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

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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.

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

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Bindu Menon

2016-01-01

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

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

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Hongxue Sun

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

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

NARCIS (Netherlands)

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

2013-01-01

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

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

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Gratianne Rabiller

2015-10-01

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

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

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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.

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

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

2013-09-01

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

Update on Inflammatory Biomarkers and Treatments in Ischemic Stroke

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Aldo Bonaventura

2016-11-01

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

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

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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

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...

Acute ischaemic stroke prediction from physiological time series patterns

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Qing Zhang,

2013-05-01

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

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

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

2011-01-01

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

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

DEFF Research Database (Denmark)

Pusch, Gabriella; Debrabant, Birgit; Molnar, Tihamer

2015-01-01

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

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

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

2018-04-01

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

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

DEFF Research Database (Denmark)

Undén, Johan; Strandberg, Karin; Malm, Jan

2009-01-01

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

Patient-specific prediction of functional recovery after stroke.

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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.

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

Science.gov (United States)

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

2018-02-01

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

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

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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

Distinguishing prognostic and predictive biomarkers: An information theoretic approach.

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

2018-05-02

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

Prediction of Major Vascular Events after Stroke

DEFF Research Database (Denmark)

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

2014-01-01

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

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

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.

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....

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)

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.

{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.)

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

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

2017-08-01

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

Coated-platelets predict stroke at 30 days following TIA.

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

2017-07-11

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

Logical Analysis of Data (LAD model for the early diagnosis of acute ischemic stroke

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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.

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

OpenAIRE

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

2014-01-01

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

Human cervicovaginal fluid biomarkers to predict term and preterm labor

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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

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

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

2016-11-01

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

Biomarkers of Tumour Radiosensitivity and Predicting Benefit from Radiotherapy.

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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.

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...

Prognostic value of serum thioredoxin levels in ischemic stroke.

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Yu, Tieer; Zhang, Wanli; Lin, Yuanshao; Li, Qian; Xue, Jie; Cai, Zhengyi; Cheng, Yifan; Shao, Bei

2017-11-01

Thioredoxin (Trx) is one of significant antioxidative molecules to diminish oxidative stress. Current evidence suggests that Trx is a potent antioxidant with cytoprotective functions. The aim of our study was to investigate specifically the association between serum Trx levels and acute ischemic stroke (AIS) patients. 198 AIS patients and 75 controls were enrolled to the study. Serum Trx levels were measured using an enzyme-linked immunosorbent assay (ELISA). Stroke severity was assessed with the National Institutes of Health Stroke Scale (NIHSS) score on admission. Clinical endpoint was functional outcome measured by Barthel Index (BI) 3 months after admission. Multivariate binary logistic regression analyses were performed to identify predictors. We found that serum Trx levels were significantly increased in patients as compared to controls. Serum Trx was an independent biomarker to predict ischemic stroke (OR, 1.264; 95% CI, 1.04-1.537; P = 0.019). In addition, there was a negative correlation between NIHSS score at admission and serum Trx levels in cardioembolic stroke patients (r = -0.422; P = 0.013). Furthermore, higher serum Trx levels in AIS patients were associated with favorable functional outcome. Serum Trx was an independent predictor for the functional outcome (OR, 0.862; 95% CI, 0.75-0.991; P = 0.037). Serum Trx might be as a biomarker of cardioembolic stroke severity. Increased serum Trx levels could be a useful tool to predict good prognosis in patients with AIS.

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

Science.gov (United States)

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

2016-06-01

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

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

Science.gov (United States)

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

2010-01-01

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

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

NARCIS (Netherlands)

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

2013-01-01

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

Copeptin, procalcitonin and routine inflammatory markers-predictors of infection after stroke.

Directory of Open Access Journals (Sweden)

Felix Fluri

Full Text Available Early predictors for the development of stroke-associated infection may identify patients at high risk and reduce post-stroke infection and mortality.In 383 prospectively enrolled acute stroke patients we assessed time point and type of post-stroke infections (i.e. pneumonia, urinary tract infection (UTI other infection (OI. Blood samples were collected on admission, and days 1, and 3 to assess white blood cells (WBC, monocytes, C-reactive protein (CRP, procalcitonin (PCT, and copeptin. To determine the magnitude of association with the development of infections, odds ratios (OR were calculated for each prognostic blood marker. The discriminatory ability of different predictors was assessed, by calculating area under the receiver operating characteristic curves (AUC. Prognostic models including the three parameters with the best performance were identified.Of 383 patients, 66 (17.2% developed an infection after onset of stroke. WBC, CRP, copeptin and PCT were all independent predictors of any infection, pneumonia and UTI developed at least 24 hours after measurements. The combination of the biomarkers WBC, CRP and copeptin (AUC: 0.92 and WBC, CRP and PCT (AUC: 0.90 showed a better predictive accuracy concerning the development of pneumonia during hospitalization compared to each marker by itself (p-Wald <0.0001.Among ischemic stroke patients, copeptin, PCT, WBC and CRP measured on admission were predictors of infection in general, and specifically for pneumonia and UTI within 5 days after stroke. The combination of these biomarkers improved the prediction of patients who developed an infection.

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

Science.gov (United States)

Lee, Hyun Haeng; Jung, Se Hee

2017-06-01

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

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

Directory of Open Access Journals (Sweden)

Uwaezuoke SN

2017-08-01

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

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

Science.gov (United States)

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

2018-05-15

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

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

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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.

Urinary proteomics to support diagnosis of stroke.

