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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

    Directory of Open Access Journals (Sweden)

    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 post-treatment FMA, MRC, and pain scores (r = −0.34, −0.31, and 0.25; 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

    Directory of Open Access Journals (Sweden)

    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. Blood Biomarkers for the Early Diagnosis of Stroke: The Stroke-Chip Study.

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    Bustamante, Alejandro; López-Cancio, Elena; Pich, Sara; Penalba, Anna; Giralt, Dolors; García-Berrocoso, Teresa; Ferrer-Costa, Carles; Gasull, Teresa; Hernández-Pérez, María; Millan, Mónica; Rubiera, Marta; Cardona, Pedro; Cano, Luis; Quesada, Helena; Terceño, Mikel; Silva, Yolanda; Castellanos, Mar; Garces, Moisés; Reverté, Silvia; Ustrell, Xavier; Marés, Rafael; Baiges, Joan Josep; Serena, Joaquín; Rubio, Francisco; Salas, Eduardo; Dávalos, Antoni; Montaner, Joan

    2017-09-01

    Stroke diagnosis could be challenging in the acute phase. We aimed to develop a blood-based diagnostic tool to differentiate between real strokes and stroke mimics and between ischemic and hemorrhagic strokes in the hyperacute phase. The Stroke-Chip was a prospective, observational, multicenter study, conducted at 6 Stroke Centers in Catalonia. Consecutive patients with suspected stroke were enrolled within the first 6 hours after symptom onset, and blood samples were drawn immediately after admission. A 21-biomarker panel selected among previous results and from the literature was measured by immunoassays. Outcomes were differentiation between real strokes and stroke mimics and between ischemic and hemorrhagic strokes. Predictive models were developed by combining biomarkers and clinical variables in logistic regression models. Accuracy was evaluated with receiver operating characteristic curves. From August 2012 to December 2013, 1308 patients were included (71.9% ischemic, 14.8% stroke mimics, and 13.3% hemorrhagic). For stroke versus stroke mimics comparison, no biomarker resulted included in the logistic regression model, but it was only integrated by clinical variables, with a predictive accuracy of 80.8%. For ischemic versus hemorrhagic strokes comparison, NT-proBNP (N-Terminal Pro-B-Type Natriuretic Peptide) >4.9 (odds ratio, 2.40; 95% confidence interval, 1.55-3.71; P 4.7 (odds ratio, 2.02; 95% confidence interval, 1.19-3.45; P =0.010), together with age, sex, blood pressure, stroke severity, atrial fibrillation, and hypertension, were included in the model. Predictive accuracy was 80.6%. The studied biomarkers were not sufficient for an accurate differential diagnosis of stroke in the hyperacute setting. Additional discovery of new biomarkers and improvement on laboratory techniques seem necessary for achieving a molecular diagnosis of stroke. © 2017 American Heart Association, Inc.

  6. Prospective of ischemic stroke biomarkers

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    Szewczak Krzysztof

    2017-06-01

    Full Text Available Methods currently used in brain vascular disorder diagnostics are neither fast enough nor clear-out; thus, there exists a necessity of finding new types of testing which could enlarge and complete the actual panel of diagnostics or be an alternative to current methods. The discovery of sensitive and specific biomarkers of ischemic brain stroke will improve the effects of treatment and will help to assess the progress or complications of the disease. The relevant diagnosis of ischemic stroke (IS within the first 4.5 hours after the initial symptoms allows for the initiation of treatment with recombinant tissue plasminogen activators which limits the magnitude of negative changes in the brain and which enhance the final effectiveness of therapy. The potential biomarkers which are under investigation are substances involved in the processes of coagulation and fibrinolysis, and are of molecules released from damaged vascular endothelial cells and from nerves and cardiac tissue. The analyzed substances are typical of oxidative stress, apoptosis, excitotoxicity and damage of the blood brain barrier.

  7. [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

  8. Aetiological blood biomarkers of ischaemic stroke.

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    Sonderer, Julian; Katan Kahles, Mira

    2015-01-01

    Each year, over 5 million people die worldwide from stroke, and at least every sixth patient who survives will experience another stroke within five years [1]. We are therefore eager to advance early and rapid diagnosis, prognosis and optimal risk stratification, as well as secondary prevention. In this context, blood biomarkers may improve patient care, as they have already done in other fields in the past, for example, troponin T/I in patients with heart attacks, natriuretic peptides in patients with heart failure or PCT (procalcitonin) [2] in patients with pneumonia. In the setting of acute stroke, a blood biomarker can be any quantifiable entity that reflects the manifestation of a stroke-related process. The most fruitful implementation of stroke biomarkers is in areas where information from traditional clinical sources is limited. There may be markers, for example, to guide risk stratification, reveal stroke aetiology, identify patients who may benefit most from interventions, monitor treatment efficacy, and recognise the risk of short-term complications or unfavourable long-term outcomes. For this review we focus on blood biomarkers that could help distinguish the underlying aetiology of an ischaemic stroke. Stroke tends to be a much more heterogeneous condition than ischaemic heart disease, which is caused by atherosclerosis in the vast majority of cases. Causes of stroke include small and large vessel disease, cardioembolism, dissections, and rare vasculo- and coagulopathies, among others. Because of this heterogeneity among stroke patients, it is clear that a monolithic approach to stroke prevention or secondary prevention is not warranted. Aetiological classification is important specifically because prognosis, risk of recurrence and management options differ greatly between aetiological subtypes. Considering that today up to 30% of stroke patients still cannot be classified into a specific subtype [3], the ability to improve aetiological classification

  9. Risk Factors and Biomarkers of Ischemic Stroke in Cancer Patients

    OpenAIRE

    Kim, Kwangsoo; Lee, Ji-Hun

    2014-01-01

    Background and Purpose Stroke is common among cancer patients. However, risk factors and biomarkers of stroke in cancer patients are not well established. This study aimed to investigate risk factors and biomarkers as well as etiology of ischemic stroke in cancer patients. Methods A retrospective review was conducted in cancer patients with ischemic stroke who were admitted to a general hospital in Busan, Korea, between January 2003 and December 2012. The risk factors and biomarkers for strok...

  10. 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.

  11. 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.

  12. 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.

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

    African Journals Online (AJOL)

    Stroke is one of the major causes of death and disability, including ischemic stroke, which accounts for 85 - 87 % of cases. Currently, there are few treatment options available for minimizing tissue death following a stroke. Emerging data suggest that biomarkers may help improve current clinical outcome of stroke. As such ...

  14. 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.

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

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    Vella, Antonio

    2017-01-01

    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. PMID:28373915

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

    Science.gov (United States)

    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.

  17. 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...

  18. Repeated Measurements of Cardiac Biomarkers in Atrial Fibrillation and Validation of the ABC Stroke Score Over Time.

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    Hijazi, Ziad; Lindahl, Bertil; Oldgren, Jonas; Andersson, Ulrika; Lindbäck, Johan; Granger, Christopher B; Alexander, John H; Gersh, Bernard J; Hanna, Michael; Harjola, Veli-Pekka; Hylek, Elaine M; Lopes, Renato D; Siegbahn, Agneta; Wallentin, Lars

    2017-06-23

    Cardiac biomarkers are independent risk markers in atrial fibrillation, and the novel biomarker-based ABC stroke score (age, biomarkers, and clinical history of prior stroke) was recently shown to improve the prediction of stroke risk in patients with atrial fibrillation. Our aim was to investigate the short-term variability of the cardiac biomarkers and evaluate whether the ABC stroke risk score provides a stable short-term risk estimate. According to the study protocol, samples were obtained at entry and also at 2 months in 4796 patients with atrial fibrillation followed for a median of 1.8 years in the ARISTOTLE (Apixaban for Reduction in Stroke and Other Thromboembolic Events in Atrial Fibrillation) trial. Cardiac troponin I, cardiac troponin T, and N-terminal pro-B-type natriuretic peptide were measured with high-sensitivity immunoassays. Associations with outcomes were evaluated by Cox regression. C indices and calibration plots were used to evaluate the ABC stroke score at 2 months. The average changes in biomarker levels during 2 months were small (median change cardiac troponin T +2.8%, troponin I +2.0%, and N-terminal pro-B-type natriuretic peptide +13.5%) and within-subject correlation was high (all ≥0.82). Repeated measurement of cardiac biomarkers provided some incremental prognostic value for mortality but not for stroke when combined with clinical risk factors and baseline levels of the biomarkers. Based on 8702 person-years of follow-up and 96 stroke/systemic embolic events, the ABC stroke score at 2 months achieved a similar C index of 0.70 (95% CI, 0.65-0.76) as compared with 0.70 (95% CI, 0.65-0.75) at baseline. The ABC stroke score remained well calibrated using predefined risk classes. In patients with stable atrial fibrillation, the variability of the cardiac biomarkers and the biomarker-based ABC stroke score during 2 months are small. The prognostic information by the ABC stroke score remains consistent and well calibrated with

  19. 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.

  20. Predicting Recovery Potential for Individual Stroke Patients Increases Rehabilitation Efficiency.

    Science.gov (United States)

    Stinear, Cathy M; Byblow, Winston D; Ackerley, Suzanne J; Barber, P Alan; Smith, Marie-Claire

    2017-04-01

    Several clinical measures and biomarkers are associated with motor recovery after stroke, but none are used to guide rehabilitation for individual patients. The objective of this study was to evaluate the implementation of upper limb predictions in stroke rehabilitation, by combining clinical measures and biomarkers using the Predict Recovery Potential (PREP) algorithm. Predictions were provided for patients in the implementation group (n=110) and withheld from the comparison group (n=82). Predictions guided rehabilitation therapy focus for patients in the implementation group. The effects of predictive information on clinical practice (length of stay, therapist confidence, therapy content, and dose) were evaluated. Clinical outcomes (upper limb function, impairment and use, independence, and quality of life) were measured 3 and 6 months poststroke. The primary clinical practice outcome was inpatient length of stay. The primary clinical outcome was Action Research Arm Test score 3 months poststroke. Length of stay was 1 week shorter for the implementation group (11 days; 95% confidence interval, 9-13 days) than the comparison group (17 days; 95% confidence interval, 14-21 days; P =0.001), controlling for upper limb impairment, age, sex, and comorbidities. Therapists were more confident ( P =0.004) and modified therapy content according to predictions for the implementation group ( P rehabilitation efficiency after stroke without compromising clinical outcome. URL: http://anzctr.org.au. Unique identifier: ACTRN12611000755932. © 2017 American Heart Association, Inc.

  1. 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)

  2. Gene expression profiling of blood for the prediction of ischemic stroke.

    Science.gov (United States)

    Stamova, Boryana; Xu, Huichun; Jickling, Glen; Bushnell, Cheryl; Tian, Yingfang; Ander, Bradley P; Zhan, Xinhua; Liu, Dazhi; Turner, Renee; Adamczyk, Peter; Khoury, Jane C; Pancioli, Arthur; Jauch, Edward; Broderick, Joseph P; Sharp, Frank R

    2010-10-01

    A blood-based biomarker of acute ischemic stroke would be of significant value in clinical practice. This study aimed to (1) replicate in a larger cohort our previous study using gene expression profiling to predict ischemic stroke; and (2) refine prediction of ischemic stroke by including control groups relevant to ischemic stroke. Patients with ischemic stroke (n=70, 199 samples) were compared with control subjects who were healthy (n=38), had vascular risk factors (n=52), and who had myocardial infarction (n=17). Whole blood was drawn ≤3 hours, 5 hours, and 24 hours after stroke onset and from control subjects. RNA was processed on whole genome microarrays. Genes differentially expressed in ischemic stroke were identified and analyzed for predictive ability to discriminate stroke from control subjects. The 29 probe sets previously reported predicted a new set of ischemic strokes with 93.5% sensitivity and 89.5% specificity. Sixty- and 46-probe sets differentiated control groups from 3-hour and 24-hour ischemic stroke samples, respectively. A 97-probe set correctly classified 86% of ischemic strokes (3 hour+24 hour), 84% of healthy subjects, 96% of vascular risk factor subjects, and 75% with myocardial infarction. This study replicated our previously reported gene expression profile in a larger cohort and identified additional genes that discriminate ischemic stroke from relevant control groups. This multigene approach shows potential for a point-of-care test in acute ischemic stroke.

  3. Predicting Clinical Outcomes Using Molecular Biomarkers

    Directory of Open Access Journals (Sweden)

    Harry B. Burke

    2016-01-01

    Full Text Available Over the past 20 years, there has been an exponential increase in the number of biomarkers. At the last count, there were 768,259 papers indexed in PubMed.gov directly related to biomarkers. Although many of these papers claim to report clinically useful molecular biomarkers, embarrassingly few are currently in clinical use. It is suggested that a failure to properly understand, clinically assess, and utilize molecular biomarkers has prevented their widespread adoption in treatment, in comparative benefit analyses, and their integration into individualized patient outcome predictions for clinical decision-making and therapy. A straightforward, general approach to understanding how to predict clinical outcomes using risk, diagnostic, and prognostic molecular biomarkers is presented. In the future, molecular biomarkers will drive advances in risk, diagnosis, and prognosis, they will be the targets of powerful molecular therapies, and they will individualize and optimize therapy. Furthermore, clinical predictions based on molecular biomarkers will be displayed on the clinician's screen during the physician–patient interaction, they will be an integral part of physician–patient-shared decision-making, and they will improve clinical care and patient outcomes.

  4. Update on Inflammatory Biomarkers and Treatments in Ischemic Stroke

    Directory of Open Access Journals (Sweden)

    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.

  5. Novel biomarkers for cardiovascular risk prediction.

    Science.gov (United States)

    Wang, Juan; Tan, Guo-Juan; Han, Li-Na; Bai, Yong-Yi; He, Miao; Liu, Hong-Bin

    2017-02-01

    Cardiovascular disease (CVD) is the leading cause of death and disability worldwide. The primary prevention of CVD is dependent upon the ability to identify high-risk individuals long before the development of overt events. This highlights the need for accurate risk stratification. An increasing number of novel biomarkers have been identified to predict cardiovascular events. Biomarkers play a critical role in the definition, prognostication, and decision-making regarding the management of cardiovascular events. This review focuses on a variety of promising biomarkers that provide diagnostic and prognostic information. The myocardial tissue-specific biomarker cardiac troponin, high-sensitivity assays for cardiac troponin, and heart-type fatty acid binding proteinall help diagnose myocardial infarction (MI) in the early hours following symptoms. Inflammatory markers such as growth differentiation factor-15, high-sensitivity C-reactive protein, fibrinogen, and uric acid predict MI and death. Pregnancy-associated plasma protein A, myeloperoxidase, and matrix metalloproteinases predict the risk of acute coronary syndrome. Lipoprotein-associated phospholipase A2 and secretory phospholipase A2 predict incident and recurrent cardiovascular events. Finally, elevated natriuretic peptides, ST2, endothelin-1, mid-regional-pro-adrenomedullin, copeptin, and galectin-3 have all been well validated to predict death and heart failure following a MI and provide risk stratification information for heart failure. Rapidly developing new areas, such as assessment of micro-RNA, are also explored. All the biomarkers reflect different aspects of the development of atherosclerosis.

  6. Gene expression in peripheral blood differs after cardioembolic compared with large-vessel atherosclerotic stroke: biomarkers for the etiology of ischemic stroke.

    Science.gov (United States)

    Xu, Huichun; Tang, Yang; Liu, Da-Zhi; Ran, Ruiqiong; Ander, Bradley P; Apperson, Michelle; Liu, Xin She; Khoury, Jane C; Gregg, Jeffrey P; Pancioli, Arthur; Jauch, Edward C; Wagner, Kenneth R; Verro, Piero; Broderick, Joseph P; Sharp, Frank R

    2008-07-01

    There are no biomarkers that differentiate cardioembolic from large-vessel atherosclerotic stroke, although the treatments differ for each and approximately 30% of strokes and transient ischemic attacks have undetermined etiologies using current clinical criteria. We aimed to define gene expression profiles in blood that differentiate cardioembolic from large-vessel atherosclerotic stroke. Peripheral blood samples were obtained from healthy controls and acute ischemic stroke patients (genes differ at least 1.5-fold between them, and a minimum number of 23 genes differentiate the two types of stroke with at least 95.2% specificity and 95.2% sensitivity for each. Genes regulated in large-vessel atherosclerotic stroke are expressed in platelets and monocytes and modulate hemostasis. Genes regulated in cardioembolic stroke are expressed in neutrophils and modulate immune responses to infectious stimuli. This new method can be used to predict whether a stroke of unknown etiology was because of cardioembolism or large-vessel atherosclerosis that would lead to different therapy. These results have wide ranging implications for similar disorders.

  7. Galectin-3: an emerging biomarker in stroke and cerebrovascular diseases.

    Science.gov (United States)

    Venkatraman, A; Hardas, S; Patel, N; Singh Bajaj, N; Arora, G; Arora, P

    2018-02-01

    The carbohydrate-binding molecule galectin-3 has garnered significant attention recently as a biomarker for various conditions ranging from cardiac disease to obesity. Although there have been several recent studies investigating its role in stroke and other cerebrovascular diseases, awareness of this emerging biomarker in the wider neurology community is limited. We performed a systematic search in PubMed, Embase, Scopus, CINAHL, Clinicaltrials.gov and the Cochrane library in November and December 2016 for articles related to galectin-3 and cerebrovascular disease. We included both human and pre-clinical studies in order to provide a comprehensive view of the state of the literature on this topic. The majority of the relevant literature focuses on stroke, cerebral ischemia and atherosclerosis, but some recent attention has also been devoted to intracranial and subarachnoid hemorrhage. Higher blood levels of galectin-3 correlate with worse outcomes in atherosclerotic disease as well as in intracranial and subarachnoid hemorrhage in human studies. However, experimental evidence supporting the role of galectin-3 in these phenotypes is not as robust. It is likely that the role of galectin-3 in the inflammatory cascade within the central nervous system following injury is responsible for many of its effects, but its varied physiological functions and multiple sites of expression mean that it may have different effects depending on the nature of the disease condition and the time since injury. In summary, experimental and human research raises the possibility that galectin-3, which is closely linked to the inflammatory cascade, could be of value as a prognostic marker and therapeutic target in cerebrovascular disease. © 2017 EAN.

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

    Directory of Open Access Journals (Sweden)

    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.

  9. 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.

  10. Relevance of Post-Stroke Circulating BDNF Levels as a Prognostic Biomarker of Stroke Outcome. Impact of rt-PA Treatment.

    Science.gov (United States)

    Rodier, Marion; Quirié, Aurore; Prigent-Tessier, Anne; Béjot, Yannick; Jacquin, Agnès; Mossiat, Claude; Marie, Christine; Garnier, Philippe

    2015-01-01

    The recombinant form of tissue plasminogen activator (rt-PA) is the only curative treatment for ischemic stroke. Recently, t-PA has been linked to the metabolism of brain-derived neurotrophic factor (BDNF), a major neurotrophin involved in post-stroke neuroplasticity. Thus, the objective of our study was to investigate the impact of rt-PA treatment on post-stroke circulating BDNF levels in humans and in animals. Serum BDNF levels and t-PA/plasmin activity were measured at hospital admission and at up to 90 days in stroke patients receiving (n = 24) or not (n = 14) rt-PA perfusion. We investigated the relationships between serum BDNF with concurrent t-PA/plasmin activity, neurological outcomes and cardiovascular scores at admission. In parallel, serum BDNF levels and t-PA/plasmin activity were assessed before and after (1, 4 and 24h) the induction of ischemic stroke in rats. Our study revealed higher serum BDNF levels and better neurological outcome in rt-PA-treated than non-treated patients. However, serum BDNF levels did not predict stroke outcome when the whole cohort of stroke patients was analyzed. By contrast, serum BDNF levels when measured at admission and at day 90 correlated with cardiovascular scores, and those at day 1 correlated with serum t-PA/plasmin activity in the whole cohort of patients whereas no association could be found in the rt-PA-treated group. In rats devoid of cardiovascular risk, no difference in post-stroke serum BDNF levels was detected between rt-PA- and vehicle-treated animals and no correlation was found between serum BDNF levels and t-PA/plasmin activity. Overall, the data suggest that serum BDNF levels may not be useful as a prognostic biomarker of stroke outcome and that endothelial dysfunction could be a confounding factor when serum BDNF levels after stroke are used to reflect of brain BDNF levels.

  11. 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...... 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...

  12. Apolipoprotein A-I and Paraoxonase-1 Are Potential Blood Biomarkers for Ischemic Stroke Diagnosis.

    Science.gov (United States)

    Walsh, Kyle B; Hart, Kimberly; Roll, Susan; Sperling, Matthew; Unruh, Dusten; Davidson, W Sean; Lindsell, Christopher J; Adeoye, Opeolu

    2016-06-01

    Blood biomarkers for ischemic and hemorrhagic stroke diagnosis remain elusive. Recent investigations suggested that apolipoprotein (Apo), matrix metalloproteinase (MMP), and paraoxonase-1 may be associated with stroke. We hypothesized that Apo A-I, Apo C-I, Apo C-III, MMP-3, MMP-9, and paraoxonase-1 are differentially expressed in ischemic stroke, hemorrhagic stroke, and controls. In a single-center prospective observational study, consecutive stroke cases were enrolled if blood samples were obtainable within 12 hours of symptom onset. Age- (±5 years), race-, and sex-matched controls were recruited. Multiplex assays were used to measure protein levels. The Wilcoxon signed-rank test and the Mann-Whitney U-test were used to compare biomarker values between ischemic stroke patients and controls, hemorrhagic stroke patients and controls, and ischemic and hemorrhagic stroke patients. The 95% confidence intervals (CIs) for the difference of 2 medians were calculated. Fourteen ischemic stroke case-control pairs and 23 intracerebral hemorrhage (ICH) case-control pairs were enrolled. Median Apo A-I levels were lower in ischemic stroke cases versus controls (140 mg/dL versus 175 mg/dL, difference of 35 mg/dL, 95% CI -54 to -16) and in ischemic stroke versus ICH cases (140 mg/dL versus 180 mg/dL, difference of 40 mg/dL, 95% CI -57 to -23). Median paraoxonase-1 was lower in ischemic stroke cases than in both ICH cases and matched controls. Median Apo C-I was slightly lower in ischemic stroke cases than in ICH cases. There were no differences between groups for MMP-3, MMP-9, and Apo C-III. Apo A-I and paraoxonase-1 levels may be clinically useful for ischemic stroke diagnosis and for differentiating between ischemic and hemorrhagic strokes. Copyright © 2016 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  13. The stroke-thrombolytic predictive instrument: a predictive instrument for intravenous thrombolysis in acute ischemic stroke.

    Science.gov (United States)

    Kent, David M; Selker, Harry P; Ruthazer, Robin; Bluhmki, Erich; Hacke, Werner

    2006-12-01

    Many patients with ischemic stroke eligible for recombinant tissue plasminogen activator (rt-PA) are not treated in part because of the risks and benefits perceived by treating physicians. Therefore, we aimed to develop a Stroke-Thrombolytic Predictive Instrument (TPI) to aid physicians considering thrombolysis for stroke. Using data from 5 major randomized clinical trials (n=2184) testing rt-PA in the 0- to 6-hour window, we developed logistic regression equations using clinical variables as potential predictors of a good outcome (modified Rankin Scale score or =5), with and without rt-PA. The models were internally validated using bootstrap re-sampling. To predict good outcome, in addition to rt-PA treatment, 7 variables significantly affected prognosis and/or the treatment-effect of rt-PA: age, diabetes, stroke severity, sex, previous stroke, systolic blood pressure, and time from symptom onset. To predict catastrophic outcome, only age, stroke severity, and serum glucose were significant; rt-PA treatment was not. For patients treated within 3 hours, the median predicted probability of a good outcome with rt-PA was 42.9% (interquartile range [IQR]=18.6% to 64.7%) versus 25.3% (IQR=9.8% to 46.2%) without rt-PA; the median predicted absolute benefit was 12.5% (IQR=5.1% to 21.0%). The median probability for a catastrophic outcome, with or without, rt-PA was 15.2% (IQR=8.0% to 31.2%). The area under the receiver-operator characteristic curve was 0.788 for the model predicting good outcome and 0.775 for the model predicting bad outcome. The Stroke-TPI predicts good and bad functional outcomes with and without thrombolysis. Incorporated into a usable tool, it may assist in decision-making.

  14. Robotic measurement of arm movements after stroke establishes biomarkers of motor recovery.

    Science.gov (United States)

    Krebs, Hermano I; Krams, Michael; Agrafiotis, Dimitris K; DiBernardo, Allitia; Chavez, Juan C; Littman, Gary S; Yang, Eric; Byttebier, Geert; Dipietro, Laura; Rykman, Avrielle; McArthur, Kate; Hajjar, Karim; Lees, Kennedy R; Volpe, Bruce T

    2014-01-01

    Because robotic devices record the kinematics and kinetics of human movements with high resolution, we hypothesized that robotic measures collected longitudinally in patients after stroke would bear a significant relationship to standard clinical outcome measures and, therefore, might provide superior biomarkers. In patients with moderate-to-severe acute ischemic stroke, we used clinical scales and robotic devices to measure arm movement 7, 14, 21, 30, and 90 days after the event at 2 clinical sites. The robots are interactive devices that measure speed, position, and force so that calculated kinematic and kinetic parameters could be compared with clinical assessments. Among 208 patients, robotic measures predicted well the clinical measures (cross-validated R(2) of modified Rankin scale=0.60; National Institutes of Health Stroke Scale=0.63; Fugl-Meyer=0.73; Motor Power=0.75). When suitably scaled and combined by an artificial neural network, the robotic measures demonstrated greater sensitivity in measuring the recovery of patients from day 7 to day 90 (increased standardized effect=1.47). These results demonstrate that robotic measures of motor performance will more than adequately capture outcome, and the altered effect size will reduce the required sample size. Reducing sample size will likely improve study efficiency.

  15. Robotic Measurement of Arm Movements After Stroke Establishes Biomarkers of Motor Recovery

    Science.gov (United States)

    Krebs, Hermano I.; Krams, Michael; Agrafiotis, Dimitris K.; DiBernardo, Allitia; Chavez, Juan C.; Littman, Gary S.; Yang, Eric; Byttebier, Geert; Dipietro, Laura; Rykman, Avrielle; McArthur, Kate; Hajjar, Karim; Lees, Kennedy R.; Volpe, Bruce T.

    2015-01-01

    Background and Purpose Because robotic devices record the kinematics and kinetics of human movements with high resolution, we hypothesized that robotic measures collected longitudinally in patients after stroke would bear a significant relationship to standard clinical outcome measures and, therefore, might provide superior biomarkers. Methods In patients with moderate-to-severe acute ischemic stroke, we used clinical scales and robotic devices to measure arm movement 7, 14, 21, 30, and 90 days after the event at 2 clinical sites. The robots are interactive devices that measure speed, position, and force so that calculated kinematic and kinetic parameters could be compared with clinical assessments. Results Among 208 patients, robotic measures predicted well the clinical measures (cross-validated R2 of modified Rankin scale=0.60; National Institutes of Health Stroke Scale=0.63; Fugl-Meyer=0.73; Motor Power=0.75). When suitably scaled and combined by an artificial neural network, the robotic measures demonstrated greater sensitivity in measuring the recovery of patients from day 7 to day 90 (increased standardized effect=1.47). Conclusions These results demonstrate that robotic measures of motor performance will more than adequately capture outcome, and the altered effect size will reduce the required sample size. Reducing sample size will likely improve study efficiency. PMID:24335224

  16. Cell-free DNA as a biomarker in stroke: Current status, problems and perspectives.

    Science.gov (United States)

    Glebova, Kristina V; Veiko, Natalya N; Nikonov, Aleksey A; Porokhovnik, Lev N; Kostuyk, Svetlana V

    2018-01-01

    There is currently no proposed stroke biomarker with consistent application in clinical practice. A number of studies have examined cell-free DNA (cfDNA), which circulates in biological fluids during stroke, as a potential biomarker of this disease. The data available suggest that dynamically-determined levels of blood cfDNA may provide new prognostic information for assessment of stroke severity and outcome. However, such an approach has its own difficulties and limitations. This review covers the potential role of cfDNA as a biomarker in stroke, and includes evidence from both animal models and clinical studies, protocols used to analyze cfDNA, and hypotheses on the origin of cfDNA.

  17. 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.

  18. Prevalence of Imaging Biomarkers to Guide the Planning of Acute Stroke Reperfusion Trials.

    Science.gov (United States)

    Jiang, Bin; Ball, Robyn L; Michel, Patrik; Jovin, Tudor; Desai, Manisha; Eskandari, Ashraf; Naqvi, Zack; Wintermark, Max

    2017-06-01

    Imaging biomarkers are increasingly used as selection criteria for stroke clinical trials. The goal of our study was to determine the prevalence of commonly studied imaging biomarkers in different time windows after acute ischemic stroke onset to better facilitate the design of stroke clinical trials using such biomarkers for patient selection. This retrospective study included 612 patients admitted with a clinical suspicion of acute ischemic stroke with symptom onset no more than 24 hours before completing baseline imaging. Patients with subacute/chronic/remote infarcts and hemorrhage were excluded from this study. Imaging biomarkers were extracted from baseline imaging, which included a noncontrast head computed tomography (CT), perfusion CT, and CT angiography. The prevalence of dichotomized versions of each of the imaging biomarkers in several time windows (time since symptom onset) was assessed and statistically modeled to assess time dependence (not lack thereof). We created tables showing the prevalence of the imaging biomarkers pertaining to the core, the penumbra and the arterial occlusion for different time windows. All continuous imaging features vary over time. The dichotomized imaging features that vary significantly over time include: noncontrast head computed tomography Alberta Stroke Program Early CT (ASPECT) score and dense artery sign, perfusion CT infarct volume, and CT angiography collateral score and visible clot. The dichotomized imaging features that did not vary significantly over time include the thresholded perfusion CT penumbra volumes. As part of the feasibility analysis in stroke clinical trials, this analysis and the resulting tables can help investigators determine sample size and the number needed to screen. © 2017 American Heart Association, Inc.

  19. 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

  20. (Very) Early technology assessment and translation of predictive biomarkers in breast cancer

    NARCIS (Netherlands)

    Miquel-Cases, Anna; Schouten, Philip C; Steuten, Lotte M G; Retèl, Valesca P; Linn, Sabine C; van Harten, Wim H

    Predictive biomarkers can guide treatment decisions in breast cancer. Many studies are undertaken to discover and translate these biomarkers, yet few biomarkers make it to practice. Before use in clinical decision making, predictive biomarkers need to demonstrate analytical validity, clinical

  1. (Very) Early technology assessment and translation of predictive biomarkers in breast cancer

    NARCIS (Netherlands)

    Miquel-Cases, Anna; Schouten, Philip C.; Steuten, Lotte M.G.; Retèl, Valesca P.; Linn, Sabine C.; van Harten, Wim H.

    2017-01-01

    Predictive biomarkers can guide treatment decisions in breast cancer. Many studies are undertaken to discover and translate these biomarkers, yet few biomarkers make it to practice. Before use in clinical decision making, predictive biomarkers need to demonstrate analytical validity, clinical

  2. Prospective clinical biomarkers of caspase-mediated apoptosis associated with neuronal and neurovascular damage following stroke and other severe brain injuries: Implications for chronic neurodegeneration

    Directory of Open Access Journals (Sweden)

    Olena Y Glushakova

    2017-01-01

    Full Text Available Acute brain injuries, including ischemic and hemorrhagic stroke, as well as traumatic brain injury (TBI, are major worldwide health concerns with very limited options for effective diagnosis and treatment. Stroke and TBI pose an increased risk for the development of chronic neurodegenerative diseases, notably chronic traumatic encephalopathy, Alzheimer's disease, and Parkinson's disease. The existence of premorbid neurodegenerative diseases can exacerbate the severity and prognosis of acute brain injuries. Apoptosis involving caspase-3 is one of the most common mechanisms involved in the etiopathology of both acute and chronic neurological and neurodegenerative diseases, suggesting a relationship between these disorders. Over the past two decades, several clinical biomarkers of apoptosis have been identified in cerebrospinal fluid and peripheral blood following ischemic stroke, intracerebral and subarachnoid hemorrhage, and TBI. These biomarkers include selected caspases, notably caspase-3 and its specific cleavage products such as caspase-cleaved cytokeratin-18, caspase-cleaved tau, and a caspase-specific 120 kDa αII-spectrin breakdown product. The levels of these biomarkers might be a valuable tool for the identification of pathological pathways such as apoptosis and inflammation involved in injury progression, assessment of injury severity, and prediction of clinical outcomes. This review focuses on clinical studies involving biomarkers of caspase-3-mediated pathways, following stroke and TBI. The review further examines their prospective diagnostic utility, as well as clinical utility for improved personalized treatment of stroke and TBI patients and the development of prophylactic treatment chronic neurodegenerative disease.

  3. Circulating MicroRNAs as Biomarkers of Acute Stroke

    Directory of Open Access Journals (Sweden)

    Sugunavathi Sepramaniam

    2014-01-01

    Full Text Available MicroRNAs have been identified as key regulators of gene expression and thus their potential in disease diagnostics, prognosis and therapy is being actively pursued. Deregulation of microRNAs in cerebral pathogenesis has been reported to a limited extent in both animal models and human. Due to the complexity of the pathology, identifying stroke specific microRNAs has been a challenge. This study shows that microRNA profiles reflect not only the temporal progression of stroke but also the specific etiologies. A panel of 32 microRNAs, which could differentiate stroke etiologies during acute phase was identified and verified using a customized TaqMan Low Density Array (TLDA. Furthermore we also found 5 microRNAs, miR-125b-2*, -27a*, -422a, -488 and -627 to be consistently altered in acute stroke irrespective of age or severity or confounding metabolic complications. Differential expression of these 5 microRNAs was also observed in rat stroke models. Hence, their specificity to the stroke pathology emphasizes the possibility of developing these microRNAs into accurate and useful tools for diagnosis of stroke.

  4. 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

  5. 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.......Aim: We aimed to construct and validate a model based on biomarkers to predict complete primary debulking surgery for ovarian cancer patients....

  6. Predicting outcome after stroke: the role of basic activities of daily living predicting outcome after stroke.

    Science.gov (United States)

    Gialanella, B; Santoro, R; Ferlucci, C

    2013-10-01

    Very few studies have investigated the influence of single activities of daily living (ADL) at admission as possible predictors of functional outcome after rehabilitation. The aim of the current study was to investigate admission functional status and performance of basic ADLs as assessed by Functional Independence Measure (FIM) scale as possible predictors of motor and functional outcome after stroke during inpatient rehabilitation. This is a prospective and observational study. Inpatients of our Department of Physical Medicine and Rehabilitation. Two hundred sixty consecutive patients with primary diagnosis of stroke were enrolled and 241 patients were used in the final analyses. Two backward stepwise regression analyses were applied to predict outcome. The first backward stepwise regression had age, gender, stroke type, stroke-lesion size, aphasia, neglect, onset to admission interval, Cumulative Illness Rating Scale, National Institute of Health Stroke Scale (NIHSS), Fugl-Meyer Scale, Trunk Control Test, and FIM (total, motor and cognitive scores) as independent variables. The second analyses included the above variables plus FIM items as an independent variable. The dependent variables were the discharge scores and effectiveness in total and motor-FIM, and discharge destination. The first multivariate analysis showed that admission Fugl-Meyer, neglect, total, motor and cognitive FIM scores were the most important predictors of FIM outcomes, while admission NIHSS score was the only predictor of discharge destination. Conversely, when admission single FIM items were included in the statistical model, admission Fugl-Meyer, neglect, grooming, dressing upper body, and social interaction scores were the most important predictors of FIM outcomes, while admission memory and bowel control scores were the only predictors of discharge destination. Our study indicates that performances of basic ADLs are important stroke outcome predictors and among which social

  7. 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....

  8. Workup for Perinatal Stroke Does Not Predict Recurrence.

    Science.gov (United States)

    Lehman, Laura L; Beaute, Jeanette; Kapur, Kush; Danehy, Amy R; Bernson-Leung, Miya E; Malkin, Hayley; Rivkin, Michael J; Trenor, Cameron C

    2017-08-01

    Perinatal stroke, including neonatal and presumed perinatal presentation, represents the age in childhood in which stroke occurs most frequently. The roles of thrombophilia, arteriopathy, and cardiac anomalies in perinatal ischemic stroke are currently unclear. We took a uniform approach to perinatal ischemic stroke evaluation to study these risk factors and their association with recurrent stroke. We reviewed records of perinatal stroke patients evaluated from August 2008 to February 2016 at a single referral center. Demographics, echocardiography, arterial imaging, and thrombophilia testing were collected. Statistical analysis was performed using Fisher exact test. Across 215 cases, the median follow-up was 3.17 years (1.49, 6.46). Females comprised 42.8% of cases. Age of presentation was neonatal (110, 51.2%) or presumed perinatal (105, 48.8%). The median age at diagnosis was 2.9 days (interquartile range, 2.0-9.9) for neonatal stroke and 12.9 months (interquartile range, 8.7-32.8) for presumed perinatal stroke. Strokes were classified as arterial (149, 69.3%), venous (60, 27.9%), both (4, 1.9%), or uncertain (2, 0.9%) by consensus imaging review. Of the 215 cases, there were 6 (2.8%) recurrent ischemic cerebrovascular events. Abnormal thrombophilia testing was not associated with recurrent stroke, except for a single patient with combined antithrombin deficiency and protein C deficiency. After excluding venous events, 155 patients were evaluated for arteriopathy and cardioembolic risk factors; neither was associated with recurrent stroke. Positive family history of thrombosis was not predictive of abnormal thrombophilia testing. Thrombophilia, arteriopathy, or cardioembolic risk factors were not predictive of recurrent events after perinatal stroke. Thrombophilia evaluation in perinatal stroke should only rarely be considered. © 2017 American Heart Association, Inc.

  9. Early depressed mood after stroke predicts long-term disability: the Northern Manhattan Stroke Study (NOMASS).

    Science.gov (United States)

    Willey, Joshua Z; Disla, Norbelina; Moon, Yeseon Park; Paik, Myunghee C; Sacco, Ralph L; Boden-Albala, Bernadette; Elkind, Mitchell S V; Wright, Clinton B

    2010-09-01

    Depression is highly prevalent after stroke and may influence recovery. We aimed to determine whether depressed mood acutely after stroke predicts subsequent disability and mortality. As part of the Northern Manhattan Stroke Study, a population-based incident stroke case follow-up study performed in a multiethnic urban population, participants were asked about depressed mood within 7 to 10 days after stroke. Participants were followed every 6 months the first 2 years and yearly thereafter for 5 years for death and disability measured by the Barthel Index. We fitted polytomous logistic regression models using a canonical link to examine the association between depressed mood after stroke and disability comparing moderate (Barthel Index 60 to 95) and severe (Barthel Index or=95). Cox proportional hazards models were created to examine the association between depressed mood and mortality. A question about depressed mood within 7 to 10 days after stroke was asked in 340 of 655 patients with ischemic stroke enrolled, and 139 reported that they felt depressed. In multivariate analyses controlling for sociodemographic factors, stroke severity, and medical conditions, depressed mood was associated with a greater odds of severe disability compared with no disability at 1 (OR 2.91, 95% CI 1.07 to 7.91) and 2 years (OR 3.72, 95% CI 1.29 to 10.71) after stroke. Depressed mood was not associated with all-cause mortality or vascular death. Depressed mood after stroke is associated with disability but not mortality after stroke. Early screening and intervention for mood disorders after stroke may improve outcomes and requires further research.

  10. Association of Osteopontin, Neopterin, and Myeloperoxidase With Stroke Risk in Patients With Prior Stroke or Transient Ischemic Attacks: Results of an Analysis of 13 Biomarkers From the Stroke Prevention by Aggressive Reduction in Cholesterol Levels Trial.

    Science.gov (United States)

    Ganz, Peter; Amarenco, Pierre; Goldstein, Larry B; Sillesen, Henrik; Bao, Weihang; Preston, Gregory M; Welch, K Michael A

    2017-12-01

    Established risk factors do not fully identify patients at risk for recurrent stroke. The SPARCL trial (Stroke Prevention by Aggressive Reduction in Cholesterol Levels) evaluated the effect of atorvastatin on stroke risk in patients with a recent stroke or transient ischemic attack and no known coronary heart disease. This analysis explored the relationships between 13 plasma biomarkers assessed at trial enrollment and the occurrence of outcome strokes. We conducted a case-cohort study of 2176 participants; 562 had outcome strokes and 1614 were selected randomly from those without outcome strokes. Time to stroke was evaluated by Cox proportional hazards models. There was no association between time to stroke and lipoprotein-associated phospholipase A 2 , monocyte chemoattractant protein-1, resistin, matrix metalloproteinase-9, N-terminal fragment of pro-B-type natriuretic peptide, soluble vascular cell adhesion molecule-1, soluble intercellular adhesion molecule-1, or soluble CD40 ligand. In adjusted analyses, osteopontin (hazard ratio per SD change, 1.362; P strokes. After adjustment for the Stroke Prognostic Instrument-II and treatment, osteopontin, neopterin, and myeloperoxidase remained independently associated with outcome strokes. The addition of these 3 biomarkers to Stroke Prognostic Instrument-II increased the area under the receiver operating characteristic curve by 0.023 ( P =0.015) and yielded a continuous net reclassification improvement (29.1%; P stroke and improved risk classification when added to a clinical risk algorithm. URL: http://www.clinicaltrials.gov. Unique Identifier: NCT00147602. © 2017 American Heart Association, Inc.

