and

  10. Clinical Risk Stratification Optimizes Value of Biomarkers to Predict New-Onset Heart Failure in a Community-Based Cohort

    NARCIS (Netherlands)

    Brouwers, Frank P.; van Gilst, Wiek H.; Damman, Kevin; van den Berg, Maarten P.; Gansevoort, Ron T.; Bakker, Stephan J. L.; Hillege, Hans L.; van Veldhuisen, Dirk J.; van der Harst, Pim; de Boer, Rudolf A.

    Background-We aim to identify and quantify the value of biomarkers for incident new-onset heart failure (HF) in a community-based cohort and subgroups based on cardiovascular risk and evaluate the prognostic value of 13 biomarkers for HF with reduced and preserved ejection fraction. Methods and

  11. A Culture-Brain Link: Negative Age Stereotypes Predict Alzheimer’s-disease Biomarkers

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    Levy, Becca R.; Ferrucci, Luigi; Zonderman, Alan B.; Slade, Martin D.; Troncoso, Juan; Resnick, Susan M.

    2016-01-01

    Although negative age stereotypes have been found to predict adverse outcomes among older individuals, it was unknown whether the influence of stereotypes extends to brain changes associated with Alzheimer’s disease. To consider this possibility, we drew on the age stereotypes of dementia-free participants in the Baltimore Longitudinal Study of Aging that had been measured decades before yearly MRIs and brain autopsies were performed. Those with more negative age stereotypes earlier in life had significantly steeper hippocampal-volume loss, and significantly greater accumulation of neurofibrillary tangles and amyloid plaques at autopsy, adjusting for relevant covariates. These findings suggest a new pathway to identifying mechanisms and potential interventions related to the neuropathology of Alzheimer’s disease. PMID:26641877

  12. A culture-brain link: Negative age stereotypes predict Alzheimer's disease biomarkers.

    Science.gov (United States)

    Levy, Becca R; Ferrucci, Luigi; Zonderman, Alan B; Slade, Martin D; Troncoso, Juan; Resnick, Susan M

    2016-02-01

    Although negative age stereotypes have been found to predict adverse outcomes among older individuals, it was unknown whether the influence of stereotypes extends to brain changes associated with Alzheimer's disease. To consider this possibility, we drew on dementia-free participants, in the Baltimore Longitudinal Study of Aging, whose age stereotypes were assessed decades before yearly magnetic resonance images and brain autopsies were performed. Those holding more-negative age stereotypes earlier in life had significantly steeper hippocampal-volume loss and significantly greater accumulation of neurofibrillary tangles and amyloid plaques, adjusting for relevant covariates. These findings suggest a new pathway to identifying mechanisms and potential interventions related to the pathology of Alzheimer's disease. (c) 2016 APA, all rights reserved).

  13. PD-L1 expression as a predictive biomarker in advanced non-small-cell lung cancer: updated survival data.

    Science.gov (United States)

    Aguiar, Pedro N; De Mello, Ramon Andrade; Hall, Peter; Tadokoro, Hakaru; Lima Lopes, Gilberto de

    2017-05-01

    The treatment of non-small-cell lung cancer has changed after the development of the immune checkpoint inhibitors. Although the most studied biomarker is PD-L1 expression, its clinical significance is still debatable. In this article, we show the updated survival analysis of all published data. We searched in network and conference data sources for relevant clinical studies of immunotherapy for non-small-cell lung cancer that assessed the PD-L1 expression even as an exploratory analysis. The updated survival hazard ratios (HR) were included in the analysis. 14 studies with 2857 patients were included (2019 treated with immunotherapy). The response rate was as higher among PD-L1-positive patients (RR: 2.19, 95% CI: 1.63-2.94). PD-L1 expression was also related to better progression-free survival (HR: 0.69, 95% CI: 0.57-0.85) and better overall survival (HR: 0.77, 95% CI: 0.67-0.89). PD-L1 overexpression predicts activity as well as better survival for patients treated with immune checkpoint inhibitors.