Directory of Open Access Journals (Sweden)

Jesse Dawson

Full Text Available Accurate diagnosis in suspected ischaemic stroke can be difficult. We explored the urinary proteome in patients with stroke (n = 69, compared to controls (n = 33, and developed a biomarker model for the diagnosis of stroke. We performed capillary electrophoresis online coupled to micro-time-of-flight mass spectrometry. Potentially disease-specific peptides were identified and a classifier based on these was generated using support vector machine-based software. Candidate biomarkers were sequenced by liquid chromatography-tandem mass spectrometry. We developed two biomarker-based classifiers, employing 14 biomarkers (nominal p-value <0.004 or 35 biomarkers (nominal p-value <0.01. When tested on a blinded test set of 47 independent samples, the classification factor was significantly different between groups; for the 35 biomarker model, median value of the classifier was 0.49 (-0.30 to 1.25 in cases compared to -1.04 (IQR -1.86 to -0.09 in controls, p<0.001. The 35 biomarker classifier gave sensitivity of 56%, specificity was 93% and the AUC on ROC analysis was 0.86. This study supports the potential for urinary proteomic biomarker models to assist with the diagnosis of acute stroke in those with mild symptoms. We now plan to refine further and explore the clinical utility of such a test in large prospective clinical trials.

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

Science.gov (United States)

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

2018-03-01

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

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

Science.gov (United States)

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

2014-01-01

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

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

Science.gov (United States)

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

2015-01-01

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

Prediction of Post-stroke Falls by Quantitative Assessment of Balance

OpenAIRE

Lee, Hyun Haeng; Jung, Se Hee

2017-01-01

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

Developing and Validating a Predictive Model for Stroke Progression

Directory of Open Access Journals (Sweden)

L.E. Craig

2011-12-01

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

Developing and validating a predictive model for stroke progression.

Science.gov (United States)

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

2011-01-01

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

Developing and Validating a Predictive Model for Stroke Progression

Science.gov (United States)

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

2011-01-01

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

Predicting discharge destination after stroke: A systematic review.

Science.gov (United States)

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

2016-03-01

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

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

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

2011-01-01

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

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

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

OpenAIRE

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

2011-01-01

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

Risk score to predict gastrointestinal bleeding after acute ischemic stroke.

Science.gov (United States)

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

2014-07-25

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

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

Science.gov (United States)

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

2011-01-01

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

Frequencies of circulating B- and T-lymphocytes as indicators for stroke outcomes

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Wang Y

2017-10-01

Full Text Available Yanling Wang,1 Jihong Liu,1 Xuemei Wang,1 Zongjian Liu,2 Fengwu Li,1 Fenghua Chen,3 Xiaokun Geng,1 Zhili Ji,2 Huishan Du,1 Xiaoming Hu1,3 1Department of Neurology, China-America Institute of Neuroscience, 2Central Laboratory, Beijing Luhe Hospital, Capital Medical University, Beijing, People’s Republic of China; 3Department of Neurology, Pittsburgh Institute of Brain Disorders and Recovery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA Background: Stroke has high mortality and morbidity. Biomarkers are required for to predict stroke outcomes, which could help clinicians to provide rationale approaches for patient management. The dynamic changes in circulating immune cells have been reported in stroke patients and animal models of stroke.Aim: The aim of this study was to explore biomarkers to predict stroke outcomes by investigating the relationship between the frequencies of circulating immune cells and stroke outcomes.Methods: In all, 50 acute ischemic stroke (AIS patients were enrolled. Their blood samples were collected upon hospital admission and on day 1 and day 7 after stroke, and the leukocyte subsets were analyzed by flow cytometry. The dynamic changes in some types of immune cells in the AIS course and their correlation with clinical parameters were analyzed. Blood samples from 123 age- and gender-matched healthy subjects were used as controls.Results: The proportions of T-lymphocytes and NK cells in stroke patients were significantly lower than in healthy controls. The frequencies of B- and T-lymphocytes were negatively correlated with stroke severity at onset, including neurological deficits as assessed by National Institutes of Health Stroke Scale (NIHSS, and infarct volume as measured by the diffusion-weighted images (DWIs of magnetic resonance (MR. Logistic regression analysis showed that modified Rankin scale (mRs scores, a score system for the long-term neurological dysfunctions, were negatively correlated

The potential role of biomarkers in predicting gestational diabetes

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Huguette S Brink

2016-08-01

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

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.

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.

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

NARCIS (Netherlands)

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

2016-01-01

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

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

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

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

Science.gov (United States)

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

2016-05-01

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

Predictive Biomarkers for Bevacizumab in Anti-tumor Therapy

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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.

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.

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.

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.

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

Science.gov (United States)

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

2015-01-01

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

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...

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

Science.gov (United States)

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

2016-06-01

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

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

Directory of Open Access Journals (Sweden)

Aleksey A. Kulesh

2017-01-01

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

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.)

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.

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...

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

Science.gov (United States)

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

2010-01-01

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

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.

Stroke-Related Translational Research

Science.gov (United States)

Caplan, Louis R.; Arenillas, Juan; Cramer, Steven C.; Joutel, Anne; Lo, Eng H.; Meschia, James; Savitz, Sean; Tournier-Lasserve, Elizabeth

2013-01-01

Stroke-related translational research is multifaceted. Herein, we highlight genome-wide association studies and genetic studies of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, COL4A1 mutations, and cerebral cavernous malformations; advances in molecular biology and biomarkers; newer brain imaging research; and recovery from stroke emphasizing cell-based and other rehabilitative modalities. PMID:21555605

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

NARCIS (Netherlands)

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

2016-01-01

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

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

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.