  11. Long-Term Stroke Risk Prediction in Patients With Atrial Fibrillation: Comparison of the ABC-Stroke and CHA2DS2-VASc Scores.

    Science.gov (United States)

    Rivera-Caravaca, José Miguel; Roldán, Vanessa; Esteve-Pastor, María Asunción; Valdés, Mariano; Vicente, Vicente; Lip, Gregory Y H; Marín, Francisco

    2017-07-20

    The ABC-stroke score (age, biomarkers [N-terminal fragment B-type natriuretic peptide, high-sensitivity troponin], and clinical history [prior stroke/transient ischemic attack]) was proposed to predict stroke in atrial fibrillation (AF). This score was derived/validated in 2 clinical trial cohorts in which patients with AF were highly selected and carefully followed-up. However, the median follow-up was 1.9 years in the trial cohort; therefore, its long-term predictive performance remains uncertain. This study aimed to compare the long-term predictive performances of the ABC-stroke and CHA 2 DS 2 -VASc (cardiac failure or dysfunction, hypertension, age ≥75 [doubled], diabetes mellitus, stroke [doubled]-vascular disease, age 65 to 74 years and sex category [female]) scores in a cohort of anticoagulated patients with AF. We recruited 1125 consecutive patients with AF who were stable on vitamin K antagonists and followed-up for a median of 6.5 years. ABC-stroke and CHA 2 DS 2 -VASc (cardiac failure or dysfunction, hypertension, age ≥75 [doubled], diabetes mellitus, stroke [doubled]-vascular disease, age 65 to 74 years and sex category [female]) scores were calculated and compared. Median CHA 2 DS 2 -VASc and ABC-stroke scores were 4 (interquartile range 3-5) and 9.1 (interquartile range 7.3-11.3), respectively. There were 114 ischemic strokes (1.55% per year) at 6.5 years. The C-index of ABC-stroke at 3.5 years was significantly higher than CHA 2 DS 2 -VASc (0.663 versus 0.600, P =0.046), but both C-indexes were nonsignificantly different at 6.5 years. Integrated discrimination improvement showed a small improvement (ABC-stroke. For ABC-stroke, net reclassification improvement was nonsignificantly different at 3.5 years, and showed a negative reclassification at 6.5 years compared with CHA 2 DS 2 -VASc. Decision curve analyses did not show a marked improvement in clinical usefulness of the ABC-stroke score over the CHA 2 DS 2 -VASc score. In

  12. Identification of Site-Specific Stroke Biomarker Candidates by Laser Capture Microdissection and Labeled Reference Peptide

    Directory of Open Access Journals (Sweden)

    Tingting Lian

    2015-06-01

    Full Text Available The search to date for accurate protein biomarkers in acute ischemic stroke has taken into consideration the stage and/or the size of infarction, but has not accounted for the site of stroke. In the present study, multiple reaction monitoring using labeled reference peptide (LRP following laser capture microdissection (LCM is used to identify site-specific protein biomarker candidates. In middle cerebral artery occlusion (MCAO rat models, both intact and infarcted brain tissue was collected by LCM, followed by on-film digestion and semi-quantification using triple-quadrupole mass spectrometry. Thirty-four unique peptides were detected for the verification of 12 proteins in both tissue homogenates and LCM-captured samples. Six insoluble proteins, including neurofilament light polypeptide (NEFL, alpha-internexin (INA, microtubule-associated protein 2 (MAP2, myelin basic protein (MBP, myelin proteolipid protein (PLP and 2′,3′-cyclic-nucleotide 3′-phosphodiesterase (CNP, were found to be site-specific. Soluble proteins, such as neuron-specific enolase (NSE and ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCHL1, and some insoluble proteins, including neurofilament heavy polypeptide (NEFH, glial fibrillary acidic protein (GFAP, microtubule-associated protein tau (MAPT and tubulin β-3 chain (TUBB3, were found to be evenly distributed in the brain. Therefore, we conclude that some insoluble protein biomarkers for stroke are site-specific, and would make excellent candidates for the design and analysis of relevant clinical studies in the future.

  13. 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...

  14. Selected nutritional biomarkers predict diet quality.

    Science.gov (United States)

    Neuhouser, Marian L; Patterson, Ruth E; King, Irena B; Horner, Neilann K; Lampe, Johanna W

    2003-10-01

    To examine associations of biomarkers of nutrient intake with overall diet quality. A convenience sample of 102 healthy postmenopausal women in Seattle, Washington (USA). Participants attended a study centre where they provided fasting blood specimens and completed a 122-item validated food-frequency questionnaire (FFQ). Data from the FFQ were used to calculate Diet Quality Index (DQI) scores and categorise women as having diets of excellent, good, fair or poor quality. The blood specimens were analysed for nine phospholipid fatty acids (as percentage of total) and serum concentrations of vitamin C, alpha-tocopherol, gamma-tocopherol, vitamin B12, folate and six carotenoids. Multivariate linear regression was used to model associations of the nutrient biomarkers with DQI scores. Compared with women with poor-quality diets, women with excellent diets, as measured by the DQI, had higher plasma concentrations of vitamin C (P for trend=0.01), alpha-tocopherol (P for trend=0.02) and beta-cryptoxanthin (P for trend=0.03). Women with excellent diets also had lower proportions of plasma phospholipid fatty acids of two potentially atherogenic fatty acids: stearic acid (P for trend=0.01) and behenic acid (P for trend=0.03). A group of six biomarkers explained a moderate proportion of the total variability in DQI scores (36%). These objective measures of dietary intake support the use of the DQI as a useful tool to measure dietary patterns.

  15. 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

  16. 18F-FDG PET/CT imaging factors that predict ischaemic stroke in cancer patients

    International Nuclear Information System (INIS)

    Kim, Jahae; Song, Ho-Chun; Choi, Kang-Ho; Kim, Joon-Tae; Park, Man-Seok; Cho, Ki-Hyun

    2016-01-01

    18 F-FDG PET/CT can acquire both anatomical and functional images in a single session. We investigated which factors of 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.)

  17. 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.

  18. 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.

  19. Spectroscopic biomarkers of motor cortex developmental plasticity in hemiparetic children after perinatal stroke.

    Science.gov (United States)

    Carlson, Helen L; MacMaster, Frank P; Harris, Ashley D; Kirton, Adam

    2017-03-01

    Perinatal stroke causes hemiparetic cerebral palsy and lifelong motor disability. Bilateral motor cortices are key hubs within the motor network and their neurophysiology determines clinical function. Establishing biomarkers of motor cortex function is imperative for developing and evaluating restorative interventional strategies. Proton magnetic resonance spectroscopy (MRS) quantifies metabolite concentrations indicative of underlying neuronal health and metabolism in vivo. We used functional magnetic resonance imaging (MRI)-guided MRS to investigate motor cortex metabolism in children with perinatal stroke. Children aged 6-18 years with MRI-confirmed perinatal stroke and hemiparetic cerebral palsy were recruited from a population-based cohort. Metabolite concentrations were assessed using a PRESS sequence (3T, TE = 30 ms, voxel = 4 cc). Voxel location was guided by functional MRI activations during finger tapping tasks. Spectra were analysed using LCModel. Metabolites were quantified, cerebral spinal fluid corrected and compared between groups (ANCOVA) controlling for age. Associations with clinical motor performance (Assisting Hand, Melbourne, Box-and-Blocks) were assessed. Fifty-two participants were studied (19 arterial, 14 venous, 19 control). Stroke participants demonstrated differences between lesioned and nonlesioned motor cortex N-acetyl-aspartate [NAA mean concentration = 10.8 ± 1.9 vs. 12.0 ± 1.2, P children with arterial but not venous strokes. Interrogation of motor cortex by fMRI-guided MRS is feasible in children with perinatal stroke. Metabolite differences between hemispheres, stroke types and correlations with motor performance support functional relevance. MRS may be valuable in understanding the neurophysiology of developmental neuroplasticity in cerebral palsy. Hum Brain Mapp 38:1574-1587, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  20. 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.

  1. 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.

  2. Biomarkers and genes predictive of disease predisposition and ...

    African Journals Online (AJOL)

    Biomarkers and genes predictive of disease predisposition and prognosis in rheumatoid arthritis. Rheumatoid arthritis is a debilitating disease which often progresses to relentlessly severe disease. Pieter W A Meyer, NHDip Med Tech, MTech, PhD. Medical Research Council Unit for Inflammation and Immunity, Department ...

  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. Identification of consensus biomarkers for predicting non-genotoxic hepatocarcinogens

    Science.gov (United States)

    Huang, Shan-Han; Tung, Chun-Wei

    2017-01-01

    The assessment of non-genotoxic hepatocarcinogens (NGHCs) is currently relying on two-year rodent bioassays. Toxicogenomics biomarkers provide a potential alternative method for the prioritization of NGHCs that could be useful for risk assessment. However, previous studies using inconsistently classified chemicals as the training set and a single microarray dataset concluded no consensus biomarkers. In this study, 4 consensus biomarkers of A2m, Ca3, Cxcl1, and Cyp8b1 were identified from four large-scale microarray datasets of the one-day single maximum tolerated dose and a large set of chemicals without inconsistent classifications. Machine learning techniques were subsequently applied to develop prediction models for NGHCs. The final bagging decision tree models were constructed with an average AUC performance of 0.803 for an independent test. A set of 16 chemicals with controversial classifications were reclassified according to the consensus biomarkers. The developed prediction models and identified consensus biomarkers are expected to be potential alternative methods for prioritization of NGHCs for further experimental validation.

  5. Prediction of Intrinsically Caused Tripping Events in Individuals With Stroke.

    Science.gov (United States)

    Zhang, Fan; Bohlen, Peter; Lewek, Michael D; Huang, He

    2017-08-01

    This study investigated the feasibility of predicting intrinsically caused trips (ICTs) in individuals with stroke. Gait kinematics collected from 12 individuals with chronic stroke, who demonstrated ICTs in treadmill walking, were analyzed. A prediction algorithm based on the outlier principle was employed. Sequential forward selection (SFS) and minimum-redundancy-maximum-relevance (mRMR) were used separately to identify the precursors for accurate ICT prediction. The results showed that it was feasible to predict ICTs around 50-260 ms before ICTs occurred in the swing phase by monitoring lower limb kinematics during the preceding stance phase. Both SFS and mRMR were effective in identifying the precursors of ICTs. For 9 out of the 12 subjects, the paretic lower limb's shank orientation in the sagittal plane and the vertical velocity of the paretic foot's center of gravity were important in predicting ICTs accurately; the averaged area under receiver operating characteristic curve achieved 0.95 and above. For the other three subjects, kinematics of the less affected limb or proximal joints in the paretic side were identified as the precursors to an ICT, potentially due to the variations of neuromotor deficits among stroke survivors. Although additional engineering efforts are still needed to address the challenges in making our design clinically practical, the outcome of this study may lead to further proactive engineering mechanisms for ICT avoidance and therefore reduce the risk of falls in individuals with stroke.

  6. Biomarkers for predicting type 2 diabetes development — Can metabolomics improve on existing biomarkers?

    DEFF Research Database (Denmark)

    Savolainen, Otto; Fagerberg, Björn; Lind, Mads Vendelbo

    2017-01-01

    Aim 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. Methods 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 followup. 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. Results Established markers of T2D (impaired fasting glucose, impaired glucose tolerance, insulin...

  7. Prediction of preeclampsia with angiogenic biomarkers

    DEFF Research Database (Denmark)

    Andersen, Louise Bjørkholt; Dechend, Ralf; Jørgensen, Jan Stener

    2016-01-01

    OBJECTIVE: We aimed to investigate how maternal serum soluble Fms-like kinase 1 (sFlt-1), placental growth factor (PlGF), and sFlt-1/PlGF ratio prospectively associate to preeclampsia (PE) and clinical subtypes. METHODS: In an unselected cohort of 1909 pregnant women, sFlt-1 and PlGF were measured...... with KRYPTOR assays in gestational weeks (GW) 8-14 and 20-34. Associations to PE were assessed by receiver operating characteristics and logistic regression. RESULTS: Concentrations of sFlt-1, PlGF, and sFlt-1/PlGF in GW20-34 were predictive of PE development, but not in GW8-14. PlGF outperformed sFlt-1/PlGF...... ratio with an area under curve (AUC) of 0.755 vs. 0.704, p = 0.002. The highest AUC values for PlGF and sFlt-1/PlGF ratio were seen for severe early-onset PE (0.901 and 0.883). Negative predictive values were high for all PE types, but positive predictive values were low. CONCLUSION: PlGF and sFlt-1/PlGF...

  8. 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.

  9. Prediction of cardioembolic, arterial, and lacunar causes of cryptogenic stroke by gene expression and infarct location.

    Science.gov (United States)

    Jickling, Glen C; Stamova, Boryana; Ander, Bradley P; Zhan, Xinhua; Liu, Dazhi; Sison, Shara-Mae; Verro, Piero; Sharp, Frank R

    2012-08-01

    The cause of ischemic stroke remains unclear, or cryptogenic, in as many as 35% of patients with stroke. Not knowing the cause of stroke restricts optimal implementation of prevention therapy and limits stroke research. We demonstrate how gene expression profiles in blood can be used in conjunction with a measure of infarct location on neuroimaging to predict a probable cause in cryptogenic stroke. The cause of cryptogenic stroke was predicted using previously described profiles of differentially expressed genes characteristic of patients with cardioembolic, arterial, and lacunar stroke. RNA was isolated from peripheral blood of 131 cryptogenic strokes and compared with profiles derived from 149 strokes of known cause. Each sample was run on Affymetrix U133 Plus 2.0 microarrays. Cause of cryptogenic stroke was predicted using gene expression in blood and infarct location. Cryptogenic strokes were predicted to be 58% cardioembolic, 18% arterial, 12% lacunar, and 12% unclear etiology. Cryptogenic stroke of predicted cardioembolic etiology had more prior myocardial infarction and higher CHA(2)DS(2)-VASc scores compared with stroke of predicted arterial etiology. Predicted lacunar strokes had higher systolic and diastolic blood pressures and lower National Institutes of Health Stroke Scale compared with predicted arterial and cardioembolic strokes. Cryptogenic strokes of unclear predicted etiology were less likely to have a prior transient ischemic attack or ischemic stroke. Gene expression in conjunction with a measure of infarct location can predict a probable cause in cryptogenic strokes. Predicted groups require further evaluation to determine whether relevant clinical, imaging, or therapeutic differences exist for each group.

  10. Assessment of cerebral small vessel disease predicts individual stroke risk

    NARCIS (Netherlands)

    M.M.F. Poels (Mariëlle); E.W. Steyerberg (Ewout); R.G. Wieberdink (Renske); A. Hofman (Albert); P.J. Koudstaal (Peter Jan); M.A. Ikram (Arfan); M.M.B. Breteler (Monique)

    2012-01-01

    textabstractBackground: Despite several known risk factors it is still difficult to foresee who will develop a stroke and who will not. Vascular brain damage, visualised with MRI, reflects how the brain tolerates the effects of vascular risk factors and may therefore be relevant in predicting

  11. Cardioembolic but Not Other Stroke Subtypes Predict Mortality Independent of Stroke Severity at Presentation

    Directory of Open Access Journals (Sweden)

    Latha Ganti Stead

    2011-01-01

    Results. The study population consisted of 500 patients who resided in the local county or the surrounding nine-county area. No patients were lost to followup. Two hundred and sixty one (52.2% were male, and the mean age at presentation was 73.7 years (standard deviation, SD = 14.3. Subtypes were as follows: large artery atherosclerosis 97 (19.4%, cardioembolic 144 (28.8%, small vessel disease 75 (15%, other causes 19 (3.8%, and unknown 165 (33%. One hundred and sixty patients died: 69 within the first 30 days, 27 within 31–90 days, 29 within 91–365 days, and 35 after 1 year. Low 90-, 180-, and 360-day survival was seen in cardioembolic strokes (67.1%, 65.5%, and 58.2%, resp., followed for cryptogenic strokes (78.0%, 75.3%, and 71.1%. Interestingly, when looking into the cryptogenic category, those with insufficient information to assign a stroke subtype had the lowest survival estimate (57.7% at 90 days, 56.1% at 180 days, and 51.2% at 1 year. Conclusion. Cardioembolic ischemic stroke subtype determined by TOAST criteria predicts long-term mortality, even after adjusting for age and stroke severity.

  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. 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

  14. Computational protein biomarker prediction: a case study for prostate cancer

    Directory of Open Access Journals (Sweden)

    Adam Bao-Ling

    2004-03-01

    Full Text Available Abstract Background Recent technological advances in mass spectrometry pose challenges in computational mathematics and statistics to process the mass spectral data into predictive models with clinical and biological significance. We discuss several classification-based approaches to finding protein biomarker candidates using protein profiles obtained via mass spectrometry, and we assess their statistical significance. Our overall goal is to implicate peaks that have a high likelihood of being biologically linked to a given disease state, and thus to narrow the search for biomarker candidates. Results Thorough cross-validation studies and randomization tests are performed on a prostate cancer dataset with over 300 patients, obtained at the Eastern Virginia Medical School using SELDI-TOF mass spectrometry. We obtain average classification accuracies of 87% on a four-group classification problem using a two-stage linear SVM-based procedure and just 13 peaks, with other methods performing comparably. Conclusions Modern feature selection and classification methods are powerful techniques for both the identification of biomarker candidates and the related problem of building predictive models from protein mass spectrometric profiles. Cross-validation and randomization are essential tools that must be performed carefully in order not to bias the results unfairly. However, only a biological validation and identification of the underlying proteins will ultimately confirm the actual value and power of any computational predictions.

  15. Pretreatment biomarkers predicting PTSD psychotherapy outcomes: A systematic review.

    Science.gov (United States)

    Colvonen, Peter J; Glassman, Lisa H; Crocker, Laura D; Buttner, Melissa M; Orff, Henry; Schiehser, Dawn M; Norman, Sonya B; Afari, Niloofar

    2017-04-01

    Although our understanding of the relationship between posttraumatic stress disorder (PTSD), brain structure and function, neural networks, stress-related systems, and genetics is growing, there is considerably less attention given to which biological markers predict evidence-based PTSD psychotherapy outcomes. Our systematic PRISMA-informed review of 20 studies examined biomarkers as predictors of evidence-based PTSD psychotherapy outcomes. Results provide preliminary evidence that specific structural and functional neural systems (involved in information processing), glucocorticoid sensitivity and metabolism (part of the hypothalamic-pituitary-adrenal axis and the response to stress), heart rate (involved with fear habituation), gene methylation, and certain genotypes (associated with serotonin and glucocorticoids) predicted positive response to PTSD treatment. These pre-treatment biomarkers are associated with processes integral to PTSD treatment, such as those affecting fear learning and extinction, cognitive restructuring, information processing, emotional processing, and interoceptive monitoring. Identifying pre-treatment biomarkers that predict treatment response may offer insight into the mechanisms of psychological treatment, provide a foundation for improving the pharmaceutical augmentation of treatment, and inform treatment matching. Published by Elsevier Ltd.

  16. 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

  17. Hyperglycemia predicts poststroke infections in acute ischemic stroke.

    Science.gov (United States)

    Zonneveld, Thomas P; Nederkoorn, Paul J; Westendorp, Willeke F; Brouwer, Matthijs C; van de Beek, Diederik; Kruyt, Nyika D

    2017-04-11

    To investigate whether admission hyperglycemia predicts poststroke infections and, if so, whether poststroke infections modify the effect of admission hyperglycemia on functional outcome in ischemic stroke. We used data from acute ischemic stroke patients in the Preventive Antibiotics in Stroke Study (PASS), a multicenter randomized controlled trial (n = 2,550) investigating the effect of preventive antibiotics on functional outcome. Admission hyperglycemia was defined as blood glucose ≥7.8 mmol/L and poststroke infection as any infection during admission judged by an expert adjudication committee. Functional outcome at 3 months was assessed with the modified Rankin Scale. Of 1,676 nondiabetic ischemic stroke patients, 338 (20%) had admission hyperglycemia. After adjustment for potential confounding variables, admission hyperglycemia was associated with poststroke infection (adjusted odds ratio [aOR] 2.31, 95% CI 1.31-4.07), worse 3-month functional outcome (common aOR 1.40, 95% CI 1.12-1.73), and 3-month mortality (aOR 2.11, 95% CI 1.40-3.19). Additional adjustment for poststroke infection in the functional outcome analysis, done to assess poststroke infection as an intermediate in the pathway from admission hyperglycemia to functional outcome, did not substantially change the model. In patients with recorded diabetes mellitus (n = 418), admission hyperglycemia was not associated with poststroke infection (aOR 0.49, 95% CI 0.15-1.58). In nondiabetic acute ischemic stroke patients, admission hyperglycemia is associated with poststroke infection and worse functional outcome. Poststroke infections did not modify the effect of admission hyperglycemia on functional outcome in ischemic stroke. © 2017 American Academy of Neurology.

  18. Neural function, injury, and stroke subtype predict treatment gains after stroke.

    Science.gov (United States)

    Burke Quinlan, Erin; Dodakian, Lucy; See, Jill; McKenzie, Alison; Le, Vu; Wojnowicz, Mike; Shahbaba, Babak; Cramer, Steven C

    2015-01-01

    This study was undertaken to better understand the high variability in response seen when treating human subjects with restorative therapies poststroke. Preclinical studies suggest that neural function, neural injury, and clinical status each influence treatment gains; therefore, the current study hypothesized that a multivariate approach incorporating these 3 measures would have the greatest predictive value. Patients 3 to 6 months poststroke underwent a battery of assessments before receiving 3 weeks of standardized upper extremity robotic therapy. Candidate predictors included measures of brain injury (including to gray and white matter), neural function (cortical function and cortical connectivity), and clinical status (demographics/medical history, cognitive/mood, and impairment). Among all 29 patients, predictors of treatment gains identified measures of brain injury (smaller corticospinal tract [CST] injury), cortical function (greater ipsilesional motor cortex [M1] activation), and cortical connectivity (greater interhemispheric M1-M1 connectivity). Multivariate modeling found that best prediction was achieved using both CST injury and M1-M1 connectivity (r(2) = 0.44, p = 0.002), a result confirmed using Lasso regression. A threshold was defined whereby no subject with >63% CST injury achieved clinically significant gains. Results differed according to stroke subtype; gains in patients with lacunar stroke were best predicted by a measure of intrahemispheric connectivity. Response to a restorative therapy after stroke is best predicted by a model that includes measures of both neural injury and function. Neuroimaging measures were the best predictors and may have an ascendant role in clinical decision making for poststroke rehabilitation, which remains largely reliant on behavioral assessments. Results differed across stroke subtypes, suggesting the utility of lesion-specific strategies. © 2014 American Neurological Association.

  19. Predicting Coronary Heart Disease and Stroke: The FINRISK Calculator.

    Science.gov (United States)

    Vartiainen, Erkki; Laatikainen, Tiina; Peltonen, Markku; Puska, Pekka

    2016-06-01

    The FINRISK risk calculator predicts 10-year risk for coronary heart disease, stroke incidence, and their combination. The model is based on 10-year cohort follow-up from 3 different cohorts in 1982, 1987, and 1992 from a random population sample in 3 areas in Finland. Coronary heart disease, stroke, and their combination are predicted by smoking, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, diabetes, and family history. The Internet-based calculator is commonly used in Finland in health services to assess the need for hypertension and hypercholesterolemia treatment and is used also in patients' counseling. Copyright © 2016 World Heart Federation (Geneva). Published by Elsevier B.V. All rights reserved.

  20. Validating imaging biomarkers of cerebral edema in patients with severe ischemic stroke.

    Science.gov (United States)

    Yoo, Albert J; Sheth, Kevin N; Kimberly, W Taylor; Chaudhry, Zeshan A; Elm, Jordan J; Jacobson, Sven; Davis, Stephen M; Donnan, Geoffrey A; Albers, Gregory W; Stern, Barney J; González, R Gilberto

    2013-08-01

    There is no validated neuroimaging marker for quantifying brain edema. We sought to test whether magnetic resonance imaging (MRI)-based metrics would reliably change during the early subacute period in a manner consistent with edema and whether they would correlate with relevant clinical endpoints. Serial MRI studies from patients in the Echoplanar Imaging Thrombolytic Evaluation Trial with initial diffusion-weighted imaging (DWI) lesion volume >82 cm(3) were analyzed. Two independent readers outlined the hemisphere and lateral ventricle on the involved side and calculated respective volumes at baseline and days 3 to 5. We assessed interrater agreement, volume change between scans, and the association of volume change with early neurologic deterioration (National Institutes of Health Stroke Scale score worsening of ≥ 4 points), a 90-day modified Rankin scale (mRS) score of 0 to 4, and mortality. Of 12 patients who met study criteria, average baseline and follow-up DWI lesion size was 138 cm(3) and 234 cm(3), respectively. The mean time to follow-up MRI was 62 hours. Concordance correlation coefficients between readers were >0.90 for both hemisphere and ventricle volume assessment. Mean percent hemisphere volume increase was 16.2 ± 8.3% (P cerebral edema. MRI-based analysis of hemisphere growth appears to be a suitable biomarker for edema formation. Copyright © 2013 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  1. Serum cholinesterase activities distinguish between stroke patients and controls and predict 12-month mortality

    DEFF Research Database (Denmark)

    Ben Assayag, Einor; Shenhar-Tsarfaty, Shani; Ofek, Keren

    2010-01-01

    To date there is no diagnostic biomarker for mild stroke, although elevation of inflammatory biomarkers has been reported at early stages. Previous studies implicated acetylcholinesterase (AChE) involvement in stroke, and circulating AChE activity reflects inflammatory response, since acetylcholine...... suppresses inflammation. Therefore, carriers of polymorphisms that modify cholinergic activity should be particularly susceptible to inflammatory damage. Our study sought diagnostic values of AChE and Cholinergic Status (CS, the total capacity for acetylcholine hydrolysis) in suspected stroke patients....... For this purpose, serum cholinesterase activities, butyrylcholinesterase-K genotype and inflammatory biomarkers were determined in 264 ischemic stroke patients and matched controls during the acute phase. AChE activities were lower (P...

  2. Accuracy of prediction scores and novel biomarkers for predicting nonalcoholic fatty liver disease in obese children.

    Science.gov (United States)

    Koot, Bart G P; van der Baan-Slootweg, Olga H; Bohte, Anneloes E; Nederveen, Aart J; van Werven, Jochem R; Tamminga-Smeulders, Christine L J; Merkus, Maruschka P; Schaap, Frank G; Jansen, Peter L M; Stoker, Jaap; Benninga, Marc A

    2013-03-01

    Accurate prediction scores for liver steatosis are demanded to enable clinicians to noninvasively screen for nonalcoholic fatty liver disease (NAFLD). Several prediction scores have been developed, however external validation is lacking. The aim was to determine the diagnostic accuracy of four existing prediction scores in severely obese children, to develop a new prediction score using novel biomarkers and to compare these results to the performance of ultrasonography. Liver steatosis was measured using proton magnetic resonance spectroscopy in 119 severely obese children (mean age 14.3 ± 2.1 years, BMI z-score 3.35 ± 0.35). Prevalence of steatosis was 47%. The four existing predictions scores ("NAFLD liver fat score," "fatty liver index," "hepatic steatosis index," and the pediatric prediction score) had only moderate diagnostic accuracy in this cohort (positive predictive value (PPV): 70, 61, 61, 69% and negative predictive value (NPV) 77, 69, 68, 75%, respectively). A new prediction score was built using anthropometry, routine biochemistry and novel biomarkers (leptin, adiponectin, TNF-alpha, IL-6, CK-18, FGF-21, and adiponutrin polymorphisms). The final model included ALT, HOMA, sex, and leptin. This equation (PPV 79% and NPV 80%) did not perform substantially better than the four other equations and did not outperform ultrasonography for excluding NAFLD (NPV 82%). The conclusion is in severely obese children and adolescents existing prediction scores and the tested novel biomarkers have insufficient diagnostic accuracy for diagnosing or excluding NAFLD. Copyright © 2012 The Obesity Society.

  3. 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...

  4. 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.

  5. 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

  6. Prediction of Recurrent Stroke or Transient Ischemic Attack After Noncardiogenic Posterior Circulation Ischemic Stroke.

    Science.gov (United States)

    Zhang, Changqing; Wang, Yilong; Zhao, Xingquan; Liu, Liping; Wang, ChunXue; Pu, Yuehua; Zou, Xinying; Pan, Yuesong; Wong, Ka Sing; Wang, Yongjun

    2017-07-01

    Posterior circulation ischemic stroke (IS) is generally considered an illness with a poor prognosis. However, there are no effective rating scales to predict recurrent stroke following it. Therefore, our aim was to identify clinical or radiological measures that could assist in predicting recurrent cerebral ischemic episodes. We prospectively enrolled 723 noncardiogenic posterior circulation IS patients with onset of symptoms Stroke risk factors, admission symptoms and signs, topographical distribution and responsible cerebral artery of acute infarcts, and any recurrent IS or transient ischemic attack (TIA) within 1 year were assessed. Cox regression was used to identify risk factors associated with recurrent IS or TIA within the year after posterior circulation IS. A total of 40 patients (5.5%) had recurrent IS or TIA within 1 year of posterior circulation IS. Multivariate Cox regression identified chief complaint with dysphagia (hazard ratio [HR], 4.16; 95% confidence interval [CI], 1.69-10.2; P =0.002), repeated TIAs within 3 months before the stroke (HR, 15.4; 95% CI, 5.55-42.5; P <0.0001), responsible artery stenosis ≥70% (HR, 7.91; 95% CI, 1.00-62.6; P =0.05), multisector infarcts (HR, 5.38; 95% CI, 1.25-23.3; P =0.02), and not on antithrombotics treatment at discharge (HR, 3.06; 95% CI, 1.09-8.58; P =0.03) as independent predictors of recurrent IS or TIA. Some posterior circulation IS patients are at higher risk for recurrent IS or TIA. Urgent assessment and preventive treatment should be offered to these patients as soon as possible. © 2017 American Heart Association, Inc.

  7. {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.)

  8. 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

  9. Robust predictive modelling of water pollution using biomarker data.

    Science.gov (United States)

    Budka, Marcin; Gabrys, Bogdan; Ravagnan, Elisa

    2010-05-01

    This paper describes the methodology of building a predictive model for the purpose of marine pollution monitoring, based on low quality biomarker data. A step-by-step, systematic data analysis approach is presented, resulting in design of a purely data-driven model, able to accurately discriminate between various coastal water pollution levels. The environmental scientists often try to apply various machine learning techniques to their data without much success, mostly because of the lack of experience with different methods and required 'under the hood' knowledge. Thus this paper is a result of a collaboration between the machine learning and environmental science communities, presenting a predictive model development workflow, as well as discussing and addressing potential pitfalls and difficulties. The novelty of the modelling approach presented lays in successful application of machine learning techniques to high dimensional, incomplete biomarker data, which to our knowledge has not been done before and is the result of close collaboration between machine learning and environmental science communities.

  10. 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.

  11. Prediction of lung cancer using volatile biomarkers in breath.

    Science.gov (United States)

    Phillips, Michael; Altorki, Nasser; Austin, John H M; Cameron, Robert B; Cataneo, Renee N; Greenberg, Joel; Kloss, Robert; Maxfield, Roger A; Munawar, Muhammad I; Pass, Harvey I; Rashid, Asif; Rom, William N; Schmitt, Peter

    2007-01-01

    Normal metabolism generates several volatile organic compounds (VOCs) that are excreted in the breath (e.g. alkanes). In patients with lung cancer, induction of high-risk cytochrome p450 genotypes may accelerate catabolism of these VOCs, so that their altered abundance in breath may provide biomarkers of lung cancer. VOCs in 1.0 L alveolar breath were analyzed in 193 subjects with primary lung cancer and 211 controls with a negative chest CT. Subjects were randomly assigned to a training set or to a prediction set in a 2:1 split. A fuzzy logic model of breath biomarkers of lung cancer was constructed in the training set and then tested in subjects in the prediction set by generating their typicality scores for lung cancer. Mean typicality scores employing a 16 VOC model were significantly higher in lung cancer patients than in the control group (pmodel predicted primary lung cancer with 84.6% sensitivity, 80.0% specificity, and 0.88 area under curve (AUC) of the receiver operating characteristic (ROC) curve. Predictive accuracy was similar in TNM stages 1 through 4, and was not affected by current or former tobacco smoking. The predictive model achieved near-maximal performance with six breath VOCs, and was progressively degraded by random classifiers. Predictions with fuzzy logic were consistently superior to multilinear analysis. If applied to a population with 2% prevalence of lung cancer, a screening breath test would have a negative predictive value of 0.985 and a positive predictive value of 0.163 (true positive rate =0.277, false positive rate =0.029). A two-minute breath test predicted lung cancer with accuracy comparable to screening CT of chest. The accuracy of the test was not affected by TNM stage of disease or tobacco smoking. Alterations in breath VOCs in lung cancer were consistent with a non-linear pathophysiologic process, such as an off-on switch controlling high-risk cytochrome p450 activity. Further research is needed to determine if detection

  12. 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 <0.001), similar to our prior external validation in the Partners National Telestroke Network. The TM score's ability to predict the presence of a stroke 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.

  13. Predicting Major Bleeding in Ischemic Stroke Patients With Atrial Fibrillation.

    Science.gov (United States)

    Hilkens, Nina A; Algra, Ale; Greving, Jacoba P

    2017-11-01

    Performance of risk scores for major bleeding in patients with atrial fibrillation and a previous transient ischemic attack or ischemic stroke is not well established. We aimed to validate risk scores for major bleeding in patients with atrial fibrillation treated with oral anticoagulants after cerebral ischemia and explore the net benefit of oral anticoagulants among bleeding risk categories. We analyzed 3623 patients with a history of transient ischemic attack or stroke included in the RE-LY trial (Randomized Evaluation of Long-Term Anticoagulation Therapy). We assessed performance of HEMORR 2 HAGES (hepatic or renal disease, ethanol abuse, malignancy, older age, reduced platelet count or function, hypertension [uncontrolled], anemia, genetic factors, excessive fall risk, and stroke), Shireman, HAS-BLED (hypertension, abnormal renal/liver function, stroke, bleeding history or predisposition, labile international normalized ratio, elderly, drugs/alcohol concomitantly), ATRIA (Anticoagulation and Risk Factors in Atrial Fibrillation), and ORBIT scores (older age, reduced haemoglobin/haematocrit/history of anaemia, bleeding history, insufficient kidney function, and treatment with antiplatelet) with C statistics and calibration plots. Net benefit of oral anticoagulants was explored by comparing risk reduction in ischemic stroke with risk increase in major bleedings on warfarin. During 6922 person-years of follow-up, 266 patients experienced a major bleed (3.8 per 100 person-years). C statistics ranged from 0.62 (Shireman) to 0.67 (ATRIA). Calibration was poor for ATRIA and moderate for other models. The reduction in recurrent ischemic strokes on warfarin was larger than the increase in major bleeding risk, irrespective of bleeding risk category. Performance of prediction models for major bleeding in patients with cerebral ischemia and atrial fibrillation is modest but comparable with performance in patients with only atrial fibrillation. Bleeding risk scores cannot

  14. Predicting mobility outcome one year after stroke: a prospective cohort study.

    NARCIS (Netherlands)

    Port, I.G. van de; Kwakkel, G.; Schepers, V.P.; Lindeman, E.

    2006-01-01

    OBJECTIVE: To develop a prognostic model to predict mobility outcome one year post-stroke. DESIGN: Prospective cohort study in patients with a first-ever stroke admitted for inpatient rehabilitation. PATIENTS: A total of 217 patients with stroke (mean age 58 years) following inpatient rehabilitation

  15. 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...

  16. Discovery of Predictive Biomarkers for Litter Size in Boar Spermatozoa*

    Science.gov (United States)

    Kwon, Woo-Sung; Rahman, Md Saidur; Lee, June-Sub; Yoon, Sung-Jae; Park, Yoo-Jin; Pang, Myung-Geol

    2015-01-01

    Conventional semen analysis has been used for prognosis and diagnosis of male fertility. Although this tool is essential for providing initial quantitative information about semen, it remains a subject of debate. Therefore, development of new methods for the prognosis and diagnosis of male fertility should be seriously considered for animal species of economic importance as well as for humans. In the present study, we applied a comprehensive proteomic approach to identify global protein biomarkers in boar spermatozoa in order to increase the precision of male fertility prognoses and diagnoses. We determined that l-amino acid oxidase, mitochondrial malate dehydrogenase 2, NAD (MDH2), cytosolic 5′-nucleotidase 1B, lysozyme-like protein 4, and calmodulin (CALM) were significantly and abundantly expressed in high-litter size spermatozoa. We also found that equatorin, spermadhesin AWN, triosephosphate isomerase (TPI), Ras-related protein Rab-2A (RAB2A), spermadhesin AQN-3, and NADH dehydrogenase [ubiquinone] iron-sulfur protein 2 (NDUFS2) were significantly and abundantly expressed in low-litter size spermatozoa (>3-fold). Moreover, RAB2A, TPI, and NDUFS2 were negatively correlated with litter size, whereas CALM and MDH2 were positively correlated. This study provides novel biomarkers for the prediction of male fertility. To the best of our knowledge, this is the first work that shows significantly increased litter size using male fertility biomarkers in a field trial. Moreover, these protein markers may provide new developmental tools for the selection of superior sires as well as for the prognosis and diagnosis of male fertility. PMID:25693803

  17. 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.

  18. 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

  19. 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.

  20. 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...

  1. (Very) Early technology assessment and translation of predictive biomarkers in breast cancer.

    Science.gov (United States)

    Miquel-Cases, Anna; Schouten, Philip C; Steuten, Lotte M G; Retèl, Valesca P; Linn, Sabine C; van Harten, Wim H

    2017-01-01

    Predictive biomarkers can guide treatment decisions in breast cancer. Many studies are undertaken to discover and translate these biomarkers, yet few biomarkers make it to practice. Before use in clinical decision making, predictive biomarkers need to demonstrate analytical validity, clinical validity and clinical utility. While attaining analytical and clinical validity is relatively straightforward, by following methodological recommendations, the achievement of clinical utility is extremely challenging. It requires demonstrating three associations: the biomarker with the outcome (prognostic association), the effect of treatment independent of the biomarker, and the differential treatment effect between the prognostic and the predictive biomarker (predictive association). In addition, economical, ethical, regulatory, organizational and patient/doctor-related aspects are hampering the translational process. Traditionally, these aspects do not receive much attention until formal approval or reimbursement of a biomarker test (informed by Health Technology Assessment (HTA)) is at stake, at which point the clinical utility and sometimes price of the test can hardly be influenced anymore. When HTA analyses are performed earlier, during biomarker research and development, they may prevent further development of those biomarkers unlikely to ever provide sufficient added value to society, and rather facilitate translation of the promising ones. Early HTA is particularly relevant for the predictive biomarker field, as expensive medicines are under pressure and the need for biomarkers to guide their appropriate use is huge. Closer interaction between clinical researchers and HTA experts throughout the translational research process will ensure that available data and methodologies will be used most efficiently to facilitate biomarker translation. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  2. 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.

  3. Predicting probable Alzheimer's disease using linguistic deficits and biomarkers.

    Science.gov (United States)

    Orimaye, Sylvester O; Wong, Jojo S-M; Golden, Karen J; Wong, Chee P; Soyiri, Ireneous N

    2017-01-14

    The manual diagnosis of neurodegenerative disorders such as Alzheimer's disease (AD) and related Dementias has been a challenge. Currently, these disorders are diagnosed using specific clinical diagnostic criteria and neuropsychological examinations. The use of several Machine Learning algorithms to build automated diagnostic models using low-level linguistic features resulting from verbal utterances could aid diagnosis of patients with probable AD from a large population. For this purpose, we developed different Machine Learning models on the DementiaBank language transcript clinical dataset, consisting of 99 patients with probable AD and 99 healthy controls. Our models learned several syntactic, lexical, and n-gram linguistic biomarkers to distinguish the probable AD group from the healthy group. In contrast to the healthy group, we found that the probable AD patients had significantly less usage of syntactic components and significantly higher usage of lexical components in their language. Also, we observed a significant difference in the use of n-grams as the healthy group were able to identify and make sense of more objects in their n-grams than the probable AD group. As such, our best diagnostic model significantly distinguished the probable AD group from the healthy elderly group with a better Area Under the Receiving Operating Characteristics Curve (AUC) using the Support Vector Machines (SVM). Experimental and statistical evaluations suggest that using ML algorithms for learning linguistic biomarkers from the verbal utterances of elderly individuals could help the clinical diagnosis of probable AD. We emphasise that the best ML model for predicting the disease group combines significant syntactic, lexical and top n-gram features. However, there is a need to train the diagnostic models on larger datasets, which could lead to a better AUC and clinical diagnosis of probable AD.