  14. Role of laboratory biomarkers in monitoring and prediction of the effectiveness of treatment of rheumatic diseases using genetically engineered drugs

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    Elena Nikolayevna Aleksandrova

    2014-03-01

    Full Text Available Significant progress in treating immunoinflammatory rheumatic diseases (RD is related to the design of a novel family of drugs, genetically engineered (GE drugs. Molecular and cellular biomarkers (antibodies, indicators of acute inflammation, cytokines, chemokines, growth factors, endothelial activation markers, immunoglobulins, cryoglobulins, T- and B-cell subpopulations, products of bone and cartilage metabolism, genetic and metabolic markers that allow one to conduct immunological monitoring and prediction of the effectiveness of RD therapy using tumor necrosis factor α inhibitors (infliximab, adalimumab, golimumab, etanercept, anti-B-cell drugs (rituximab, belimumab, interleukin-6 receptor antagonist (tocilizumab, and T-cell costimulation blocker (abatacept have been detected in blood, synovial fluid, urine, and bioptates of the affected tissues. In addition to the conventional uniplex immunodiagnostics techniques, multiplex analysis of marker, which is based on genetic, transcriptomic and proteomic technologies using DNA and protein microarrays, polymerase chain reaction, and flow cytometry, is becoming increasingly widespread. The search for and validation of immunological predictors of the effective response to GE drug therapy make it possible to optimize and reduce the cost of therapy using these drugs in future.

  15. Role of laboratory biomarkers in monitoring and prediction of the effectiveness of treatment of rheumatic diseases using genetically engineered drugs

    Directory of Open Access Journals (Sweden)

    Elena Nikolayevna Aleksandrova

    2014-01-01

    Full Text Available Significant progress in treating immunoinflammatory rheumatic diseases (RD is related to the design of a novel family of drugs, genetically engineered (GE drugs. Molecular and cellular biomarkers (antibodies, indicators of acute inflammation, cytokines, chemokines, growth factors, endothelial activation markers, immunoglobulins, cryoglobulins, T- and B-cell subpopulations, products of bone and cartilage metabolism, genetic and metabolic markers that allow one to conduct immunological monitoring and prediction of the effectiveness of RD therapy using tumor necrosis factor α inhibitors (infliximab, adalimumab, golimumab, etanercept, anti-B-cell drugs (rituximab, belimumab, interleukin-6 receptor antagonist (tocilizumab, and T-cell costimulation blocker (abatacept have been detected in blood, synovial fluid, urine, and bioptates of the affected tissues. In addition to the conventional uniplex immunodiagnostics techniques, multiplex analysis of marker, which is based on genetic, transcriptomic and proteomic technologies using DNA and protein microarrays, polymerase chain reaction, and flow cytometry, is becoming increasingly widespread. The search for and validation of immunological predictors of the effective response to GE drug therapy make it possible to optimize and reduce the cost of therapy using these drugs in future.

  16. The imbalance in expression of angiogenic and anti-angiogenic factors as candidate predictive biomarker in preeclampsia

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    Pooneh Nikuei

    2015-07-01

    Full Text Available Preeclampsia is an important pregnancy disorder with serious maternal and fetal complications which its etiology has not been completely understood yet. Early diagnosis and management of disease could reduce its potential side effects. The vascular endothelial growth factor (VEGF family including VEGF-A is the most potent endothelial growth factor which induces angiogenesis and endothelial cell proliferation and has basic role in vasculogenesis. VEGF and its tyrosine kinase receptors (Flt1 and KDR are major factors for fetal and placental angiogenic development. Finding mechanisms involved in expression of angiogenic factors may lead to new prognostic and therapeutic points in management of preeclampsia. Recent researches, has shown capability of some anti-angiogenic factors as potential candidate to be used as early predictors for preeclampsia. Soluble fms-like tyrosin kinase-1 (sFlt1 is a truncated splice variant of the membrane-bound VEGF receptor Flt1, that is produced by the placenta and it can bind to angiogenic growth factors and neutraliz, their effects. It is also observed that the ratio of sFlt1 to placental growth factor is valuable as prognostic marker. In this review, VEGF family member’s role in angiogenesis is evaluated as biomarkers to be used for prediction of preeclampsia.