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

Science.gov (United States)

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

2011-04-01

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

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.

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

Science.gov (United States)

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

2017-10-01

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

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.

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

Science.gov (United States)

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

2016-01-01

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

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.

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.

The NINDS Parkinson's disease biomarkers program: The Ninds Parkinson's Disease Biomarkers Program

Energy Technology Data Exchange (ETDEWEB)

Rosenthal, Liana S. [Department of Neurology, Johns Hopkins University School of Medicine, Baltimore Maryland USA; Drake, Daniel [Department of Biostatistics, Columbia University, New York New York USA; Alcalay, Roy N. [Department of Neurology, Columbia University, New York New York USA; Babcock, Debra [National Institute of Neurological Diseases and Stroke, National Institutes of Health, Bethesda Maryland USA; Bowman, F. DuBois [Department of Biostatistics, Columbia University, New York New York USA; Chen-Plotkin, Alice [Department of Neurology, University of Pennsylvania, Philadelphia Pennsylvania USA; Dawson, Ted M. [Department of Neurology, Johns Hopkins University School of Medicine, Baltimore Maryland USA; Neuroregeneration and Stem Cell Programs, Institute for Cell Engineering, Solomon H. Snyder Department of Neuroscience, Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore Maryland USA; Dewey, Richard B. [Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center, Dallas USA; German, Dwight C. [Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas USA; Huang, Xuemei [Department of Neurology, Penn State Hershey Medical Center, Hershey Pennsylvania USA; Landin, Barry [Center for Information Technology, National Institutes of Health, Bethesda Maryland USA; McAuliffe, Matthew [Center for Information Technology, National Institutes of Health, Bethesda Maryland USA; Petyuk, Vladislav A. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland Washington USA; Scherzer, Clemens R. [Department of Neurology, Brigham & Women' s Hospital, Harvard Medical School, Cambridge Massachusetts USA; Hillaire-Clarke, Coryse St. [National Institute of Neurological Diseases and Stroke, National Institutes of Health, Bethesda Maryland USA; Sieber, Beth-Anne [National Institute of Neurological Diseases and Stroke, National Institutes of Health, Bethesda Maryland USA; Sutherland, Margaret [National Institute of Neurological Diseases and Stroke, National Institutes of Health, Bethesda Maryland USA; Tarn, Chi [Coriell Institute for Medical Research, Camden New Jersey USA; West, Andrew [Department of Neurology, University of Alabama at Birmingham, Birmingham USA; Vaillancourt, David [Department of Applied Physiology and Kinesiology, University of Florida, Gainesville Florida USA; Zhang, Jing [Department of Pathology, University of Washington, Seattle Washington USA; Gwinn, Katrina [National Institute of Neurological Diseases and Stroke, National Institutes of Health, Bethesda Maryland USA

2015-10-07

Background: Neuroprotection for Parkinson Disease (PD) remains elusive. Biomarkers hold the promise of removing roadblocks to therapy development. The National Institute of Neurological Disorders and Stroke (NINDS) has therefore established the Parkinson’s Disease Biomarkers Program (PDBP) to promote discovery of biomarkers for use in phase II-III clinical trials in PD. Methods: The PDBP facilitates biomarker development to improve neuroprotective clinical trial design, essential for advancing therapeutics for PD. To date, eleven consortium projects in the PDBP are focused on the development of clinical and laboratory-based PD biomarkers for diagnosis, progression tracking, and/or the prediction of prognosis. Seven of these projects also provide detailed longitudinal data and biospecimens from PD patients and controls, as a resource for all PD researchers. Standardized operating procedures and pooled reference samples have been created in order to allow cross-project comparisons and assessment of batch effects. A web-based Data Management Resource facilitates rapid sharing of data and biosamples across the entire PD research community for additional biomarker projects. Results: Here we describe the PDBP, highlight standard operating procedures for the collection of biospecimens and data, and provide an interim report with quality control analysis on the first 1082 participants and 1033 samples with quality control analysis collected as of October 2014. Conclusions: By making samples and data available to academics and industry, encouraging the adoption of existing standards, and providing a resource which complements existing programs, the PDBP will accelerate the pace of PD biomarker research, with the goal of improving diagnostic methods and treatment.

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

Science.gov (United States)

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

2014-07-01

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

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

Science.gov (United States)

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

1996-12-01

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

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)

[Cellular microparticles, potential useful biomarkers in the identification of cerebrovascular accidents].

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Anglés-Cano, Eduardo; Vivien, Denis

2009-10-01

The clinical utility of biomarkers depends on their ability to identify high-risk individuals in order to establish preventive, diagnostic or therapeutic measures. Currently, no practical, rapid and sensitive test is available for the diagnosis of acute ischemic stroke. A number of soluble molecules have been identified that are merely associated to these cerebrovascular accidents. Despite this association not a single molecule has the characteristics of a true biomarker directly involved in the pathophysiology of ischemic stroke-none of them is organ-specific and may therefore be elevated in the context of medical comorbidities. When explored as a combination of biomarkers, e.g. matrix metalloproteinase 9, brain natriuretic protein, D-dimer, protein S100B, the question still remains whether serial biomarker analysis provides additional prognostic information. Even S100B, a glial activation protein, has a low specificity for acute ischemic stroke because it may originate from extracranial sources. Current knowledge from the field of cell-derived microparticles suggests that these membrane fragments may represent reliable biomarkers as they are cell-specific and are released early in the pathophysiological cascade of a disease. These microparticles can be found not only in the cerebrospinal fluid but also in tears and circulating blood in case of blood-brain barrier dysfunction. They represent a new challenge in stroke diagnosis and management.