  4. 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

  5. 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...

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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...

  11. Renal Function Predicts Outcomes in Patients with Ischaemic Stroke and Haemorrhagic Stroke.

    Science.gov (United States)

    Snarska, Katarzyna; Kapica-Topczewska, Katarzyna; Bachórzewska-Gajewska, Hanna; Małyszko, Jolanta

    2016-01-01

    We evaluated renal function and the impact of renal function on in-hospital outcomes in patients with ischaemic and haemorrhagic stroke. We collected data from 766 patients with stroke; 637 (83.2 %) with ischaemic and 129 with haemorrhagic one. The mean serum creatinine on admission in patients with both types of stroke, who died, was significantly higher than in those who survived. Multivariate analysis showed that independent predictors of mortality in patients with ischaemic stroke were: ischemic heart disease or prior myocardial infarction, diabetes, admission glucose and eGFR on admission. Also, multivariate analysis showed that independent predictors of mortality in patients with haemorrhagic stroke were: age and admission glucose. Patients with haemorrhagic stroke, in particular with acute kidney injury during hospitalisation had significantly worse outcomes than patients with ischaemic stroke. Assessment of kidney function is prerequisite to employ the necessary measures to decrease the risk of in-hospital mortality among patients with acute stroke. Appropriate approach to patients with renal dysfunction (adequate hydration, avoidance of nephrotoxic drugs, drug dose adjustment etc) should be considered as preventive and therapeutic strategies in the management of acute stroke. © 2016 The Author(s) Published by S. Karger AG, Basel.

  12. 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.

  13. Predicted risk of stroke and bleeding and use of oral anticoagulants in atrial fibrillation

    DEFF Research Database (Denmark)

    Dukanovic, Alexandar; Staerk, Laila; Fosbøl, Emil Loldrup

    2017-01-01

    Introduction, materials and methods We used Danish nationwide registries to examine temporal trends in the predicted stroke and bleeding risks (mean CHA2DS2-VASc and HAS-BLED scores per year, respectively) as well as the combination of selected stroke and bleeding risk factors per year among atrial...... dabigatran initiators. In the study period, apixaban initiators in general had the highest frequency of prior stroke and age ≥ 75 years. Conclusions Danish AF patients receiving standard dose dabigatran had the lowest and decreasing predicted stroke and bleeding risks during almost all study years. Patients...... receiving reduced dose apixaban had rather stable predicted risk of stroke during the study period and the highest mean CHA2DS2-VASc score in 2016....

  14. 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.

  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. Weakness of Eye Closure with Central Facial Paralysis after Unilateral Hemispheric Stroke Predicts a Worse Outcome.

    Science.gov (United States)

    Lin, Jianwen; Chen, Yicong; Wen, Hongmei; Yang, Zhiyun; Zeng, Jinsheng

    2017-04-01

    Upper facial dysfunction is not generally considered a feature of central facial paralysis after unilateral hemispheric stroke; however, weakness of eye closure (WEC) has been observed in some cases. We aimed to investigate the frequency and characteristics of WEC in unilateral stroke and its association with stroke prognosis. Patients with unilateral stroke and central facial paralysis were prospectively recruited within 7 days of onset. Facial paralysis was evaluated via the fourth item in the National Institute of Health Stroke Scale (NIHSS-4) and the Japan Facial Score (JFS) on admission, and at days 7, 14, 21, and 30 after stroke. Eye closure strength was measured daily using an ergometer for 30 days after stroke. Primary outcome was assessed using the modified Rankin Scale (mRS) at 90 and 180 days. Univariate and multivariate analyses were performed to investigate risk factors of WEC. WEC was identified in 16 of 242 patients (6.6%). Baseline characteristics, stroke risk factors, and lesion volume were not significantly different between patients with and patients without WEC. Patients with WEC featured higher NIHSS-4 scores and lower JFS between admission and at 21 days after stroke. Severe central facial paralysis (odds ratio [OR] = 8.1, 95% confidence interval [CI] = 2.3-28.6, P = .001) and right hemispheric stroke (OR = 13.7, 95% CI = 3.7-51.2, P WEC. At 180 days after stroke, patients with WEC demonstrated a lower rate of functional independence (mRS = 0-2: 37.5% versus 72.1%, P WEC, which predicts a worse functional outcome at 180 days after unilateral stroke, demonstrates an association with severe central facial paralysis and right hemispheric stroke. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  17. Prediction of hemorrhagic transformation after experimental ischemic stroke using MRI-based algorithms

    NARCIS (Netherlands)

    Bouts, Mark. J. R. J.; Tiebosch, Ivo A.C.W.; Rudrapatna, Umesh S; van der Toorn, Annette; Wu, Ona; Dijkhuizen, Rick M.

    2017-01-01

    Estimation of hemorrhagic transformation (HT) risk is crucial for treatment decision–making after acute ischemic stroke. We aimed to determine the accuracy of multiparametric MRI-based predictive algorithms in calculating probability of HT after stroke. Spontaneously, hypertensive rats were

  18. Circulating microRNAs as Prognostic and Predictive Biomarkers in Patients with Colorectal Cancer

    Directory of Open Access Journals (Sweden)

    Jakob Vasehus Schou

    2016-06-01

    Full Text Available MiRNAs are suggested as promising cancer biomarkers. They are stable and extractable from a variety of clinical tissue specimens (fresh frozen or formalin fixed paraffin embedded tissue and a variety of body fluids (e.g., blood, urine, saliva. However, there are several challenges that need to be solved, considering their potential as biomarkers in cancer, such as lack of consistency between biomarker panels in independent studies due to lack of standardized sample handling and processing, use of inconsistent normalization approaches, and differences in patients populations. Focusing on colorectal cancer (CRC, divergent results regarding circulating miRNAs as prognostic or predictive biomarkers are reported in the literature. In the present review, we summarize the current data on circulating miRNAs as prognostic/predictive biomarkers in patients with localized and metastatic CRC (mCRC.

  19. 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.

  20. 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.)

  1. 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)

  2. Accuracy of Physical Therapists' Early Predictions of Upper-Limb Function in Hospital Stroke Units: The EPOS Study

    NARCIS (Netherlands)

    Nijland, R.H.M.; van Wegen, E.E.H.; Harmeling-van Wel, B.; Kwakkel, G.

    2013-01-01

    Background. Early prediction of outcome after stroke is becoming increasingly important, as most patients are discharged from hospital stroke units within several days after stroke. Objectives. The primary purposes of this study were: (1) to determine the accuracy of physical therapists' predictions

  3. Reflux of Anterior Spinal Artery Predicts Recurrent Posterior Circulation Stroke in Bilateral Vertebral Artery Disease.

    Science.gov (United States)

    Fukuda, Hitoshi; Hayashi, Kosuke; Handa, Akira; Kurosaki, Yoshitaka; Lo, Benjamin; Yamagata, Sen

    2015-11-01

    Predictive value of reflux of anterior spinal artery for recurrent posterior circulation ischemia in bilateral vertebral arteries steno-occlusive disease was evaluated. We retrospectively reviewed 55 patients with symptomatic posterior circulation stroke caused by bilateral stenotic (>70%) lesions of the vertebral artery. We investigated any correlation of clinical and angiographic characteristics including collateral flow patterns, with recurrent stroke. Risk factors for poor 3-month functional outcome were also evaluated. Recurrent posterior circulation stroke was observed in 15 (27.3%) patients. Multivariable analysis using Cox proportional hazards model showed anterior spinal artery reflux as a significant risk factor for stroke recurrence (adjusted hazard ratio, 19.3 [95% confidence interval, 5.35-69.9]; Pdisease, anterior spinal artery reflux predicted recurrent posterior circulation stroke and poor functional outcome. © 2015 American Heart Association, Inc.

  4. Predicting Disability after Ischemic Stroke Based on Comorbidity Index and Stroke Severity—From the Virtual International Stroke Trials Archive-Acute Collaboration

    Directory of Open Access Journals (Sweden)

    Thanh G. Phan

    2017-05-01

    Full Text Available Background and aimThe availability and access of hospital administrative data [coding for Charlson comorbidity index (CCI] in large data form has resulted in a surge of interest in using this information to predict mortality from stroke. The aims of this study were to determine the minimum clinical data set to be included in models for predicting disability after ischemic stroke adjusting for CCI and clinical variables and to evaluate the impact of CCI on prediction of outcome.MethodWe leverage anonymized clinical trial data in the Virtual International Stroke Trials Archive. This repository contains prospective data on stroke severity and outcome. The inclusion criteria were patients with available stroke severity score such as National Institutes of Health Stroke Scale (NIHSS, imaging data, and outcome disability score such as 90-day Rankin Scale. We calculate CCI based on comorbidity data in this data set. For logistic regression, we used these calibration statistics: Nagelkerke generalised R2 and Brier score; and for discrimination we used: area under the receiver operating characteristics curve (AUC and integrated discrimination improvement (IDI. The IDI was used to evaluate improvement in disability prediction above baseline model containing age, sex, and CCI.ResultsThe clinical data among 5,206 patients (55% males were as follows: mean age 69 ± 13 years, CCI 4.2 ± 0.8, and median NIHSS of 12 (IQR 8, 17 on admission and 9 (IQR 5, 15 at 24 h. In Model 2, adding admission NIHSS to the baseline model improved AUC from 0.67 (95% CI 0.65–0.68 to 0.79 (95% CI 0.78–0.81. In Model 3, adding 24-h NIHSS to the baseline model resulted in substantial improvement in AUC to 0.90 (95% CI 0.89–0.91 and increased IDI by 0.23 (95% CI 0.22–0.24. Adding the variable recombinant tissue plasminogen activator did not result in a further change in AUC or IDI to this regression model. In Model 3, the variable NIHSS at 24 h explains 87.3% of

  5. Predicting sickness impact profile at six months after stroke: further results from the European multi-center CERISE study

    NARCIS (Netherlands)

    Stummer, C.A.; Verheyden, G.; Putman, K.; Jenni, W.; Schupp, W.; Wit, L. De

    2015-01-01

    PURPOSE: To develop prognostic models and equations for predicting participation at six months after stroke. METHODS: This European prospective cohort study recruited 532 consecutive patients from four rehabilitation centers. Participation was assessed at six months after stroke with the Sickness

  6. 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

  7. Stroke

    Science.gov (United States)

    ... adjust your treatment as needed. Rehabilitation After a stroke, you may need rehabilitation (rehab) to help you recover. Rehab may include working with speech, physical, and occupational therapists. Language, ... may have trouble communicating after a stroke. You may not be able to find the ...

  8. STARTING-SICH Nomogram to Predict Symptomatic Intracerebral Hemorrhage After Intravenous Thrombolysis for Stroke.

    Science.gov (United States)

    Cappellari, Manuel; Turcato, Gianni; Forlivesi, Stefano; Zivelonghi, Cecilia; Bovi, Paolo; Bonetti, Bruno; Toni, Danilo

    2018-02-01

    Symptomatic intracerebral hemorrhage (sICH) is a rare but the most feared complication of intravenous thrombolysis for ischemic stroke. We aimed to develop and validate a nomogram for individualized prediction of sICH in intravenous thrombolysis-treated stroke patients included in the multicenter SITS-ISTR (Safe Implementation of Thrombolysis in Stroke-International Stroke Thrombolysis Register). All patients registered in the SITS-ISTR by 179 Italian centers between May 2001 and March 2016 were originally included. The main outcome measure was sICH per the European Cooperative Acute Stroke Study II definition (any type of intracerebral hemorrhage with increase of ≥4 National Institutes of Health Stroke Scale score points from baseline or death Stroke Scale score, glucose, aspirin alone, aspirin plus clopidogrel, anticoagulant with INR ≤1.7, current infarction sign, hyperdense artery sign) nomogram. The area under the receiver-operating characteristic curve of STARTING-SICH was 0.739. Calibration was good ( P =0.327 for the Hosmer-Lemeshow test). The STARTING-SICH is the first nomogram developed and validated in a large SITS-ISTR cohort for individualized prediction of sICH in intravenous thrombolysis-treated stroke patients. © 2018 American Heart Association, Inc.

  9. 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.

  10. Run-in phase III trial design with pharmacodynamics predictive biomarkers.

    Science.gov (United States)

    Hong, Fangxin; Simon, Richard

    2013-11-06

    Developments in biotechnology have stimulated the use of predictive biomarkers to identify patients who are likely to benefit from a targeted therapy. Several randomized phase III designs have been introduced for development of a targeted therapy using a diagnostic test. Most such designs require biomarkers measured before treatment. In many cases, it has been very difficult to identify such biomarkers. Promising candidate biomarkers can sometimes be effectively measured after a short run-in period on the new treatment. We introduce a new design for phase III trials with a candidate predictive pharmacodynamic biomarker measured after a short run-in period. Depending on the therapy and the biomarker performance, the trial would either randomize all patients but perform a separate analysis on the biomarker-positive patients or only randomize marker-positive patients after the run-in period. We evaluate the proposed design compared with the conventional phase III design and discuss how to design a run-in trial based on phase II studies. The proposed design achieves a major sample size reduction compared with the conventional randomized phase III design in many cases when the biomarker has good sensitivity (≥0.7) and specificity (≥0.7). This requires that the biomarker be measured accurately and be indicative of drug activity. However, the proposed design loses some of its advantage when the proportion of potential responders is large (>50%) or the effect on survival from run-in period is substantial. Incorporating a pharmacodynamic biomarker requires careful consideration but can expand the capacity of clinical trials to personalize treatment decisions and enhance therapeutics development.

  11. 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.

  12. Adherence to a Mediterranean diet and prediction of incident stroke.

    Science.gov (United States)

    Tsivgoulis, Georgios; Psaltopoulou, Theodora; Wadley, Virginia G; Alexandrov, Andrei V; Howard, George; Unverzagt, Frederick W; Moy, Claudia; Howard, Virginia J; Kissela, Brett; Judd, Suzanne E

    2015-03-01

    There are limited data on the potential association of adherence to Mediterranean diet (MeD) with incident stroke. We sought to assess the longitudinal association between greater adherence to MeD and risk of incident stroke. We prospectively evaluated a population-based cohort of 30 239 individuals enrolled in REasons for Geographic and Racial Differences in Stroke (REGARDS) study, after excluding participants with stroke history, missing demographic data or food frequency questionnaires, and unavailable follow-up information. Adherence to MeD was categorized using MeD score. Incident stroke was adjudicated by expert panel review of medical records during a mean follow-up period of 6.5 years. Incident stroke was identified in 565 participants (2.8%; 497 and 68 cases of ischemic stroke [IS] and hemorrhagic stroke, respectively) of 20 197 individuals fulfilling the inclusion criteria. High adherence to MeD (MeD score, 5-9) was associated with lower risk of incident IS in unadjusted analyses (hazard ratio, 0.83; 95% confidence interval, 0.70-1.00; P=0.046). The former association retained its significance (hazard ratio, 0.79; 95% confidence interval, 0.65-0.96; P=0.016) after adjustment for demographics, vascular risk factors, blood pressure levels, and antihypertensive medications. When MeD was evaluated as a continuous variable, a 1-point increase in MeD score was independently associated with a 5% reduction in the risk of incident IS (95% confidence interval, 0-11%). We documented no association of adherence to MeD with incident hemorrhagic stroke. There was no interaction of race (P=0.37) on the association of adherence to MeD with incident IS. High adherence to MeD seems to be associated with a lower risk of incident IS independent of potential confounders. Adherence to MeD is not related to the risk of incident hemorrhagic stroke. © 2015 American Heart Association, Inc.

  13. Predicting stroke evolution: comparison of susceptibility-weighted MR imaging with MR perfusion

    International Nuclear Information System (INIS)

    Kao, Hung-Wen; Tsai, Fong Y.; Hasso, Anton N.

    2012-01-01

    To investigate the ability of susceptibility-weighted imaging (SWI) to predict stroke evolution in comparison with perfusion-weighted imaging (PWI). In a retrospective analysis of 15 patients with non-lacunar ischaemic stroke studied no later than 24 h after symptom onset, we used the Alberta Stroke Program Early CT Score (ASPECTS) to compare lesions on initial diffusion-weighted images (DWI), SWI, PWI and follow-up studies obtained at least 5 days after symptom onset. The National Institutes of Health Stroke Scale scores at entry and stroke risk factors were documented. The clinical-DWI, SWI-DWI and PWI-DWI mismatches were calculated. SWI-DWI and mean transit time (MTT)-DWI mismatches were significantly associated with higher incidence of infarct growth (P = 0.007 and 0.028) and had similar ability to predict stroke evolution (P = 1.0). ASPECTS values on initial DWI, SWI and PWI were significantly correlated with those on follow-up studies (P ≤ 0.026) but not associated with infarct growth. The SWI ASPECTS values were best correlated with MTT ones (ρ = 0.8, P < 0.001). SWI is an alternative to PWI to assess penumbra and predict stroke evolution. Further prospective studies are needed to evaluate the role of SWI in guiding thrombolytic therapy. (orig.)

  14. 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.

  15. Design and validation of a clinical scale for prehospital stroke recognition, severity grading and prediction of large vessel occlusion: the shortened NIH Stroke Scale for emergency medical services.

    Science.gov (United States)

    Purrucker, Jan Christoph; Härtig, Florian; Richter, Hardy; Engelbrecht, Andreas; Hartmann, Johannes; Auer, Jonas; Hametner, Christian; Popp, Erik; Ringleb, Peter Arthur; Nagel, Simon; Poli, Sven

    2017-09-01

    To develop an NIH Stroke Scale (NIHSS)-compatible, all-in-one scale for rapid and comprehensive prehospital stroke assessment including stroke recognition, severity grading and progression monitoring as well as prediction of large vessel occlusion (LVO). Emergency medical services (EMS) personnel and stroke physicians (n=326) rated each item of the NIHSS regarding suitability for prehospital use; best rated items were included. Stroke recognition was evaluated retrospectively in 689 consecutive patients with acute stroke or stroke mimics, prediction of LVO in 741 consecutive patients with ischaemic stroke with acute vessel imaging independent of admission NIHSS score. Nine of the NIHSS items were rated as 'suitable for prehospital use.' After excluding two items in order to increase specificity, the final scale (termed shortened NIHSS for EMS, sNIHSS-EMS) consists of 'level of consciousness', 'facial palsy', 'motor arm/leg', 'sensory', 'language' and 'dysarthria'. Sensitivity for stroke recognition of the sNIHSS-EMS is 91% (95% CI 86 to 94), specificity 52% (95% CI 47 to 56). Receiver operating curve analysis revealed an optimal cut-off point for LVO prediction of ≥6 (sensitivity 70% (95% CI 65 to 76), specificity 81% (95% CI 76 to 84), positive predictive value 70 (95% CI 65 to 75), area under the curve 0.81 (95% CI 0.78 to 0.84)). Test characteristics were non-inferior to non-comprehensive scales. The sNIHSS-EMS may overcome the sequential use of multiple emergency stroke scales by permitting parallel stroke recognition, severity grading and LVO prediction. Full NIHSS-item compatibility allows for evaluation of stroke progression starting at the prehospital phase. © 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.

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

    Science.gov (United States)

    Luvizutto, Gustavo José; Gabriel, Maicon Gonçalves; Braga, Gabriel Pereira; Fernandes, Thiago Dias; Resende, Luiz Antônio de Lima; Pontes Neto, Octávio Marques; Bazan, Rodrigo

    2015-05-01

    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. 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. ASPECTS was correlated with National Institute of Health Stroke Scale (NIHSS) at admission (r = -0.52; p 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. The SSS can predict worst neurological impairment when associated with lower values of ASPECTS.

  17. Predicting disease progression from short biomarker series using expert advice algorithm

    Science.gov (United States)

    Morino, Kai; Hirata, Yoshito; Tomioka, Ryota; Kashima, Hisashi; Yamanishi, Kenji; Hayashi, Norihiro; Egawa, Shin; Aihara, Kazuyuki

    2015-05-01

    Well-trained clinicians may be able to provide diagnosis and prognosis from very short biomarker series using information and experience gained from previous patients. Although mathematical methods can potentially help clinicians to predict the progression of diseases, there is no method so far that estimates the patient state from very short time-series of a biomarker for making diagnosis and/or prognosis by employing the information of previous patients. Here, we propose a mathematical framework for integrating other patients' datasets to infer and predict the state of the disease in the current patient based on their short history. We extend a machine-learning framework of ``prediction with expert advice'' to deal with unstable dynamics. We construct this mathematical framework by combining expert advice with a mathematical model of prostate cancer. Our model predicted well the individual biomarker series of patients with prostate cancer that are used as clinical samples.

  18. 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.

  19. 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.

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

    NARCIS (Netherlands)

    Pontillo, Claudia; Zhang, Zhen-Yu; Schanstra, Joost P; Jacobs, Lotte; Zürbig, Petra; Thijs, Lutgarde; Ramírez-Torres, Adela; Heerspink, Hiddo J L; Lindhardt, Morten; Klein, Ronald; Orchard, Trevor; Porta, Massimo; Bilous, Rudolf W; Charturvedi, Nishi; Rossing, Peter; Vlahou, Antonia; Schepers, Eva; Glorieux, Griet; Mullen, William; Delles, Christian; Verhamme, Peter; Vanholder, Raymond; Staessen, Jan A; Mischak, Harald; Jankowski, Joachim

    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 <60 ml/min per 1.73 m2. Methods: In analyses of 2087 individuals from 6

  1. A Clinical and Biomarker Scoring System to Predict the Presence of Obstructive Coronary Artery Disease

    NARCIS (Netherlands)

    Ibrahim, N.E.; Januzzi, J.L., Jr.; Magaret, C.A.; Gaggin, H.K.; Rhyne, R.F.; Gandhi, P.U.; Kelly, N.; Simon, M.L.; Motiwala, S.R.; Belcher, A.M.; Kimmenade, R.R. van

    2017-01-01

    BACKGROUND: Noninvasive models to predict the presence of coronary artery disease (CAD) may help reduce the societal burden of CAD. OBJECTIVES: From a prospective registry of patients referred for coronary angiography, the goal of this study was to develop a clinical and biomarker score to predict

  2. 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.

  3. Predicting total, abdominal, visceral and hepatic adiposity with circulating biomarkers in Caucasian and Japanese American women.

    Directory of Open Access Journals (Sweden)

    Unhee Lim

    Full Text Available Characterization of abdominal and intra-abdominal fat requires imaging, and thus is not feasible in large epidemiologic studies.We investigated whether biomarkers may complement anthropometry (body mass index [BMI], waist circumference [WC], and waist-hip ratio [WHR] in predicting the size of the body fat compartments by analyzing blood biomarkers, including adipocytokines, insulin resistance markers, sex steroid hormones, lipids, liver enzymes and gastro-neuropeptides.Fasting levels of 58 blood markers were analyzed in 60 healthy, Caucasian or Japanese American postmenopausal women who underwent anthropometric measurements, dual energy X-ray absorptiometry (DXA, and abdominal magnetic resonance imaging. Total, abdominal, visceral and hepatic adiposity were predicted based on anthropometry and the biomarkers using Random Forest models.Total body fat was well predicted by anthropometry alone (R(2 = 0.85, by the 5 best predictors from the biomarker model alone (leptin, leptin-adiponectin ratio [LAR], free estradiol, plasminogen activator inhibitor-1 [PAI1], alanine transaminase [ALT]; R(2 = 0.69, or by combining these 5 biomarkers with anthropometry (R(2 = 0.91. Abdominal adiposity (DXA trunk-to-periphery fat ratio was better predicted by combining the two types of predictors (R(2 = 0.58 than by anthropometry alone (R(2 = 0.53 or the 5 best biomarkers alone (25(OH-vitamin D(3, insulin-like growth factor binding protein-1 [IGFBP1], uric acid, soluble leptin receptor [sLEPR], Coenzyme Q10; R(2 = 0.35. Similarly, visceral fat was slightly better predicted by combining the predictors (R(2 = 0.68 than by anthropometry alone (R(2 = 0.65 or the 5 best biomarker predictors alone (leptin, C-reactive protein [CRP], LAR, lycopene, vitamin D(3; R(2 = 0.58. Percent liver fat was predicted better by the 5 best biomarker predictors (insulin, sex hormone binding globulin [SHBG], LAR, alpha-tocopherol, PAI1; R(2 = 0.42 or by combining the predictors (R(2 = 0

  4. Predictive biomarkers in colorectal cancer: usage, validation, and design in clinical trials.

    Science.gov (United States)

    Shi, Qian; Mandrekar, Sumithra J; Sargent, Daniel J

    2012-03-01

    As cancer treatment development has shifted its attention to targeted therapies, it is becoming increasingly important to provide tools for selecting the right treatment for an individual patient to achieve optimal clinical benefit. Biomarkers, identified and studied in the process of understanding the nature of the disease at the molecular pathogenesis level, have been increasingly recognized as a critical aspect in more accurate diagnosis, prognosis assessment, and therapeutic targeting. Predictive biomarkers, which can aid treatment decisions, require extensive data for validation. In this article, we discuss the definition, clinical usages, and more extensively the clinical trial designs for the validation of predictive biomarkers. Predictive biomarker validation methods can be broadly grouped into retrospective and prospective designs. Retrospective validation utilizes data from previously conducted prospective randomized controlled trials. Prospective designs include enrichment designs, treatment-by-marker interaction designs, marker-based strategy designs, and adaptive designs. We discuss each design with examples and provide comparisons of the advantages and disadvantages among the different designs. We conclude that the combination of scientific, clinical, statistical, ethical, and practical considerations provides guidance for the choice of the clinical trial design for validation of each proposed predictive biomarker.

  5. 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...

  6. Changes in predicted muscle coordination with subject-specific muscle parameters for individuals after stroke.

    Science.gov (United States)

    Knarr, Brian A; Reisman, Darcy S; Binder-Macleod, Stuart A; Higginson, Jill S

    2014-01-01

    Muscle weakness is commonly seen in individuals after stroke, characterized by lower forces during a maximal volitional contraction. Accurate quantification of muscle weakness is paramount when evaluating individual performance and response to after stroke rehabilitation. The objective of this study was to examine the effect of subject-specific muscle force and activation deficits on predicted muscle coordination when using musculoskeletal models for individuals after stroke. Maximum force generating ability and central activation ratio of the paretic plantar flexors, dorsiflexors, and quadriceps muscle groups were obtained using burst superimposition for four individuals after stroke with a range of walking speeds. Two models were created per subject: one with generic and one with subject-specific activation and maximum isometric force parameters. The inclusion of subject-specific muscle data resulted in changes in the model-predicted muscle forces and activations which agree with previously reported compensation patterns and match more closely the timing of electromyography for the plantar flexor and hamstring muscles. This was the first study to create musculoskeletal simulations of individuals after stroke with subject-specific muscle force and activation data. The results of this study suggest that subject-specific muscle force and activation data enhance the ability of musculoskeletal simulations to accurately predict muscle coordination in individuals after stroke.

  7. Changes in Predicted Muscle Coordination with Subject-Specific Muscle Parameters for Individuals after Stroke

    Directory of Open Access Journals (Sweden)

    Brian A. Knarr

    2014-01-01

    Full Text Available Muscle weakness is commonly seen in individuals after stroke, characterized by lower forces during a maximal volitional contraction. Accurate quantification of muscle weakness is paramount when evaluating individual performance and response to after stroke rehabilitation. The objective of this study was to examine the effect of subject-specific muscle force and activation deficits on predicted muscle coordination when using musculoskeletal models for individuals after stroke. Maximum force generating ability and central activation ratio of the paretic plantar flexors, dorsiflexors, and quadriceps muscle groups were obtained using burst superimposition for four individuals after stroke with a range of walking speeds. Two models were created per subject: one with generic and one with subject-specific activation and maximum isometric force parameters. The inclusion of subject-specific muscle data resulted in changes in the model-predicted muscle forces and activations which agree with previously reported compensation patterns and match more closely the timing of electromyography for the plantar flexor and hamstring muscles. This was the first study to create musculoskeletal simulations of individuals after stroke with subject-specific muscle force and activation data. The results of this study suggest that subject-specific muscle force and activation data enhance the ability of musculoskeletal simulations to accurately predict muscle coordination in individuals after stroke.

  8. Early prediction of polymyxin-induced nephrotoxicity with next-generation urinary kidney injury biomarkers.

    Science.gov (United States)

    Keirstead, Natalie D; Wagoner, Matthew P; Bentley, Patricia; Blais, Marie; Brown, Crystal; Cheatham, Letitia; Ciaccio, Paul; Dragan, Yvonne; Ferguson, Douglas; Fikes, Jim; Galvin, Melanie; Gupta, Anshul; Hale, Michael; Johnson, Nakpangi; Luo, Wenli; McGrath, Frank; Pietras, Mark; Price, Sally; Sathe, Abhishek G; Sasaki, Jennifer C; Snow, Debra; Walsky, Robert L; Kern, Gunther

    2014-02-01

    Despite six decades of clinical experience with the polymyxin class of antibiotics, their dose-limiting nephrotoxicity remains difficult to predict due to a paucity of sensitive biomarkers. Here, we evaluate the performance of standard of care and next-generation biomarkers of renal injury in the detection and monitoring of polymyxin-induced acute kidney injury in male Han Wistar rats using colistin (polymyxin E) and a polymyxin B (PMB) derivative with reduced nephrotoxicity, PMB nonapeptide (PMBN). This study provides the first histopathological and biomarker analysis of PMBN, an important test of the hypothesis that fatty acid modifications and charge reductions in polymyxins can reduce their nephrotoxicity. The results indicate that alterations in a panel of urinary kidney injury biomarkers can be used to monitor histopathological injury, with Kim-1 and α-GST emerging as the most sensitive biomarkers outperforming clinical standards of care, serum or plasma creatinine and blood urea nitrogen. To enable the prediction of polymyxin-induced nephrotoxicity, an in vitro cytotoxicity assay was employed using human proximal tubule epithelial cells (HK-2). Cytotoxicity data in these HK-2 cells correlated with the renal toxicity detected via safety biomarker data and histopathological evaluation, suggesting that in vitro and in vivo methods can be incorporated within a screening cascade to prioritize polymyxin class analogs with more favorable renal toxicity profiles.

  9. 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.

  10. Addition of 24 hour heart rate variability parameters to the cardiovascular health study stroke risk score and prediction of incident stroke : The cardiovascular health study

    NARCIS (Netherlands)

    Bodapati, R.K.; Kizer, J.R.; Kop, W.J.; Stein, P.K.

    2017-01-01

    Background Heart rate variability (HRV) characterizes cardiac autonomic functioning. The association of HRV with stroke is uncertain. We examined whether 24‐hour HRV added predictive value to the Cardiovascular Health Study clinical stroke risk score (CHS‐SCORE), previously developed at the baseline

  11. 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....

  12. 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.

  13. Cord Blood DNA Methylation Biomarkers for Predicting Neurodevelopmental Outcomes

    Directory of Open Access Journals (Sweden)

    Nicolette A. Hodyl

    2016-12-01

    Full Text Available Adverse environmental exposures in pregnancy can significantly alter the development of the fetus resulting in impaired child neurodevelopment. Such exposures can lead to epigenetic alterations like DNA methylation, which may be a marker of poor cognitive, motor and behavioral outcomes in the infant. Here we review studies that have assessed DNA methylation in cord blood following maternal exposures that may impact neurodevelopment of the child. We also highlight some key studies to illustrate the potential for DNA methylation to successfully identify infants at risk for poor outcomes. While the current evidence is limited, in that observations to date are largely correlational, in time and with larger cohorts analyzed and longer term follow-up completed, we may be able to develop epigenetic biomarkers that not only indicate adverse early life exposures but can also be used to identify individuals likely to be at an increased risk of impaired neurodevelopment even in the absence of detailed information regarding prenatal environment.

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

    Science.gov (United States)

    Asadi, Hamed; Dowling, Richard; Yan, Bernard; Mitchell, Peter

    2014-01-01

    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. 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. 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). We showed promising accuracy of outcome prediction, using supervised machine learning algorithms, with potential for incorporation of larger multicenter datasets, likely further improving prediction. Finally, we

  15. 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

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

    DEFF Research Database (Denmark)

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

    2011-01-01

    substudy. Results: During follow-up, a total of 91 primary endpoints occurred. At baseline, lower left ventricular stroke volume was associated with smaller body size, female sex, lower left ventricular mass and stress-corrected midwall shortening, higher relative wall thickness and total peripheral...... 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 mass and concentric geometry and in a secondary model also independent of stress-corrected midwall shortening...... resistance, more concentric left ventricular geometry and impaired diastolic relaxation (all P indexed for height2.04 was associated...

  17. 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...... was calculated. Death within 30 days was used as outcome. Area under the receiver operating characteristics curve (AUROC) and a Kaplan-Meier curve were computed to examine the prognostic validity of EWS. RESULTS: A total of 24 patients (8.8%) died within 30 days. The prognostic performance was high for both...... 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....

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

    DEFF Research Database (Denmark)

    Mayer, Gert; Heerspink, Hiddo J Lambers; 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...... group of patients with type 2 diabetes and CKD at various stages. RESEARCH DESIGN AND METHODS: We used publicly available "omics" data to develop a molecular process model of CKD in diabetes and identified a representative parsimonious set of nine molecular biomarkers: chitinase 3-like protein 1, growth...... 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 R(2...

  19. Computational prediction of human salivary proteins from blood circulation and application to diagnostic biomarker identification.

    Directory of Open Access Journals (Sweden)

    Jiaxin Wang

    Full Text Available 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.

  20. Clusterin in kidney transplantation: novel biomarkers versus serum creatinine for early prediction of delayed graft function.

    Science.gov (United States)

    Pianta, Timothy J; Peake, Philip W; Pickering, John W; Kelleher, Michaela; Buckley, Nicholas A; Endre, Zoltan H

    2015-01-01

    Current methods for rapid detection of delayed graft function (DGF) after kidney transplantation are unreliable. Urinary clusterin is a biomarker of kidney injury but its utility for prediction of graft dysfunction is unknown. In a single-center, prospective cohort study of renal transplant recipients (N=81), urinary clusterin was measured serially between 4 hr and 7 days after transplantation. The utility of clusterin for prediction of DGF (hemodialysis within 7 days of transplantation) was compared with urinary interleukin (IL)-18, neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1, serum creatinine, and clinical variables. At 4 hr after reperfusion, anuria was highly specific, but of low sensitivity for detection of DGF. At 4 hr, receiver operating characteristic analysis suggested that urinary clusterin, IL-18, kidney injury molecule-1, and NGAL concentration were predictive of DGF. After adjusting for preoperative clinical variables and anuria, clusterin and IL-18 independently enhanced the clinical model for prediction of DGF. Kidney injury molecule-1 only modestly improved the prediction of DGF, whereas NGAL, serum creatinine, and the creatinine reduction ratio did not improve on the clinical model. At 12 hr, the creatinine reduction ratio independently predicted DGF. Both urinary clusterin and IL-18 are useful biomarkers and may allow triaging of patients with DGF within 4 hr of transplantation. Relative performance of biomarkers for prediction of graft function is time-dependant. Early and frequent measurements of serum creatinine and calculation of the creatinine reduction ratio also predict DGF within 12 hr of reperfusion.

  1. 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.

  2. Predicting mortality with biomarkers: a population-based prospective cohort study for elderly Costa Ricans

    Directory of Open Access Journals (Sweden)

    Rosero-Bixby Luis

    2012-06-01

    Full Text Available Abstract Background Little is known about adult health and mortality relationships outside high-income nations, partly because few datasets have contained biomarker data in representative populations. Our objective is to determine the prognostic value of biomarkers with respect to total and cardiovascular mortality in an elderly population of a middle-income country, as well as the extent to which they mediate the effects of age and sex on mortality. Methods This is a prospective population-based study in a nationally representative sample of elderly Costa Ricans. Baseline interviews occurred mostly in 2005 and mortality follow-up went through December 2010. Sample size after excluding observations with missing values: 2,313 individuals and 564 deaths. Main outcome: prospective death rate ratios for 22 baseline biomarkers, which were estimated with hazard regression models. Results Biomarkers significantly predict future death above and beyond demographic and self-reported health conditions. The studied biomarkers account for almost half of the effect of age on mortality. However, the sex gap in mortality became several times wider after controlling for biomarkers. The most powerful predictors were simple physical tests: handgrip strength, pulmonary peak flow, and walking speed. Three blood tests also predicted prospective mortality: C-reactive protein (CRP, glycated hemoglobin (HbA1c, and dehydroepiandrosterone sulfate (DHEAS. Strikingly, high blood pressure (BP and high total cholesterol showed little or no predictive power. Anthropometric measures also failed to show significant mortality effects. Conclusions This study adds to the growing evidence that blood markers for CRP, HbA1c, and DHEAS, along with organ-specific functional reserve indicators (handgrip, walking speed, and pulmonary peak flow, are valuable tools for identifying vulnerable elderly. The results also highlight the need to better understand an anomaly noted previously in

  3. Multi-Center Prediction of Hemorrhagic Transformation in Acute Ischemic Stroke using Permeability Imaging Features

    Science.gov (United States)

    Scalzo, Fabien; Alger, Jeffry R.; Hu, Xiao; Saver, Jeffrey L.; Dani, Krishna A.; Muir, Keith W.; Demchuk, Andrew M.; Coutts, Shelagh B.; Luby, Marie; Warach, Steven; Liebeskind, David S.

    2013-01-01

    Permeability images derived from magnetic resonance (MR) perfusion images are sensitive to blood-brain barrier derangement of the brain tissue and have been shown to correlate with subsequent development of hemorrhagic transformation (HT) in acute ischemic stroke. This paper presents a multi-center retrospective study that evaluates the predictive power in terms of HT of six permeability MRI measures including contrast slope (CS), final contrast (FC), maximum peak bolus concentration (MPB), peak bolus area (PB), relative recirculation (rR), and percentage recovery (%R). Dynamic T2*-weighted perfusion MR images were collected from 263 acute ischemic stroke patients from four medical centers. An essential aspect of this study is to exploit a classifier-based framework to automatically identify predictive patterns in the overall intensity distribution of the permeability maps. The model is based on normalized intensity histograms that are used as input features to the predictive model. Linear and nonlinear predictive models are evaluated using a crossvalidation to measure generalization power on new patients and a comparative analysis is provided for the different types of parameters. Results demonstrate that perfusion imaging in acute ischemic stroke can predict HT with an average accuracy of more than 85% using a predictive model based on a nonlinear regression model. Results also indicate that the permeability feature based on the percentage of recovery performs significantly better than the other features. This novel model may be used to refine treatment decisions in acute stroke. PMID:23587928

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

    NARCIS (Netherlands)

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

    2015-01-01

    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

  5. Cardiovascular biomarkers predict susceptibility 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

    2013-05-01

    Pulmonary vascular loss is an early feature of chronic obstructive pulmonary disease. Biomarkers of inflammation and of metabolic syndrome predict loss of lung function in World Trade Center (WTC) lung injury (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 subcohort of 124 out of 801 subjects with serum drawn within 6 months of 9/11 defined CVD biomarker distribution. Post-9/11 forced expiratory volume in 1 s (FEV1) at defined cases were as follows: susceptible WTC-LI cases with FEV1 ≤77% predicted (66 out of 801) and resistant WTC-LI cases with FEV1 ≥107% predicted (68 out of 801). All models were adjusted for WTC exposure intensity, body mass index at SPE, age on 9/11 and pre-9/11 FEV1. Susceptible WTC-LI cases had higher levels of apolipoprotein-AII, C-reactive protein and macrophage inflammatory protein-4 with significant relative risks (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 soluble vascular cell adhesion molecule and lower myeloperoxidase, with RRs of 2.24 and 2.89, respectively (AUC 0.830). Biomarkers of CVD in serum 6 months post-9/11 predicted either susceptibility or resistance to WTC-LI. These biomarkers may define pathways either producing or protecting subjects from pulmonary vascular disease and associated loss of lung function after an irritant exposure.