  17. Biomarkers S100B and neuron-specific enolase predict outcome in hypothermia-treated encephalopathic newborns*.

    Science.gov (United States)

    Massaro, An N; Chang, Taeun; Baumgart, Stephen; McCarter, Robert; Nelson, Karin B; Glass, Penny

    2014-09-01

    To evaluate if serum S100B protein and neuron-specific enolase measured during therapeutic hypothermia are predictive of neurodevelopmental outcome at 15 months in children with neonatal encephalopathy. Prospective longitudinal cohort study. A level IV neonatal ICU in a freestanding children's hospital. Term newborns with moderate to severe neonatal encephalopathy referred for therapeutic hypothermia during the study period. Serum neuron-specific enolase and S100B were measured at 0, 12, 24, and 72 hours of hypothermia. Of the 83 infants enrolled, 15 (18%) died in the newborn period. Survivors were evaluated by the Bayley Scales of Infant Development-II at 15 months. Outcomes were assessed in 49 of 68 survivors (72%) at a mean age of 15.2 ± 2.7 months. Neurodevelopmental outcome was classified by Bayley Scales of Infant Development-II Mental Developmental Index and Psychomotor Developmental Index scores, reflecting cognitive and motor outcomes, respectively. Four-level outcome classifications were defined a priori: normal = Mental Developmental Index/Psychomotor Developmental Index within 1 SD (> 85), mild = Mental Developmental Index/Psychomotor Developmental Index less than 1 SD (70-85), moderate/severe = Mental Developmental Index/Psychomotor Developmental Index less than 2 SD (encephalopathy are associated with neurodevelopmental outcome at 15 months. These putative biomarkers of brain injury may help direct care during therapeutic hypothermia.

  18. Epidemiological and Clinical Baseline Characteristics as Predictive Biomarkers of Response to Anti-VEGF Treatment in Patients with Neovascular AMD

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    Miltiadis K. Tsilimbaris

    2016-01-01

    Full Text Available Purpose. To review the current literature investigating patient response to antivascular endothelial growth factor-A (VEGF therapy in the treatment of neovascular age-related macular degeneration (nAMD and to identify baseline characteristics that might predict response. Method. A literature search of the PubMed database was performed, using the keywords: AMD, anti-VEGF, biomarker, optical coherence tomography, treatment outcome, and predictor. The search was limited to articles published from 2006 to date. Exclusion criteria included phase 1 trials, case reports, studies focusing on indications other than nAMD, and oncology. Results. A total of 1467 articles were identified, of which 845 were excluded. Of the 622 remaining references, 47 met all the search criteria and were included in this review. Conclusion. Several baseline characteristics correlated with anti-VEGF treatment response, including best-corrected visual acuity, age, lesion size, and retinal thickness. The majority of factors were associated with disease duration, suggesting that longer disease duration before treatment results in worse treatment outcomes. This highlights the need for early treatment for patients with nAMD to gain optimal treatment outcomes. Many of the identified baseline characteristics are interconnected and cannot be evaluated in isolation; therefore multivariate analyses will be required to determine any specific relationship with treatment response.

  19. Malnutrition risk predicts recovery of full oral intake among older adult stroke patients undergoing enteral nutrition: Secondary analysis of a multicentre survey (the APPLE study).

    Science.gov (United States)

    Nishioka, Shinta; Okamoto, Takatsugu; Takayama, Masako; Urushihara, Maki; Watanabe, Misuzu; Kiriya, Yumiko; Shintani, Keiko; Nakagomi, Hiromi; Kageyama, Noriko

    2017-08-01

    Whether malnutrition risk correlates with recovery of swallowing function of convalescent stroke patients is unknown. This study was conducted to clarify whether malnutrition risks predict achievement of full oral intake in convalescent stroke patients undergoing enteral nutrition. We conducted a secondary analysis of 466 convalescent stroke patients, aged 65 years or over, who were undergoing enteral nutrition. Patients were extracted from the "Algorithm for Post-stroke Patients to improve oral intake Level; APPLE" study database compiled at the Kaifukuki (convalescent) rehabilitation wards. Malnutrition risk was determined by the Geriatric Nutritional Risk Index as follows: severe (malnutrition risks (≥98). Swallowing function was assessed by Fujishima's swallowing grade (FSG) on admission and discharge. The primary outcome was achievement of full oral intake, indicated by FSG ≥ 7. Binary logistic regression analysis was performed to identify predictive factors, including malnutrition risk, for achieving full oral intake. Estimated hazard risk was computed by Cox's hazard model. Of the 466 individuals, 264 were ultimately included in this study. Participants with severe malnutrition risk showed a significantly lower proportion of achievement of full oral intake than lower severity groups (P = 0.001). After adjusting for potential confounders, binary logistic regression analysis showed that patients with severe malnutrition risk were less likely to achieve full oral intake (adjusted odds ratio: 0.232, 95% confidence interval [95% CI]: 0.047-1.141). Cox's proportional hazard model revealed that severe malnutrition risk was an independent predictor of full oral intake (adjusted hazard ratio: 0.374, 95% CI: 0.166-0.842). Compared to patients who did not achieve full oral intake, patients who achieved full oral intake had significantly higher energy intake, but there was no difference in protein intake and weight change. Severe malnutrition risk independently