Aspects correlates with Scandinavian Stroke Scale for predicting early neurological impairment

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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.

Prediction of stroke thrombolysis outcome using CT brain machine learning

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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.

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

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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.

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

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

2012-10-01

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

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

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

2015-01-01

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

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

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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.

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

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

2015-05-01

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

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

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Borlawsky Tara B

2010-10-01

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

Neuropeptide Y - an early biomarker for cerebral vasospasm after aneurysmal subarachnoid hemorrhage.

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Schebesch, Karl-Michael; Brawanski, Alexander; Bele, Sylvia; Schödel, Petra; Herbst, Andreas; Bründl, Elisabeth; Kagerbauer, Simone Maria; Martin, Jan; Lohmeier, Anette; Stoerr, Eva-Maria; Proescholdt, Martin

2013-12-01

In the human brain, the potent vasoconstrictive neuropeptide Y (NPY) is abundantly expressed. Neuropeptide Y, which is stored in perivascular nerve fibers of the cerebral arteries, regulates the cerebral vascular diameter as well as cerebral blood flow. However, the role of NPY in the pathogenesis of cerebral vasospasm (CV) related to subarachnoid hemorrhage (SAH) is unclear. We prospectively analyzed and compared the release of endogenous NPY in the cerebrospinal fluid (CSF) of 66 patients with SAH to NPY release in a control group. Additionally, we correlated the levels of NPY with CV and consecutive ischemic stroke. Sixty-six consecutive patients (40 women, 26 men; mean age 53·1 years) with aneurysmal SAH were included. In the SAH group, CSF was drawn daily from day 1 to day 10 after the onset of SAH. The CSF of 29 patients undergoing spinal anesthesia for orthopedic surgery served as control samples. The NPY levels were determined in duplicate CSF samples by means of a competitive enzyme immunoassay (EIA). The levels of NPY in CSF were correlated with the development of CV over the 10-day period after the onset of SAH and to the occurrence of consecutive ischemic stroke. To evaluate CSF NPY levels as a predictive biomarker for vasospasm, we calculated the sensitivity and specificity as well as the positive and negative predictive values. The NPY levels were significantly higher in the SAH group than in the control group (p 0·05). Patients with CV showed significantly higher NPY levels than patients without CV during the entire observation period. The NPY levels of the non-CV group dissipated over time, whereas the CV group showed continuously increasing values. The NPY levels from day 4 to 10 were significantly higher in patients with CV-related stroke than in non-stroke patients. Using 0·3 ng/ml as a cut-off value, NPY levels on day 3 predicted the occurrence of CV with a sensitivity and specificity of 82% and 72%, respectively. High NPY levels, starting on

Posterior superior temporal sulcus responses predict perceived pleasantness of skin stroking

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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.

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

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Heewon Park

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

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

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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.

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

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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...

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

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

2015-07-01

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

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

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

2015-05-01

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

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

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

2016-11-01

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

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

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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...

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

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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.

Cell-derived microparticles in atherosclerosis: biomarkers and targets for pharmacological modulation?

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Baron, Morgane; Boulanger, Chantal M; Staels, Bart; Tailleux, Anne

2012-07-01

Cardiovascular diseases remain an important cause of morbi-mortality. Atherosclerosis, which predisposes to cardiovascular disorders such as myocardial infarction and stroke, develops silently over several decades. Identification of circulating biomarkers to evaluate cardiovascular event risk and pathology prognosis is of particular importance. Microparticles (MPs) are small vesicles released from cells upon apoptosis or activation. Microparticles are present in blood of healthy individuals. Studies showing a modification of their concentrations in patients with cardiovascular risk factors and after cardiovascular events identify MPs as potential biomarkers of disease. Moreover, the pathophysiological properties of MPs may contribute to atherosclerosis development. In addition, pharmacological compounds, used in the treatment of cardiovascular disease, can reduce plasma MP concentrations. Nevertheless, numerous issues remain to be solved before MP measurement can be applied as routine biological tests to improve cardiovascular risk prediction. In particular, prospective studies to identify the predictive values of MPs in pathologies such as cardiovascular diseases are needed to demonstrate whether MPs are useful biomarkers for the early detection of the disease and its progression. © 2012 The Authors Journal of Cellular and Molecular Medicine © 2012 Foundation for Cellular and Molecular Medicine/Blackwell Publishing Ltd.

Predictive Biomarkers of Radiation Sensitivity in Rectal Cancer

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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

Endothelial dysfunction, vascular disease and stroke: the ARTICO study.