  6. Prediction of hemorrhagic transformation after experimental ischemic stroke using MRI-based algorithms.

    Science.gov (United States)

    Bouts, Mark Jrj; Tiebosch, Ivo Acw; Rudrapatna, Umesh S; van der Toorn, Annette; Wu, Ona; Dijkhuizen, Rick M

    2017-08-01

    Estimation of hemorrhagic transformation (HT) risk is crucial for treatment decision-making after acute ischemic stroke. We aimed to determine the accuracy of multiparametric MRI-based predictive algorithms in calculating probability of HT after stroke. Spontaneously, hypertensive rats were subjected to embolic stroke and, after 3 h treated with tissue plasminogen activator (Group I: n = 6) or vehicle (Group II: n = 7). Brain MRI measurements of T 2 , T 2 *, diffusion, perfusion, and blood-brain barrier permeability were obtained at 2, 24, and 168 h post-stroke. Generalized linear model and random forest (RF) predictive algorithms were developed to calculate the probability of HT and infarction from acute MRI data. Validation against seven-day outcome on MRI and histology revealed that highest accuracy of hemorrhage prediction was achieved with a RF-based model that included spatial brain features (Group I: area under the receiver-operating characteristic curve (AUC) = 0.85 ± 0.14; Group II: AUC = 0.89 ± 0.09), with significant improvement over perfusion- or permeability-based thresholding methods. However, overlap between predicted and actual tissue outcome was significantly lower for hemorrhage prediction models (maximum Dice's Similarity Index (DSI) = 0.20 ± 0.06) than for infarct prediction models (maximum DSI = 0.81 ± 0.06). Multiparametric MRI-based predictive algorithms enable early identification of post-ischemic tissue at risk of HT and may contribute to improved treatment decision-making after acute ischemic stroke.

  7. Prognostic and predictive biomarkers in adult and paediatric gliomas: towards personalised brain tumour treatment

    Directory of Open Access Journals (Sweden)

    Harry R Haynes

    2014-03-01

    Full Text Available It is increasingly clear that both adult and paediatric glial tumour entities represent collections of neoplastic lesions, each with individual pathological molecular events and treatment responses. In this review we discuss the current prognostic biomarkers validated for clinical use or with future clinical validity for gliomas. Accurate prognostication is crucial for managing patients as treatments may be associated with high morbidity and the benefits of high risk interventions must be judged by the treating clinicians. We also review biomarkers with predictive validity which may become clinically relevant with the development of targeted therapies for adult and paediatric gliomas.

  8. 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...

  9. 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.

  10. Albuminuria predicts early neurological deterioration in patients with acute ischemic stroke.

    Science.gov (United States)

    Kanamaru, Takuya; Suda, Satoshi; Muraga, Kanako; Okubo, Seiji; Watanabe, Yoko; Tsuruoka, Syuichi; Kimura, Kazumi

    2017-01-15

    Reduced glomerular filtration rate (GFR) and albuminuria have been independently associated with an increased risk of stroke and unfavorable long-term outcomes. However, the association between GFR, albuminuria, and early neurological deterioration (END) in patients with ischemic stroke has not been well studied to date. We therefore investigated the ability of estimated GFR (eGFR) and albuminuria to predict END in patients with acute ischemic stroke. We retrospectively enrolled 294 patients that were admitted to our stroke center with acute ischemic stroke between January 2011 and September 2012. General blood and urine examinations, including eGFR and urinary albumin/creatinine ratio (UACR) measurements, were performed on admission. Kidney dysfunction was defined by a low eGFR value (albuminuria (≥30mg/g creatinine). END was defined as a ≥2-point increase in the National Institutes of Health Stroke Scale (NIHSS) score within 7days after admission. Kidney dysfunction was diagnosed in 200 of the 294 patients (68.0%). END was observed in 60 patients (20.4%). Age, blood glucose level on admission, UACR on admission, and NIHSS score on admission were significantly associated with END, while no relationship between eGFR on admission and END was identified. A multivariable logistic regression analysis showed that END was positively associated with high UACR (≥39.6mg/g creatinine) and a high NIHSS score (≥6 points). Our data suggest that high UACR on admission may predict END in patients with acute ischemic stroke. Larger prospective studies are required to validate the correlation between albuminuria and END. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Tumor Microvessel Density as a Potential Predictive Marker for Bevacizumab Benefit: GOG-0218 Biomarker Analyses.

    Science.gov (United States)

    Bais, Carlos; Mueller, Barbara; Brady, Mark F; Mannel, Robert S; Burger, Robert A; Wei, Wei; Marien, Koen M; Kockx, Mark M; Husain, Amreen; Birrer, Michael J

    2017-11-01

    Combining bevacizumab with frontline chemotherapy statistically significantly improved progression-free survival (PFS) but not overall survival (OS) in the phase III GOG-0218 trial. Evaluation of candidate biomarkers was an exploratory objective. Patients with stage III (incompletely resected) or IV ovarian cancer were randomly assigned to receive six chemotherapy cycles with placebo or bevacizumab followed by single-agent placebo or bevacizumab. Five candidate tumor biomarkers were assessed by immunohistochemistry. The biomarker-evaluable population was categorized into high or low biomarker-expressing subgroups using median and quartile cutoffs. Associations between biomarker expression and efficacy were analyzed. All statistical tests were two-sided. The biomarker-evaluable population (n = 980) comprising 78.5% of the intent-to-treat population had representative baseline characteristics and efficacy outcomes. Neither prognostic nor predictive associations were seen for vascular endothelial growth factor (VEGF) receptor-2, neuropilin-1, or MET. Higher microvessel density (MVD; measured by CD31) showed predictive value for PFS (hazard ratio [HR] for bevacizumab vs placebo = 0.40, 95% confidence interval [CI] = 0.29 to 0.54, vs 0.80, 95% CI = 0.59 to 1.07, for high vs low MVD, respectively, P interaction = .003) and OS (HR = 0.67, 95% CI = 0.51 to 0.88, vs 1.10, 95% CI = 0.84 to 1.44, P interaction = .02). Tumor VEGF-A was not predictive for PFS but showed potential predictive value for OS using a third-quartile cutoff for high VEGF-A expression. These retrospective tumor biomarker analyses suggest a positive association between density of vascular endothelial cells (the predominant cell type expressing VEGF receptors) and tumor VEGF-A levels and magnitude of bevacizumab effect in ovarian cancer. The potential predictive value of MVD (CD31) and tumor VEGF-A is consistent with a mechanism of action driven by VEGF-A signaling blockade. © The

  12. Predicting major bleeding in patients with noncardioembolic stroke on antiplatelets: S2TOP-BLEED

    NARCIS (Netherlands)

    Hilkens, Nina A.; Algra, Ale; Diener, Hans-Christoph; Reitsma, Johannes B.; Bath, Philip M.; Csiba, Laszlo; Hacke, Werner; Kappelle, L. Jaap; Koudstaal, Peter J.; Leys, Didier; Mas, Jean-Louis; Sacco, Ralph L.; Amarenco, Pierre; Sissani, Leila; Greving, Jacoba P.; Gent, M.; Beaumont, D.; Blanchard, J.; Bousser, M. G.; Coffman, J.; Easton, J. D.; Hampton, J. R.; Harker, L. A.; Janzon, L.; Kusmierek, Jje; Panak, E.; Roberts, R. S.; Shannon, S.; Sicurella, J.; Tognoni, G.; Topol, E. J.; Verstraete, M.; Warlow, C.; Blard, J. M.; Capildeo, R.; Diener, H. C.; Ersmark, B.; Escartin, A.; Ferro, J.; Galvin, R.; Hogenhuis, Lah; Laterre, C.; Provincial, L.; Rinne, U. K.; Bovim, G.; Lowenthal, A.; Bogousslavsky, J.; Brass, L.; Cimminiello, C.; Csiba, L.; Kaste, M.; Leys, D.; Matias-Guiu, J.; Rupprecht, H. J.; Berger, P. B.; Bhatt, D. L.; Black, H. R.; Boden, W. E.; Cacoub, P.; Cohen, E. A.; Creager, M. A.; Flather, M. D.; Fox, Kaa; Hacke, W.; Haffner, S. M.; Hamm, C. W.; Hankey, G. J.; Johnston, S. C.; Mak, K. H.; Mas, J. L.; Montalescot, G.; Pearson, T. A.; Steg, P. G.; Steinhubl, S. R.; Weber, M. A.; Aichner, F.; Algra, A.; Chamorro, A.; Chen, Cplh; de Schryver, Ellm; Ferro, J. M.; van Gijn, J.; Hertzberger, L. I.; Koudstaal, P. J.; Ricci, S.; Ringelstein, E. B.; Vanhooren, G.; Venables, G. S.; Albers, G.; Bath, P.; Bornstein, N.; Chan, B.; Chen, S.-T.; Cunha, L.; Dahlöf, B.; DeKeyser, J.; Donnan, G.; Estol, C.; Gorelick, P.; Lu, C.; Pais, P.; Roberts, R.; Sacco, R.; Skvortsova, V.; Teal, P.; Toni, D.; Weber, M.; Yoon, B. W.; Yusuf, S.; Amarenco, P.; Bousser, M.-G.; Fisher, M.; Ford, I.; Fox, K. M.; Hennerici, M. G.; Mattle, H. P.; Rothwell, P.; Sissani, L.; Labreuche, J.; Steg, G.; Vicaut, E.

    2017-01-01

    To develop and externally validate a prediction model for major bleeding in patients with a TIA or ischemic stroke on antiplatelet agents. We combined individual patient data from 6 randomized clinical trials (CAPRIE, ESPS-2, MATCH, CHARISMA, ESPRIT, and PRoFESS) investigating antiplatelet therapy

  13. What Factors Predict Who Will Have a Strong Social Network Following a Stroke?

    Science.gov (United States)

    Northcott, Sarah; Marshall, Jane; Hilari, Katerina

    2016-01-01

    Purpose: Measures of social networks assess the number and nature of a person's social contacts, and strongly predict health outcomes. We explored how social networks change following a stroke and analyzed concurrent and baseline predictors of social networks 6 months poststroke. Method: We conducted a prospective longitudinal observational study.…

  14. Early Prediction of Outcome of Activities of Daily Living After Stroke A Systematic Review

    NARCIS (Netherlands)

    Veerbeek, Janne M.; Kwakkel, Gert; van Wegen, Erwin E. H.; Ket, Johannes C. F.; Heymans, Martijn W.

    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

  15. 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 ...

  16. Prediction of Ischemic Heart Disease and Stroke in Survivors of Childhood Cancer

    NARCIS (Netherlands)

    Chow, Eric J.; Chen, Yan; Hudson, Melissa M.; Feijen, Elizabeth A. M.; Kremer, Leontien C.; Border, William L.; Green, Daniel M.; Meacham, Lillian R.; Mulrooney, Daniel A.; Ness, Kirsten K.; Oeffinger, Kevin C.; Ronckers, Cécile M.; Sklar, Charles A.; Stovall, Marilyn; van der Pal, Helena J.; van Dijk, Irma W. E. M.; van Leeuwen, Flora E.; Weathers, Rita E.; Robison, Leslie L.; Armstrong, Gregory T.; Yasui, Yutaka

    2018-01-01

    Purpose We aimed to predict individual risk of ischemic heart disease and stroke in 5-year survivors of childhood cancer. Patients and Methods Participants in the Childhood Cancer Survivor Study (CCSS; n = 13,060) were observed through age 50 years for the development of ischemic heart disease and

  17. What predicts a poor outcome in older stroke survivors? A systematic review of the literature

    NARCIS (Netherlands)

    van Almenkerk, S.; Smalbrugge, M.; Depla, M.F.I.A.; Eefsting, J.A.; Hertogh, C.M.P.M.

    2013-01-01

    Purpose: To identify factors in the early post-stroke period that have a predictive value for a poor outcome, defined as institutionalization or severe disability. Methods: MEDLINE, PSYCINFO, EMBASE and CINAHL were systematically searched for observational cohort studies in which adult and/or

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

    NARCIS (Netherlands)

    Veerbeek, J.M.; Kwakkel, G.; van Wegen, 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

  19. 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.

  20. A Model for Predicting Persistent Elevation of Factor VIII among Patients with Acute Ischemic Stroke

    Science.gov (United States)

    Samai, Alyana A.; Boehme, Amelia K.; Shaban, Amir; George, Alexander J.; Dowell, Lauren; Monlezun, Dominique J.; Leissinger, Cindy; Schluter, Laurie; El Khoury, Ramy; Martin-Schild, Sheryl

    2016-01-01

    Background and Purpose Elevated levels of coagulation factor VIII (FVIII) may persist independent of the acute-phase response; however, this relationship has not been investigated relative to acute ischemic stroke (AIS). We examined the frequency and predictors of persistently elevated FVIII in AIS patients. Methods AIS patients admitted between July 2008 and May 2014 with elevated baseline FVIII levels and repeat FVIII levels drawn for more than 7 days postdischarge were included. The patients were dichotomized by repeat FVIII level for univariate analysis at 150% and 200% activity thresholds. An adjusted model was developed to predict the likelihood of persistently elevated FVIII levels. Results Among 1616 AIS cases, 98 patients with elevated baseline FVIII had repeat FVIII levels. Persistent FVIII elevation was found in more than 75% of patients. At the 150% threshold, the prediction score ranged from 0 to 7 and included black race, female sex, prior stroke, hyperlipidemia, smoking, baseline FVIII > 200%, and baseline von Willebrand factor (vWF) level greater than 200%. At the 200% threshold, the prediction score ranged from 0–5 and included female sex, prior stroke, diabetes mellitus, baseline FVIII level greater 200%, and baseline vWF level greater than 200%. For each 1-point increase in score, the odds of persistent FVIII at both the 150% threshold (odds ratio [OR] = 10.4, 95% confidence interval [CI] 1.63–66.9, P = .0134) and 200% threshold (OR = 10.2, 95% CI 1.82–57.5, P = .0083) increased 10 times. Conclusion Because an elevated FVIII level confers increased stroke risk, our model for anticipating a persistently elevated FVIII level may identify patients at high risk for recurrent stroke. FVIII may be a target for secondary stroke prevention. PMID:26777556

  1. Overestimation of Susceptibility Vessel Sign: A Predictive Marker of Stroke Cause.

    Science.gov (United States)

    Zhang, Ruiting; Zhou, Ying; Liu, Chang; Zhang, Meixia; Yan, Shenqiang; Liebeskind, David S; Lou, Min

    2017-07-01

    The extent of blooming artifact may reflect the amount of paramagnetic material. We thus assessed the overestimation ratio of susceptibility vessel sign (SVS) on susceptibility-weighted imaging, defined as the extent of SVS width beyond the lumen and examined its value for predicting the stroke cause in acute ischemic stroke patients. We included consecutive acute ischemic stroke patients with proximal large artery occlusion who underwent both susceptibility-weighted imaging and time-of-flight magnetic resonance angiography within 8 hours poststroke onset. We calculated the length, width, and overestimation ratio of SVS on susceptibility-weighted imaging and then investigated their values for predicting the stroke cause, respectively. One-hundred eleven consecutive patients (72 female; mean age, 66.6±13.4 years) were enrolled, among whom 39 (35.1%) were diagnosed with cardiogenic embolism, 43 (38.7%) with large artery atherosclerosis, and 29 (26.1%) with undetermined cause. The presence, length, width, and overestimation ratio of SVS were all independently associated with the cause of cardiogenic embolism after adjusting for baseline National Institute of Health Stroke Scale and infarct volume. After excluded patients with undetermined cause, the sensitivity and specificity of overestimation ratio of SVS for cardiogenic embolism were 0.971 and 0.913; for the length of SVS, they were 0.629 and 0.739; for the width of SVS, they were 0.829 and 0.826, respectively. The overestimation ratio of SVS can predict cardiogenic embolism, with both high sensitivity and specificity, which can be helpful for the management of acute ischemic stroke patients in hyperacute stage. © 2017 American Heart Association, Inc.

  2. 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.

  3. Diagnostic, Predictive, Prognostic, and Therapeutic Molecular Biomarkers in Third Millennium: A Breakthrough in Gastric Cancer

    Directory of Open Access Journals (Sweden)

    Nicola Carlomagno

    2017-01-01

    Full Text Available Introduction. Gastric cancer is the fifth most common cancer and the third cause of cancer death. The clinical outcomes of the patients are still not encouraging with a low rate of 5 years’ survival. Often the disease is diagnosed at advanced stages and this obviously negatively affects patients outcomes. A deep understanding of molecular basis of gastric cancer can lead to the identification of diagnostic, predictive, prognostic, and therapeutic biomarkers. Main Body. This paper aims to give a global view on the molecular classification and mechanisms involved in the development of the tumour and on the biomarkers for gastric cancer. We discuss the role of E-cadherin, HER2, fibroblast growth factor receptor (FGFR, MET, human epidermal growth factor receptor (EGFR, hepatocyte growth factor receptor (HGFR, mammalian target of rapamycin (mTOR, microsatellite instability (MSI, PD-L1, and TP53. We have also considered in this manuscript new emerging biomarkers as matrix metalloproteases (MMPs, microRNAs, and long noncoding RNAs (lncRNAs. Conclusions. Identifying and validating diagnostic, prognostic, predictive, and therapeutic biomarkers will have a huge impact on patients outcomes as they will allow early detection of tumours and also guide the choice of a targeted therapy based on specific molecular features of the cancer.

  4. 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.

  5. Prediction of Pneumonia in Acute Stroke Patients Using Tongue Pressure Measurements.

    Science.gov (United States)

    Nakamori, Masahiro; Hosomi, Naohisa; Ishikawa, Kenichi; Imamura, Eiji; Shishido, Takeo; Ohshita, Tomohiko; Yoshikawa, Mineka; Tsuga, Kazuhiro; Wakabayashi, Shinichi; Maruyama, Hirofumi; Matsumoto, Masayasu

    2016-01-01

    Swallowing dysfunction caused by stroke is a risk factor for aspiration pneumonia. Tongue pressure measurement is a simple and noninvasive method for evaluating swallowing dysfunction. We have hypothesized that low tongue pressure may be able to predict pneumonia occurrence in acute stroke patients. Tongue pressure was measured using balloon-type equipment in 220 acute stroke patients. The modified Mann Assessment of Swallowing Ability (MASA) score was evaluated independently on the same day. Tongue pressure was measured every week thereafter. An improvement in tongue pressure was observed within the first 2 weeks. Receiver operating curve analysis was performed to determine the ability of tongue pressure to predict modified MASA score tongue pressure was 21.6 kPa (χ2 = 45.82, ptongue pressure was significantly lower in patients with pneumonia than in those without pneumonia. Using a Cox proportional hazard model for pneumonia onset with a cutoff tongue pressure value of 21.6 kPa and adjustment for age, sex, and National Institutes of Health Stroke Scale score at admission, the tongue pressure had additional predictive power for pneumonia onset (hazard ratio, 7.95; 95% confidence interval, 2.09 to 52.11; p = 0.0013). In the group with low tongue pressure, 27 of 95 patients showed improvement of tongue pressure within 2 weeks. Pneumonia occurred frequently in patients without improvement of tongue pressure, but not in patients with improvement (31/68 and 2/27, pTongue pressure is a sensitive indicator for predicting pneumonia occurrence in acute stroke patients.

  6. Prediction of prognosis of upper-extremity function following stroke-related paralysis using brain imaging.

    Science.gov (United States)

    Nakashima, Akira; Moriuchi, Takefumi; Mitsunaga, Wataru; Yonezawa, Takehito; Kataoka, Hideki; Nakashima, Ryusei; Koizumi, Tetsuji; Shimizu, Tadashi; Ryu, Nobutoshi; Higashi, Toshio

    2017-08-01

    [Purpose] Diffusion tensor imaging (DTI) has attracted attention as a method for determining prognosis following paralysis after stroke. However, DTI can assess the degree of damage to the corticospinal tract but cannot evaluate other brain regions. In this study, we examined in detail the prognosis of upper-limb function of the paralyzed side following stroke, using DTI and voxel-based morphometry (VBM). [Subjects and Methods] We studied 17 consecutive patients diagnosed with stroke, including hemorrhagic and ischemic types, who exhibited hemiparesis and were treated in our hospital. DTI and VBM were performed 14 days after admission. Outcome measurements that assessed upper limb function were Fugl-Meyer Assessment (FMA) and Motor Activity Log (MAL), which were applied after 3 months. [Results] The fractional anisotropy ratio of the bilateral cerebral peduncles (rFA) was significantly correlated with FMA, amount of use, and quality of movement 3 months after stroke. The precentral gyrus significantly degenerated as compared with the control group for a case with notable motor paralysis, for which rFA was high. [Conclusion] We suggest it may be possible to predict recovery of upper limb function following stroke by combining DTI and VBM visualization methods.

  7. Use of Oxygen Pulse in Predicting Doppler-Derived Maximal Stroke Volume in Adolescents.

    Science.gov (United States)

    Unnithan, Vishwanath; Rowland, Thomas W

    2015-08-01

    Clinical exercise physiologists and physicians administering stress tests in the young have used oxygen pulse as a surrogate measure of stroke volume. It is important to recognize 1) the accuracy of O₂ pulse in predicting maximal stroke volume during exercise, and 2) the normal pattern of O₂ pulse during a progressive exercise test. This study examined both of these issues in a cohort of 44 healthy adolescent males and females (ages 14-16 years) who performed routine progressive cycle exercise to exhaustion. Gas exchange variables were measured by standard open circuit techniques. Stroke volume at rest and during exercise was assessed by the Doppler ultrasound method. At peak exercise O₂ pulse correlated closely with stroke volume (r = .73) with a SEE of 12.6 ml·beat⁻¹. Values of maximal O₂ pulse in nonathletic boys and girls were 13.3 ± 2.5 and 11.0 ± 1.7 ml·beat⁻¹, respectively. After the initial workload, a steady rise was observed in O₂ pulse, entirely reflecting an increasing arterial venous oxygen difference, with a slope of approximately 4 ml/beat per 100 watts work load. The findings support the use of O₂ pulse as a valid predictor of stroke volume during exercise in youth with a moderately high level of accuracy.

  8. 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.

  9. 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.

  10. 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.

  11. ETS Gene Fusions as Predictive Biomarkers of Resistance to Radiation Therapy for Prostate Cancer

    Science.gov (United States)

    2016-05-01

    Award  Number:    W81XWH-10-1-0582 TITLE:      ETS Gene Fusions as Predictive Biomarkers of Resistance to Radiation Therapy for Prostate Cancer...5a.  CONTRACT  NUMBER   ETS Gene Fusions as Predictive Biomarkers of Resistance to Radiation Therapy for Prostate Cancer 5b.  GRANT  NUMBER   W81XWH...ramifications,  particularly  in  the  context  of   radiation   therapy ,   which  represents  a  primary  treatment  modality  for  localized  prostate

  12. 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

    (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...... to PARP-1i. Here we addressed these issues using PARP-1i on 20 human cell lines from carcinomas of the breast, prostate, colon, pancreas and ovary. Aberrations of the Mre11-Rad50-Nbs1 (MRN) complex sensitized cancer cells to PARP-1i, while p53 status was less predictive, even in response to PARP-1i...... 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...

  13. 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.

  14. 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.

  15. Sialylated Fetuin-A as a candidate predictive biomarker for successful grass pollen allergen immunotherapy

    OpenAIRE

    Caillot, Noemie; Bouley, Julien; Jain, Karine; Mariano, Sandrine; Luce, Sonia; Horiot, Stéphane; Airouche, Sabi; Beuraud, Chloe; Beauvallet, Christian; Devillier, Philippe; Chollet-Martin, Sylvie; Kellenberger, Christine; Mascarell, Laurent; Chabre, Henri; Batard, Thierry

    2017-01-01

    Background: Eligibility to immunotherapy is based on the determination of IgE reactivity to a specific allergen by means of skin prick or in vitro testing. Biomarkers predicting the likelihood of clinical improvement during immunotherapy would significantly improve patient selection. Methods: Proteins were differentially assessed by using 2-dimensional differential gel electrophoresis and label-free mass spectrometry in pretreatment sera obtained from clinical responders and nonresponders wit...

  16. 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

  17. Prediction of outcome in patients with suspected acute ischaemic stroke with CT perfusion and CT angiography: the Dutch acute stroke trial (DUST) study protocol.

    Science.gov (United States)

    van Seeters, Tom; Biessels, Geert Jan; van der Schaaf, Irene C; Dankbaar, Jan Willem; Horsch, Alexander D; Luitse, Merel J A; Niesten, Joris M; Mali, Willem P T M; Kappelle, L Jaap; van der Graaf, Yolanda; Velthuis, Birgitta K

    2014-02-25

    Prediction of clinical outcome in the acute stage of ischaemic stroke can be difficult when based on patient characteristics, clinical findings and on non-contrast CT. CT perfusion and CT angiography may provide additional prognostic information and guide treatment in the early stage. We present the study protocol of the Dutch acute Stroke Trial (DUST). The DUST aims to assess the prognostic value of CT perfusion and CT angiography in predicting stroke outcome, in addition to patient characteristics and non-contrast CT. For this purpose, individualised prediction models for clinical outcome after stroke based on the best predictors from patient characteristics and CT imaging will be developed and validated. The DUST is a prospective multi-centre cohort study in 1500 patients with suspected acute ischaemic stroke. All patients undergo non-contrast CT, CT perfusion and CT angiography within 9 hours after onset of the neurological deficits, and, if possible, follow-up imaging after 3 days. The primary outcome is a dichotomised score on the modified Rankin Scale, assessed at 90 days. A score of 0-2 represents good outcome, and a score of 3-6 represents poor outcome. Three logistic regression models will be developed, including patient characteristics and non-contrast CT (model A), with addition of CT angiography (model B), and CT perfusion parameters (model C). Model derivation will be performed in 60% of the study population, and model validation in the remaining 40% of the patients. Additional prognostic value of the models will be determined with the area under the curve (AUC) from the receiver operating characteristic (ROC) curve, calibration plots, assessment of goodness-of-fit, and likelihood ratio tests. This study will provide insight in the added prognostic value of CTP and CTA parameters in outcome prediction of acute stroke patients. The prediction models that will be developed in this study may help guide future treatment decisions in the acute stage of

  18. Sit-and-reach test can predict mobility of patients recovering from acute stroke.

    Science.gov (United States)

    Tsang, Yuk Lan; Mak, Margaret Kit

    2004-01-01

    To establish the test-retest reliability of the sit-and-reach test (SRT) and to determine the capacity of the SRT to predict mobility of patients recovering from acute stroke. Study 1 consisted of repeating the SRT to examine its reliability over trials (same day) and sessions (alternate days). Study 2 consisted of measuring performance in the SRT 7 to 10 days poststroke and measuring mobility at discharge for prospective analysis. Medical and rehabilitation wards in hospital in Hong Kong. Thirty-six subjects with acute stroke (study 1, n=10; study 2, n=26). Not applicable. Between 7 and 10 days of stroke onset, distance reached on the SRT was measured. Mobility at discharge was assessed using the transfer and locomotion scale of the FIM instrument (FIM mobility) and a timed walk test. The intertrial and intersession reliability of the SRT were rated good, with intraclass correlation coefficients of .98 and .79, respectively. Distance reached on the SRT correlated with the FIM mobility score on discharge (r=.572, P=.002) and the distance achieved on the timed walk test (r=.524, P=.006). Distance reached on the SRT accounted for 32.7% and 27.5% of the variance in the FIM mobility score at discharge and the distance achieved on the timed walk test, respectively. Performance in the SRT is reliable and can significantly predict the mobility of patients with acute stroke at discharge.

  19. The predictive value of CT signs in the early and subacute stages of ischaemic stroke

    International Nuclear Information System (INIS)

    Podkowa, J.; Kowalewski, K.; Filarski, J.; Sasiadek, M.; Sokolowska, D.; Podemski, R.; Guranski, K.

    2003-01-01

    Computed tomography (CT), despite the development of new imaging methods like diffusion-weighted MR and perfusion MR, is usually the initial examination procedure in stroke patients. However, the predictive value of early CT signs in ischaemic stroke has not been established yet. Therefore, the purpose of this study was to assess the clinical significance of CT findings in the early and subacute stages of the ischaemic stroke. Thirty-five patients with ischaemic stroke of middle cerebral artery territory had CT studies performed within 18 hours after ictus and on the 5th day. Following CT signs were analyzed: the extent of hypodensity and mass effect (both calculated using our own method), obscuring of the lentiform and caudate nuclei, as well as the insular ribbon, Sylvian fissure and lateral ventricle compression, ventricular displacement, and hyperdense middle cerebral artery sign (HMCAS). The results were compared statistically with clinical scorings at admission and on day 30. Among the early CT signs only lentiform nucleus obscuring was correlated with both early and the late clinical scales. Caudate nucleus obscuring, Sylvian fissure compression and mass effect extent were correlated with early clinical scoring only, while lateral ventricle compression with the late clinical scale. Other findings affected neither early nor late clinical scorings. Most of the follow-up CT symptoms showed a strong correlation with the late clinical scoring, with an exception of Sylvian fissure compression and HMCAS. Early CT has limited predictive value in assessing stroke patients. The only statistically significant signs are lentiform nucleus obscuring and ventricular compression. However, most subacute CT findings have high predictive value. (author)

  20. Do clinical assessments, steady-state or daily-life gait characteristics predict falls in ambulatory chronic stroke survivors?

    NARCIS (Netherlands)

    Punt, Michiel; Bruijn, Sjoerd M.; Wittink, Harriet; van de Port, Ingrid G.; Van Dieën, Jaap H.

    2017-01-01

    Objective: This exploratory study investigated to what extent gait characteristics and clinical physical therapy assessments predict falls in chronic stroke survivors. Design: Prospective study. Subjects: Chronic fall-prone and non-fall-prone stroke survivors. Methods: Steady-state gait

  1. Circulating Biomarkers for Predicting Infliximab Response in Rheumatoid Arthritis: A Systematic Bioinformatics Analysis.

    Science.gov (United States)

    Huang, Qiu-Lan; Zhou, Fu-Jiang; Wu, Cheng-Bin; Xu, Chao; Qian, Wen-Ying; Fan, De-Ping; Cai, Xu-Shan

    2017-04-17

    BACKGROUND Infliximab shows good efficacy in treating refractory rheumatoid arthritis (RA). However, many patients responded poorly and related studies were inconsistent in predictive biomarkers. This study aimed to identify circulating biomarkers for predicting infliximab response in RA. MATERIAL AND METHODS Public databases of Gene Expression Omnibus (GEO) and ArrayExpress were searched for related microarray datasets, focused on the response to infliximab in RA. All peripheral blood samples were collected before infliximab treatment and gene expression profiles were measured using microarray. Differential genes associated with infliximab efficacy were analyzed. The genes recognized by half of the datasets were regarded as candidate biomarkers and validated by prospective datasets. RESULTS Eight microarray datasets were identified with 374 blood samples of RA patients, among which 191 (51.1%) were diagnosed as non-responders in the subsequent infliximab treatment. Five genes (FKBP1A, FGF12, ANO1, LRRC31, and AKR1D1) were associated with the efficacy and recognized by half of the datasets. The 5-gene model showed a good predictive power in random- and prospective-designed studies, with AUC (area under receiver operating characteristic [ROC] curve)=0.963 and 1.000, and it was also applicable at the early phase of treatment (at week 2) for predicting the response at week 14 (AUC=1.000). In the placebo group, the model failed to predict the response (AUC=0.697), indicating the model's specificity in infliximab treatment. CONCLUSIONS The model of FKBP1A, FGF12, ANO1, LRRC31, and AKR1D1 in peripheral blood is useful for efficiently predicting the response to infliximab treatment in rheumatoid arthritis.

  2. 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.

  3. Reduced Maximum Pitch Elevation Predicts Silent Aspiration of Small Liquid Volumes in Stroke Patients

    Directory of Open Access Journals (Sweden)

    Akila Theyyar Rajappa

    2017-08-01

    Full Text Available Background and purposePreliminary evidence has shown that reduced ability to maximally raise vocal pitch correlates with the occurrence of aspiration (i.e., airway invasion by food or liquid. However, it is unclear if this simple task can be used as a reliable predictor of aspiration in stroke patients. Our aim was to examine whether maximum vocal pitch elevation predicted airway invasion and dysphagia in stroke.MethodsForty-five consecutive stroke patients (<1 month poststroke at a rehabilitation setting participated in a videofluoroscopic swallow study and two maximum vocal pitch elevation tasks. Maximum pitch was evaluated acoustically [maximum fundamental frequency (max F0] and perceptually. Swallowing safety was rated using the Penetration/Aspiration Scale and swallowing performance was assessed using components of the Modified Barium Swallow Impairment Profile (MBSImPTM©. Data were analyzed using simple regression and receiver operating characteristics curves to test the sensitivity and specificity of max F0 in predicting aspiration. Correlations between max F0 and MBSImP variables were also examined.ResultsMax F0 predicted silent aspiration of small liquid volumes with 80% sensitivity and 65% specificity (p = 0.023; area under the curve: 0.815; cutoff value of 359.03 Hz. Max F0 did not predict non-silent aspiration or penetration in this sample and did not significantly correlate with MBSImP variables. Furthermore, all participants who aspirated silently on small liquid volumes (11% of sample had suffered cortical or subcortical lesions.ConclusionIn stroke patients (<1 month poststroke, reduced maximum pitch elevation predicts silent aspiration of small liquid volumes with high sensitivity and moderate specificity. Future large-scale studies focusing on further validating this finding and exploring the value of this simple and non-invasive tool as part of a dysphagia screening are warranted.

  4. 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

  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. Proteinuria, but Not eGFR, Predicts Stroke Risk in Chronic Kidney Disease: Chronic Renal Insufficiency Cohort Study.

    Science.gov (United States)

    Sandsmark, Danielle K; Messé, Steven R; Zhang, Xiaoming; Roy, Jason; Nessel, Lisa; Lee Hamm, Lotuce; He, Jiang; Horwitz, Edward J; Jaar, Bernard G; Kallem, Radhakrishna R; Kusek, John W; Mohler, Emile R; Porter, Anna; Seliger, Stephen L; Sozio, Stephen M; Townsend, Raymond R; Feldman, Harold I; Kasner, Scott E

    2015-08-01

    Chronic kidney disease is associated with an increased risk of cardiovascular events. However, the impact of chronic kidney disease on cerebrovascular disease is less well understood. We hypothesized that renal function severity would be predictive of stroke risk, independent of other vascular risk factors. The study population included 3939 subjects enrolled in the Chronic Renal Insufficiency Cohort (CRIC) study, a prospective observational cohort. Stroke events were reported by participants and adjudicated by 2 vascular neurologists. Cox proportional hazard models were used to compare measures of baseline renal function with stroke events. Multivariable analysis was performed to adjust for key covariates. In 3939 subjects, 143 new stroke events (0.62 events per 100 person-years) occurred over a mean follow-up of 6.4 years. Stroke risk was increased in subjects who had worse baseline measurements of renal function (estimated glomerular filtration rate and total proteinuria or albuminuria). When adjusted for variables known to influence stroke risk, total proteinuria or albuminuria, but not estimated glomerular filtration rate, were associated with an increased risk of stroke. Treatment with blockers of the renin-angiotensin system did not decrease stroke risk in individuals with albuminuria. Proteinuria and albuminuria are better predictors of stroke risk in patients with chronic kidney disease than estimated glomerular filtration rate. The impact of therapies targeting proteinuria/albuminuria in individuals with chronic kidney disease on stroke prevention warrants further investigation. © 2015 American Heart Association, Inc.

  7. 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.

  8. 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.

  9. Relative efficiency of precision medicine designs for clinical trials with predictive biomarkers.

    Science.gov (United States)

    Shih, Weichung Joe; Lin, Yong

    2018-02-28

    Prospective randomized clinical trials addressing biomarkers are time consuming and costly, but are necessary for regulatory agencies to approve new therapies with predictive biomarkers. For this reason, recently, there have been many discussions and proposals of various trial designs and comparisons of their efficiency in the literature. We compare statistical efficiencies between the marker-stratified design and the marker-based precision medicine design regarding testing/estimating 4 hypotheses/parameters of clinical interest, namely, treatment effects in each marker-positive and marker-negative cohorts, marker-by-treatment interaction, and the marker's clinical utility. As may be expected, the stratified design is more efficient than the precision medicine design. However, it is perhaps surprising to find out how low the relative efficiency can be for the precision medicine design. We quantify the relative efficiency as a function of design factors including the marker-positive prevalence rate, marker assay and classification sensitivity and specificity, and the treatment randomization ratio. It is interesting to examine the trends of the relative efficiency with these design parameters in testing different hypotheses. We advocate to use the stratified design over the precision medicine design in clinical trials with predictive biomarkers. Copyright © 2017 John Wiley & Sons, Ltd.

  10. EEG biomarkers in major depressive disorder: discriminative power and prediction of treatment response.

    Science.gov (United States)

    Olbrich, Sebastian; Arns, Martijn

    2013-10-01

    Major depressive disorder (MDD) has high population prevalence and is associated with substantial impact on quality of life, not least due to an unsatisfactory time span of sometimes several weeks from initiation of treatment to clinical response. Therefore extensive research focused on the identification of cost-effective and widely available electroencephalogram (EEG)-based biomarkers that not only allow distinguishing between patients and healthy controls but also have predictive value for treatment response for a variety of treatments. In this comprehensive overview on EEG research on MDD, biomarkers that are either assessed at baseline or during the early course of treatment and are helpful in discriminating patients from healthy controls and assist in predicting treatment outcome are reviewed, covering recent decades up to now. Reviewed markers include quantitative EEG (QEEG) measures, connectivity measures, EEG vigilance-based measures, sleep-EEG-related measures and event-related potentials (ERPs). Further, the value and limitations of these different markers are discussed. Finally, the need for integrated models of brain function and the necessity for standardized procedures in EEG biomarker research are highlighted to enhance future research in this field.

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

    Science.gov (United States)

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

    2016-06-01

    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. 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. 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. 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.

  12. 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

  13. 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.

  14. Predicting long-term outcome after acute ischemic stroke: a simple index works in patients from controlled clinical trials.

    Science.gov (United States)

    König, Inke R; Ziegler, Andreas; Bluhmki, Erich; Hacke, Werner; Bath, Philip M W; Sacco, Ralph L; Diener, Hans C; Weimar, Christian

    2008-06-01

    An early and reliable prognosis for recovery in stroke patients is important for initiation of individual treatment and for informing patients and relatives. We recently developed and validated models for predicting survival and functional independence within 3 months after acute stroke, based on age and the National Institutes of Health Stroke Scale score assessed within 6 hours after stroke. Herein we demonstrate the applicability of our models in an independent sample of patients from controlled clinical trials. The prognostic models were used to predict survival and functional recovery in 5419 patients from the Virtual International Stroke Trials Archive (VISTA). Furthermore, we tried to improve the accuracy by adapting intercepts and estimating new model parameters. The original models were able to correctly classify 70.4% (survival) and 72.9% (functional recovery) of patients. Because the prediction was slightly pessimistic for patients in the controlled trials, adapting the intercept improved the accuracy to 74.8% (survival) and 74.0% (functional recovery). Novel estimation of parameters, however, yielded no relevant further improvement. For acute ischemic stroke patients included in controlled trials, our easy-to-apply prognostic models based on age and National Institutes of Health Stroke Scale score correctly predicted survival and functional recovery after 3 months. Furthermore, a simple adaptation helps to adjust for a different prognosis and is recommended if a large data set is available.

  15. 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.

  16. 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.

  17. F-18 fluoromisonidazole PET predicts early lesion progression in acute ischemic stroke patients

    Energy Technology Data Exchange (ETDEWEB)

    Lee, G. H.; Kim, J. S.; Oh, S. J.; Cho, A. H.; Cho, K. H.; Kang, D. H.; Kim, J. S.; Kwon, S. E. [Asan Medical Center, Seoul (Korea, Republic of)

    2007-07-01

    F-18 fluoromisonidazole (FMISO) PET has been known to image viable hypoxic area. We performed this study to define whether FMISO PET can reveal ischemic penumbra of acute ischemic stroke. We prospectively selected acute ischemic stroke patients with large diffusion-perfusion mismatch due to occlusion of MCA or ICA on MRI among patients who visited emergency room within 24 hours after stroke onset. FMISO PET and diffusion weighted MR image (DWI) performed within 48 hours after initial MRI. We excluded the patients who performed any reperfusion procedure. To define the final infarcted area, DWI was performed again 2 days after PET scan. Brain FMISO PET was performed 3 hour after the injection of FMISO (370 MBq). FMISO PET was assessed by visual and quantitative analysis. The extent of abnormally increased FMISO uptake was automatically calculated by the number and size of voxels having higher count than upper 3SD of the mean count of contralateral normal hemisphere. We compared the extent of abnormal FMISO uptake area with the change of the extent of ischemic lesions on DWI. Fifteen patients were enrolled in this study. Ten of these patients showed abnormally increased FMISO uptake in peri-infarct area. Ischemic lesion size on follow-up DWI significantly increased in all patients with abnormally increased FMISO uptake except one patient of whom the MCA spontaneously recanalized on follow up angiogram. Ischemic lesions on DWI increased in only one of five patients without abnormally increased FMISO uptake. The extent of abnormally increased FMISO uptake area was positively correlated with infarct size progression on DWI (Spearman correlation coefficient = 0.757, p<0.01). FMISO uptake specifically and sensitively predicted early lesion progression in acute ischemic stroke patients with large diffusion-perfusion mismatch. Therefore, FMISO PET will be a good indicator of the revascularization or reperfusion procedure for acute ischemic stroke by defining ischemic

  18. 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

    Directory of Open Access Journals (Sweden)

    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.

  19. Usefulness of Multiple Biomarkers for Predicting Incident Major Adverse Cardiac Events in Patients Who Underwent Diagnostic Coronary Angiography (from the Catheter Sampled Blood Archive in Cardiovascular Diseases [CASABLANCA] Study).