  20. CircRNA-0004904, CircRNA-0001855, and PAPP-A: Potential Novel Biomarkers for the Prediction of Preeclampsia

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    Min Jiang

    2018-05-01

    Full Text Available Background/Aims: Circular RNAs (circRNAs are transcribed prevalently in the genome; however, their potential roles in multiple cardiovascular diseases, particularly preeclampsia (PE, are not yet well understood. This study investigated the expression profiles of circRNAs and explored circRNA-mediated pregnancy-associated plasma protein A (PAPP-A expression as a potential biomarker for PE before 20 weeks of pregnancy. Methods: A nested case-control two-phase screening/validation study was performed in pregnant women before 20 weeks of gestation (before clinical diagnosis at Guangzhou Women and Children’s Medical Center from 2012 to 2015. In the screening phase, circRNA expression profiles of blood cells were assessed using a human circRNA microarray, which was designed to detect simultaneously 5396 circRNAs, in 5 patients with PE and 5 age- and gestational week-matched controls. In the validation phase, 18 circRNAs in blood cells predicted by bioinformatics tools were validated by quantitative reverse transcription PCR in a cohort of 60 patients (PE and age-, gestational week-, and sample storage time-matched controls. Then, we examined the involvement of circRNAs in PE-related pathways via interactions with miRNAs by multiple bioinformatics approaches. Bioinformatics analysis predicted that hsa_circ_0004904 and hsa_circ_0001855 miRNA sponges directly target PAPP-A. PAPP-A was verified in the serum of the same cohort of patients using an enzyme-linked immunosorbent assay. Finally, we combined PAPP-A with circRNAs to create a novel preclinical diagnostic model for PE with logistic regression and evaluated the efficiency of this model with receiver operating curve analysis. Results: Volcano plot analysis using various parameters showed that circRNAs were differentially expressed among both groups (P < 0.01, fold change > 2. In the screening phase, we found that 2178 circRNAs were differentially expressed between the control and PE groups, in

  1. Comparison of ATRIA and CHA2DS2-VASc risk stratification schemes for the prediction of stroke in the individual patient with atrial fibrillation and the impact on treatment decisions

    NARCIS (Netherlands)

    Van Den Ham, H.A.; Klungel, O.H.; Singer, D.E.; Leufkens, H.G.M.; Van Staa, T.P.

    2014-01-01

    Purpose: To compare the predictive ability of the currently recommended CHA2DS2-VASc ischaemic stroke risk score with the new ATRIA stroke risk score in patients with atrial fibrillation (AF). Methods: Patients with AF, not using warfarin, were assembled from the Clinical Practice Research Datalink

  2. Value of Combining Left Atrial Diameter and Amino-terminal Pro-brain Natriuretic Peptide to the CHA2DS2-VASc Score for Predicting Stroke and Death in Patients with Sick Sinus Syndrome after Pacemaker Implantation

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    Bin-Feng Mo

    2017-01-01

    Conclusions: CHA2DS2-VASc score is valuable for predicting stroke and death risk in patients with SSS after pacemaker implantation. The addition of LAD and NT-proBNP to the CHA2DS2-VASc score improved its predictive power for stroke and death, respectively, in this patient cohort. Future prospective studies are warranted to validate the benefit of adding LAD and NT-proBNP to the CHA2DS2-VASc score for predicting stroke and death risk in non-AF populations.