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Roquer, J; Segura, T; Serena, J; Castillo, J

2009-01-01

Endothelial dysfunction is a fundamental step in the atherosclerotic disease process. Its presence is a risk factor for the development of clinical events, and may represent a marker of atherothrombotic burden. Also, endothelial dysfunction contributes to enhanced plaque vulnerability, may trigger plaque rupture, and favors thrombus formation. The assessment of endothelial vasomotion is a useful marker of atherosclerotic vascular disease. There are different methods to assess endothelial function: endothelium-dependent vasodilatation brachial flow-mediated dilation, cerebrovascular reactivity to L-arginine, and the determination of some biomarkers such as microalbuminuria, platelet function, and C-reactive protein. Endothelial dysfunction has been observed in stroke patients and has been related to stroke physiopathology, stroke subtypes, clinical severity and outcome. Resting ankle-brachial index (ABI) is also considered an indicator of generalized atherosclerosis, and a low ABI is associated with an increase in stroke incidence in the elderly. Despite all these data, there are no studies analyzing the predictive value of ABI for new cardiovascular events in patients after suffering an acute ischemic stroke. ARTICO is an ongoing prospective, observational, multicenter study being performed in 50 Spanish hospitals. The aim of the ARTICO study is to evaluate the prognostic value of a pathological ABI (ARTICO study will increase the knowledge of patient outcome after ischemic stroke and may help to improve our ability to detect patients at high risk of stroke recurrence or major cardiovascular events. (c) 2009 S. Karger AG, Basel.

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

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

2013-01-01

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

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...

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

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

2016-01-01

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

Predicting muscle forces of individuals with hemiparesis following stroke

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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.

Phosphoproteomic biomarkers predicting histologic nonalcoholic steatohepatitis and fibrosis.

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

2010-06-04

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

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

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

2016-05-01

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

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

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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.

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

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

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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.

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

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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

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

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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.

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

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

2015-01-01

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

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.

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

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

2016-01-01

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

Advancing stroke genomic research in the age of Trans-Omics big data science: Emerging priorities and opportunities.

Science.gov (United States)

Owolabi, Mayowa; Peprah, Emmanuel; Xu, Huichun; Akinyemi, Rufus; Tiwari, Hemant K; Irvin, Marguerite R; Wahab, Kolawole Wasiu; Arnett, Donna K; Ovbiagele, Bruce

2017-11-15

We systematically reviewed the genetic variants associated with stroke in genome-wide association studies (GWAS) and examined the emerging priorities and opportunities for rapidly advancing stroke research in the era of Trans-Omics science. Using the PRISMA guideline, we searched PubMed and NHGRI- EBI GWAS catalog for stroke studies from 2007 till May 2017. We included 31 studies. The major challenge is that the few validated variants could not account for the full genetic risk of stroke and have not been translated for clinical use. None of the studies included continental Africans. Genomic study of stroke among Africans presents a unique opportunity for the discovery, validation, functional annotation, Trans-Omics study and translation of genomic determinants of stroke with implications for global populations. This is because all humans originated from Africa, a continent with a unique genomic architecture and a distinctive epidemiology of stroke; as well as substantially higher heritability and resolution of fine mapping of stroke genes. Understanding the genomic determinants of stroke and the corresponding molecular mechanisms will revolutionize the development of a new set of precise biomarkers for stroke prediction, diagnosis and prognostic estimates as well as personalized interventions for reducing the global burden of stroke. Copyright © 2017 Elsevier B.V. All rights reserved.

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

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

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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.

Association of serial biochemical markers with acute ischemic stroke: the National Institute of Neurological Disorders and Stroke recombinant tissue plasminogen activator Stroke Study.

Science.gov (United States)

Jauch, Edward C; Lindsell, Christopher; Broderick, Joseph; Fagan, Susan C; Tilley, Barbara C; Levine, Steven R

2006-10-01

found no difference in the early release of the 4 biomarkers between treatment groups. Further study will define the role of biomarkers in acute stroke management and prognostication.

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

Science.gov (United States)

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

2014-09-09

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

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

Science.gov (United States)

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

2013-01-01

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

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

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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.

Novel TIA biomarkers identified by mass spectrometry-based proteomics.

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George, Paul M; Mlynash, Michael; Adams, Christopher M; Kuo, Calvin J; Albers, Gregory W; Olivot, Jean-Marc

2015-12-01

Transient ischemic attacks remain a clinical diagnosis with significant variability between physicians. Finding reliable biomarkers to identify transient ischemic attacks would improve patient care and optimize treatment. Our aim is to identify novel serum TIA biomarkers through the use of mass spectroscopy-based proteomics. Patients with transient neurologic symptoms were prospectively enrolled. Mass spectrometry-based proteomics, an unbiased method to identify candidate proteins, was used to test the serum of the patients for biomarkers of cerebral ischemia. Three candidate proteins were found, and serum concentrations of these proteins were measured by enzyme-linked immunosorbent assay in a second cohort of prospectively enrolled patients. The Student's t-test was used for comparison. The Benjamini-Hochberg false discovery rate controlling procedure for multiple comparison adjustments determined significance for the proteomic screen. Patients with transient ischemic attacks (n = 20), minor strokes (n = 15), and controls (i.e. migraine, seizure, n = 12) were enrolled in the first cohort. Ceruloplasmin, complement component C8 gamma (C8γ), and platelet basic protein were significantly different between the ischemic group (transient ischemic attack and minor stroke) and the controls (P = 0·0001, P = 0·00027, P = 0·00105, respectively). A second cohort of patients with transient ischemic attack (n = 22), minor stroke (n = 20), and controls' (n = 12) serum was enrolled. Platelet basic protein serum concentrations were increased in the ischemic samples compared with control (for transient ischemic attack alone, P = 0·019, for the ischemic group, P = 0·046). Ceruloplasmin trended towards increased concentrations in the ischemic group (P = 0·127); no significant difference in C8γ (P = 0·44) was found. Utilizing mass spectrometry-based proteomics, platelet basic protein has been identified as a candidate serum

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

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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

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

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

2017-08-18

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

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

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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.