    Science.gov (United States)

    McCarthy, Cian P; van Kimmenade, Roland R J; Gaggin, Hanna K; Simon, Mandy L; Ibrahim, Nasrien E; Gandhi, Parul; Kelly, Noreen; Motiwala, Shweta R; Belcher, Arianna M; Harisiades, Jamie; Magaret, Craig A; Rhyne, Rhonda F; Januzzi, James L

    2017-07-01

    We sought to develop a multiple biomarker approach for prediction of incident major adverse cardiac events (MACE; composite of cardiovascular death, myocardial infarction, and stroke) in patients referred for coronary angiography. In a 649-participant training cohort, predictors of MACE within 1 year were identified using least-angle regression; over 50 clinical variables and 109 biomarkers were analyzed. Predictive models were generated using least absolute shrinkage and selection operator with logistic regression. A score derived from the final model was developed and evaluated with a 278-patient validation set during a median of 3.6 years follow-up. The scoring system consisted of N-terminal pro B-type natriuretic peptide (NT-proBNP), kidney injury molecule-1, osteopontin, and tissue inhibitor of metalloproteinase-1; no clinical variables were retained in the predictive model. In the validation cohort, each biomarker improved model discrimination or calibration for MACE; the final model had an area under the curve (AUC) of 0.79 (p Time-to-first MACE was shorter in those with an elevated score (p <0.001); such risk extended to at least to 4 years. In conclusion, in a cohort of patients who underwent coronary angiography, we describe a novel multiple biomarker score for incident MACE within 1 year (NCT00842868). Copyright © 2017 Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

    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.

  1. Prediction of final infarct volume on subacute MRI by quantifying cerebral edema in ischemic stroke.

    Science.gov (United States)

    Tipirneni-Sajja, Aaryani; Christensen, Soren; Straka, Matus; Inoue, Manabu; Lansberg, Maarten G; Mlynash, Michael; Bammer, Roland; Parsons, Mark W; Donnan, Geoffrey A; Davis, Stephen M; Albers, Gregory W

    2017-08-01

    Final infarct volume in stroke trials is assessed on images obtained between 30 and 90 days after stroke onset. Imaging at such delayed timepoints is problematic because patients may be lost to follow-up or die before the scan. Obtaining an early assessment of infarct volume on subacute scans avoids these limitations; however, it overestimates true infarct volume because of edema. The aim of this study was to develop a novel approach to quantify edema so that final infarct volumes can be approximated on subacute scans. We analyzed data from 20 stroke patients (median age, 75 years) who had baseline, subacute (fu5d) and late (fu90d) MRI scans. Edema displaces CSF from sulci and ventricles; therefore, edema volume was estimated as change in CSF volume between baseline and spatially coregistered fu5d ADC maps. The median (interquartile range, IQR) estimated edema volume was 13.3 (7.5-37.7) mL. The fu5d lesion volumes correlated well with fu90d infarct volumes with slope: 1.24. With edema correction, fu5d infarct volumes are in close agreement, slope: 0.97 and strongly correlated with actual fu90d volumes. The median (IQR) difference between actual and predicted infarct volumes was 0.1 (-3.0-5.7) mL. In summary, this novel technique for estimation of edema allows final infarct volume to be predicted from subacute MRI.

  2. Metabolomics based predictive biomarker model of ARDS: A systemic measure of clinical hypoxemia.

    Directory of Open Access Journals (Sweden)

    Neeraj Sinha

    Full Text Available Despite advancements in ventilator technologies, lung supportive and rescue therapies, the outcome and prognostication in acute respiratory distress syndrome (ARDS remains incremental and ambiguous. Metabolomics is a potential insightful measure to the diagnostic approaches practiced in critical disease settings. In our study patients diagnosed with mild and moderate/severe ARDS clinically governed by hypoxemic P/F ratio between 100-300 but with indistinct molecular phenotype were discriminated employing nuclear magnetic resonance (NMR based metabolomics of mini bronchoalveolar lavage fluid (mBALF. Resulting biomarker prototype comprising six metabolites was substantiated highlighting ARDS susceptibility/recovery. Both the groups (mild and moderate/severe ARDS showed distinct biochemical profile based on 83.3% classification by discriminant function analysis and cross validated accuracy of 91% using partial least squares discriminant analysis as major classifier. The predictive performance of narrowed down six metabolites were found analogous with chemometrics. The proposed biomarker model consisting of six metabolites proline, lysine/arginine, taurine, threonine and glutamate were found characteristic of ARDS sub-stages with aberrant metabolism observed mainly in arginine, proline metabolism, lysine synthesis and so forth correlating to diseased metabotype. Thus NMR based metabolomics has provided new insight into ARDS sub-stages and conclusively a precise biomarker model proposed, reflecting underlying metabolic dysfunction aiding prior clinical decision making.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  5. Distinctive cytokines as biomarkers predicting fatal outcome of severe Staphylococcus aureus bacteremia in mice.

    Science.gov (United States)

    van den Berg, Sanne; Laman, Jon D; Boon, Louis; ten Kate, Marian T; de Knegt, Gerjo J; Verdijk, Rob M; Verbrugh, Henri A; Nouwen, Jan L; Bakker-Woudenberg, Irma A J M

    2013-01-01

    Invasive Staphylococcus aureus infections are frequently associated with bacteraemia. To support clinical decisions on antibiotic therapy, there is an urgent need for reliable markers as predictors of infection outcome. In the present study in mice, bacteraemia was established by intravenous inoculation of a clinical S. aureus isolate at the LD50 inoculum. As potential biomarkers for fatal outcome, blood culture (qualitative and quantitative), serum levels of C-reactive protein (CRP), as well as 31 selected cytokines and chemokines were assessed during the first three days of infection. A positive S. aureus blood culture, the quantitative blood culture, CRP levels, and levels of eight cytokines were indicative for the presence of S. aureus bacteraemia. However, only tumor necrosis factor (TNF) α, interleukin (IL) 1α, and keratinocyte chemoattractant (KC; a functional homologue of human IL-8) were each significantly elevated in eventually non-surviving infected mice versus eventually surviving infected mice. In severe S. aureus bacteraemia in mice, TNF-α, IL-1α, and KC are biomarkers predicting fatal outcome of infection. KC was a biomarker elevated irrespective the progression of infection, which is very interesting regarding clinical application in view of the heterogeneity of patients experiencing bacteraemia in this respect.

  6. 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.

  7. 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.

  8. Predictive impact of daily physical activity on new vascular events in patients with mild ischemic stroke.

    Science.gov (United States)

    Kono, Yuji; Kawajiri, Hiroyuki; Kamisaka, Kenta; Kamiya, Kuniyasu; Akao, Keigo; Asai, Chikako; Inuzuka, Kana; Yamada, Sumio

    2015-02-01

    negative predictive values of less than 6025 steps were 38.0% and 91.6%, respectively. Our data indicate that daily physical activity evaluated by step counts may be useful for forecasting the prognosis in patients with mild ischemic stroke. Daily step counts of approximately 6000 steps per day may be an initial target level for reducing new vascular events. © 2014 World Stroke Organization.

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

    Science.gov (United States)

    Quesada, Andrés; Vargas, Félix; Montoro-Molina, Sebastián; O'Valle, Francisco; Rodríguez-Martínez, María Dolores; Osuna, Antonio; Prieto, Isabel; Ramírez, Manuel; Wangensteen, Rosemary

    2012-01-01

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  13. Biomarker expression in cervical intraepithelial neoplasia: potential progression predictive factors for low-grade lesions

    OpenAIRE

    Ozaki, Satoru; Zen, Yoh; Inoue, Masaki

    2011-01-01

    The aim of this study was to reveal whether 3 biomarkers (p16INK4a, ProEx C, and human papilloma virus DNA) are useful in the diagnosis of cervical intraepithelial neoplasia and whether they could predict disease progression of cervical intraepithelial neoplasia-1. We analyzed 252 cervical specimens: nondysplastic mucosa (n = 9), cervical intraepithelial neoplasia (n = 229), and squamous cell carcinoma (n = 14). Immunostaining for p16INK4a and ProEx C, and the hybridcapture II assay for human...

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

    Science.gov (United States)

    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

  15. Robust predictive modelling of water pollution using\\ud biomarker data

    OpenAIRE

    Budka, Marcin; Gabrys, Bogdan; Ravagnan, Elisa

    2010-01-01

    This paper describes the methodology of building a predictive model for the\\ud purpose of marine pollution monitoring, based on low quality biomarker data.\\ud A step–by–step, systematic data analysis approach is presented, resulting in\\ud design of a purely data–driven model, able to accurately discriminate between\\ud various coastal water pollution levels.\\ud The environmental scientists often try to apply various machine learning\\ud techniques to their data without much success, mostly beca...

  16. Feature Selection Methods for Early Predictive Biomarker Discovery Using Untargeted Metabolomic Data.

    Science.gov (United States)

    Grissa, Dhouha; Pétéra, Mélanie; Brandolini, Marion; Napoli, Amedeo; Comte, Blandine; Pujos-Guillot, Estelle

    2016-01-01

    Untargeted metabolomics is a powerful phenotyping tool for better understanding biological mechanisms involved in human pathology development and identifying early predictive biomarkers. This approach, based on multiple analytical platforms, such as mass spectrometry (MS), chemometrics and bioinformatics, generates massive and complex data that need appropriate analyses to extract the biologically meaningful information. Despite various tools available, it is still a challenge to handle such large and noisy datasets with limited number of individuals without risking overfitting. Moreover, when the objective is focused on the identification of early predictive markers of clinical outcome, few years before occurrence, it becomes essential to use the appropriate algorithms and workflow to be able to discover subtle effects among this large amount of data. In this context, this work consists in studying a workflow describing the general feature selection process, using knowledge discovery and data mining methodologies to propose advanced solutions for predictive biomarker discovery. The strategy was focused on evaluating a combination of numeric-symbolic approaches for feature selection with the objective of obtaining the best combination of metabolites producing an effective and accurate predictive model. Relying first on numerical approaches, and especially on machine learning methods (SVM-RFE, RF, RF-RFE) and on univariate statistical analyses (ANOVA), a comparative study was performed on an original metabolomic dataset and reduced subsets. As resampling method, LOOCV was applied to minimize the risk of overfitting. The best k-features obtained with different scores of importance from the combination of these different approaches were compared and allowed determining the variable stabilities using Formal Concept Analysis. The results revealed the interest of RF-Gini combined with ANOVA for feature selection as these two complementary methods allowed selecting the 48

  17. Predicting major bleeding in patients with noncardioembolic stroke on antiplatelets: S2TOP-BLEED.

    Science.gov (United States)

    Hilkens, Nina A; Algra, Ale; Diener, Hans-Christoph; Reitsma, Johannes B; Bath, Philip M; Csiba, Laszlo; Hacke, Werner; Kappelle, L Jaap; Koudstaal, Peter J; Leys, Didier; Mas, Jean-Louis; Sacco, Ralph L; Amarenco, Pierre; Sissani, Leila; Greving, Jacoba P

    2017-08-29

    To develop and externally validate a prediction model for major bleeding in patients with a TIA or ischemic stroke on antiplatelet agents. We combined individual patient data from 6 randomized clinical trials (CAPRIE, ESPS-2, MATCH, CHARISMA, ESPRIT, and PRoFESS) investigating antiplatelet therapy after TIA or ischemic stroke. Cox regression analyses stratified by trial were performed to study the association between predictors and major bleeding. A risk prediction model was derived and validated in the PERFORM trial. Performance was assessed with the c statistic and calibration plots. Major bleeding occurred in 1,530 of the 43,112 patients during 94,833 person-years of follow-up. The observed 3-year risk of major bleeding was 4.6% (95% confidence interval [CI] 4.4%-4.9%). Predictors were male sex, smoking, type of antiplatelet agents (aspirin-clopidogrel), outcome on modified Rankin Scale ≥3, prior stroke, high blood pressure, lower body mass index, elderly, Asian ethnicity, and diabetes (S 2 TOP-BLEED). The S 2 TOP-BLEED score had a c statistic of 0.63 (95% CI 0.60-0.64) and showed good calibration in the development data. Major bleeding risk ranged from 2% in patients aged 45-54 years without additional risk factors to more than 10% in patients aged 75-84 years with multiple risk factors. In external validation, the model had a c statistic of 0.61 (95% CI 0.59-0.63) and slightly underestimated major bleeding risk. The S 2 TOP-BLEED score can be used to estimate 3-year major bleeding risk in patients with a TIA or ischemic stroke who use antiplatelet agents, based on readily available characteristics. The discriminatory performance may be improved by identifying stronger predictors of major bleeding. © 2017 American Academy of Neurology.

  18. 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.

  19. 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.

  20. 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.

  1. A Multiplex Cancer/Testis Antigen-Based Biomarker Panel to Predict Aggressive Phenotype of Prostate Cancer

    Science.gov (United States)

    2015-10-01

    correlated with no protein translation. 15. SUBJECT TERMS Prostate cancer; metastatic prostate cancer; cancer/testis antigens (CTA); biomarker ; gene...Antigen retrieval was performed under heat and adequate pH. After that, steps for endogenous peroxide activity and unspecific protein blocking were...AWARD NUMBER: W81XWH-12-1-0535 TITLE: A Multiplex Cancer/Testis Antigen-Based Biomarker Panel to Predict Aggressive Phenotype of Prostate

  2. Accuracy of prediction scores and novel biomarkers for predicting nonalcoholic fatty liver disease in obese children

    NARCIS (Netherlands)

    Koot, Bart G. P.; van der Baan-Slootweg, Olga H.; Bohte, Anneloes E.; Nederveen, Aart J.; van Werven, Jochem R.; Tamminga-Smeulders, Christine L. J.; Merkus, Maruschka P.; Schaap, Frank G.; Jansen, Peter L. M.; Stoker, Jaap; Benninga, Marc A.

    2013-01-01

    Accurate prediction scores for liver steatosis are demanded to enable clinicians to noninvasively screen for nonalcoholic fatty liver disease (NAFLD). Several prediction scores have been developed, however external validation is lacking. The aim was to determine the diagnostic accuracy of four

  3. 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

  4. Risk assessment and predicting outcomes in patients with depressive symptoms: A review of potential role of peripheral blood based biomarkers.

    Directory of Open Access Journals (Sweden)

    Bhautesh Dinesh Jani

    2015-02-01

    Full Text Available Depression is one of the major global health challenges and a leading contributor of health related disability and costs. Depression is a heterogeneous disorder and current methods for assessing its severity in clinical practice rely on symptom count, however this approach is unreliable and inconsistent. The clinical evaluation of depressive symptoms is particularly challenging in primary care, where the majority of patients with depression are managed, due to the presence of co-morbidities. Current methods for risk assessment of depression do not accurately predict treatment response or clinical outcomes. Several biological pathways have been implicated in the pathophysiology of depression; however, accurate and predictive biomarkers remain elusive. We conducted a systematic review of the published evidence supporting the use of peripheral biomarkers to predict outcomes in depression, using Medline and Embase. Peripheral biomarkers in depression were found to be statistically significant predictors of mental health outcomes such as treatment response, poor outcome and symptom remission; and physical health outcomes such as increased incidence of cardiovascular events and deaths, and all-cause mortality. However, the available evidence has multiple methodological limitations which must be overcome to make any real clinical progress. Despite extensive research on the relationship of depression with peripheral biomarkers, its translational application in practice remains uncertain. In future, peripheral biomarkers identified with novel techniques and combining multiple biomarkers may have a potential role in depression risk assessment but further research is needed in this area.

  5. Current immunological and molecular tools for leptospirosis: diagnostics, vaccine design, and biomarkers for predicting severity.

    Science.gov (United States)

    Rajapakse, Senaka; Rodrigo, Chaturaka; Handunnetti, Shiroma M; Fernando, Sumadhya Deepika

    2015-01-16

    Leptospirosis is a zoonotic spirochaetal illness that is endemic in many tropical countries. The research base on leptospirosis is not as strong as other tropical infections such as malaria. However, it is a lethal infection that can attack many vital organs in its severe form, leading to multi-organ dysfunction syndrome and death. There are many gaps in knowledge regarding the pathophysiology of leptospirosis and the role of host immunity in causing symptoms. This hinders essential steps in combating disease, such as developing a potential vaccine. Another major problem with leptospirosis is the lack of an easy to perform, accurate diagnostic tests. Many clinicians in resource limited settings resort to clinical judgment in diagnosing leptospirosis. This is unfortunate, as many other diseases such as dengue, hanta virus, rickettsial infections, and even severe bacterial sepsis, can mimic leptospirosis. Another interesting problem is the prediction of disease severity at the onset of the illness. The majority of patients recover from leptospirosis with only a mild febrile illness, while a few others have severe illness with multi-organ failure. Clinical features are poor predictors of potential severity of infection, and therefore the search is on for potential biomarkers that can serve as early warnings for severe disease. This review concentrates on these three important aspects of this neglected tropical disease: diagnostics, developing a vaccine, and potential biomarkers to predict disease severity.

  6. 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.

  7. Chymase Level Is a Predictive Biomarker of Dengue Hemorrhagic Fever in Pediatric and Adult Patients.

    Science.gov (United States)

    Tissera, Hasitha; Rathore, Abhay P S; Leong, Wei Yee; Pike, Brian L; Warkentien, Tyler E; Farouk, Farouk S; Syenina, Ayesa; Eong Ooi, Eng; Gubler, Duane J; Wilder-Smith, Annelies; St John, Ashley L

    2017-11-27

    Most patients with dengue experience mild disease, dengue fever (DF), while few develop the life-threatening diseases dengue hemorrhagic fever (DHF) or dengue shock syndrome (DSS). No laboratory tests predict DHF or DSS. We evaluated whether the serum chymase level can predict DHF or DSS in adult and pediatric patients and the influence of preexisting conditions (PECs) on chymase levels. Serum chymase levels were measured in patients presenting with undifferentiated fever to hospitals in Colombo District, Sri Lanka. The value of serum the chymase concentration and clinical signs and symptoms as predictors of DHF and/or DSS was evaluated by multivariate analysis. We assessed the influence of age, PECs, and day after fever onset on the robustness of the chymase level as a biomarker for DHF and/or DSS. An elevated chymase level in acute phase blood samples was highly indicative of later diagnosis of DHF or DSS for pediatric and adult patients with dengue. No recorded PECs prevented an increase in the chymase level during DHF. However, certain PECs (obesity and cardiac or lung-associated diseases) resulted in a concomitant increase in chymase levels among adult patients with DHF. These results show that patients with acute dengue who present with high levels of serum chymase consistently are at greater risk of DHF. The chymase level is a robust prognostic biomarker of severe dengue for adult and pediatric patients. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America.

  8. Predicting Prostate Biopsy Results Using a Panel of Plasma and Urine Biomarkers Combined in a Scoring System

    DEFF Research Database (Denmark)

    Albitar, Maher; Ma, Wanlong; Lund, Lars

    2016-01-01

    , and PTEN in plasma and urine. Patient age, serum prostate-specific antigen (sPSA) level, and biomarkers data were used to develop two independent algorithms, one for predicting the presence of PCa and the other for predicting high-grade PCa (Gleason score [GS] ≥7). RESULTS: Using training and validation...

  9. 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

  10. Prediction of Clinical Outcome in Acute Hemorrhagic Stroke from a Single CT Scan on Admission.

    Science.gov (United States)

    Nag, Chiranjib; Das, Kamalesh; Ghosh, Mrinalkanti; Khandakar, M R

    2012-10-01

    From a single CT scan in primary intracerebral hemorrhage (ICH), clinical outcome can be assessed on admission by using the CT scan parameters. The study aims to find out how hematoma volume, location of stroke, midline shift, intraventricular extension of bleed and ventricle compression influence the clinical outcome in patients with acute ICH. Non-contrast CT scan was done on admission in hospital for every patient with acute hemorrhagic stroke and was analyzed accordingly. Clinical assessments were done in National Institute of Health Stroke Scale (NIHSS). Chi-square test and multiple logistic regression analysis were used for statistical analysis. Mean hematoma volume associated with death before 30 days is 33.16 cm(3) (P 30 cm(3) (OR = 27.857), brain stem hemorrhage (OR = 6.000), intraventricular extension of bleed from other location (OR = 7.846), presence of ventricular compression alone (OR = 2.700) and in combination with midline shift of ≥ 5 mm (OR = 2.124). From a single CT scan during hospital admission, mortality and morbidity in next 30 days can be predicted. A hematoma volume >30 cm(3), brain stem hematoma, intraventricular extension of bleed and ventricular compression along and with midline shift are associated with early mortality in ICH.

  11. Predicting future biomass yield inMiscanthususing the carbohydrate metabolic profile as a biomarker.

    Science.gov (United States)

    Maddison, Anne L; Camargo-Rodriguez, Anyela; Scott, Ian M; Jones, Charlotte M; Elias, Dafydd M O; Hawkins, Sarah; Massey, Alice; Clifton-Brown, John; McNamara, Niall P; Donnison, Iain S; Purdy, Sarah J

    2017-07-01

    In perennial energy crop breeding programmes, it can take several years before a mature yield is reached when potential new varieties can be scored. Modern plant breeding technologies have focussed on molecular markers, but for many crop species, this technology is unavailable. Therefore, prematurity predictors of harvestable yield would accelerate the release of new varieties. Metabolic biomarkers are routinely used in medicine, but they have been largely overlooked as predictive tools in plant science. We aimed to identify biomarkers of productivity in the bioenergy crop, Miscanthus, that could be used prognostically to predict future yields. This study identified a metabolic profile reflecting productivity in Miscanthus by correlating the summer carbohydrate composition of multiple genotypes with final yield 6 months later. Consistent and strong, significant correlations were observed between carbohydrate metrics and biomass traits at two separate field sites over 2 years. Machine-learning feature selection was used to optimize carbohydrate metrics for support vector regression models, which were able to predict interyear biomass traits with a correlation ( R ) of >0.67 between predicted and actual values. To identify a causal basis for the relationships between the glycome profile and biomass, a 13 C-labelling experiment compared carbohydrate partitioning between high- and low-yielding genotypes. A lower yielding and slower growing genotype partitioned a greater percentage of the 13 C pulse into starch compared to a faster growing genotype where a greater percentage was located in the structural biomass. These results supported a link between plant performance and carbon flow through two rival pathways (starch vs. sucrose), with higher yielding plants exhibiting greater partitioning into structural biomass, via sucrose metabolism, rather than starch. Our results demonstrate that the plant metabolome can be used prognostically to anticipate future yields and

  12. 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.

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

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    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.)

  14. Endothelial Progenitor Cells Predict Cardiovascular Events after Atherothrombotic Stroke and Acute Myocardial Infarction. A PROCELL Substudy.

    Directory of Open Access Journals (Sweden)

    Elisa Cuadrado-Godia

    Full Text Available The aim of this study was to determine prognostic factors for the risk of new vascular events during the first 6 months after acute myocardial infarction (AMI or atherothrombotic stroke (AS. We were interested in the prognostic role of endothelial progenitor cells (EPC and circulating endothelial cells (CEC.Between February 2009 and July 2012, 100 AMI and 50 AS patients were consecutively studied in three Spanish centres. Patients with previously documented coronary artery disease or ischemic strokes were excluded. Samples were collected within 24h of onset of symptoms. EPC and CEC were studied using flow cytometry and categorized by quartiles. Patients were followed for up to 6 months. NVE was defined as new acute coronary syndrome, transient ischemic attack (TIA, stroke, or any hospitalization or death from cardiovascular causes. The variables included in the analysis included: vascular risk factors, carotid intima-media thickness (IMT, atherosclerotic burden and basal EPC and CEC count. Multivariate survival analysis was performed using Cox regression analysis.During follow-up, 19 patients (12.66% had a new vascular event (5 strokes; 3 TIAs; 4 AMI; 6 hospitalizations; 1 death. Vascular events were associated with age (P = 0.039, carotid IMT≥0.9 (P = 0.044, and EPC count (P = 0.041 in the univariate analysis. Multivariate Cox regression analysis showed an independent association with EPC in the lowest quartile (HR: 10.33, 95%CI (1.22-87.34, P = 0.032] and IMT≥0.9 [HR: 4.12, 95%CI (1.21-13.95, P = 0.023].Basal EPC and IMT≥0.9 can predict future vascular events in patients with AMI and AS, but CEC count does not affect cardiovascular risk.

  15. Predicting ischemic stroke after carotid artery stenting based on proximal calcification and the jellyfish sign.

    Science.gov (United States)

    Ichinose, Nobuhiko; Hama, Seiji; Tsuji, Toshio; Soh, Zu; Hayashi, Hideaki; Kiura, Yoshihiro; Sakamoto, Shigeyuki; Okazaki, Takahito; Ishii, Daizo; Shinagawa, Katsuhiro; Kurisu, Kaoru

    2017-07-07

    OBJECTIVE Carotid artery stenting (CAS) has been considered to prevent ischemic strokes caused by stenosis of the cervical carotid artery. The most common complication of CAS is new cerebral infarction. The authors have previously reported that the jellyfish sign-the rise and fall of the mobile component of the carotid plaque surface detected by carotid ultrasonography-suggests thinning and rupture of the fibrous cap over the unstable plaque content, such as the lipid-rich necrotic core or internal plaque hemorrhage. The authors' aim in the present study was to evaluate the risk of a new ischemic lesion after CAS by using many risk factors including calcification (size and location) and the jellyfish sign. METHODS Eighty-six lesions (77 patients) were treated with CAS. The presence of ischemic stroke was determined using diffusion-weighted imaging (DWI). Risk factors included calcification of the plaque (classified into 5 groups for size and 3 groups for location) and the jellyfish sign, among others. Multiple linear regression analysis (stepwise analysis and partial least squares [PLS] analysis) was conducted, followed by a machine learning analysis using an artificial neural network (ANN) based on the log-linearized gaussian mixture network (LLGMN). The additive effects of the jellyfish sign and calcification on ischemic stroke after CAS were examined using the Kruskal-Wallis test, followed by the Steel-Dwass test. RESULTS The stepwise analysis selected the jellyfish sign, proximal calcification (proximal Ca), low-density lipoprotein (LDL) cholesterol, and patient age for the prediction model to predict new DWI lesions. The PLS analysis revealed the same top 3 variables (jellyfish sign, proximal Ca, and LDL cholesterol) according to the variable importance in projection scores. The ANN was then used, showing that these 3 variables remained. The accuracy of the ANN improved; areas under the receiver operating characteristic curves of the stepwise analysis, the PLS

  16. 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.

  17. Accuracy of Prediction Instruments for Diagnosing Large Vessel Occlusion in Individuals With Suspected Stroke: A Systematic Review for the 2018 Guidelines for the Early Management of Patients With Acute Ischemic Stroke.

    Science.gov (United States)

    Smith, Eric E; Kent, David M; Bulsara, Ketan R; Leung, Lester Y; Lichtman, Judith H; Reeves, Mathew J; Towfighi, Amytis; Whiteley, William N; Zahuranec, Darin B

    2018-03-01

    Endovascular thrombectomy is a highly efficacious treatment for large vessel occlusion (LVO). LVO prediction instruments, based on stroke signs and symptoms, have been proposed to identify stroke patients with LVO for rapid transport to endovascular thrombectomy-capable hospitals. This evidence review committee was commissioned by the American Heart Association/American Stroke Association to systematically review evidence for the accuracy of LVO prediction instruments. Medline, Embase, and Cochrane databases were searched on October 27, 2016. Study quality was assessed with the Quality Assessment of Diagnostic Accuracy-2 tool. Thirty-six relevant studies were identified. Most studies (21 of 36) recruited patients with ischemic stroke, with few studies in the prehospital setting (4 of 36) and in populations that included hemorrhagic stroke or stroke mimics (12 of 36). The most frequently studied prediction instrument was the National Institutes of Health Stroke Scale. Most studies had either some risk of bias or unclear risk of bias. Reported discrimination of LVO mostly ranged from 0.70 to 0.85, as measured by the C statistic. In meta-analysis, sensitivity was as high as 87% and specificity was as high as 90%, but no threshold on any instruments predicted LVO with both high sensitivity and specificity. With a positive LVO prediction test, the probability of LVO could be 50% to 60% (depending on the LVO prevalence in the population), but the probability of LVO with a negative test could still be ≥10%. No scale predicted LVO with both high sensitivity and high specificity. Systems that use LVO prediction instruments for triage will miss some patients with LVO and milder stroke. More prospective studies are needed to assess the accuracy of LVO prediction instruments in the prehospital setting in all patients with suspected stroke, including patients with hemorrhagic stroke and stroke mimics. © 2018 American Heart Association, Inc.

  18. 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.

  19. 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.

  20. Human Hippocampal Structure: A Novel Biomarker Predicting Mnemonic Vulnerability to, and Recovery from, Sleep Deprivation

    Science.gov (United States)

    Goldstein-Piekarski, Andrea N.; Greer, Stephanie M.; Stark, Shauna; Stark, Craig E.

    2016-01-01

    Sleep deprivation impairs the formation of new memories. However, marked interindividual variability exists in the degree to which sleep loss compromises learning, the mechanistic reasons for which are unclear. Furthermore, which physiological sleep processes restore learning ability following sleep deprivation are similarly unknown. Here, we demonstrate that the structural morphology of human hippocampal subfields represents one factor determining vulnerability (and conversely, resilience) to the impact of sleep deprivation on memory formation. Moreover, this same measure of brain morphology was further associated with the quality of nonrapid eye movement slow wave oscillations during recovery sleep, and by way of such activity, determined the success of memory restoration. Such findings provide a novel human biomarker of cognitive susceptibility to, and recovery from, sleep deprivation. Moreover, this metric may be of special predictive utility for professions in which memory function is paramount yet insufficient sleep is pervasive (e.g., aviation, military, and medicine). SIGNIFICANCE STATEMENT Sleep deprivation does not impact all people equally. Some individuals show cognitive resilience to the effects of sleep loss, whereas others express striking vulnerability, the reasons for which remain largely unknown. Here, we demonstrate that structural features of the human brain, specifically those within the hippocampus, accurately predict which individuals are susceptible (or conversely, resilient) to memory impairments caused by sleep deprivation. Moreover, this same structural feature determines the success of memory restoration following subsequent recovery sleep. Therefore, structural properties of the human brain represent a novel biomarker predicting individual vulnerability to (and recovery from) the effects of sleep loss, one with occupational relevance in professions where insufficient sleep is pervasive yet memory function is paramount. PMID:26911684

  1. Return to work after mild-to-moderate stroke: work satisfaction and predictive factors

    NARCIS (Netherlands)

    van der Kemp, Jet; Kruithof, Willeke J.; Nijboer, Tanja C. W.; van Bennekom, Coen A. M.; van Heugten, Caroline; Visser-Meily, Johanna M. A.

    2017-01-01

    A large proportion of stroke patients are unable to return to work (RTW), although figures vary greatly. A total of 121 mild-to-moderate stroke patients, who had a paid job at the time of their stroke were included (a) to quantify RTW and work satisfaction one-year post-stroke (using the Utrecht

  2. A biomarker-based risk score to predict death in patients with atrial fibrillation: the ABC (age, biomarkers, clinical history) death risk score

    Science.gov (United States)

    Hijazi, Ziad; Oldgren, Jonas; Lindbäck, Johan; Alexander, John H; Connolly, Stuart J; Eikelboom, John W; Ezekowitz, Michael D; Held, Claes; Hylek, Elaine M; Lopes, Renato D; Yusuf, Salim; Granger, Christopher B; Siegbahn, Agneta; Wallentin, Lars

    2018-01-01

    Abstract Aims In atrial fibrillation (AF), mortality remains high despite effective anticoagulation. A model predicting the risk of death in these patients is currently not available. We developed and validated a risk score for death in anticoagulated patients with AF including both clinical information and biomarkers. Methods and results The new risk score was developed and internally validated in 14 611 patients with AF randomized to apixaban vs. warfarin for a median of 1.9 years. External validation was performed in 8548 patients with AF randomized to dabigatran vs. warfarin for 2.0 years. Biomarker samples were obtained at study entry. Variables significantly contributing to the prediction of all-cause mortality were assessed by Cox-regression. Each variable obtained a weight proportional to the model coefficients. There were 1047 all-cause deaths in the derivation and 594 in the validation cohort. The most important predictors of death were N-terminal pro B-type natriuretic peptide, troponin-T, growth differentiation factor-15, age, and heart failure, and these were included in the ABC (Age, Biomarkers, Clinical history)-death risk score. The score was well-calibrated and yielded higher c-indices than a model based on all clinical variables in both the derivation (0.74 vs. 0.68) and validation cohorts (0.74 vs. 0.67). The reduction in mortality with apixaban was most pronounced in patients with a high ABC-death score. Conclusion A new biomarker-based score for predicting risk of death in anticoagulated AF patients was developed, internally and externally validated, and well-calibrated in two large cohorts. The ABC-death risk score performed well and may contribute to overall risk assessment in AF. ClinicalTrials.gov identifier NCT00412984 and NCT00262600 PMID:29069359

  3. 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.)

  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. Prediction of early stroke risk in transient symptoms with infarction: relevance to the new tissue-based definition.

    Science.gov (United States)

    Arsava, E Murat; Furie, Karen L; Schwamm, Lee H; Sorensen, A Gregory; Ay, Hakan

    2011-08-01

    The risk of stroke shortly after transient ischemic attack with infarction on diffusion-weighted images, also known as transient symptoms with infarction (TSI), is substantially higher than is the risk after imaging-normal transient ischemic attack. We sought to assess the utility of a Web-based recurrence risk estimator (RRE; http://www.nmr.mgh.harvard.edu/RRE/) originally developed for use in patients with ischemic stroke for predicting 7-day risk of stroke in patients with TSI. We calculated RRE and ABCD² scores in a retrospective series of 257 consecutive patients with TSI diagnosed by diffusion-weighted images within 24 hours of symptom onset. We defined subsequent stroke as clinical deterioration associated with new infarction spatially distinct from the index lesion. We assessed the predictive performance of each model by computing the area under receiver-operating characteristics curve. Over 7-day follow-up, 16 patients developed a recurrent stroke (6.2%). The sensitivity and specificity of an RRE score of ≥ 2 for predicting 7-day stroke risk were 87% and 73%, respectively. The area under the receiver-operating characteristics curve was 0.85 (95% CI, 0.78-0.92) for RRE and 0.57 (95% CI, 0.45-0.69) for ABCD² score (z-test; Prisk of stroke after a TSI. If further validated in larger data sets, the RRE score could be useful in identifying high-risk patients with TSI who may benefit from early intervention with targeted stroke prevention strategies.

  6. Addition of 24-Hour Heart Rate Variability Parameters to the Cardiovascular Health Study Stroke Risk Score and Prediction of Incident Stroke: The Cardiovascular Health Study

    Science.gov (United States)

    Bodapati, Rohan K.; Kizer, Jorge R.; Kop, Willem J.; Kamel, Hooman; Stein, Phyllis K.

    2018-01-01

    Background Heart rate variability (HRV) characterizes cardiac autonomic functioning. The association of HRV with stroke is uncertain. We examined whether 24-hour HRV added predictive value to the Cardiovascular Health Study clinical stroke risk score (CHS-SCORE), previously developed at the baseline examination. Methods and Results N=884 stroke-free CHS participants (age 75.3 ± 4.6), with 24-hour Holters adequate for HRV analysis at the 1994–1995 examination, had 68 strokes over ≤8 year follow-up (median 7.3 [interquartile range 7.1–7.6] years). The value of adding HRV to the CHS-SCORE was assessed with stepwise Cox regression analysis. The CHS-SCORE predicted incident stroke (HR=1.06 per unit increment, P=0.005). Two HRV parameters, decreased coefficient of variance of NN intervals (CV%, P=0.031) and decreased power law slope (SLOPE, P=0.033) also entered the model, but these did not significantly improve the c-statistic (P=0.47). In a secondary analysis, dichotomization of CV% (LOWCV% ≤12.8%) was found to maximally stratify higher-risk participants after adjustment for CHS-SCORE. Similarly, dichotomizing SLOPE (LOWSLOPE <− 1.4) maximally stratified higher-risk participants. When these HRV categories were combined (eg, HIGHCV% with HIGHSLOPE), the c-statistic for the model with the CHS-SCORE and combined HRV categories was 0.68, significantly higher than 0.61 for the CHS-SCORE alone (P=0.02). Conclusions In this sample of older adults, 2 HRV parameters, CV% and power law slope, emerged as significantly associated with incident stroke when added to a validated clinical risk score. After each parameter was dichotomized based on its optimal cut point in this sample, their composite significantly improved prediction of incident stroke during ≤8-year follow-up. These findings will require validation in separate, larger cohorts. PMID:28396041

  7. Swimming and diving energetics in dolphins: a stroke-by-stroke analysis for predicting the cost of flight responses in wild odontocetes.

    Science.gov (United States)

    Williams, Terrie M; Kendall, Traci L; Richter, Beau P; Ribeiro-French, Courtney R; John, Jason S; Odell, Kim L; Losch, Barbara A; Feuerbach, David A; Stamper, M Andrew

    2017-03-15

    Exponential increases in hydrodynamic drag and physical exertion occur when swimmers move quickly through water, and underlie the preference for relatively slow routine speeds by marine mammals regardless of body size. Because of this and the need to balance limited oxygen stores when submerged, flight (escape) responses may be especially challenging for this group. To examine this, we used open-flow respirometry to measure the energetic cost of producing a swimming stroke during different levels of exercise in bottlenose dolphins ( Tursiops truncatus ). These data were then used to model the energetic cost of high-speed escape responses by other odontocetes ranging in mass from 42 to 2738 kg. The total cost per stroke during routine swimming by dolphins, 3.31±0.20 J kg -1  stroke -1 , was doubled during maximal aerobic performance. A comparative analysis of locomotor costs (LC; in J kg -1  stroke -1 ), representing the cost of moving the flukes, revealed that LC during routine swimming increased with body mass ( M ) for odontocetes according to LC=1.46±0.0005 M ; a separate relationship described LC during high-speed stroking. Using these relationships, we found that continuous stroking coupled with reduced glide time in response to oceanic noise resulted in a 30.5% increase in metabolic rate in the beaked whale, a deep-diving odontocete considered especially sensitive to disturbance. By integrating energetics with swimming behavior and dive characteristics, this study demonstrates the physiological consequences of oceanic noise on diving mammals, and provides a powerful tool for predicting the biological significance of escape responses by cetaceans facing anthropogenic disturbances. © 2017. Published by The Company of Biologists Ltd.

  8. Identification of Predictive Early Biomarkers for Sterile-SIRS after Cardiovascular Surgery.

    Science.gov (United States)

    Stoppelkamp, Sandra; Veseli, Kujtim; Stang, Katharina; Schlensak, Christian; Wendel, Hans Peter; Walker, Tobias

    2015-01-01

    Systemic inflammatory response syndrome (SIRS) is a common complication after cardiovascular surgery that in severe cases can lead to multiple organ dysfunction syndrome and even death. We therefore set out to identify reliable early biomarkers for SIRS in a prospective small patient study for timely intervention. 21 Patients scheduled for planned cardiovascular surgery were recruited in the study, monitored for signs of SIRS and blood samples were taken to investigate biomarkers at pre-assigned time points: day of admission, start of surgery, end of surgery, days 1, 2, 3, 5 and 8 post surgery. Stored plasma and cryopreserved blood samples were analyzed for cytokine expression (IL1β, IL2, IL6, IL8, IL10, TNFα, IFNγ), other pro-inflammatory markers (sCD163, sTREM-1, ESM-1) and response to endotoxin. Acute phase proteins CRP, PCT and pro-inflammatory cytokines IL6 and IL8 were significantly increased (pSIRS group at the end of surgery. Soluble TREM-1 plasma concentrations were significantly increased in patients with SIRS (pSIRS after cardiovascular surgery. A combination of normalized IL1β plasma levels, responses to endotoxin and soluble TREM-1 plasma concentrations at the end of surgery are predictive markers of SIRS development in this small scale study and could act as an indicator for starting early therapeutic interventions.

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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

  14. 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

  15. Somatosensory and Brainstem Auditory Evoked Potentials Assessed between 4 and 7 Days after Severe Stroke Onset Predict Unfavorable Outcome

    Directory of Open Access Journals (Sweden)

    Yan Zhang

    2015-01-01

    Full Text Available Our objective was to explore the best predictive timing of short-latency somatosensory evoked potentials (SLSEP and brainstem auditory evoked potentials (BAEP for unfavorable outcomes in patients with early stage severe stroke. One hundred fifty-six patients with acute severe supratentorial stroke were monitored according to SLSEP, BAEP, and the Glasgow Coma Scale (GCS at 1–3 days and 4–7 days after the onset of stroke. All patients were followed up for outcomes at 6 months after onset using the modified Rankin Scale (mRS, with a score of 5-6 considered unfavorable. The predictive values of SLSEP, BAEP, and the GCS at 1–3 days were compared with 4–7 days after onset. Our results show that, according to the analysis of prognostic authenticity, the predictive values of SLSEP and BAEP at 4–7 days after stroke onset improved when compared with the values at 1–3 days for unfavorable outcomes. Most of the patients with change of worsening evoked potentials from 1–3 days to 4–7 days after onset had unfavorable outcomes. In conclusion, SLSEP and BAEP assessed at 4–7 days after onset predicted unfavorable outcomes for acute severe stroke patients. The worsening values of SLSEP and BAEP between 1–3 days and 4–7 days also present a prognostic value.