  3. Prediction of medial tibiofemoral compartment joint space loss progression using volumetric cartilage measurements: Data from the FNIH OA biomarkers consortium

    Energy Technology Data Exchange (ETDEWEB)

    Hafezi-Nejad, Nima; Demehri, Shadpour [Johns Hopkins University School of Medicine, Musculoskeletal Radiology, Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, MD (United States); Guermazi, Ali [Boston University School of Medicine, Quantitative Imaging Center, Department of Radiology, Boston, MA (United States); Roemer, Frank W. [University of Erlangen-Nuremberg, Department of Radiology, Erlangen (Germany); Hunter, David J. [Royal North Shore Hospital Sydney, Institute of Bone and Joint Research, Kolling Institute, University of Sydney, and Rheumatology Department, Sydney (Australia); Dam, Erik B. [Biomediq, Copenhagen (Denmark); Zikria, Bashir [Johns Hopkins University, Department of Orthopaedic Surgery, Baltimore, MD (United States); Kwoh, C.K. [University of Arizona, Division of Rheumatology and Clinical Immunology, Tucson, AZ (United States)

    2017-02-15

    Investigating the association between baseline cartilage volume measurements (and initial 24th month volume loss) with medial compartment Joint-Space-Loss (JSL) progression (>0.7 mm) during 24-48th months of study. Case and control cohorts (Biomarkers Consortium subset from the Osteoarthritis Initiative (OAI)) were defined as participants with (n=297) and without (n=303) medial JSL progression (during 24-48th months). Cartilage volume measurements (baseline and 24th month loss) were obtained at five knee plates (medial-tibial, lateral-tibial, medial-femoral, lateral-femoral and patellar), and standardized values were analysed. Multivariate logistic regression was used with adjustment for known confounders. Artificial-Neural-Network analysis was conducted by Multi-Layer-Perceptrons (MLPs) including baseline determinants, and baseline (1) and interval changes (2) in cartilage volumes. Larger baseline lateral-femoral cartilage volume was predictive of medial JSL (OR: 1.29 (1.01-1.64)). Greater initial 24th month lateral-femoral cartilage volume-loss (OR: 0.48 (0.27-0.84)) had protective effect on medial JSL during 24-48th months of study. Baseline and interval changes in lateral-femoral cartilage volume, were the most important estimators for medial JSL progression (importance values: 0.191(0.177-0.204), 0.218(0.207-0.228)) in the ANN analyses. Cartilage volumes (both at baseline and their change during the initial 24 months) in the lateral femoral plate were predictive of medial JSL progression. (orig.)

  4. SNPs in genes implicated in radiation response are associated with radiotoxicity and evoke roles as predictive and prognostic biomarkers

    International Nuclear Information System (INIS)

    Alsbeih, Ghazi; El-Sebaie, Medhat; Al-Harbi, Najla; Al-Hadyan, Khaled; Shoukri, Mohamed; Al-Rajhi, Nasser

    2013-01-01

    Biomarkers are needed to individualize cancer radiation treatment. Therefore, we have investigated the association between various risk factors, including single nucleotide polymorphisms (SNPs) in candidate genes and late complications to radiotherapy in our nasopharyngeal cancer patients. A cohort of 155 patients was included. Normal tissue fibrosis was scored using RTOG/EORTC grading system. A total of 45 SNPs in 11 candidate genes (ATM, XRCC1, XRCC3, XRCC4, XRCC5, PRKDC, LIG4, TP53, HDM2, CDKN1A, TGFB1) were genotyped by direct genomic DNA sequencing. Patients with severe fibrosis (cases, G3-4, n = 48) were compared to controls (G0-2, n = 107). Univariate analysis showed significant association (P < 0.05) with radiation complications for 6 SNPs (ATM G/A rs1801516, HDM2 promoter T/G rs2279744 and T/A rs1196333, XRCC1 G/A rs25487, XRCC5 T/C rs1051677 and TGFB1 C/T rs1800469). In addition, Kaplan-Meier analyses have also highlighted significant association between genotypes and length of patients’ follow-up after radiotherapy. Multivariate logistic regression has further sustained these results suggesting predictive and prognostic roles of SNPs. Univariate and multivariate analysis suggest that radiation toxicity in radiotherapy patients are associated with certain SNPs, in genes including HDM2 promoter studied for the 1st time. These results support the use of SNPs as genetic predictive markers for clinical radiosensitivity and evoke a prognostic role for length of patients’ follow-up after radiotherapy

  5. An Evidence-Based Approach to the Use of Predictive Biomarkers in the Treatment of Non- Small Cell Lung Cancer (NSCLC)