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

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

2014-06-01

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

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

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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.

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

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

2003-04-01

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

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

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

2016-07-01

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

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

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

2013-05-01

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

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

Directory of Open Access Journals (Sweden)

Otto Savolainen

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

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

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

2014-05-01

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

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

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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.

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

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

2016-06-15

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

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

Science.gov (United States)

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

2018-06-01

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

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.

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.

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

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

2015-12-01

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

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

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

DEFF Research Database (Denmark)

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

2017-01-01

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

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

Science.gov (United States)

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

2012-01-01

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

B-type natriuretic peptide as a marker for heart failure in patients with acute stroke.

Science.gov (United States)

Koenig, Matthew A; Puttgen, H Adrian; Prabhakaran, Vivek; Reich, Daniel; Stevens, Robert D

2007-09-01

To determine whether serum N-terminal pro-B-type natriuretic peptide (N-BNP), a biomarker of myocardial wall stress, is specific to acute heart failure (HF) in patients hospitalized with stroke. Case-control study. Tertiary hospital, Neurosciences Critical Care Unit and Stroke Unit. Consecutive patients with acute ischemic or hemorrhagic stroke who were evaluated for HF. None. Cases and controls were classified, respectively, as patients with or without HF, defined according to modified Framingham criteria. Seventy-two patients were evaluated, 39 with ischemic stroke, 22 with aneurysmal subarachnoid hemorrhage (SAH), and 11 with intracerebral hemorrhage (ICH). Thirty-four patients (47%) met criteria for HF, and 47 patients (65%) had systolic or diastolic left ventricular (LV) dysfunction on echocardiogram. Serum N-BNP was measured a median of 48 h following the onset of stroke and was increased (> 900 pg/ml) in 56 patients (78%), with higher levels in non-survivors (11898 +/- 12741 vs 4073 +/-5691; p = 0.001). In a multiple regression model, N-BNP elevation was not independently associated with HF (OR 5.4, 95% CI 0.8-36.0, p = 0.084). At a cut-off of 900 pg/ml, the sensitivity of N-BNP for HF was 94%, specificity 37%, positive predictive value (PPV) 57%, and negative predictive value (NPV) 88%. For systolic or diastolic LV dysfunction, the sensitivity of N-BNP was 89%, specificity 44%, PPV 75%, and NPV 69%. These results demonstrate that N-BNP elevation is not specific to HF or LV dysfunction in patients with acute ischemic stroke, SAH, and ICH.

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

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

2013-01-01

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

Levels of acute phase proteins remain stable after ischemic stroke

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Paik Myunghee C

2006-10-01

Full Text Available Abstract Background Inflammation and inflammatory biomarkers play an important role in atherosclerosis and cardiovascular disease. Little information is available, however, on time course of serum markers of inflammation after stroke. Methods First ischemic stroke patients ≥40 years old had levels of high-sensitivity C-reactive protein (hsCRP, serum amyloid A (SAA, and fibrinogen measured in plasma samples drawn at 1, 2, 3, 7, 14, 21 and 28 days after stroke. Levels were log-transformed as needed, and parametric and non-parametric statistical tests were used to test for evidence of a trend in levels over time. Levels of hsCRP and SAA were also compared with levels in a comparable population of stroke-free participants. Results Mean age of participants with repeated measures (n = 21 was 65.6 ± 11.6 years, and 13 (61.9% were men, and 15 (71.4% were Hispanic. Approximately 75% of patients (n = 15 had mild strokes (NIH Stroke Scale score 0–5. There was no evidence of a time trend in levels of hsCRP, SAA, or fibrinogen for any of the markers during the 28 days of follow-up. Mean log(hsCRP was 1.67 ± 1.07 mg/L (median hsCRP 6.48 mg/L among stroke participants and 1.00 ± 1.18 mg/L (median 2.82 mg/L in a group of 1176 randomly selected stroke-free participants from the same community (p = 0.0252. Conclusion Levels of hsCRP are higher in stroke patients than in stroke-free subjects. Levels of inflammatory biomarkers associated with atherosclerosis, including hsCRP, appear to be stable for at least 28 days after first ischemic stroke.

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

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

2005-10-01

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

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

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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.

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

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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.

PR Interval Prolongation and Cryptogenic Stroke: A Multicenter Retrospective Study.

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Montalvo, Mayra; Tadi, Prasanna; Merkler, Alexander; Gialdini, Gino; Martin-Schild, Sheryl; Navalkele, Digvijaya; Samai, Alyana; Nouh, Amre; Hussain, Mohammad; Goldblatt, Steven; Hemendinger, Morgan; Chu, Antony; Song, Christopher; Kamel, Hooman; Furie, Karen L; Yaghi, Shadi