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

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    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.)

  17. Functional Status Predicts Acute Care Readmissions from Inpatient Rehabilitation in the Stroke Population.

    Directory of Open Access Journals (Sweden)

    Chloe Slocum

    Full Text Available Acute care readmission risk is an increasingly recognized problem that has garnered significant attention, yet the reasons for acute care readmission in the inpatient rehabilitation population are complex and likely multifactorial. Information on both medical comorbidities and functional status is routinely collected for stroke patients participating in inpatient rehabilitation. We sought to determine whether functional status is a more robust predictor of acute care readmissions in the inpatient rehabilitation stroke population compared with medical comorbidities using a large, administrative data set.A retrospective analysis of data from the Uniform Data System for Medical Rehabilitation from the years 2002 to 2011 was performed examining stroke patients admitted to inpatient rehabilitation facilities. A Basic Model for predicting acute care readmission risk based on age and functional status was compared with models incorporating functional status and medical comorbidities (Basic-Plus or models including age and medical comorbidities alone (Age-Comorbidity. C-statistics were compared to evaluate model performance.There were a total of 803,124 patients: 88,187 (11% patients were transferred back to an acute hospital: 22,247 (2.8% within 3 days, 43,481 (5.4% within 7 days, and 85,431 (10.6% within 30 days. The C-statistics for the Basic Model were 0.701, 0.672, and 0.682 at days 3, 7, and 30 respectively. As compared to the Basic Model, the best-performing Basic-Plus model was the Basic+Elixhauser model with C-statistics differences of +0.011, +0.011, and + 0.012, and the best-performing Age-Comorbidity model was the Age+Elixhauser model with C-statistic differences of -0.124, -0.098, and -0.098 at days 3, 7, and 30 respectively.Readmission models for the inpatient rehabilitation stroke population based on functional status and age showed better predictive ability than models based on medical comorbidities.

  18. 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

  19. 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

  20. Model predicting survival/exitus after traumatic brain injury: biomarker S100B 24h.

    Science.gov (United States)

    Gonzćlez-Mao, M C; Repáraz-Andrade, A; Del Campo-Pérez, V; Alvarez-García, E; Vara-Perez, C; Andrade-Olivié, M A

    2011-01-01

    The enigma of Traumatic Brain Injury (TBI), reflected in recent scientific literature, is its uncertain consequences, variability of the final prognosis with apparently similar TBI, necessity for peripheral biomarkers, and more specific predictive models. To study the relationship between serum S100B and survival in TBI patients in various serious situations; the S100B level in patients without traumatic pathology or associated tumour, subjected to stressful situations such as neurological intensive care unit (NICU) stay; the possible overestimation caused by extracerebral liberation in TBI patients and associated polytraumatism; the predictive cutoffs to determine the most sensitive and specific chronology; and achieve a predictive prognostic model. Patients admitted to the NICU within 6 hours after TBI were selected. We measured: a) clinical: exitus yes/no; age and gender, traumatic mechanism, polytraumatism yes/no, GCS score, unconsciousness duration, amnesia duration, neurological focality, and surgical interventions; b) radiological: CT scan for radiological lesions; c) biochemical: serum SB100B at 6, 24, 48 and 72 hours after TBI and drug abuse detected in the urine; d) GOS on hospital discharge. N: 149 TBI patients, independent of polytraumatism, mean serum S100B at 6, 24, 48, and 72 hours: 2.1, 1.3, 1.2, and 0.6 microg/L, respectively; N: 124 without associated polytraumatism, S100B at 6, 24, 48, and 72 hours: 2.0, 1.4, 1.3, and 0.6 microg/L; N: 50 control I S100B 24 hours: 0.17 microg/L (0.04 - 0.56) and 25 healthy subjects S100B 0.057 microg/L (0.02-0.094). Significantly higher S100B levels are observed on exitus, with excellent TBI prognosis and evolution performance. Hospital stay in the NICU produces significant increases in S100B compared to healthy subjects, without invalidating it as a biomarker. Polytraumatism associated to TBI does not significantly alter S100B levels. S100B at 24 hours > or = 0.90 microg/L appears to predict unfavourable TBI

  1. 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.

  2. Radiomics signature: A potential biomarker for the prediction of MGMT promoter methylation in glioblastoma.

    Science.gov (United States)

    Xi, Yi-Bin; Guo, Fan; Xu, Zi-Liang; Li, Chen; Wei, Wei; Tian, Ping; Liu, Ting-Ting; Liu, Lin; Chen, Gang; Ye, Jing; Cheng, Guang; Cui, Long-Biao; Zhang, Hong-Juan; Qin, Wei; Yin, Hong

    2017-09-19

    In glioblastoma (GBM), promoter methylation of the DNA repair gene O-methylguanine-DNA methyltransferase (MGMT) is associated with beneficial chemotherapy. To analyze radiomics features for utilizing the full potential of medical imaging as biomarkers of MGMT promoter methylation. Retrospective. In all, 98 GBM patients with known MGMT (48 methylated and 50 unmethylated tumors). 3.0T magnetic resonance (MR) images, containing T 1 -weighted image (T 1 WI), T 2 -weighted image (T 2 WI), and enhanced T 1 WI. A region of interest (ROI) of the tumor was delineated. A total of 1665 radiomics features were extracted and quantized, and were reduced using least absolute shrinkage and selection operator (LASSO) regularization. After the support vector machine construction, accuracy, sensitivity, and specificity were computed for different sequences. An independent validation cohort containing 20 GBM patients was utilized to further evaluate the radiomics model performance. Radiomics features of T 1 WI reached an accuracy of 67.54%. Enhanced T 1 WI features reached an accuracy of 82.01%, while T 2 WI reached an accuracy of 69.25%. The best classification system for predicting MGMT promoter methylation status originated from the combination of 36 T 1 WI, T 2 WI, and enhanced T 1 WI images features, with an accuracy of 86.59%. Further validation on the independent cohort of 20 patients produced similar results, with an accuracy of 80%. Our results provide further evidence that radiomics MR features could predict MGMT methylation status in preoperative GBM. Multiple imaging modalities together can yield putative noninvasive biomarkers for the identification of MGMT. 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017. © 2017 International Society for Magnetic Resonance in Medicine.

  3. Biomarker expression in cervical intraepithelial neoplasia: potential progression predictive factors for low-grade lesions.

    Science.gov (United States)

    Ozaki, Satoru; Zen, Yoh; Inoue, Masaki

    2011-07-01

    The aim of this study was to reveal whether 3 biomarkers (p16INK4a, ProEx C, and human papilloma virus DNA) are useful in the diagnosis of cervical intraepithelial neoplasia and whether they could predict disease progression of cervical intraepithelial neoplasia-1. We analyzed 252 cervical specimens: nondysplastic mucosa (n = 9), cervical intraepithelial neoplasia (n = 229), and squamous cell carcinoma (n = 14). Immunostaining for p16INK4a and ProEx C, and the hybridcapture II assay for human papilloma virus DNA were performed. Expression of p16INK4a and staining for ProEx C were significantly higher in intraepithelial neoplasia 2/3 (96%-100%) than in nondysplastic mucosa (11%) or intraepithelial neoplasia 1 (40%-53%). Human papilloma virus DNA was detected in 69% of intraepithelial neoplasia-1, 95% of intraepithelial neoplasia-2, and 100% of intraepithelial neoplasia 3. Of 99 patients with intraepithelial neoplasia 1 for whom follow-up data was available, 62 (73%) showed spontaneous regression, 17 (20%) demonstrated persistent low-grade lesion, and 7 (7%) progressed to intraepithelial neoplasia 2/3. Expressions of p16INK4a and staining with ProEx C were significantly higher in the progression group than in the regression group. Testing for p16INK4a and ProEx C was sensitive (86%) and moderately specific (60% and 61%, respectively) in predicting the progression of cervical intraepithelial neoplasia 1. Human papilloma virus DNA testing was highly sensitive (100%) but less specific (37%). In conclusion, this study revealed that p16INK4a and ProEx C are useful biomarkers for the diagnosis of cervical intraepithelial neoplasia, and have potential as predictors of progression of low-grade lesions. Copyright © 2011 Elsevier Inc. All rights reserved.

  4. Serum biomarkers may help predict successful misoprostol management of early pregnancy failure.

    Science.gov (United States)

    Schreiber, Courtney A; Ratcliffe, Sarah J; Quinley, Kelly E; Miller, Carrie; Sammel, Mary D

    2015-06-01

    In order to simplify management of early pregnancy loss, our goal was to elucidate predictors of successful medical management of miscarriage with a single dose of misoprostol. In this secondary analysis of data from a multicenter randomized controlled trial, candidate biomarkers were compared between 49 women with missed abortion who succeeded in passing their pregnancy with a single dose of misoprostol and 46 women who did not pass their pregnancy with a misoprostol single dose. We computed the precision of trophoblastic protein and hormone concentrations to discriminate between women who succeed or fail single dose misoprostol management. We also included demographic factors in our analyses. We found overlap in the concentrations of the individual markers between women who succeeded and failed single-dose misoprostol. However, hCG levels ≥ 4000 mIU/mL and ADAM-12 levels ≥ 2500 pg/mL were independently associated with complete uterine expulsion after one dose of misoprostol in our population. A multivariable logistic model for success included non-Hispanic ethnicity and parity <2 in addition to hCG ≥ 4000 mIU/mL and ADAM-12 ≥ 2500 pg/mL and had an area under the receiver operating characteristic (ROC) of 0.81 (95% confidence interval: 72-90%). Categorizing women with a predicted probability of ≥ 0.65 resulted in a sensitivity of 75.0%, specificity 77.1% and positive predictive value of 81.8%. While preliminary, our data suggest that serum biomarkers, especially when combined with demographic characteristics, may be helpful in guiding patient decision-making regarding the management of early pregnancy failure (EPF). Further study is warranted. Copyright © 2015 Society for Biology of Reproduction & the Institute of Animal Reproduction and Food Research of Polish Academy of Sciences in Olsztyn. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

  5. The World Health Organization Disability Assessment Schedule 2.0 can predict the institutionalization of patients with stroke.

    Science.gov (United States)

    Hu, Hsiang-Yueh; Chi, Wen-Chou; Chang, Kwang-Hwa; Yen, Chia-Feng; Escorpizo, Reuben; Liao, Hua-Fang; Huang, Shih-Wei; Liou, Tsan-Hon

    2017-12-01

    The World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is a well-known questionnaire used to evaluate disability. We can not only evaluate disability but also obtain additional information by using the standardized WHODAS 2.0 scores. To predict the institutionalization of the patients with stroke by using the standardized WHODAS 2.0 scores. Observational study. The data of 10,255 patients with stroke were acquired from the Data Bank of Persons with Disabilities (TDPD) in Taiwan. Patients with either ischemic or hemorrhagic stroke during chronic stage. For the patients with stroke, we used a χ2 analysis for the categorical variables, and an independent Student's t test to compare the standardized WHODAS 2.0 scores in the six domains between different groups. We also generated a receiver operating characteristic curve using the standardized WHODAS 2.0 scores, and applied Youden Index to calculating the optimal cut-off point on the ROC curve. Then, we used a binary logistic regression analysis to determine risk factors for the institutionalization. All WHODAS 2.0 domains had higher scores in the institution group than in the community group. The ROC curve used to predict the institutionalization of patients with stroke revealed that all WHODAS 2.0 domains were statistically significant. The cognition, and mobility domains and the sum of WHODAS 2.0 scores were more accurate for predicting the risk of institutionalization in a long-term care facility. In a logistic regression analysis, standardized WHODAS 2.0 scores ≥69, residence in an urban area, and severity of impairment were factors for predicting the institutionalization of the patients with stroke. WHODAS 2.0 scores, urbanization level, and severity of impairment were positive factors for the institutionalization of patients with stroke in long-term care facilities, whereas the female sex and an age of ≥85 years were negative factors. The cognition and mobility domains and standardized

  6. 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.

  7. 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.

  8. Serum lipid profiles: novel biomarkers predicting advanced prostate cancer in patients receiving radical prostatectomy

    Directory of Open Access Journals (Sweden)

    Gui-Ming Zhang

    2015-04-01

    Full Text Available This study aimed to evaluate the role of serum lipid profiles as novel biomarkers in predicting pathological characteristics of prostate cancer (PCa. We retrospectively analyzed 322 consecutive patients with clinically localized PCa receiving radical prostatectomy (RP and extended pelvic lymphadenectomy. Unconditional logistic regression was used to estimate the prostatectomy Gleason score (pGS, pathological stage and lymph node involvement (LNI in RP specimens. Preoperative prostate-specific antigen (PSA levels, biopsy GS (bGS, and preoperative tumor, node, metastasis staging were used as basic variables to predict postoperative pathological characteristics. Preoperative serum lipid profiles were introduced as potential predictors. A receiver operating characteristic (ROC curve was used to determine predictive efficacy. Significant differences in pathological characteristics were observed among patients with normal and abnormal total cholesterol (TC, triglyceride (TG, and low-density lipoprotein (LDL levels, with the exception of pGS in the TG group. Multivariable regression analysis revealed that the odds ratio for high levels of TC for LNI compared with normal TC levels was 6.386 (95% confidence interval [CI] 1.510-27.010, 3.270 (95% CI: 1.470-7.278 for high levels of TG for pT3-4 disease, and 2.670 (95% CI: 1.134-6.287 for high levels of LDL for pGS. The area under the ROC curve of the models with dyslipidemia was larger than that in models without dyslipidemia, in predicting pathological characteristics. Abnormal TC, TG, and LDL levels are significantly associated with postoperative pathological status in PCa patients. Together with preoperative PSA levels, bGS, and clinical stage, dyslipidemia is more accurate in predicting pathological characteristics.

  9. 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.

  10. 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.

  11. 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

  12. Improving the prediction of overall survival for head and neck cancer patients using image biomarkers in combination with clinical parameters

    NARCIS (Netherlands)

    Zhai, Tian-Tian; van Dijk, Lisanne V; Huang, Bao-Tian; Lin, Zhi-Xiong; Ribeiro, Cássia O; Brouwer, Charlotte L; Oosting, Sjoukje F; Halmos, Gyorgy B; Witjes, Max J H; Langendijk, Johannes A; Steenbakkers, Roel J H M; Sijtsema, Nanna M

    Purpose: To develop and validate prediction models of overall survival (OS) for head and neck cancer (HNC) patients based on image biomarkers (IBMs) of the primary tumor and positive lymph nodes (Ln) in combination with clinical parameters. Material and methods: The study cohort was composed of 289

  13. 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.

  14. 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.

  15. Folate and MMA predict cognitive impairment in elderly stroke survivors: A cross sectional study.

    Science.gov (United States)

    Pascoe, Michaela C; Linden, Thomas

    2016-09-30

    Elderly stroke survivors are at risk of malnutrition and long-term cognitive impairment. Vitamin B-related metabolites, folate and methylmalonic acid, have been implicated in cognitive function. We conducted a study exploring the relationship between blood folate, methylmalonic acid and post-stroke cognitive impairment. This is a cross sectional study of elderly Swedish patients (n=149) 20 months post-stroke, assessed using the Mini Mental State Examination, serum blood levels of methylmalonic acid and red blood cell levels of folate. Linear modeling indicated that low levels of blood folate and elevated methylmalonic acid significantly contributed to cognitive impairment in stroke survivors. Half of the stroke survivors were shown to have folate deficiency at 20 months after stroke. Folate deficiency is common long term after stroke and both low folate and elevated methylmalonic acid appear to be associated with long term cognitive impairment, in elderly Swedish stroke survivors. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  16. 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.

  17. Inflammatory biomarkers and prediction for intensive care unit admission in severe community-acquired pneumonia.

    Science.gov (United States)

    Ramírez, Paula; Ferrer, Miquel; Martí, Verónica; Reyes, Soledad; Martínez, Raquel; Menéndez, Rosario; Ewig, Santiago; Torres, Antoni

    2011-10-01

    Increased inflammatory response is related to severity and outcome in community-acquired pneumonia, but the role of inflammatory biomarkers in deciding intensive care unit admission is unknown. We assessed the relationship between inflammatory response, prediction for intensive care unit admission, delayed intensive care unit admission, and outcome in patients with community-acquired pneumonia. Prospective clinical study. Intensive care units of two university hospitals. We included 627 ward and 58 intensive care unit patients with community-acquired pneumonia, 36 with direct and 22 with delayed intensive care unit admission. Serum levels of C-reactive protein, procalcitonin, tumor necrosis factor-α, interleukin-1, interleukin-6, interleukin-8, and interleukin-10 at admission. We assessed the prediction for intensive care unit admission of biomarkers and the Infectious Diseases Society of America/American Thoracic Society guidelines minor criteria for severe community-acquired pneumonia. Procalcitonin (p=.001), C-reactive protein (p=.005), tumor necrosis factor-α (p=.042), and interleukin-6 (p=.003) levels were higher in intensive care unit-admitted patients; however, the Infectious Diseases Society of America/American Thoracic Society guidelines minor severity criteria predicted better intensive care unit admission (odds ratio, 12.03; 95% confidence interval, 5.13-28.20; pintensive care unit admission compared with 14 (23%) with levels above the cutoff (p=.032). In patients initially admitted to wards, procalcitonin (p=.012) and C-reactive protein (p=.039) were higher in those 22 patients subsequently transferred to the intensive care unit after adjusting for age, comorbidities, and Pneumonia Severity Index risk class. Despite initially admitted to wards, 14 (64%) patients with delayed intensive care unit admission had already criteria for severe community-acquired pneumonia at admission compared with 73 (12%) ward patients (pintensive care unit admission

  18. Mass spectrometric analysis of gingival crevicular fluid biomarkers can predict periodontal disease progression.

    Science.gov (United States)

    Ngo, L H; Darby, I B; Veith, P D; Locke, A G; Reynolds, E C

    2013-06-01

    Gingival crevicular fluid has been suggested as a possible source of biomarkers for periodontal disease progression. This paper describes a technique for the analysis of gingival crevicular fluid from individual sites using mass spectrometry. It explores the novel use of mass spectrometry to examine the relationship between the relative amounts of proteins and peptides in gingival crevicular fluid and their relationship with clinical indices and periodontal attachment loss in periodontal maintenance patients. The aim of this paper was to assess whether the mass spectrometric analysis of gingival crevicular fluid may allow for the site-specific prediction of periodontal disease progression. Forty-one periodontal maintenance subjects were followed over 12 mo, with clinical measurements taken at baseline and every 3 mo thereafter. Gingival crevicular fluid was collected from subjects at each visit and was analysed using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. Samples were classified based upon pocket depth, modified gingival index (MGI), plaque index and attachment loss, and were analysed within these groups. A genetic algorithm was used to create a model based on pattern analysis to predict sites undergoing attachment loss. Three hundred and eighty-five gingival crevicular fluid samples were analysed. Twenty-five sites under observation in 14 patients exhibited attachment loss of > 2 mm over the 12-mo period. The clinical indices pocket depth, MGI, plaque levels and bleeding on probing served as poor discriminators of gingival crevicular fluid mass spectra. Models generated from the gingival crevicular fluid mass spectra could predict attachment loss at a site with a high specificity (97% recognition capability and 67% cross-validation). Gingival crevicular fluid mass spectra could be used to predict sites with attachment loss. The use of algorithm-generated models based on gingival crevicular fluid mass spectra may

  19. 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.

  20. Using biomarkers to predict treatment response in major depressive disorder: evidence from past and present studies.

    Science.gov (United States)

    Thase, Michael E

    2014-12-01

    Major depressive disorder (MDD) is a heterogeneous condition with a variable response to a wide range of treatments. Despite intensive efforts, no biomarker has been identified to date that can reliably predict response or non-response to any form of treatment, nor has one been identified that can be used to identify those at high risk of developing treatment-resistant depression (ie, non-response to a sequence of treatments delivered for adequate duration and intensity). This manuscript reviews some past areas of research that have proved informative, such as studies using indexes of hypercortisolism or sleep disturbance, and more recent research findings using measures of inflammation and different indicators of regional cortical activation to predict treatment response. It is concluded that, although no method has yet been demonstrated to be sufficiently accurate to be applied in clinical practice, progress has been made. It thus seems likely that--at some point in the not-too-distant future--it will be possible to prospectively identify, at least for some MDD patients, the likelihood of response or non-response to cognitive therapy or various antidepressant medications.

  1. Predicting outcome in patients with chronic stroke: findings of a 3-year follow-up study

    NARCIS (Netherlands)

    Port, I.G.L. van de

    2006-01-01

    This thesis is based on the findings of the FuPro-Stroke study (the Stroke section of the Functional Prognostification and disability study on neurological disorders), which is a multicentre, prospective cohort study among patients with stroke, who were included during inpatient rehabilitation. The

  2. 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.

  3. 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.

  4. 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

  5. Stroke volume variation does not predict fluid responsiveness in patients with septic shock on pressure support ventilation

    DEFF Research Database (Denmark)

    Perner, A; Faber, T

    2006-01-01

    Stroke volume variation (SVV)--as measured by the pulse contour cardiac output (PiCCO) system--predicts the cardiac output response to a fluid challenge in patients on controlled ventilation. Whether this applies to patients on pressure support ventilation is unknown....

  6. 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.

  7. 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...

  8. 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

  9. Biomarkers of microvascular endothelial dysfunction predict incident dementia: a population-based prospective study.

    Science.gov (United States)

    Holm, H; Nägga, K; Nilsson, E D; Ricci, F; Melander, O; Hansson, O; Bachus, E; Magnusson, M; Fedorowski, A

    2017-07-01

    Cerebral endothelial dysfunction occurs in a spectrum of neurodegenerative diseases. Whether biomarkers of microvascular endothelial dysfunction can predict dementia is largely unknown. We explored the longitudinal association of midregional pro-atrial natriuretic peptide (MR-proANP), C-terminal endothelin-1 (CT-proET-1) and midregional proadrenomedullin (MR-proADM) with dementia and subtypes amongst community-dwelling older adults. A population-based cohort of 5347 individuals (men, 70%; age, 69 ± 6 years) without prevalent dementia provided plasma for determination of MR-proANP, CT-proET-1 and MR-proADM. Three-hundred-and-seventy-three patients (7%) were diagnosed with dementia (120 Alzheimer's disease, 83 vascular, 102 mixed, and 68 other aetiology) over a period of 4.6 ± 1.3 years. Relations between baseline biomarker plasma concentrations and incident dementia were assessed using multivariable Cox regression analysis. Higher levels of MR-proANP were significantly associated with increased risk of all-cause and vascular dementia (hazard ratio [HR] per 1 SD: 1.20, 95% confidence interval [CI], 1.07-1.36; P = 0.002, and 1.52; 1.21-1.89; P dementia increased across the quartiles of MR-proANP (p for linear trend = 0.004; Q4, 145-1681 pmol L -1 vs. Q1, 22-77 pmol L -1 : HR: 1.83; 95%CI: 1.23-2.71) and was most pronounced for vascular type (p for linear trend = 0.005: HR: 2.71; 95%CI: 1.14-6.46). Moreover, the two highest quartiles of CT-proET-1 predicted vascular dementia with a cut-off value at 68 pmol L -1 (Q3-Q4, 68-432 pmol L -1 vs. Q1-Q2,4-68 pmol L -1 ; HR: 1.94; 95%CI: 1.12-3.36). Elevated levels of MR-proADM indicated no increased risk of developing dementia after adjustment for traditional risk factors. Elevated plasma concentration of MR-proANP is an independent predictor of all-cause and vascular dementia. Pronounced increase in CT-proET-1 indicates higher risk of vascular dementia. © 2017 The Association for the Publication of the

  10. Hypertension and diabetes mellitus as a predictive risk factors for stroke.

    Science.gov (United States)

    Alloubani, Aladeen; Saleh, Abdulmoneam; Abdelhafiz, Ibrahim

    2018-03-19

    Stroke is becoming a major challenge in healthcare systems, and this has necessitated the study of the various risk factors. As the number of people with hypertension, diabetes mellitus and obesity increases, the problem is expected to worsen. This review paper evaluates what can be done to eliminate or reduce the risk of stroke. The aim of the research is to evaluate the risk factors for stroke. The paper also aims to understand how these risks can be handled to avoid incidences of stroke. Published clinical trials of stroke risk factors studies were recognised by a search of EMBASE and MEDLINE databases with keywords hypertension, blood pressure, diabetes mellitus, stroke or cardiovascular disease, or prospective study, and meta-analysis. The findings of this review are that the prevention of stroke starts with identifying risk factors for stroke, most of the patients diagnosed with stroke have various risk factors. Consequently, it is a very significant to identify all the risk factors for stroke as well as to teach the patient how to dominate them. after summarising all the studies mentioned in the paper, it can be established that hypertension and diabetes mellitus are a stroke risk factors and correlated in patients with atherosclerosis. Copyright © 2018 Diabetes India. Published by Elsevier Ltd. All rights reserved.

  11. Predictive Biomarkers of Bacillus Calmette-Guérin Immunotherapy Response in Bladder Cancer: Where Are We Now?

    Directory of Open Access Journals (Sweden)

    Luís Lima

    2012-01-01

    Full Text Available The most effective therapeutic option for managing nonmuscle invasive bladder cancer (NMIBC, over the last 30 years, consists of intravesical instillations with the attenuated strain Bacillus Calmette-Guérin (the BCG vaccine. This has been performed as an adjuvant therapeutic to transurethral resection of bladder tumour (TURBT and mostly directed towards patients with high-grade tumours, T1 tumours, and in situ carcinomas. However, from 20% to 40% of the patients do not respond and frequently present tumour progression. Since BCG effectiveness is unpredictable, it is important to find consistent biomarkers that can aid either in the prediction of the outcome and/or side effects development. Accordingly, we conducted a systematic critical review to identify the most preeminent predictive molecular markers associated with BCG response. To the best of our knowledge, this is the first review exclusively focusing on predictive biomarkers for BCG treatment outcome. Using a specific query, 1324 abstracts were gathered, then inclusion/exclusion criteria were applied, and finally 87 manuscripts were included. Several molecules, including CD68 and genetic polymorphisms, have been identified as promising surrogate biomarkers. Combinatory analysis of the candidate predictive markers is a crucial step to create a predictive profile of treatment response.

  12. Evaluation of Biomarkers Predictive of Benefit From PD-1 Inhibitor MK-3475 in Patients with Non-Small Cell Lung Cancer and Brain Metastases

    Science.gov (United States)

    2016-07-01

    metastases • Biomarker 3. ACCOMPLISHMENTS: a. What were the major goals of the project? The major goals of the project are to identify biomarkers that...10% b. What was accomplished under these goals? The objective of this grant is to identify biomarkers predictive of benefit to immunotherapy in...Yale “A phase 2 study of MK-3475 in patients with metastatic melanoma and non-small cell lung cancer with untreated brain metastases.” Since the trial

  13. Predictive Value of Updating te Score Cardiovascular Risk Assessment Engine with Novel Biomarkers in a Type 2 Diabetes Population

    Directory of Open Access Journals (Sweden)

    Popa Loredana Mӑdӑlina

    2016-12-01

    Full Text Available Background and Aims: The aim of the study was to estimate the predictive value of some new biomarkers in the assessment of cardiovascular disease (CVD risk in a type 2 diabetes (T2DM population and to perform a correlation between the SCORE risk results and the risk profile estimated by the use of these biomarkers. Finally, we aimed to establish if the CVD risk assessment can be improved by adding the biomarkers into the SCORE risk equation. Material and Methods: In the study population the CVD risk assessment was performed using the SCORE High Risk Chart. The new individual biomarkers were: estimated glomerular filtration rate (eGFR, urinary albumin excretion (UAE rate, albumin/creatinine ratio (UACR, cystatin C, plasminogen activator inhibitor-1 (PAI-1, high-sensitivity C-reactive protein (hs-CRP, high density lipoprotein cholesterol (HDL and apolipoprotein B (apo-B. Results: The SCORE risk prediction model results were significantly altered by adding in the equation apo-B and HDLc values. An increase of one standard deviation of the apo-B values caused the increase of the SCORE results with 0.19 standard deviations while an increase of one standard deviation of the HDLc values decreased the SCORE results with 0.26 standard deviations. Conclusions: Advanced lipid testing, including the measurement of apo-B, provides a more comprehensive cardiac risk assessment and should be used in the development of specifically designed risk-scores for T2DM individuals.

  14. 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.

  15. Alberta Stroke Program Early CT Scale evaluation of multimodal computed tomography in predicting clinical outcomes of stroke patients treated with aspiration thrombectomy.

    Science.gov (United States)

    Psychogios, Marios-Nikos; Schramm, Peter; Frölich, Andreas Maximilian; Kallenberg, Kai; Wasser, Katrin; Reinhardt, Lars; Kreusch, Andreas S; Jung, Klaus; Knauth, Michael

    2013-08-01

    Patient selection is crucial in the endovascular treatment of acute ischemic stroke patients. Baseline computed tomographic (CT) images, evaluated with the Alberta Stroke Program Early CT Scale (ASPECTS), are considered significant predictors of outcome. In this study, we evaluated CT images and perfusion parameters, analyzed with ASPECTS, as final outcome predictors after endovascular stroke treatment. We analyzed a cohort of patients with acute ischemic stroke and endovascular treatment. Patients with an occlusion of the M1 segment and multimodal CT imaging were included. CT perfusion data were reconstructed using commercial software. Two experienced neuroradiologists separately reviewed and scored CT and CT perfusion images with the ASPECTS score. Parameters were compared between patients with poor and with favorable follow-up outcome. Significantly different variables were further analyzed by forward stepwise logistic regression. Fifty-one patients were included in our study. Baseline characteristics did not differ between patients with favorable and poor outcomes. No significant difference in recanalization status, the various times, or CT ASPECTS was demonstrated between these 2 groups. Significant differences were demonstrated for age (P=0.0049), cerebral blood volume ASPECTS (P=0.0007), and between cerebral blood volume and cerebral blood flow ASPECTS (P=0.0045). Cerebral blood volume ASPECTS>7 demonstrated the highest sensitivity and specificity for favorable outcome with 84% and 79%, respectively. CT perfusion parameters, evaluated with ASPECTS, are optimal predictors of outcome and are more sensitive and specific than CT ASPECTS in the prediction of favorable outcome. Use of these parameters in treatment decisions could reduce futile recanalizations.

  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. 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.

  18. Human Hippocampal Structure: A Novel Biomarker Predicting Mnemonic Vulnerability to, and Recovery from, Sleep Deprivation.

    Science.gov (United States)

    Saletin, Jared M; Goldstein-Piekarski, Andrea N; Greer, Stephanie M; Stark, Shauna; Stark, Craig E; Walker, Matthew P

    2016-02-24

    Sleep deprivation impairs the formation of new memories. However, marked interindividual variability exists in the degree to which sleep loss compromises learning, the mechanistic reasons for which are unclear. Furthermore, which physiological sleep processes restore learning ability following sleep deprivation are similarly unknown. Here, we demonstrate that the structural morphology of human hippocampal subfields represents one factor determining vulnerability (and conversely, resilience) to the impact of sleep deprivation on memory formation. Moreover, this same measure of brain morphology was further associated with the quality of nonrapid eye movement slow wave oscillations during recovery sleep, and by way of such activity, determined the success of memory restoration. Such findings provide a novel human biomarker of cognitive susceptibility to, and recovery from, sleep deprivation. Moreover, this metric may be of special predictive utility for professions in which memory function is paramount yet insufficient sleep is pervasive (e.g., aviation, military, and medicine). Copyright © 2016 the authors 0270-6474/16/362355-09$15.00/0.

  19. Urinary biomarkers for the prediction of reversibility in acute-on-chronic renal failure.

    Science.gov (United States)

    Luk, Cathy Choi-Wan; Chow, Kai-Ming; Kwok, Jeffrey Sung-Shing; Kwan, Bonnie Ching-Ha; Chan, Michael Ho-Ming; Lai, Ka-Bik; Lai, Fernand Mac-Moune; Wang, Gang; Li, Philip Kam-Tao; Szeto, Cheuk-Chun

    2013-01-01

    There is no reliable clinical test to predict the reversibility of acute-on-chronic renal failure. We study whether urinary biomarkers could be used as a noninvasive prognostic marker in patients with acute-on-chronic renal failure. We studied 39 adult patients with pre-existing chronic renal impairment presenting to us with acute-on-chronic renal failure. Urinary neutrophil gelatinase-associated lipocalin (NGAL) level was measured. The mRNA of kidney injury molecule-1 (KIM-1), interleukin-18 (IL-18), alpha-1-microglobulin (α1M), sodium/hydrogen exchanger-3 (NHE3), beta-2 microglobulin (β2M), and N-acetyl-β-D-glucosaminidase (NAG) in urinary sediment were quantified. Urinary NGAL level significantly correlated with the serum creatinine at presentation (r=0.762, pacute tubular necrosis than other causes of acute kidney injury (prenal function (r=0.387, p=0.026), as well as the estimated GFR 6 months later (r=0.386, p=0.027). In patients with acute-on-chronic renal failure, urinary NGAL level correlates with the severity of renal failure, while urinary α1M expression correlates with the degree of renal function recovery. Quantification of urinary α1M mRNA may be developed as an non-invasive tool for risk stratification of this group of patients.

  20. 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.

  1. Neuroimaging biomarkers to predict treatment response in schizophrenia: the end of 30 years of solitude?

    Science.gov (United States)

    Dazzan, Paola

    2014-12-01

    Studies that have used structural magnetic resonance imaging (MRI) suggest that individuals with psychoses have brain alterations, particularly in frontal and temporal cortices, and in the white matter tracts that connect them. Furthermore, these studies suggest that brain alterations may be particularly prominent, already at illness onset, in those individuals more likely to have poorer outcomes (eg, higher number of hospital admissions, and poorer symptom remission, level of functioning, and response to the first treatment with antipsychotic drugs). The fact that, even when present, these brain alterations are subtle and distributed in nature, has limited, until now, the utility of MRI in the clinical management of these disorders. More recently, MRI approaches, such as machine learning, have suggested that these neuroanatomical biomarkers can be used for direct clinical benefits. For example, using support vector machine, MRI data obtained at illness onset have been used to predict, with significant accuracy, whether a specific individual is likely to experience a remission of symptoms later on in the course of the illness. Taken together, this evidence suggests that validated, strong neuroanatomical markers could be used not only to inform tailored intervention strategies in a single individual, but also to allow patient stratification in clinical trials for new treatments.

  2. The role of cardiac disease parameters in predicting the results of Holter monitoring in patients with acute ischaemic stroke.

    Science.gov (United States)

    Atmuri, Kiran; Hughes, Andrew; Coles, David; Ahmad, Omar; Neeman, Teresa; Lueck, Christian

    2012-07-01

    There is limited evidence supporting the routine use of Holter monitoring (HM) in patients with acute ischaemic stroke. This study aimed to assess the diagnostic yield of HM and determine whether any cardiac disease parameter(s) would permit more focused targeting of HM. We performed a retrospective evaluation of HM in patients with acute ischaemic stroke admitted to our hospital over a one-year period to assess diagnostic yield and whether certain cardiac disease parameters were correlated with HM results. The diagnostic yield was 9%, the number needed to screen was 11, and the cost to detect one clinically significant case was AUS$1,300. Apart from age, stratifying patients by cardiac disease parameters did not predict HM result. This strengthens the use of HM in all patients presenting with acute ischaemic stroke of unknown aetiology. Copyright © 2011 Elsevier Ltd. All rights reserved.

  3. 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?

  4. 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.

  5. 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

  6. Diagnostic value of urinary CXCL10 as a biomarker for predicting Hunner type interstitial cystitis.

    Science.gov (United States)

    Niimi, Aya; Igawa, Yasuhiko; Aizawa, Naoki; Honma, Toshiki; Nomiya, Akira; Akiyama, Yoshiyuki; Kamei, Jun; Fujimura, Tetsuya; Fukuhara, Hiroshi; Homma, Yukio

    2017-10-19

    To investigate the feasibility of chemokines and cytokines potentially elevated in the bladder tissue of Hunner type interstitial cystitis (HIC) as urinary markers for distinguishing HIC from non-Hunner type interstitial cystitis (NHIC) METHODS: Urine specimens were collected from 41 HIC patients, 25 NHIC patients, and 31 healthy volunteers (control). The supernatants of urine specimens were subjected to ELISA kits for measurements of 10 cytokines and chemokines, whose gene expression was known to be elevated in HIC bladder tissue. Urinary levels normalized by urinary creatinine (Cr) concentration were compared among three groups. Efficiency in differentiating IC and IC subtypes was explored by ROC analysis. The correlation of marker levels with symptom severity, assessed by O'Leary-Sant's symptom index (OSSI) and problem index (OSPI), was examined. The urinary levels of CXCL10 and NGF were significantly higher in HIC than NHIC. CXCL10 and NGF differentiated HIC against NHIC with AUC of 0.78 and 0.68, respectively. Combination of CXCL10 and NGF levels yielded an AUS of 0.81. The CXCL10 cut-off of 53.2 pg/mg Cr had sensitivity of 46.1%, specificity of 93.7%, positive predictive value of 97.7%, and negative predictive value of 60.0%. The urinary level of other cytokines showed no significant difference between HIC and NHIC. Significant correlation with symptoms was detected for CXCL10 alone. The results suggested that increased urinary level of CXCL10 combined with or without high NGF level could be a promising supplementary biomarker for differentiating HIC from NHIC with modest sensitivity and high specificity. © 2017 Wiley Periodicals, Inc.

  7. Molecular biomarkers predictive of sertraline treatment response in young children with fragile X syndrome.

    Science.gov (United States)

    AlOlaby, Reem Rafik; Sweha, Stefan R; Silva, Marisol; Durbin-Johnson, Blythe; Yrigollen, Carolyn M; Pretto, Dalyir; Hagerman, Randi J; Tassone, Flora

    2017-06-01

    Several neurotransmitters involved in brain development are altered in fragile X syndrome (FXS), the most common monogenic cause of autism spectrum disorder (ASD). Serotonin plays a vital role in synaptogenesis and postnatal brain development. Deficits in serotonin synthesis and abnormal neurogenesis were shown in young children with autism, suggesting that treating within the first years of life with a selective serotonin reuptake inhibitor might be the most effective time. In this study we aimed to identify molecular biomarkers involved in the serotonergic pathway that could predict the response to sertraline treatment in young children with FXS. Genotypes were determined for several genes involved in serotonergic pathway in 51 children with FXS, ages 24-72months. Correlations between genotypes and deviations from baseline in primary and secondary outcome measures were modeled using linear regression models. A significant association was observed between a BDNF polymorphism and improvements for several clinical measures, including the Clinical Global Impression scale (P=0.008) and the cognitive T score (P=0.017) in those treated with sertraline compared to those in the placebo group. Additionally, polymorphisms in the MAOA, Cytochrome P450 2C19 and 2D6, and in the 5-HTTLPR gene showed a significant correlation with some of the secondary measures included in this study. This study shows that polymorphisms of genes involved in the serotonergic pathway could play a potential role in predicting response to sertraline treatment in young children with FXS. Larger studies are warranted to confirm these initial findings. Copyright © 2017 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

  8. 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.

  9. 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.

  10. 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

    Fruit and vegetable consumption produces changes in several biomarkers in blood. The present study aimed to examine the dose-response curve between fruit and vegetable consumption and carotenoid (α-carotene, β-carotene, β-cryptoxanthin, lycopene, lutein and zeaxanthin), folate and vitamin C...... 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...... intake (including and excluding fruit and vegetable juices). The study population in the present individual participant data meta-analysis consisted of 526 men and women. Carotenoid, folate and vitamin C concentrations showed a positive relationship with fruit and vegetable intake. Measures...

  11. The potential utility of urinary biomarkers for risk prediction in combat casualties: a prospective observational cohort study

    OpenAIRE

    Stewart, Ian J.; Glass, Kristen R.; Howard, Jeffrey T.; Morrow, Benjamin D.; Sosnov, Jonathan A.; Siew, Edward D.; Wickersham, Nancy; Latack, Wayne; Kwan, Hana K.; Heegard, Kelly D.; Diaz, Christina; Henderson, Aaron T.; Saenz, Kristin K.; Ikizler, T. Alp; Chung, Kevin K.

    2015-01-01

    Introduction Traditional risk scoring prediction models for trauma use either anatomically based estimations of injury or presenting vital signs. Markers of organ dysfunction may provide additional prognostic capability to these models. The objective of this study was to evaluate if urinary biomarkers are associated with poor outcomes, including death and the need for renal replacement therapy. Methods We conducted a prospective, observational study in United States Military personnel with tr...