2017-10-01

Atrial dysfunction or "cardiopathy" has been recently proposed as a mechanism in cryptogenic stroke. A prolonged PR interval may reflect impaired atrial conduction and thus may be a biomarker of atrial cardiopathy. We aim to compare the prevalence of PR interval prolongation in patients with cryptogenic stroke (CS) when compared with known non-cryptogenic non-cardioembolic stroke (NCNCS) subtypes. We used prospective ischemic stroke databases of 3 comprehensive stroke centers to identify patients 18 years or older with a discharge diagnosis of ischemic non-cardioembolic stroke between December 1, 2013 and August 31, 2015. The main outcome was ischemic stroke subtype (CS versus NCNCS). We compared PR intervals as a continuous and categorical variable (PR interval prolongation and CS. We identified 644 patients with ischemic non-cardioembolic stroke (224 CS and 420 NCNCS). Patients with CS were more likely to have a PR of 200 milliseconds or greater when compared with those with NCNCS (23.2% versus 13.8%, P = .009). After adjusting for factors that were significant in univariate analyses, a PR of 200 milliseconds or greater was independently associated with CS (odds ratio [OR] 1.70, 95% CI 1.08-2.70). The association was more pronounced when excluding patients on atrioventricular nodal blocking agents (OR 2.64, 95% CI 1.44-4.83). A PR of 200 milliseconds or greater is associated with CS and may be a biomarker of atrial cardiopathy in the absence of atrial fibrillation. Prospective studies are needed to confirm this association. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

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

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An, SeungHeon; Lee, YunBok; Lee, GyuChang

2014-06-01

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

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

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

2018-01-01

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

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

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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.

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

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

2016-10-21

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

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

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

2016-09-15

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

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

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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....

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

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

2013-01-01

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

DR6 as a diagnostic and predictive biomarker in adult sarcoma.

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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.

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

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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.

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

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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.

Clinical-Radiological Parameters Improve the Prediction of the Thrombolysis Time Window by Both MRI Signal Intensities and DWI-FLAIR Mismatch.

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Madai, Vince Istvan; Wood, Carla N; Galinovic, Ivana; Grittner, Ulrike; Piper, Sophie K; Revankar, Gajanan S; Martin, Steve Z; Zaro-Weber, Olivier; Moeller-Hartmann, Walter; von Samson-Himmelstjerna, Federico C; Heiss, Wolf-Dieter; Ebinger, Martin; Fiebach, Jochen B; Sobesky, Jan

2016-01-01

With regard to acute stroke, patients with unknown time from stroke onset are not eligible for thrombolysis. Quantitative diffusion weighted imaging (DWI) and fluid attenuated inversion recovery (FLAIR) MRI relative signal intensity (rSI) biomarkers have been introduced to predict eligibility for thrombolysis, but have shown heterogeneous results in the past. In the present work, we investigated whether the inclusion of easily obtainable clinical-radiological parameters would improve the prediction of the thrombolysis time window by rSIs and compared their performance to the visual DWI-FLAIR mismatch. In a retrospective study, patients from 2 centers with proven stroke with onset value/mean value of the unaffected hemisphere). Additionally, the visual DWI-FLAIR mismatch was evaluated. Prediction of the thrombolysis time window was evaluated by the area-under-the-curve (AUC) derived from receiver operating characteristic (ROC) curve analysis. Factors such as the association of age, National Institutes of Health Stroke Scale, MRI field strength, lesion size, vessel occlusion and Wahlund-Score with rSI were investigated and the models were adjusted and stratified accordingly. In 82 patients, the unadjusted rSI measures DWI-mean and -SD showed the highest AUCs (AUC 0.86-0.87). Adjustment for clinical-radiological covariates significantly improved the performance of FLAIR-mean (0.91) and DWI-SD (0.91). The best prediction results based on the AUC were found for the final stratified and adjusted models of DWI-SD (0.94) and FLAIR-mean (0.96) and a multivariable DWI-FLAIR model (0.95). The adjusted visual DWI-FLAIR mismatch did not perform in a significantly worse manner (0.89). ADC-rSIs showed fair performance in all models. Quantitative DWI and FLAIR MRI biomarkers as well as the visual DWI-FLAIR mismatch provide excellent prediction of eligibility for thrombolysis in acute stroke, when easily obtainable clinical-radiological parameters are included in the prediction

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

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

2017-07-01

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

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

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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.

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

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

2017-10-01

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

Does use of the recognition of stroke in the emergency room stroke assessment tool enhance stroke recognition by ambulance clinicians?

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Fothergill, Rachael T; Williams, Julia; Edwards, Melanie J; Russell, Ian T; Gompertz, Patrick

2013-11-01

U.K ambulance services assess patients with suspected stroke using the Face Arm Speech Test (FAST). The Recognition Of Stroke In the Emergency Room (ROSIER) tool has been shown superior to the FAST in identifying strokes in emergency departments but has not previously been tested in the ambulance setting. We investigated whether ROSIER use by ambulance clinicians can improve stroke recognition. Ambulance clinicians used the ROSIER in place of the FAST to assess patients with suspected stroke. As the ROSIER includes all FAST elements, we calculated a FAST score from the ROSIER to enable comparisons between the two tools. Ambulance clinicians' provisional stroke diagnoses using the ROSIER and calculated FAST were compared with stroke consultants' diagnosis. We used stepwise logistic regression to compare the contribution of individual ROSIER and FAST items and patient demographics to the prediction of consultants' diagnoses. Sixty-four percent of strokes and 78% of nonstrokes identified by ambulance clinicians using the ROSIER were subsequently confirmed by a stroke consultant. There was no difference in the proportion of strokes correctly detected by the ROSIER or FAST with both displaying excellent levels of sensitivity. The ROSIER detected marginally more nonstroke cases than the FAST, but both demonstrated poor specificity. Facial weakness, arm weakness, seizure activity, age, and sex predicted consultants' diagnosis of stroke. The ROSIER was not better than the FAST for prehospital recognition of stroke. A revised version of the FAST incorporating assessment of seizure activity may improve stroke identification and decision making by ambulance clinicians.

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

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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.