  12. 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.

  13. Predicting asymptomatic coronary artery disease in patients with ischemic stroke and transient ischemic attack: the PRECORIS score.

    Science.gov (United States)

    Calvet, David; Song, Dongbeom; Yoo, Joonsang; Turc, Guillaume; Sablayrolles, Jean-Louis; Choi, Byoung Wook; Heo, Ji Hoe; Mas, Jean-Louis

    2014-01-01

    Identifying occult coronary artery stenosis may improve secondary prevention of stroke patients. The aim of this study was to derive and validate a simple score to predict severe occult coronary artery stenosis in stroke patients. We derived a score from a French hospital-based cohort of consecutive patients (n=300) who had an ischemic stroke or a transient ischemic attack and no previous history of coronary heart disease (Predicting Asymptomatic Coronary Artery Disease in Patients With Ischemic Stroke and Transient Ischemic Attack [PRECORIS] score) and validated the score in a similar Korean cohort (n=1602). In both cohorts, severe coronary artery stenosis was defined by the presence of at least 1≥50% coronary artery stenosis as detected by 64-section CT coronary angiography. A 5-point score (Framingham Risk Score-predicted 10-year coronary heart disease risk [≥20%=3; 10-19%=1; disease or 3-vessel disease were considered (C-statistic=0.83 [0.74-0.92] and 0.70 [0.66-0.74] in derivation and validation cohorts, respectively). The prevalence of occult≥50% coronary artery stenosis and ≥50% left main trunk or 3-vessel disease increased gradually with the PRECORIS score, reaching 44.2% and 13.5% in derivation cohort and 49.8% and 12.8% in validation cohort in patients with a PRECORIS score≥4. The PRECORIS score can identify a population of stroke or transient ischemic attack patients with a high prevalence of occult severe coronary artery stenosis.

  14. 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.

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

    Science.gov (United States)

    Pereira, Edimar Cristiano; Bertolami, Marcelo Chiara; Faludi, André Arpad; Monte, Osmar; Xavier, Hermes Toros; Pereira, Tiago Veiga

    2015-01-01

    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. PMID:26089875

  16. Novel biomarkers predict liver fibrosis in hepatitis C patients: alpha 2 macroglobulin, vitamin D binding protein and apolipoprotein AI

    Directory of Open Access Journals (Sweden)

    Lee Jing-Ying

    2010-07-01

    Full Text Available Abstract Background The gold standard of assessing liver fibrosis is liver biopsy, which is invasive and not without risk. Therefore, searching for noninvasive serologic biomarkers for liver fibrosis is an importantly clinical issue. Methods A total of 16 healthy volunteers and 45 patients with chronic hepatitis C virus (HCV were enrolled (F0: n = 16, F1: n = 7, F2: n = 17, F3: n = 8 and F4: n = 13, according to the METAVIR classification. Three serum samples of each fibrotic stage were analyzed by two-dimension difference gel electrophoresis (2D-DIGE. The differential proteins were identified by the cooperation of MALDI-TOF/TOF and MASCOT; then western blotting and Bio-Plex Suspension Array were used to quantify the protein levels. Results Three prominent candidate biomarkers were identified: alpha 2 macroglobulin (A2M is up regulated; vitamin D binding protein (VDBP and apolipoprotein AI (ApoAI are down regulated. The serum concentration of A2M was significantly different among normal, mild (F1/F2 and advanced fibrosis (F3/F4 (p p Conclusions This study not only reveals three putative biomarkers of liver fibrosis (A2M, VDBP and ApoAI but also proves the differential expressions of those markers in different stages of fibrosis. We expect that combination of these novel biomarkers could be applied clinically to predict the stage of liver fibrosis without the need of liver biopsy.

  17. Predictive biomarkers for the treatment of resectable esophageal and esophago-gastric junction adenocarcinoma: from hypothesis generation to clinical validation.

    Science.gov (United States)

    Piro, Geny; Carbone, Carmine; Santoro, Raffaela; Tortora, Giampaolo; Melisi, Davide

    2018-03-16

    Introduction Esophageal and esophago-gastric junction (EGJ) adenocarcinomas remain a major health problem worldwide with a worryingly increasing incidence. Recent trials indicate survivals benefit for preoperative or perioperative chemoradiotherapy compared to surgery alone. Beside standard chemoradiotherapy regimens, new therapeutic approaches with targeted therapies have been proposed for the treatment of resectable disease. However, clinical outcomes remain extremely poor due to drug resistance phenomena. The failure of these approaches could be partially ascribed to their incorrect application in patients. Therefore, the identification of strong biomarkers for optimal patient management is urgently needed. Areas covered This review aims to summarize and critically discuss the most relevant findings regarding predictive biomarker development for neoadjuvant treatment of resectable esophageal and esophago-gastric junction adenocarcinoma patients. Expert commentary Optimizing the currently available therapeutic modalities through a more accurate selection of patients may avoid the use of ineffective and potentially toxic treatments. During the last decade, the advent of high-throughput "-omics" technologies has set the basis for a new biomarker discovery approach from "molecule by molecule" screening towards a large-scale systematic screening process with exponential increases in putative biomarkers, which often failed to provide adequate clinical validation.

  18. Regional cortical thinning and cerebrospinal biomarkers predict worsening daily functioning across the Alzheimer disease spectrum

    Science.gov (United States)

    Marshall, Gad A.; Lorius, Natacha; Locascio, Joseph J.; Hyman, Bradley T.; Rentz, Dorene M.; Johnson, Keith A.; Sperling, Reisa A.

    2014-01-01

    Background Impairment in instrumental activities of daily living (IADL) heralds the transition from mild cognitive impairment (MCI) to dementia and is a major source of burden for both the patient and caregiver. Objective To investigate the relationship between IADL and regional cortical thinning and cerebrospinal fluid (CSF) Alzheimer disease (AD) biomarkers cross-sectionally and longitudinally in clinically normal (CN) elderly, MCI, and mild AD dementia subjects. Methods Two hundred and twenty nine CN, 395 MCI, and 188 AD dementia subjects participating in the Alzheimer's Disease Neuroimaging Initiative underwent baseline magnetic resonance imaging, baseline lumbar puncture, and clinical assessments, including the Functional Activities Questionnaire used to measure IADL, every 6 to 12 months up to 3 years. General linear regression and mixed effects models were employed. Results IADL impairment was associated with the interactions between lower inferior temporal cortical thickness and diagnosis (pdiagnosis (pdiagnosis (p=0.0002) at baseline (driven by AD dementia). Lower baseline supramarginal (p=0.02) and inferior temporal (p=0.05) cortical thickness, lower Aβ1-42 (p<0.0001), and greater total tau (t-tau) (p=0.02) were associated with greater rate of IADL impairment over time. Conclusions Temporal atrophy is associated with IADL impairment in mild AD dementia at baseline, while baseline parietal and temporal atrophy, lower CSF Aβ1-42, and greater t-tau predict worsening IADL impairment over time across the AD spectrum. These results emphasize the importance of assessing IADL at the stage of MCI and even at the transition from CN to MCI. PMID:24685624

  19. Sialylated Fetuin-A as a candidate predictive biomarker for successful grass pollen allergen immunotherapy.

    Science.gov (United States)

    Caillot, Noémie; Bouley, Julien; Jain, Karine; Mariano, Sandrine; Luce, Sonia; Horiot, Stéphane; Airouche, Sabi; Beuraud, Chloé; Beauvallet, Christian; Devillier, Philippe; Chollet-Martin, Sylvie; Kellenberger, Christine; Mascarell, Laurent; Chabre, Henri; Batard, Thierry; Nony, Emmanuel; Lombardi, Vincent; Baron-Bodo, Véronique; Moingeon, Philippe

    2017-09-01

    Eligibility to immunotherapy is based on the determination of IgE reactivity to a specific allergen by means of skin prick or in vitro testing. Biomarkers predicting the likelihood of clinical improvement during immunotherapy would significantly improve patient selection. Proteins were differentially assessed by using 2-dimensional differential gel electrophoresis and label-free mass spectrometry in pretreatment sera obtained from clinical responders and nonresponders within a cohort of 82 patients with grass pollen allergy receiving sublingual immunotherapy or placebo. Functional studies of Fetuin-A (FetA) were conducted by using gene silencing in a mouse asthma model, human dendritic cell in vitro stimulation assays, and surface plasmon resonance. Analysis by using quantitative proteomics of pretreatment sera from patients with grass pollen allergy reveals that high levels of O-glycosylated sialylated FetA isoforms are found in patients exhibiting a strong decrease in rhinoconjunctivitis symptoms after sublingual immunotherapy. Although FetA is involved in numerous inflammatory conditions, its potential role in allergy is unknown. In vivo silencing of the FETUA gene in BALB/c mice results in a dramatic upregulation of airway hyperresponsiveness, lung resistance, and T H 2 responses after allergic sensitization to ovalbumin. Both sialylated and nonsialytated FetA bind to LPS, but only the former synergizes with LPS and grass pollen or mite allergens to enhance the Toll-like receptor 4-mediated proallergic properties of human dendritic cells. As a reflection of the patient's inflammatory status, pretreatment levels of sialylated FetA in the blood are indicative of the likelihood of clinical responses during grass pollen immunotherapy. Copyright © 2016 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

  20. 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.

  1. 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

  2. Statistical design for a confirmatory trial with a continuous predictive biomarker: A case study.

    Science.gov (United States)

    Joshi, Adarsh; Zhang, Jenny; Fang, Liang

    2017-12-01

    With targeted therapies, it is often hypothesized that their effect may be specific to the subpopulation in which the target pathway is activated. We consider the problem of designing a confirmatory trial when the biological hypothesis of the experimental therapy is strongly supported by the pre-clinical data but limited clinical data is available to pre-define a subpopulation based on a biomarker with continuous values. The study design is further complicated if interim evaluations of the biomarker-based subpopulations are also being considered. We compared several strategies, including a naïve threshold nomination approach, a modification of the "explore and confirm" strategy proposed by Friedlin et al. (2005), and a novel biomarker sequential testing approach, motivated by the "general bivariate normal method" discussed by Wang el al. (2007), and further discussions in Spiessens and Debois (2010) and Holmgren (2017), in a setting where all-comers and biomarker subpopulation evaluations can be performed at interim analyses as well as the end of study. Based on extensive simulations, we concluded that the novel biomarker sequential testing approach out-performed other strategies when there was limited prior information for biomarker threshold determination. This design was implemented in a recently completed clinical trial of simtuzumab (RAINIER study) and provides a useful case study for designing future confirmatory clinical trials of novel targeted therapies. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Autonomic Nervous System and Stress to Predict Secondary Ischemic Events after Transient Ischemic Attack or Minor Stroke: Possible Implications of Heart Rate Variability.

    Science.gov (United States)

    Guan, Ling; Collet, Jean-Paul; Mazowita, Garey; Claydon, Victoria E

    2018-01-01

    Transient ischemic attack (TIA) and minor stroke have high risks of recurrence and deterioration into severe ischemic strokes. Risk stratification of TIA and minor stroke is essential for early effective treatment. Traditional tools have only moderate predictive value, likely due to their inclusion of the limited number of stroke risk factors. Our review follows Hans Selye's fundamental work on stress theory and the progressive shift of the autonomic nervous system (ANS) from adaptation to disease when stress becomes chronic. We will first show that traditional risk factors and acute triggers of ischemic stroke are chronic and acute stress factors or "stressors," respectively. Our first review shows solid evidence of the relationship between chronic stress and stroke occurrence. The stress response is tightly regulated by the ANS whose function can be assessed with heart rate variability (HRV). Our second review demonstrates that stress-related risk factors of ischemic stroke are correlated with ANS dysfunction and impaired HRV. Our conclusions support the idea that HRV parameters may represent the combined effects of all body stressors that are risk factors for ischemic stroke and, thus, may be of important predictive value for the risk of subsequent ischemic events after TIA or minor stroke.

  4. Autonomic Nervous System and Stress to Predict Secondary Ischemic Events after Transient Ischemic Attack or Minor Stroke: Possible Implications of Heart Rate Variability

    Science.gov (United States)

    Guan, Ling; Collet, Jean-Paul; Mazowita, Garey; Claydon, Victoria E.

    2018-01-01

    Transient ischemic attack (TIA) and minor stroke have high risks of recurrence and deterioration into severe ischemic strokes. Risk stratification of TIA and minor stroke is essential for early effective treatment. Traditional tools have only moderate predictive value, likely due to their inclusion of the limited number of stroke risk factors. Our review follows Hans Selye’s fundamental work on stress theory and the progressive shift of the autonomic nervous system (ANS) from adaptation to disease when stress becomes chronic. We will first show that traditional risk factors and acute triggers of ischemic stroke are chronic and acute stress factors or “stressors,” respectively. Our first review shows solid evidence of the relationship between chronic stress and stroke occurrence. The stress response is tightly regulated by the ANS whose function can be assessed with heart rate variability (HRV). Our second review demonstrates that stress-related risk factors of ischemic stroke are correlated with ANS dysfunction and impaired HRV. Our conclusions support the idea that HRV parameters may represent the combined effects of all body stressors that are risk factors for ischemic stroke and, thus, may be of important predictive value for the risk of subsequent ischemic events after TIA or minor stroke. PMID:29556209

  5. 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.)

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

    Directory of Open Access Journals (Sweden)

    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.

  7. [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.

  8. Do Performance Measures of Strength, Balance, and Mobility Predict Quality of Life and Community Reintegration After Stroke?

    Science.gov (United States)

    Cohen, Joshua W; Ivanova, Tanya D; Brouwer, Brenda; Miller, Kimberly J; Bryant, Dianne; Garland, S Jayne

    2018-04-01

    To investigate the extent to which physical performance measures of strength, balance, and mobility taken at discharge from inpatient stroke rehabilitation can predict health-related quality of life (HRQoL) and community reintegration after 6 months. Longitudinal study. University laboratory. Adults (N=75) recruited within 1 month of discharge home from inpatient stroke rehabilitation. Not applicable. 36-Item Short Form Health Survey (SF-36) for HRQoL and Subjective Index of Physical and Social Outcome (SIPSO) for community reintegration. Physical performance measures were the 6-minute walk test, timed Up and Go (TUG) test, Berg Balance Scale, Community Balance and Mobility Scale, and isokinetic torque and power of hip, knee, and ankle on the paretic and nonparetic sides. Other prognostic variables included age, sex, stroke type and location, comorbidities, and motor FIM score. Separate stepwise linear regressions were performed using the SF-36 and SIPSO as dependent variables. The total paretic lower limb torque and 6-minute walk test predicted the SF-36 Physical Component Summary (adjusted R 2 =.30). The total paretic lower limb torque and TUG test predicted the SIPSO physical component (adjusted R 2 =.47). The total paretic lower limb torque significantly predicted the SF-36 Mental Component Summary, but the adjusted R 2 was low (.06). Similarly, the TUG test significantly predicted the SIPSO social component, but again the adjusted R 2 was low (.09). Measures of physical performance including muscle strength and mobility at discharge can partially predict HRQoL and community reintegration 6 months later. Further research is necessary for more accurate predictions. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  9. 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.

  10. 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.

  11. Determination of predictive - prognostic biomarkers of imbalance between energy and plastic potentials in blood cells of patients with oncopathology

    International Nuclear Information System (INIS)

    Krasnosel's'kij, M.V.; Krut'ko, Je.M.; Movchan, O.V.; Gramatyuk, S.M.

    2017-01-01

    Determination of predictive -prognostic biomarkers of imbalance between energy and plastic potentials in blood cells of patients with oncopathology. An important and dynamically regulated metabolic pathway is glycolysis, an ancient chemical route of carbohydrate utilization that produces ATP, NADH and intermediate metabolites for the synthesis of nucleotides, fatty acids and amino acids. The inhibition of triosephosphate isomerase in glycolysis by the pyruvate kinase substrate phosphoenolpyruvate results in a newly discovered feedback loop that counters oxidative stress in cancer and actively respiring cells. Reduced activity of glycerol-3-phosphate dehydrogenase (p . 0.005), glyceraldehyde-3-phosphate dehydrogenase activity, which characterizes the intensity of glycolytic cleavage of glucose, was, on the contrary, increased (p . 0.01). In other words, we can assume the possible presence of imbalance between energy and plastic potentials in red blood cells of cancer patients and to use these indicators as biomarkers of the disease.

  12. 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

  13. Circulating plasma MiR-141 is a novel biomarker for metastatic colon cancer and predicts poor prognosis.

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    Hanyin Cheng

    Full Text Available BACKGROUND: Colorectal cancer (CRC remains one of the major cancer types and cancer related death worldwide. Sensitive, non-invasive biomarkers that can facilitate disease detection, staging and prediction of therapeutic outcome are highly desirable to improve survival rate and help to determine optimized treatment for CRC. The small non-coding RNAs, microRNAs (miRNAs, have recently been identified as critical regulators for various diseases including cancer and may represent a novel class of cancer biomarkers. The purpose of this study was to identify and validate circulating microRNAs in human plasma for use as such biomarkers in colon cancer. METHODOLOGY/PRINCIPAL FINDINGS: By using quantitative reverse transcription-polymerase chain reaction, we found that circulating miR-141 was significantly associated with stage IV colon cancer in a cohort of 102 plasma samples. Receiver operating characteristic (ROC analysis was used to evaluate the sensitivity and specificity of candidate plasma microRNA markers. We observed that combination of miR-141 and carcinoembryonic antigen (CEA, a widely used marker for CRC, further improved the accuracy of detection. These findings were validated in an independent cohort of 156 plasma samples collected at Tianjin, China. Furthermore, our analysis showed that high levels of plasma miR-141 predicted poor survival in both cohorts and that miR-141 was an independent prognostic factor for advanced colon cancer. CONCLUSIONS/SIGNIFICANCE: We propose that plasma miR-141 may represent a novel biomarker that complements CEA in detecting colon cancer with distant metastasis and that high levels of miR-141 in plasma were associated with poor prognosis.

  14. Collateral blood vessels in acute ischemic stroke: a physiological window to predict future outcomes

    Directory of Open Access Journals (Sweden)

    Heitor Castelo Branco Rodrigues Alves

    2016-01-01

    Full Text Available ABSTRACT Collateral circulation is a physiologic pathway that protects the brain against ischemic injury and can potentially bypass the effect of a blocked artery, thereby influencing ischemic lesion size and growth. Several recent stroke trials have provided information about the role of collaterals in stroke pathophysiology, and collateral perfusion has been recognized to influence arterial recanalization, reperfusion, hemorrhagic transformation, and neurological outcomes after stroke. Our current aim is to summarize the anatomy and physiology of the collateral circulation and to present and discuss a comprehensible review of the related knowledge, particularly the effects of collateral circulation on the time course of ischemic injury and stroke severity, as well as imaging findings and therapeutic implications.

  15. 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

    Cooperative Acute Stroke Study II criteria. Recanalization and reperfusion were assessed on 3-hour follow-up MRI. RESULTS: Of the 110 patients, hemorrhagic transformation occurred in 59 patients, including 7 PH. In univariate analysis, the acute National Institutes of Health Stroke Scale score (P=0...... hemorrhagic transformation or PH. CONCLUSION: Very low CBV was the only independent predictor of PH in patients with acute stroke.......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...

  16. Soluble urokinase-type plasminogen activator receptor is a novel biomarker predicting acute exacerbation in COPD

    Directory of Open Access Journals (Sweden)

    Gumus A

    2015-02-01

    Full Text Available Aziz Gumus,1 Nejat Altintas,2 Halit Cinarka,1 Aynur Kirbas,3 Muge Haziroglu,1 Mevlut Karatas,1 Unal Sahin1 1Department of Pulmonary Medicine, School of Medicine, Recep Tayyip Erdogan University, Rize, Turkey; 2Department of Pulmonary Medicine, School of Medicine, Namik Kemal University, Tekirdag, Turkey; 3Department of Clinical Biochemistry, School of Medicine, Recep Tayyip Erdogan University, Rize, Turkey Background: Chronic obstructive pulmonary disease (COPD is a chronic inflammatory condition, and progresses with acute exacerbations. (AE. During AE, levels of acute phase reactants such as C-reactive protein (CRP and inflammatory cells in the circulation increase. Soluble urokinase-type plasminogen activator receptor (suPAR levels increase in acute viral and bacterial infections and in diseases involving chronic inflammation. The purpose of this study was to investigate the effectiveness of suPAR in predicting diagnosis of AE of COPD (AE-COPD and response to treatment. Methods: The study population consisted of 43 patients diagnosed with AE-COPD and 30 healthy controls. suPAR, CRP, and fibrinogen levels were measured on the first day of hospitalization and on the seventh day of treatment. Results: We found that fibrinogen (P<0.001, CRP (P<0.001, and suPAR (P<0.001 were significantly higher in patients with AE-COPD than in healthy controls. Fibrinogen (P<0.001, CRP (P=0.001, and suPAR (P<0.001 were significantly decreased by the seventh day of treatment. However, the area under receiver operator characteristic curve showed that suPAR is superior to CRP and fibrinogen in distinguishing AE-COPD. There was a correlation between fibrinogen, CRP, and suPAR. However, only fibrinogen was a powerful predictor of suPAR in multiple linear regression. In multiple logistic regression, only suPAR and fibrinogen were strong predictors of AE-COPD (P=0.002 and P=0.014, respectively. Serum suPAR was negatively correlated with forced expiratory volume in 1

  17. Vascular biomarkers to predict response to exercise in Alzheimer's disease: the study protocol

    Science.gov (United States)

    Li, Danni; Thomas, Robin; Tsai, Michael Y; Li, Ling; Vock, David M; Greimel, Susan; Yu, Fang

    2016-01-01

    Introduction Exercise interventions are a promising treatment for improving cognition in persons with Alzheimer's disease. This is similar to Alzheimer's disease pharmacotherapies in which only 18–48% of treated patients demonstrate improvement in cognition. Aerobic exercise interventions positively affect brain structure and function through biologically sound pathways. However, an under-studied mechanism of aerobic exercise's effects is n-3 fatty acids in plasma. The objective of this pilot study is to inform a future large-scale study to develop n-3 fatty acids-based prediction of cognitive responses to aerobic exercise treatment in Alzheimer's disease. Methods and analysis This study will recruit and follow a cohort of 25 subjects enrolled in the FIT-AD Trial, an ongoing randomised controlled trial that investigates the effects of a 6-month moderate-intensity cycling intervention on cognition and hippocampal volume in older adults with mild to moderate Alzheimer's disease over a year. This study will collect blood from subjects at baseline and at 3 and 6 months to assay vascular biomarkers (ie, plasma fatty acids). Global cognition as measured by the Alzheimer's Disease Assessment Scale-Cognition (ADAS-Cog) at baseline, 3, 6, 9 and 12 months will be used as the main outcome. A multiple linear-regression model will be used with 12-month change in cognition as the outcome and baseline measure of n-3 fatty acids or changes in the ratio of n-3 to n-6 fatty-acid levels in plasma at 3 and/or 6 months, randomised treatment group, and their interaction as predictors. Ethics and dissemination We have obtained Institutional Review Board approval for our study. We obtain consent or assent/surrogate consent from all subjects depending on their consenting capacity assessment. Data of this study are/will be stored in the Research Electronic Data Capture (REDCap). We plan to present and publish our study findings through presentations and manuscripts. Trial

  18. Vascular biomarkers to predict response to exercise in Alzheimer's disease: the study protocol.

    Science.gov (United States)

    Li, Danni; Thomas, Robin; Tsai, Michael Y; Li, Ling; Vock, David M; Greimel, Susan; Yu, Fang

    2016-12-30

    Exercise interventions are a promising treatment for improving cognition in persons with Alzheimer's disease. This is similar to Alzheimer's disease pharmacotherapies in which only 18-48% of treated patients demonstrate improvement in cognition. Aerobic exercise interventions positively affect brain structure and function through biologically sound pathways. However, an under-studied mechanism of aerobic exercise's effects is n-3 fatty acids in plasma. The objective of this pilot study is to inform a future large-scale study to develop n-3 fatty acids-based prediction of cognitive responses to aerobic exercise treatment in Alzheimer's disease. This study will recruit and follow a cohort of 25 subjects enrolled in the FIT-AD Trial, an ongoing randomised controlled trial that investigates the effects of a 6-month moderate-intensity cycling intervention on cognition and hippocampal volume in older adults with mild to moderate Alzheimer's disease over a year. This study will collect blood from subjects at baseline and at 3 and 6 months to assay vascular biomarkers (ie, plasma fatty acids). Global cognition as measured by the Alzheimer's Disease Assessment Scale-Cognition (ADAS-Cog) at baseline, 3, 6, 9 and 12 months will be used as the main outcome. A multiple linear-regression model will be used with 12-month change in cognition as the outcome and baseline measure of n-3 fatty acids or changes in the ratio of n-3 to n-6 fatty-acid levels in plasma at 3 and/or 6 months, randomised treatment group, and their interaction as predictors. We have obtained Institutional Review Board approval for our study. We obtain consent or assent/surrogate consent from all subjects depending on their consenting capacity assessment. Data of this study are/will be stored in the Research Electronic Data Capture (REDCap). We plan to present and publish our study findings through presentations and manuscripts. NCT01954550. Published by the BMJ Publishing Group Limited. For permission to

  19. Discriminative and predictive validity of the short-form activities-specific balance confidence scale for predicting fall of stroke survivors.

    Science.gov (United States)

    An, SeungHeon; Lee, Yunbok; Lee, DongGeon; Cho, Ki-Hun; Lee, GyuChang; Park, Dong-Sik

    2017-04-01

    [Purpose] The present study aimed to investigate the discriminative validity of the short-form activities-specific balance confidence scale (ABC scale) in predicting falls, and its validity. [Subjects and Methods] 43 stroke survivors were identified as a group with a history of multiple falls (faller group) and a group without or with a history of one falls (non-faller group). The balance confidence was examined using the ABC scale and the short-form ABC scale. Functional abilities were examined with Fugl-Meyer assessment, sit-to-stand test, and Berg balance scale. [Results] The area under the curve of the ABC scale and the short-form ABC scale in predicting fall was>0.77. This result indicates that both examination tools have discriminative validity in predicting falls. Although both tools showed an identical predictable specificity of 72% in the non-faller and faller groups, the short-form ABC scale exhibited a predictable sensitivity of 86% in the faller group, which is higher than that of the ABC scale (71%). [Conclusion] Results of this study showed that the short-form ABC scale is an efficient clinical tool to evaluate and predict the balance confidence of stroke survivors.

  20. 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.

  1. Predicting Progression of Intracranial Arteriopathies in Childhood Stroke With Vessel Wall Imaging.

    Science.gov (United States)

    Stence, Nicholas V; Pabst, Lisa L; Hollatz, Amanda L; Mirsky, David M; Herson, Paco S; Poisson, Sharon; Traystman, Richard J; Bernard, Timothy J

    2017-08-01

    Childhood arterial ischemic stroke is frequently associated with an intracranial arteriopathy that often progresses in the first 3 to 6 months post stroke. We hypothesized that children with enhancing arteriopathies on vessel wall imaging (VWI) would have a higher risk of arteriopathy progression than those without enhancement. Our institutional radiographic database was searched for cases of childhood stroke with VWI. Inclusion criteria consisted of age ranging from 1 month through 20 years, diagnosis of arterial ischemic stroke, available VWI, and follow-up magnetic resonance angiogram. Imaging was reviewed to systematically describe VWI findings, categorize arteriopathies, steroid therapy, and identify progressive arteriopathies using CACADE definitions. Sixteen cases of childhood stroke at Children's Hospital Colorado between January 1, 2010 and July 1, 2016 were reviewed. Strong vessel wall enhancement at presentation was associated with progressive arteriopathy in 83% of cases (10/12), when compared with 0% (0/4) without strong enhancement ( P =0.008). Our case series demonstrates the potential benefit of VWI in children with stroke because it may identify patients who will have progressive arterial disease. © 2017 American Heart Association, Inc.

  2. Irregularity and lack of p-waves in short tachycardia episodes predict atrial fibrillation and ischemic stroke.

    Science.gov (United States)

    Johnson, Linda S B; Persson, Anders P; Wollmer, Per; Juul-Möller, Steen; Juhlin, Tord; Engström, Gunnar

    2018-02-12

    Atrial fibrillation (AF) is defined as an irregular supraventricular tachycardia (SVT) without p-waves, with a duration >30s. It is not known whether AF characteristics in shorter SVT episodes predict AF and stroke. To determine if irregularity and lack of p-waves, alone or in combination, at short SVT episodes increased the risk of incident AF and ischemic stroke. The population-based Malmö Diet and Cancer study includes 24hECG screening of 377 AF-free individuals (mean age 64.5 years, 43% men) who were prospectively followed for >13 years. There were 65 AF events and 25 ischemic stroke events during follow-up. Subjects with an SVT episode ≥5 beats were identified and the longest SVT episode was assessed for irregularity and lack of p-waves. The association between SVT classification and AF and stroke was assessed using multivariable adjusted Cox regression. Incidence of AF increased with increasing abnormality of the SVTs. The risk-factor adjusted hazards ratio (HR) for AF was 4.95 (95%CI 2.06-11.9, pSVT episodes without p-waves (HR 14.2 (95%CI 3.76-57.6, pSVT episodes at detected at 24hECG screening are associated with incident AF and ischemic stroke. Short irregular SVTs without p-waves likely represent early stages of AF or atrial myopathy. 24hECG could identify subjects suitable for primary prevention efforts. Copyright © 2018. Published by Elsevier Inc.

  3. Low thrombin generation predicts poor prognosis in ischemic stroke patients after thrombolysis.

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    Renáta Hudák

    Full Text Available Thrombolysis by intravenous recombinant tissue plasminogen activator (rt-PA is an effective therapy in acute ischemic stroke (AIS. Thrombin generation test (TGT is a global hemostasis test providing information about the speed and amount of generated thrombin in plasma. Here we aimed to find out whether results of this test before the initiation of thrombolysis might predict outcomes. Study population included 120 consecutive AIS patients, all within 4.5 hours of their symptom onset, who underwent thrombolysis by rt-PA. Blood samples were collected from all patients upon admission and TGT was performed using platelet poor plasma. Clinical data of patients including the NIHSS were registered at admission, day 1 and 7 after therapy. The ASPECT score was assessed using CT images taken before and 24 hours after thrombolysis. Long-term functional outcome was defined 3 months after the event by the modified Rankin Scale. Endogenous Thrombin Potential (ETP and Peak Thrombin were significantly lower in patients with cardioembolic IS. Symptomatic intracranial hemorrhage (SICH was found in 6 patients and was significantly associated with low ETP and Peak Thrombin levels. A multiple logistic regression model revealed that an ETP result in the lower quartile is an independent predictor of mortality within the first two weeks (OR: 6.03; 95%CI: 1.2-30.16, p<0.05 and three months after the event (OR: 5.28; 95%CI: 1.27-21.86, p<0.05. Low levels of ETP and Peak Thrombin parameters increase the risk of therapy associated SICH. A low ETP result is an independent predictor of short- and long-term mortality following thrombolysis.

  4. Using biomarkers to predict progression from clinically isolated syndrome to multiple sclerosis

    NARCIS (Netherlands)

    Tossberg, J.T.; Crooke, P.S.; Henderson, M.A.; Sriram, S.; Mrelashvili, D.; Vosslamber, S.; Verweij, C.L.; Olsen, N.J.; Aune, T.M.

    2013-01-01

    Background: Detection of brain lesions disseminated in space and time by magnetic resonance imaging remains a cornerstone for the diagnosis of clinically definite multiple sclerosis. We have sought to determine if gene expression biomarkers could contribute to the clinical diagnosis of multiple

  5. Functional connectivity classification of autism identifies highly predictive brain features but falls short of biomarker standards

    Directory of Open Access Journals (Sweden)

    Mark Plitt

    2015-01-01

    Conclusions: While individuals can be classified as having ASD with statistically significant accuracy from their rs-fMRI scans alone, this method falls short of biomarker standards. Classification methods provided further evidence that ASD functional connectivity is characterized by dysfunction of large-scale functional networks, particularly those involved in social information processing.

  6. Biomarkers for early diagnosis, prognosis, prediction, and recurrence monitoring of non-small cell lung cancer

    Directory of Open Access Journals (Sweden)

    Tang Y

    2017-09-01

    Full Text Available Yong Tang,1,2,* Guibin Qiao,1,2,* Enwu Xu,2 Yiwen Xuan,2 Ming Liao,2 Guilin Yin1 1Southern Medical University, Guangzhou, Guangdong Province, China, 2Department of Thoracic Surgery, General Hospital of Guangzhou Military Command of PLA, Yuexiu District, Guangzhou City, Guangdong Province, China *These authors contributed equally to this work Abstract: Despite advances in the management of non-small cell lung cancer, it remains to be the leading cause of cancer-related deaths worldwide primarily because of diagnosis at a late stage with an overall 5-year survival rate of 17%. A reduction in mortality was achieved by low-dose computed tomography screening of high-risk patients. However, the benefit was later challenged by the high false positive rate, resulting in unnecessary follow-ups, thus entailing a burden on both the health care system and the individual. The diagnostic dilemma imposed by imaging modalities has created a need for the development of biomarkers capable of differentiating benign nodules from malignant ones. In the past decade, with the advancements in high-throughput profiling technologies, a huge amount of work has been done to derive biomarkers to supplement clinical diagnosis. However, only a few of them have efficient sensitivity and specificity to be utilized in clinical settings. Therefore, there is an urgent need for the development of sensitive and specific means to detect and diagnose lung cancers at an early stage, when curative interventions are still possible. Due to the invasiveness of tissue biopsies and inability to capture tumor heterogeneity, nowadays enormous efforts have been invested in the development of technologies and biomarkers that enable sensitive and cost-effective testing using substrates that can be obtained in a noninvasive manner. This review, primarily focusing on liquid biopsy, summarizes all documented potential biomarkers for diagnosis, monitoring recurrence treatment response. Keywords

  7. 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.

  8. 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.

  9. Combination of 24-Hour and 7-Day Relative Neurological Improvement Strongly Predicts 90-Day Functional Outcome of Endovascular Stroke Therapy.

    Science.gov (United States)

    Pu, Jie; Wang, Huaiming; Tu, Mingyi; Zi, Wenjie; Hao, Yonggang; Yang, Dong; Liu, Wenhua; Wan, Yue; Geng, Yu; Lin, Min; Jin, Ping; Xiong, Yunyun; Xu, Gelin; Yin, Qin; Liu, Xinfeng

    2018-01-03

    Early judgment of long-term prognosis is the key to making medical decisions in acute anterior circulation large-vessel occlusion stroke (LVOS) after endovascular treatment (EVT). We aimed to investigate the relationship between the combination of 24-hour and 7-day relative neurological improvement (RNI) and 90-day functional outcome. We selected the target population from a multicenter ischemic stroke registry. The National Institutes of Health Stroke Scale (NIHSS) scores at baseline, 24 hours, and 7 days were collected. RNI was calculated by the following equation: (baseline NIHSS - 24-hour/7-day NIHSS)/baseline NIHSS × 100%. A modified Rankin Scale score of 0-2 at 90 days was defined as a favorable outcome. Multivariable logistic regression analysis was used to evaluate the relationship between RNI and 90-day outcome. Receiver operator characteristic curve analysis was performed to identify the predictive power and cutoff point of RNI for functional outcome. A total of 568 patients were enrolled. Both 24-hour and 7-day RNI were independent predictors of 90-day outcome. The best cutoff points of 24-hour and 7-day RNI were 28% and 42%, respectively. Compared with those with 24-hour RNI of less than 28% and 7-day RNI of less than 42%, patients with 24-hour RNI of 28% or greater and 7-day RNI of 42% or greater had a 39.595-fold (95% confidence interval 22.388-70.026) increased probability of achieving 90-day favorable outcome. The combination of 24-hour and 7-day RNI very strongly predicts 90-day functional outcome in patients with acute anterior circulation LVOS who received EVT, and it can be used as an early accurate surrogate of long-term outcome. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  10. Integration of Known DNA, RNA and Protein Biomarkers Provides Prediction of Anti-TNF Response in Rheumatoid Arthritis

    DEFF Research Database (Denmark)

    Folkersen, Lasse; Brynedal, Boel; Marcela Diaz-Gallo, Lina

    2016-01-01

    to test the claim that the current state-of-the-art precision medicine will benefit RA patients. METHODS: We collected 451 blood samples from 61 healthy individuals and 185 RA patients initiating treatment, before treatment initiation and at a 3 month follow-up time. All samples were subjected to high...... and replication. Taking advantage of this we surveyed the current state-of-the-art of drug-response stratification in RA, and identified a small set of previously published biomarkers available in peripheral blood which predicts clinical response to TNF blockade in this independent cohort....

  11. One-Leg Standing Time of the Affected Side Moderately Predicts for Postdischarge Falls in Community Stroke Patients.

    Science.gov (United States)

    Yoshimoto, Yoshinobu; Oyama, Yukitsuna; Tanaka, Mamoru; Sakamoto, Asuka

    2016-08-01

    The purpose of the present study was to investigate the predictive accuracy of one-leg standing time at hospital discharge on falls in stroke patients. This was a retrospective cohort study. Participants included stroke patients (n = 65) who could walk when discharged from inpatient rehabilitation ward. To investigate the relationship between one-leg standing time and falls, logistic analysis was utilized with a criterion variable including the presence or absence of falls after 1-year hospital discharge as well as explanatory variables including Brunnstrom stage, knee extension strength on the affected side, Barthel Index, 10-m walking speed, and one-leg standing time on both sides. The accuracy of prediction by one-leg standing time was measured by the area under the curve of the receiver operating characteristic curve. Among the 65 patients, 38 (58.5%) experienced a fall 1 year after discharge. One-leg standing time of the affected side was not significantly associated with the falls (odds ratio: .89; 95% confidence interval: .79-1.01). When the fall incidents were assessed by area under the curve of the receiver operating characteristic curve, one-leg standing time of the affected side was observed to have increased marginally to .93 (95% confidence interval: .87-.99) as compared to the traditional prediction mode area under the curve (area under the curve .88; 95% confidence interval: .81-.97). One-leg standing time of the affected side may be considered as a moderately effective and simple assessment method for predicting postdischarge falls in a clinical setting. Copyright © 2016 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  12. 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

  13. Predicting episodic memory performance using different biomarkers: results from Argentina-Alzheimer’s Disease Neuroimaging Initiative

    Directory of Open Access Journals (Sweden)

    Russo MJ

    2016-09-01

    Full Text Available María Julieta Russo,1 Gabriela Cohen,1 Patricio Chrem Mendez,1 Jorge Campos,1 Federico E Nahas,1 Ezequiel I Surace,1 Silvia Vazquez,1 Deborah Gustafson,2,3 Salvador Guinjoan,1 Ricardo F Allegri,1 Gustavo Sevlever1 On behalf of the Argentina-Alzheimer’s Disease Neuroim­aging Initiative group 1Center of Aging and Memory of Neurological Research Institute (FLENI, Buenos Aires, Argentina; 2Department of Neurology, State University of New York-Downstate Medical Center, Brooklyn, NY, USA; 3Neuropsychiatric Epidemiology Unit, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, SwedenPurpose: Argentina-Alzheimer’s Disease Neuroimaging Initiative (Arg-ADNI is the first ADNI study to be performed in Latin America at a medical center with the appropriate infrastructure. Our objective was to describe baseline characteristics and to examine whether biomarkers related to Alzheimer’s disease (AD physiopathology were associated with worse memory performance.Patients and methods: Fifteen controls and 28 mild cognitive impairment and 13 AD dementia subjects were included. For Arg-ADNI, all biomarker parameters and neuropsychological tests of ADNI-II were adopted. Results of positron emission tomography (PET with fluorodeoxyglucose and 11C-Pittsburgh compound-B (PIB-PET were available from all participants. Cerebrospinal fluid biomarker results were available from 39 subjects.Results: A total of 56 participants were included and underwent baseline evaluation. The three groups were similar with respect to years of education and sex, and they differed in age (F=5.10, P=0.01. Mean scores for the baseline measurements of the neuropsychological evaluation differed significantly among the three groups at P<0.001, showing a continuum in their neuropsychological performance. No significant correlations were found between the principal measures (long-delay recall, C-Pittsburgh compound-B scan, left hippocampal

  14. 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.

  15. Predicting tissue outcome from acute stroke magnetic resonance imaging: improving model performance by optimal sampling of training data.

    Science.gov (United States)

    Jonsdottir, Kristjana Yr; Østergaard, Leif; Mouridsen, Kim

    2009-09-01

    It has been hypothesized that algorithms predicting the final outcome in acute ischemic stroke may provide future tools for identifying salvageable tissue and hence guide individualized therapy. We developed means of quantifying predictive model performance to identify model training strategies that optimize performance and reduce bias in predicted lesion volumes. We optimized predictive performance based on the area under the receiver operating curve for logistic regression and used simulated data to illustrate the effect of an unbalanced (unequal number of infarcting and surviving voxels) training set on predicted infarct risk. We then tested the performance and optimality of models based on perfusion-weighted, diffusion-weighted, and structural MRI modalities by changing the proportion of mismatch voxels in balanced training material. Predictive performance (area under the receiver operating curve) based on all brain voxels is excessively optimistic and lacks sensitivity in performance in mismatch tissue. The ratio of infarcting and noninfarcting voxels used for training predictive algorithms significantly biases tissue infarct risk estimates. Optimal training strategy is obtained using a balanced training set. We show that 60% of noninfarcted voxels consists of mismatch voxels in an optimal balanced training set for the patient data presented. An equal number of infarcting and noninfarcting voxels should be used when training predictive models. The choice of test and training sets critically affects predictive model performance and should be closely evaluated before comparisons across patient cohorts.

  16. The need for a network to establish and validate predictive biomarkers in cancer immunotherapy

    Directory of Open Access Journals (Sweden)

    Giuseppe V. Masucci

    2017-11-01

    Full Text Available Abstract Immunotherapies have emerged as one of the most promising approaches to treat patients with cancer. Recently, the entire medical oncology field has been revolutionized by the introduction of immune checkpoints inhibitors. Despite success in a variety of malignancies, responses typically only occur in a small percentage of patients for any given histology or treatment regimen. There are also concerns that immunotherapies are associated with immune-related toxicity as well as high costs. As such, identifying biomarkers to determine which patients are likely to derive clinical benefit from which immunotherapy and/or be susceptible to adverse side effects is a compelling clinical and social need. In addition, with several new immunotherapy agents in different phases of development, and approved therapeutics being tested in combination with a variety of different standard of care treatments, there is a requirement to stratify patients and select the most appropriate population in which to assess clinical efficacy. The opportunity to design parallel biomarkers studies that are integrated within key randomized clinical trials could be the ideal solution. Sample collection (fresh and/or archival tissue, PBMC, serum, plasma, stool, etc. at specific points of treatment is important for evaluating possible biomarkers and studying the mechanisms of responsiveness, resistance, toxicity and relapse. This white paper proposes the creation of a network to facilitate the sharing and coordinating of samples from clinical trials to enable more in-depth analyses of correlative biomarkers than is currently possible and to assess the feasibilities, logistics, and collated interests. We propose a high standard of sample collection and storage as well as exchange of samples and knowledge through collaboration, and envisage how this could move forward using banked samples from completed studies together with prospective planning for ongoing and future clinical

  17. Biomarkers predict outcome in Charcot-Marie-Tooth disease 1A.

    Science.gov (United States)

    Fledrich, Robert; Mannil, Manoj; Leha, Andreas; Ehbrecht, Caroline; Solari, Alessandra; Pelayo-Negro, Ana L; Berciano, José; Schlotter-Weigel, Beate; Schnizer, Tuuli J; Prukop, Thomas; Garcia-Angarita, Natalia; Czesnik, Dirk; Haberlová, Jana; Mazanec, Radim; Paulus, Walter; Beissbarth, Tim; Walter, Maggie C; Triaal, Cmt-; Hogrel, Jean-Yves; Dubourg, Odile; Schenone, Angelo; Baets, Jonathan; De Jonghe, Peter; Shy, Michael E; Horvath, Rita; Pareyson, Davide; Seeman, Pavel; Young, Peter; Sereda, Michael W

    2017-11-01

    Charcot-Marie-Tooth disease type 1A (CMT1A) is the most common inherited neuropathy, a debilitating disease without known cure. Among patients with CMT1A, disease manifestation, progression and severity are strikingly variable, which poses major challenges for the development of new therapies. Hence, there is a strong need for sensitive outcome measures such as disease and progression biomarkers, which would add powerful tools to monitor therapeutic effects in CMT1A. We established a pan-European and American consortium comprising nine clinical centres including 311 patients with CMT1A in total. From all patients, the CMT neuropathy score and secondary outcome measures were obtained and a skin biopsy collected. In order to assess and validate disease severity and progression biomarkers, we performed qPCR on a set of 16 animal model-derived potential biomarkers in skin biopsy mRNA extracts. In 266 patients with CMT1A, a cluster of eight cutaneous transcripts differentiates disease severity with a sensitivity and specificity of 90% and 76.1%, respectively. In an additional cohort of 45 patients with CMT1A, from whom a second skin biopsy was taken after 2-3 years, the cutaneous mRNA expression of GSTT2, CTSA, PPARG, CDA, ENPP1 and NRG1-Iis changing over time and correlates with disease progression. In summary, we provide evidence that cutaneous transcripts in patients with CMT1A serve as disease severity and progression biomarkers and, if implemented into clinical trials, they could markedly accelerate the development of a therapy for CMT1A. © 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.

  18. Imaging biomarkers predict response to anti-HER2 (ErbB2) therapy in preclinical models of breast cancer.

    Science.gov (United States)

    Shah, Chirayu; Miller, Todd W; Wyatt, Shelby K; McKinley, Eliot T; Olivares, Maria Graciela; Sanchez, Violeta; Nolting, Donald D; Buck, Jason R; Zhao, Ping; Ansari, M Sib; Baldwin, Ronald M; Gore, John C; Schiff, Rachel; Arteaga, Carlos L; Manning, H Charles

    2009-07-15

    To evaluate noninvasive imaging methods as predictive biomarkers of response to trastuzumab in mouse models of HER2-overexpressing breast cancer. The correlation between tumor regression and molecular imaging of apoptosis, glucose metabolism, and cellular proliferation was evaluated longitudinally in responding and nonresponding tumor-bearing cohorts. Mammary tumors from MMTV/HER2 transgenic female mice were transplanted into syngeneic female mice. BT474 human breast carcinoma cell line xenografts were grown in athymic nude mice. Tumor cell apoptosis (NIR700-Annexin V accumulation), glucose metabolism [2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography ([18F]FDG-PET)], and proliferation [3'-[18F]fluoro-3'-deoxythymidine-PET ([18F]FLT-PET)] were evaluated throughout a biweekly trastuzumab regimen. Imaging metrics were validated by direct measurement of tumor size and immunohistochemical analysis of cleaved caspase-3, phosphorylated AKT, and Ki67. NIR700-Annexin V accumulated significantly in trastuzumab-treated MMTV/HER2 and BT474 tumors that ultimately regressed but not in nonresponding or vehicle-treated tumors. Uptake of [18F]FDG was not affected by trastuzumab treatment in MMTV/HER2 or BT474 tumors. [18F]FLT-PET imaging predicted trastuzumab response in BT474 tumors but not in MMTV/HER2 tumors, which exhibited modest uptake of [18F]FLT. Close agreement was observed between imaging metrics and immunohistochemical analysis. Molecular imaging of apoptosis accurately predicts trastuzumab-induced regression of HER2+ tumors and may warrant clinical exploration to predict early response to neoadjuvant trastuzumab. Trastuzumab does not seem to alter glucose metabolism substantially enough to afford [18F]FDG-PET significant predictive value in this setting. Although promising in one preclinical model, further studies are required to determine the overall value of [18F]FLT-PET as a biomarker of response to trastuzumab in HER2+ breast cancer.

  19. The potential biomarkers in predicting pathologic response of breast cancer to three different chemotherapy regimens: a case control study

    Directory of Open Access Journals (Sweden)

    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.

  20. 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.

  1. 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.

  2. Pharmacogenetic Biomarkers to Predict Treatment Response in Multiple Sclerosis: Current and Future Perspectives

    Directory of Open Access Journals (Sweden)

    Patricia K. Coyle

    2017-01-01

    Full Text Available Disease-modifying therapies (DMTs have significantly advanced the treatment of relapsing multiple sclerosis (MS, decreasing the frequency of relapses, disability, and magnetic resonance imaging lesion formation. However, patients’ responses to and tolerability of DMTs vary considerably, creating an unmet need for biomarkers to identify likely responders and/or those who may have treatment-limiting adverse reactions. Most studies in MS have focused on the identification of pharmacogenetic markers, using either the candidate-gene approach, which requires prior knowledge of the genetic marker and its role in the target disease, or genome-wide association, which examines multiple genetic variants, typically single nucleotide polymorphisms (SNPs. Both approaches have implicated numerous alleles and SNPs in response to selected MS DMTs. None have been validated for use in clinical practice. This review covers pharmacogenetic markers in clinical practice in other diseases and then reviews the current status of MS DMT markers (interferon β, glatiramer acetate, and mitoxantrone. For a complex disease such as MS, multiple biomarkers may need to be evaluated simultaneously to identify potential responders. Efforts to identify relevant biomarkers are underway and will need to be expanded to all MS DMTs. These will require extensive validation in large patient groups before they can be used in clinical practice.

  3. Inflammatory biomarkers improve clinical prediction of mortality in chronic obstructive pulmonary disease

    DEFF Research Database (Denmark)

    Celli, Bartolome R; Locantore, Nicholas; Yates, Julie

    2012-01-01

    Accurate prediction of mortality helps select patients for interventions aimed at improving outcome.......Accurate prediction of mortality helps select patients for interventions aimed at improving outcome....

  4. Cues and clues predicting presence of symptoms of depression in stroke survivors.

    Science.gov (United States)

    Barra, Mathias; Evensen, Gina Sophie Hvidsten; Valeberg, Berit Taraldsen

    2017-02-01

    To investigate to what extent self-reported cues about lack of treatment or concerns about inadequate health care from stroke survivors were associated with symptoms of depression. Stroke survivors are prone to depression, and thus, any easily available cues which may inform healthcare workers about patients' mental well-being are potentially important. This study investigates whether two such cues - Cue 1 the subjectively reported lack of access to rehabilitation, and more generally, Cue 2 an expressed concern that their healthcare needs may not be adequately met - may be clinically relevant to be on the outlook for. A cross-sectional survey of stroke survivors three months after discharge from a stroke unit. Analysis of data on stroke survivors collected at three months after discharge from a hospital's stroke unit, by means of a mailed questionnaire. Descriptive statistics for the sample population were computed, and a binary logistic model fitted to estimate the impact of subjectively perceived lack of rehabilitation and subjectively reported low confidence in the healthcare system on symptoms of depression as measured by the Hospital Anxiety and Depression Scale. The percentage of patients reporting the presence of symptoms of depression three months postdischarge (22·6%) was consistent with the main body of literature on this subject. Both cues investigated had a significant (p Cue 1 odds ratio = 4·7 (1·3-18·4) and Cue 2 odds ratio = 2·8 (1·2-6·4), respectively - for showing symptoms of depression in our population. Healthcare workers who come in contact with stroke survivors who report having missed out on rehabilitation or express concern that their care needs may not be adequately met by their access to health care should ensure that the patients' mental well-being is being duly monitored and should consider further investigation for depression. Healthcare workers who come into contact with stroke survivors should pay attention to patients

  5. Predictive factors of subjective sleep quality and insomnia complaint in patients with stroke: implications for clinical practice.

    Science.gov (United States)

    Da Rocha, Patrícia C; Barroso, Marina T M; Dantas, Ana Amália T S G; Melo, Luciana P; Campos, Tania F

    2013-09-01

    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.

  6. 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.

  7. 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.

  8. A data mining approach for identifying pathway-gene biomarkers for predicting clinical outcome: A case study of erlotinib and sorafenib.

    Directory of Open Access Journals (Sweden)

    David G Covell

    Full Text Available A novel data mining procedure is proposed for identifying potential pathway-gene biomarkers from preclinical drug sensitivity data for predicting clinical responses to erlotinib or sorafenib. The analysis applies linear ridge regression modeling to generate a small (N~1000 set of baseline gene expressions that jointly yield quality predictions of preclinical drug sensitivity data and clinical responses. Standard clustering of the pathway-gene combinations from gene set enrichment analysis of this initial gene set, according to their shared appearance in molecular function pathways, yields a reduced (N~300 set of potential pathway-gene biomarkers. A modified method for quantifying pathway fitness is used to determine smaller numbers of over and under expressed genes that correspond with favorable and unfavorable clinical responses. Detailed literature-based evidence is provided in support of the roles of these under and over expressed genes in compound efficacy. RandomForest analysis of potential pathway-gene biomarkers finds average treatment prediction errors of 10% and 22%, respectively, for patients receiving erlotinib or sorafenib that had a favorable clinical response. Higher errors were found for both compounds when predicting an unfavorable clinical response. Collectively these results suggest complementary roles for biomarker genes and biomarker pathways when predicting clinical responses from preclinical data.

  9. Left Atrial Enlargement on Transthoracic Echocardiography Predicts Left Atrial Thrombus on Transesophageal Echocardiography in Ischemic Stroke Patients

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    James Anaissie

    2016-01-01

    Full Text Available Background. Transesophageal echocardiogram (TEE is superior to transthoracic echocardiogram (TTE in detecting left atrial thrombus (LAT, a risk factor for stroke, but is costly and invasive, carrying a higher risk for complications. Aims. To determine the utility of using left atrial enlargement (LAE on TTE to predict LAT on TEE. Methods. AIS patients who presented in 06/2008–7/2013 and underwent both TTE and TEE were identified from our prospective stroke registry. Analysis consisted of multivariate logistic regression with propensity score adjustment and receiver operating characteristic (ROC area under the curve (AUC analyses. Results. 219 AIS patients underwent both TTE and TEE. LAE on TTE was detected in 113 (51.6% of AIS patients. Patients with LAE on TTE had higher proportion of LAT on TEE (8.4% versus 1.0%, p=0.018. LAE on TTE predicted increased odds of LAT on TEE (OR=8.83, 95% CI 1.04–74.83, p=0.046. The sensitivity and specificity for LAT on TEE by LAE on TEE were 88.89% and 52.20%, respectively (AUC=0.7054, 95% CI 0.5906–0.8202. Conclusions. LAE on TTE can predict LAT detected on TEE in nearly 90% of patients. This demonstrates the utility of LAE on TTE as a potential screening tool for LAT, potentially limiting unneeded costs and complications associated with TEE.

  10. Left Atrial Enlargement on Transthoracic Echocardiography Predicts Left Atrial Thrombus on Transesophageal Echocardiography in Ischemic Stroke Patients.

    Science.gov (United States)

    Anaissie, James; Monlezun, Dominique; Seelochan, A; Siegler, James E; Chavez-Keatts, Maria; Tiu, Jonathan; Pineda, Denise; George, Alexander; Shaban, Amir; Abi Rafeh, Nidal; Schluter, Laurie; Martin-Schild, Sheryl; El Khoury, Ramy

    2016-01-01

    Background. Transesophageal echocardiogram (TEE) is superior to transthoracic echocardiogram (TTE) in detecting left atrial thrombus (LAT), a risk factor for stroke, but is costly and invasive, carrying a higher risk for complications. Aims. To determine the utility of using left atrial enlargement (LAE) on TTE to predict LAT on TEE. Methods. AIS patients who presented in 06/2008-7/2013 and underwent both TTE and TEE were identified from our prospective stroke registry. Analysis consisted of multivariate logistic regression with propensity score adjustment and receiver operating characteristic (ROC) area under the curve (AUC) analyses. Results. 219 AIS patients underwent both TTE and TEE. LAE on TTE was detected in 113 (51.6%) of AIS patients. Patients with LAE on TTE had higher proportion of LAT on TEE (8.4% versus 1.0%, p = 0.018). LAE on TTE predicted increased odds of LAT on TEE (OR = 8.83, 95% CI 1.04-74.83, p = 0.046). The sensitivity and specificity for LAT on TEE by LAE on TEE were 88.89% and 52.20%, respectively (AUC = 0.7054, 95% CI 0.5906-0.8202). Conclusions. LAE on TTE can predict LAT detected on TEE in nearly 90% of patients. This demonstrates the utility of LAE on TTE as a potential screening tool for LAT, potentially limiting unneeded costs and complications associated with TEE.

  11. 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...

  12. Prediction of the response to citalopram and reboxetine in post-stroke depressed patients.

    Science.gov (United States)

    Rampello, Liborio; Chiechio, Santina; Nicoletti, Giovanni; Alvano, Alessandro; Vecchio, Ignazio; Raffaele, Rocco; Malaguarnera, Mariano

    2004-04-01

    Depression is a significant complication of stroke. The effectiveness of antidepressant drugs in the management of post-stroke depression (PSD) has been widely investigated. However, the choice of antidepressant drug is critically influenced by its safety and tolerability and by its effect on concurrent pathologies. Here we investigate the efficacy and safety of a selective serotonin reuptake inhibitor (SSRI), citalopram, and a noradrenaline reuptake inhibitor (NARI), reboxetine, in post-stroke patients affected by anxious depression or retarded depression. This was a randomized double-blind study. Seventy-four post-stroke depressed patients were diagnosed as affected by anxious or retarded depression by using a synoptic table. Randomisation was planned so that 50% of the patients in each subgroup were assigned for 16 weeks to treatment with citalopram and the remaining 50% were assigned to treatment with reboxetine. The Beck Depression Inventory (BDI), the Hamilton Depression Rating Scale (HDRS) and a synoptic table were used to score depressive symptoms. Both citalopram and reboxetine showed good safety and tolerability. Citalopram exhibited greater efficacy in anxious depressed patients, while reboxetine was more effective in retarded depressed patients. Citalopram or other SSRIs and reboxetine may be of first choice treatment in PSD because of their good efficacy and lack of severe side effects. In addition, PSD patients should be classified according to their clinical profile (similarly to patients affected by primary depression) for the selection of SSRIs or reboxetine as drugs of choice in particular subgroups of patients.

  13. The Discovery of Novel Biomarkers Improves Breast Cancer Intrinsic Subtype Prediction and Reconciles the Labels in the METABRIC Data Set

    Science.gov (United States)

    Milioli, Heloisa Helena; Vimieiro, Renato; Riveros, Carlos; Tishchenko, Inna; Berretta, Regina; Moscato, Pablo

    2015-01-01

    Background The prediction of breast cancer intrinsic subtypes has been introduced as a valuable strategy to determine patient diagnosis and prognosis, and therapy response. The PAM50 method, based on the expression levels of 50 genes, uses a single sample predictor model to assign subtype labels to samples. Intrinsic errors reported within this assay demonstrate the challenge of identifying and understanding the breast cancer groups. In this study, we aim to: a) identify novel biomarkers for subtype individuation by exploring the competence of a newly proposed method named CM1 score, and b) apply an ensemble learning, as opposed to the use of a single classifier, for sample subtype assignment. The overarching objective is to improve class prediction. Methods and Findings The microarray transcriptome data sets used in this study are: the METABRIC breast cancer data recorded for over 2000 patients, and the public integrated source from ROCK database with 1570 samples. We first computed the CM1 score to identify the probes with highly discriminative patterns of expression across samples of each intrinsic subtype. We further assessed the ability of 42 selected probes on assigning correct subtype labels using 24 different classifiers from the Weka software suite. For comparison, the same method was applied on the list of 50 genes from the PAM50 method. Conclusions The CM1 score portrayed 30 novel biomarkers for predicting breast cancer subtypes, with the confirmation of the role of 12 well-established genes. Intrinsic subtypes assigned using the CM1 list and the ensemble of classifiers are more consistent and homogeneous than the original PAM50 labels. The new subtypes show accurate distributions of current clinical markers ER, PR and HER2, and survival curves in the METABRIC and ROCK data sets. Remarkably, the paradoxical attribution of the original labels reinforces the limitations of employing a single sample classifiers to predict breast cancer intrinsic subtypes

  14. The clinical significance of MiR-148a as a predictive biomarker in patients with advanced colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Masanobu Takahashi

    Full Text Available Development of robust prognostic and/or predictive biomarkers in patients with colorectal cancer (CRC is imperative for advancing treatment strategies for this disease. We aimed to determine whether expression status of certain miRNAs might have prognostic/predictive value in CRC patients treated with conventional cytotoxic chemotherapies.We studied a cohort of 273 CRC specimens from stage II/III patients treated with 5-fluorouracil-based adjuvant chemotherapy and stage IV patients subjected to 5-fluorouracil and oxaliplatin-based chemotherapy. In a screening set (n = 44, 13 of 21 candidate miRNAs were successfully quantified by multiplex quantitative RT-PCR. In the validation set comprising of the entire patient cohort, miR-148a expression status was assessed by quantitative RT-PCR, and its promoter methylation was quantified by bisulfite pyrosequencing. Lastly, we analyzed the associations between miR-148a expression and patient survival.Among the candidate miRNAs studied, miR-148a expression was most significantly down-regulated in advanced CRC tissues. In stage III and IV CRC, low miR-148a expression was associated with significantly shorter disease free-survival (DFS, a worse therapeutic response, and poor overall survival (OS. Furthermore, miR-148a methylation status correlated inversely with its expression, and was associated with worse survival in stage IV CRC. In multivariate analysis, miR-148a expression was an independent prognostic/predictive biomarker for advanced CRC patients (DFS in stage III, low vs. high expression, HR 2.11; OS in stage IV, HR 1.93.MiR-148a status has a prognostic/predictive value in advanced CRC patients treated with conventional chemotherapy, which has important clinical implications in improving therapeutic strategies and personalized management of this malignancy.

  15. 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.

  16. Prediction of atrial fibrillation after ischemic stroke using P-wave signal averaged electrocardiography.

    Science.gov (United States)

    Yodogawa, Kenji; Seino, Yoshihiko; Ohara, Toshihiko; Hayashi, Meiso; Miyauchi, Yasushi; Katoh, Takao; Mizuno, Kyoichi

    2013-01-01

    Atrial fibrillation (AF) is highly prevalent in patients with ischemic stroke, but the diagnosis is often difficult. This study consisted of 68 stroke patients in sinus rhythm without history of AF. All patients underwent P-wave signal-averaged electrocardiography (P-SAECG), echocardiography, 24-h Holter monitoring, and measurement of plasma B-type natriuretic peptide (BNP) concentrations at admission. An abnormal P-SAECG was found in 34 of 68 stroke patients. In the follow-up period of 11 ± 4 months, AF developed in 17 patients (AF group). The remaining 51 patients were classified as the non-AF group. The prevalence of atrial late potentials (ALP) on P-SAECG, and the number of premature atrial contractions (PACs) were significantly higher in the AF group than those in the non-AF group (88.2% vs 37.3%; p<0.001, 149 ± 120 vs 79 ± 69; p=0.030, respectively). However, there were no significant differences in age, left atrial dimension, or BNP concentrations between both groups. Cox proportional hazards analysis revealed that the presence of ALP (risk ratio 11.15; p=0.002) and frequent PACs (more than 100/24h) (risk ratio 4.53; p=0.007) had significant correlation to the occurrence of AF. ALP may be a novel predictor of AF in stroke patients. P-SAECG should be considered in stroke of undetermined etiology. Copyright © 2012 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

  17. 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.

  18. Are biomarkers evaluated in biopsy specimens predictive of prostate cancer aggressiveness?

    Science.gov (United States)

    Carozzi, Francesca; Tamburrino, Lara; Bisanzi, Simonetta; Marchiani, Sara; Paglierani, Milena; Di Lollo, Simonetta; Crocetti, Emanuele; Buzzoni, Carlotta; Burroni, Elena; Greco, Luana; Baldi, Elisabetta; Sani, Cristina

    2016-01-01

    To evaluate biomarkers involved in biological pathways for prostate cancer (PCa) progression, measured in biopsy specimens, in order to distinguish patients at higher risk for fatal PCa and thus improve the initial management of disease. Retrospective case-control study. In 129 PCa patients who underwent ultrasound-guided needle prostate biopsy and subsequent radical prostatectomy from 1987 to 1999 at the University Hospital of Careggi, we evaluated: (1) mRNA expression of the serine 2 (TMPRSS2): erythroblastosis virus E26 oncogene homolog (ERG); (2) expression of matrix metalloproteinases (MMP)-2 and 9 (epithelial and stromal); (3) expression of androgen receptor; (4) expression of prognostic marker Ki67 (MIB1); (5) presence and typing of human papilloma virus; (6) DNA methylation of CpG islands of several genes involved in PCa progression. The cohort consists of 38 cases (patients with PCa and died of PCa within 10 years from diagnosis) and 91 controls (patients with PCa but alive 10 years after diagnosis). Gleason bioptic score, epithelial MMP expression and SERPINB5 methylation correlated with statistically significant increase in death risk OR. Compared with patients with high level of MMP, patients with low level of MMP had OR for specific death 4.78 times higher (p = 0.0066). After adjustment for age and Gleason score, none of the investigated biomarkers showed increased OR for PCa death. Our preliminary results suggest that evaluation, in prostate biopsy specimens, of a panel of biomarkers known to be involved in PCa progression is poorly indicative of tumor outcome.

  19. Plasma specific miRNAs as predictive biomarkers for diagnosis and prognosis of glioma

    Directory of Open Access Journals (Sweden)

    Wang Qiong

    2012-11-01

    Full Text Available Abstract Objective Glioblastoma multiforme (GBM is a highly malignant brain tumor with a poor prognosis. MicroRNAs (miRNAs are a class of small non-coding RNAs, approximately 21–25 nucleotides in length. Recently, some researchers have demonstrated that plasma miRNAs are sensitive and specific biomarkers of various cancers. The primary aim of the study is to investigate whether miRNAs present in the plasma of GBM patients can be used as diagnostic biomarkers and are associated with glioma classification and clinical treatment. Materials and Methods Plasma samples were attained by venipuncture from 50 patients and 10 healthy donors. Plasma levels of miRNAs were determined by real-time quantitative polymerase chain reaction. Results The plasma levels of miR-21, miR-128 and miR-342-3p were significantly altered in GBM patients compared to normal controls and could discriminate glioma from healthy controls with high specificity and sensitivity. However, these three miRNAs were not significantly changed in patients with other brain tumors such as meningioma or pituitary adenoma. Furthermore, the plasma levels of these three miRNAs in GBM patients treated by operation and chemo-radiation almost revived to normal levels. Finally, we also demonstrated that miR-128 and miR-342-3p were positively correlated with histopathological grades of glioma. Conclusions These findings suggest that plasma specific miRNAs have potential use as novel biomarkers of glioma and may be useful in clinical management for glioma patients.

  20. 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

  1. 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

  2. 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.

  3. 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

  4. Identification and validation of potential prognostic gene biomarkers for predicting survival in patients with acute myeloid leukemia

    Directory of Open Access Journals (Sweden)

    Huang R

    2017-11-01

    Full Text Available Rui Huang,1,* Xiwen Liao,2,* Qiaochuan Li1 1Department of Hematology, 2Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People’s Republic of China *These authors contributed equally to this work Background: Molecular analysis is a promising source of clinically useful prognostic biomarkers. The aim of this investigation was to identify prognostic biomarkers for patients with acute myeloid leukemia (AML by using the gene expression profile dataset from public database. Methods: The gene expression profile dataset and corresponding overall survival (OS information of three cohorts of AML patients from GSE12417 and The Cancer Genome Atlas AML project (TCGA-LAML were included in the present study. Prognostic gene screening was performed by using a survival package, whereas time-dependent receiver operating characteristic (ROC curve analysis was performed using the survivalROC package. Results: In the three cohorts, 11 genes were identified that were significantly associated with AML OS. A linear prognostic model of the 11 genes was constructed and weighted by regression coefficient (β from the multivariate Cox regression analyses of GSE12417 HG-U133A cohort to divide patients into high- and low-risk groups. GSE12417 HG-U133 plus 2.0 and TCGA-LAML were validation cohorts. Patients assigned to the high-risk group exhibited poor OS compared to patients in the low-risk group. The 11-gene signature is a prognostic marker of AML and demonstrates good performance for predicting 1-, 3-, and 5-year OS as evaluated by survivalROC in the three cohorts. Conclusion: Our study has identified an mRNA signature including 11 genes, which may serve as a potential prognostic marker of AML. Keywords: acute myeloid leukemia, prognosis, biomarker, GEO, TCGA

  5. 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

  6. 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.

  7. Failure of renal biomarkers to predict worsening renal function in high-risk patients presenting with oliguria.

    Science.gov (United States)

    Legrand, Matthieu; Jacquemod, Aurélien; Gayat, Etienne; Collet, Corinne; Giraudeaux, Veronique; Launay, Jean-Marie; Payen, Didier

    2015-01-01

    Oliguria is a common symptom in critically ill patients and puts patients in a high risk category for further worsening renal function (WRF). We performed this study to explore the predictive value of biomarkers to predict WRF in oliguric intensive care unit (ICU) patients. Single-center prospective observational study. ICU patients were included when they presented a first episode of oliguria. Plasma and urine biomarkers were measured: plasma and urine neutrophil gelatinase-associated lipocalin (pNGAL and uNGAL), urine α1-microglobulin, urine γ-glutamyl transferase, urine indices of tubular function, cystatin C, C terminal fragment of pro-arginine vasopressin (CT-ProAVP), and proadrenomedullin (MR-ProADM). One hundred eleven patients formed the cohort, of whom 41 [corrected] had worsening renal function. Simplified Acute Physiology Score (SAPS) II was 41 (31-51). WRF was associated with increased mortality (hazard ratio 8.65 [95 % confidence interval (CI) 3.0-24.9], p = 0.0002). pNGAL, MR-ProADM, and cystatin C had the best odds ratio and area under the receiver-operating characteristic curve (AUC-ROC: 0.83 [0.75-0.9], 0.82 [0.71-0.91], and 0.83 [0.74-0.90]), but not different from serum creatinine (Screat, 0.80 [0.70-0.88]). A clinical model that included age, sepsis, SAPS II, and Screat had AUC-ROC of 0.79 [0.69-0.87]; inclusion of pNGAL increased the AUC-ROC to 0.86 (p = 0.03). The category-free net reclassification index improved with pNGAL (total net reclassification index for events to higher risk 61 % and nonevents to lower 82 %). All episodes of oliguria do not carry the same risk. No biomarker further improved prediction of WRF compared with Screat in this selected cohort of patients at increased risk defined by oliguria.

  8. 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.

  9. 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.

  10. Prediction of functional outcomes in stroke patients: the role of motor patterns according to limb synergies.

    Science.gov (United States)

    Gialanella, Bernardo; Santoro, Raffaele

    2015-10-01

    To address the relationships among motor patterns evaluated according to the limb synergies and functional outcomes in stroke patients and clarify which motor pattern was the most important predictor of functional outcomes. The study was conducted on 208 patients with primary diagnosis of stroke admitted for in-hospital rehabilitation. At entry, the Fugl-Meyer Scale was administered to assess motor function according to limb synergies. Pearson's correlation was used to assess the relationship between variables, and backward stepwise regression analysis was used to identify the outcome determinants. Final functional independence measure (FIM) scores and length of in-hospital stay were the outcome measures. At the end of rehabilitation, motor-FIM scores of patients with extensor and flexor synergies, mixing synergies, and no dependence from the synergies were higher than those of no movements and flexor synergy. Multivariate regression analysis showed that extensor synergy of upper limb was an independent predictor of final motor-FIM, personal care and mobility, extensor synergy of lower limb of locomotion, while mixing synergies of upper limb was an independent predictor of length of in-hospital stay. In stroke rehabilitation, the patients' motor patterns according to the synergies strongly relate with functional outcomes and are important outcome predictors.

  11. 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.

  12. What do carotid intima-media thickness and plaque add to the prediction of stroke and cardiovascular disease risk in older adults? The cardiovascular health study.

    Science.gov (United States)

    Gardin, Julius M; Bartz, Traci M; Polak, Joseph F; O'Leary, Daniel H; Wong, Nathan D

    2014-09-01

    The aim of this study was to evaluate whether the addition of ultrasound carotid intima-media thickness (CIMT) measurements and risk categories of plaque help predict incident stroke and cardiovascular disease (CVD) in older adults. Carotid ultrasound studies were recorded in the multicenter Cardiovascular Health Study. CVD was defined as coronary heart disease plus heart failure plus stroke. Ten-year risk prediction Cox proportional-hazards models for stroke and CVD were calculated using Cardiovascular Health Study-specific coefficients for Framingham risk score factors. Categories of CIMT and CIMT plus plaque were added to Framingham risk score prediction models, and categorical net reclassification improvement (NRI) and Harrell's c-statistic were calculated. In 4,384 Cardiovascular Health Study participants (61% women, 14% black; mean baseline age, 72 ± 5 years) without CVD at baseline, higher CIMT category and the presence of plaque were both associated with higher incidence rates for stroke and CVD. The addition of CIMT improved the ability of Framingham risk score-type risk models to discriminate cases from noncases of incident stroke and CVD (NRI = 0.062, P = .015, and NRI = 0.027, P adults, the addition of CIMT modestly improves 10-year risk prediction for stroke and CVD beyond a traditional risk factor model, mainly by down-classifying risk in those without stroke or CVD; the addition of plaque to CIMT adds no statistical benefit in the overall cohort, although there is evidence of down-classification in those without events. Copyright © 2014 American Society of Echocardiography. Published by Elsevier Inc. All rights reserved.

  13. Copeptin: Limited Usefulness in Early Stroke Differentiation?

    Directory of Open Access Journals (Sweden)

    Johannes von Recum

    2015-01-01

    Full Text Available Background. Stroke can be a challenging diagnosis in an emergency-setting. We sought to determine whether copeptin may be a useful biomarker to differentiate between ischemic stroke (IS, transient ischemic attack (TIA, and stroke-mimics. Methods. In patients with suspected stroke arriving within 4.5 hours of symptom-onset, copeptin-levels were measured in initial blood-samples. The final diagnosis was adjudicated by vascular neurologists blinded to copeptin-values. Results. Of all 36 patients with available copeptin-values (median age 71 years, IQR: 54–76; 44% female, 20 patients (56% were diagnosed with IS, no patient was diagnosed with hemorrhagic stroke, nine patients (25% were diagnosed with TIA, and seven patients (19% were stroke-mimics. Copeptin-levels (in pmol/L tended to be higher in patients with IS [19.1 (11.2–48.5] compared to TIA [9.4 (5.4–13.8]. In stroke-mimics the range of values was extremely broad [33.3 (7.57–255.7]. The diagnostic accuracy of copeptin for IS was 63% with a sensitivity of 80% and a positive predictive value of 64%. Conclusion. In this cohort of patients copeptin-levels within 4.5 hours of symptom onset were higher in patients with IS compared to TIA but the broad range of values in stroke-mimics limits diagnostic accuracy. This trial is registered with UTN: U1111-1119-7602.

  14. 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.

  15. 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

  16. 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

  17. Stroke Treatments

    Science.gov (United States)

    ... Month Infographic Stroke Hero F.A.S.T. Quiz Stroke Treatment Stroke used to rank fourth in leading causes of ... type of treatment depends on the type of stroke. Ischemic stroke happens when a clot blocks a ...

  18. Predictive value of vertebral artery extracranial color-coded duplex sonography for ischemic stroke-related vertigo

    Directory of Open Access Journals (Sweden)

    Li-Min Liou

    2013-12-01

    Full Text Available 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

  19. EPID-28. PROGNOSTIC AND PREDICTIVE BIOMARKERS IN RECURRENT WHO GRADE 3 GLIOMA PATIENTS TREATED WITH BEVACIZUMAB AND IRINOTECAN

    DEFF Research Database (Denmark)

    Toft, Anders; Urup, Thomas; Grunnet, Kirsten

    2015-01-01

    BACKGROUND: Bevacizumab, a monoclonal antibody targeting vascular endothelial growth factor A (VEGF-A) has shown activity in the treatment of recurrent malignant glioma. Predictive markers and prognostic models are required in order to individualize treatment for grade 3 glioma patients. The prim......BACKGROUND: Bevacizumab, a monoclonal antibody targeting vascular endothelial growth factor A (VEGF-A) has shown activity in the treatment of recurrent malignant glioma. Predictive markers and prognostic models are required in order to individualize treatment for grade 3 glioma patients....... The primary endpoint of this study was to identify predictive biomarkers associated with response to bevacizumab therapy. The secondary endpoint was to identify prognostic factors associated with progression-free survival (PFS) and overall survival (OS). METHODS: A total of 62 consecutive, recurrent grade 3...... glioma patients were administered bevacizumab and irinotecan between December 2005 andNovember 2014 according to a previously published clinical protocol.Awide range of clinical, histopathological and molecular factors were screened for significant correlation (p , 0.05) with response and survival...

  20. Ratio of matrix metalloproteinase-2 to -9 is a more accurate predictive biomarker in women with suspected pre-eclampsia.

    Science.gov (United States)

    Feng, Hao; Wang, Li; Zhang, Min; Zhang, Zhiwei; Guo, Wei; Wang, Xietong

    2017-04-30

    Pre-eclampsia (PE) is a condition unique to pregnancy, and abnormal expression of matrix metalloproteinases (MMPs) has been implicated in its pathogenesis. We aimed to evaluate the reliability of plasma levels of MMP-2, MMP-9 and their relative ratio in predicting PE. A total of 318 women with suspected PE were recruited for the study, who were subsequently either cleared or diagnosed of PE and grouped accordingly. Their baseline characteristics were compared. Blood samples were also collected from all participants, to determine the plasma levels of MMP-2 and MMP-9. The predictive values of levels of MMP-2 and MMP-9, as well as their ratio, were analyzed using the receiver operating characteristic (ROC) curve. Either MMP-2 or MMP-9 alone did not exhibit any obvious differences between normal and PE pregnancies. However the ratio of MMP-2/MMP-9 was significantly higher in PE-affected pregnancy than normal control group. ROC curve analysis also indicated that the MMP-2/MMP-9 ratio provided better compromise between specificity and sensitivity in distinguishing PE from normal pregnancies, than either of the two MMPs alone. MMP-2/MMP-9 ratio is a more accurate biomarker to predict PE than either MMP-2 or MMP-9 alone. © 2017 The Author(s).

  1. Identification of Predictive Biomarkers for Cytokine Release Syndrome after Chimeric Antigen Receptor T cell Therapy for Acute Lymphoblastic Leukemia

    Science.gov (United States)

    Teachey, David T.; Lacey, Simon F.; Shaw, Pamela A.; Melenhorst, J. Joseph; Maude, Shannon L.; Frey, Noelle; Pequignot, Edward; Gonzalez, Vanessa E.; Chen, Fang; Finklestein, Jeffrey; Barrett, David M.; Weiss, Scott L.; Fitzgerald, Julie C.; Berg, Robert A.; Aplenc, Richard; Callahan, Colleen; Rheingold, Susan R.; Zheng, Zhaohui; Rose-John, Stefan; White, Jason C.; Nazimuddin, Farzana; Wertheim, Gerald; Levine, Bruce L.; June, Carl H.; Porter, David L.; Grupp, Stephan A.

    2017-01-01

    Chimeric antigen receptor (CAR)-modified T cells with anti-CD19 specificity are a highly effective novel immune therapy for relapsed/refractory acute lymphoblastic leukemia (ALL). Cytokine release syndrome (CRS) is the most significant and life-threatening toxicity. To improve understanding of CRS, we measured cytokines and clinical biomarkers in 51 CTL019-treated patients. Peak levels of 24 cytokines, including IFNγ, IL6, sgp130, and sIL6R in the first month after infusion were highly associated with severe CRS. Using regression modeling, we could accurately predict which patients would develop severe CRS with a signature composed of three cytokines. Results validated in an independent cohort. Changes in serum biochemical markers, including C-reactive protein and ferritin, were associated with CRS but failed to predict development of severe CRS. These comprehensive profiling data provide novel insights into CRS biology, and importantly represent the first data that can accurately predict which patients have a high probability of becoming critically ill. PMID:27076371

  2. 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

  3. 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

  4. 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

    2014-01-01

    ABSTRACT 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. IMPORTANCE 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

  5. 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

  6. Biomarker in Blood May Help Predict Recovery Time for Sports Concussions

    Science.gov (United States)

    ... in blood may help predict recovery time for sports concussions Monday, January 9, 2017 Researchers at the ... time before safely returning to play after a sports-related concussion. The study, supported by the National ...

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

    Directory of Open Access Journals (Sweden)

    Claudia Pontillo

    2017-11-01

    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.

  8. IL-10 and socs3 Are Predictive Biomarkers of Dengue Hemorrhagic Fever

    Science.gov (United States)

    Estrada-Jiménez, Tania; Sedeño-Monge, Virginia; Moreno, Margarita; Manjarrez, María del Consuelo; González-Ochoa, Guadalupe; Millán-Pérez Peña, Lourdes

    2017-01-01

    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) (p 199.8-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. PMID:28827898

  9. 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.

  10. IL-10 and socs3 Are Predictive Biomarkers of Dengue Hemorrhagic Fever.

    Science.gov (United States)

    Flores-Mendoza, Lilian Karem; Estrada-Jiménez, Tania; Sedeño-Monge, Virginia; Moreno, Margarita; Manjarrez, María Del Consuelo; González-Ochoa, Guadalupe; Millán-Pérez Peña, Lourdes; Reyes-Leyva, Julio

    2017-01-01

    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. To explore the association of cytokine and socs levels with disease severity in dengue patients. 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. 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) ( p 199.8-fold), socs1 (134 pg/ml) have the highest sensitivity and specificity to discriminate between DF and DHF. Simultaneous changes in IL-10 and socs1/socs3 could be used as prognostic biomarkers of dengue severity.

  11. 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.)

  12. 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.)