Frontoparietal white matter integrity predicts haptic performance in chronic stroke

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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

Frontoparietal white matter integrity predicts haptic performance in chronic stroke.

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

2016-01-01

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

Brain-Heart Interaction: Cardiac Complications After Stroke.

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Chen, Zhili; Venkat, Poornima; Seyfried, Don; Chopp, Michael; Yan, Tao; Chen, Jieli

2017-08-04

Neurocardiology is an emerging specialty that addresses the interaction between the brain and the heart, that is, the effects of cardiac injury on the brain and the effects of brain injury on the heart. This review article focuses on cardiac dysfunction in the setting of stroke such as ischemic stroke, brain hemorrhage, and subarachnoid hemorrhage. The majority of post-stroke deaths are attributed to neurological damage, and cardiovascular complications are the second leading cause of post-stroke mortality. Accumulating clinical and experimental evidence suggests a causal relationship between brain damage and heart dysfunction. Thus, it is important to determine whether cardiac dysfunction is triggered by stroke, is an unrelated complication, or is the underlying cause of stroke. Stroke-induced cardiac damage may lead to fatality or potentially lifelong cardiac problems (such as heart failure), or to mild and recoverable damage such as neurogenic stress cardiomyopathy and Takotsubo cardiomyopathy. The role of location and lateralization of brain lesions after stroke in brain-heart interaction; clinical biomarkers and manifestations of cardiac complications; and underlying mechanisms of brain-heart interaction after stroke, such as the hypothalamic-pituitary-adrenal axis; catecholamine surge; sympathetic and parasympathetic regulation; microvesicles; microRNAs; gut microbiome, immunoresponse, and systemic inflammation, are discussed. © 2017 American Heart Association, Inc.

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

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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.

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

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Edimar Cristiano Pereira

2015-01-01

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

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

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

2015-08-01

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

Role of Acute Lesion Topography in Initial Ischemic Stroke Severity and Long-Term Functional Outcomes.

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Wu, Ona; Cloonan, Lisa; Mocking, Steven J T; Bouts, Mark J R J; Copen, William A; Cougo-Pinto, Pedro T; Fitzpatrick, Kaitlin; Kanakis, Allison; Schaefer, Pamela W; Rosand, Jonathan; Furie, Karen L; Rost, Natalia S

2015-09-01

Acute infarct volume, often proposed as a biomarker for evaluating novel interventions for acute ischemic stroke, correlates only moderately with traditional clinical end points, such as the modified Rankin Scale. We hypothesized that the topography of acute stroke lesions on diffusion-weighted magnetic resonance imaging may provide further information with regard to presenting stroke severity and long-term functional outcomes. Data from a prospective stroke repository were limited to acute ischemic stroke subjects with magnetic resonance imaging completed within 48 hours from last known well, admission NIH Stroke Scale (NIHSS), and 3-to-6 months modified Rankin Scale scores. Using voxel-based lesion symptom mapping techniques, including age, sex, and diffusion-weighted magnetic resonance imaging lesion volume as covariates, statistical maps were calculated to determine the significance of lesion location for clinical outcome and admission stroke severity. Four hundred ninety subjects were analyzed. Acute stroke lesions in the left hemisphere were associated with more severe NIHSS at admission and poor modified Rankin Scale at 3 to 6 months. Specifically, injury to white matter (corona radiata, internal and external capsules, superior longitudinal fasciculus, and uncinate fasciculus), postcentral gyrus, putamen, and operculum were implicated in poor modified Rankin Scale. More severe NIHSS involved these regions, as well as the amygdala, caudate, pallidum, inferior frontal gyrus, insula, and precentral gyrus. Acute lesion topography provides important insights into anatomic correlates of admission stroke severity and poststroke outcomes. Future models that account for infarct location in addition to diffusion-weighted magnetic resonance imaging volume may improve stroke outcome prediction and identify patients likely to benefit from aggressive acute intervention and personalized rehabilitation strategies. © 2015 American Heart Association, Inc.

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

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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.

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

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

2015-11-01

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

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

NARCIS (Netherlands)

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

2017-01-01

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

DI/LC-MS/MS-Based Metabolic Profiling for Identification of Early Predictive Serum Biomarkers of Metritis in Transition Dairy Cows.

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Zhang, Guanshi; Deng, Qilan; Mandal, Rupasri; Wishart, David S; Ametaj, Burim N

2017-09-27

The objectives of this study were to evaluate alterations of metabolites in the blood of dairy cows before, during, and after diagnosis of metritis and identify predictive serum metabolite biomarkers for metritis. DI/LC-MS/MS was used to analyze serum samples collected from both healthy and metritic cows during -8, -4, disease diagnosis, +4, and +8 wks relative to parturition. Results indicated that cows with metritis experienced altered concentrations of serum amino acids, glycerophospholipids, sphingolipids, acylcarnitines, and biogenic amines during the entire experimental period. Moreover, two sets of predictive biomarker models and one set of diagnostic biomarker models for metritis were developed, and all of them showed high sensitivity and specificity (e.g., high AUC values by the ROC curve evaluation), which indicate that serum metabolites identified have pretty accurate predictive, diagnostic, and prognostic abilities for metritis in transition dairy cows.

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

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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

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

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.

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

DEFF Research Database (Denmark)

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

2015-01-01

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

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.)

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

International Nuclear Information System (INIS)

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

2015-01-01

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

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

Science.gov (United States)

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

2017-05-31

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

Correlation of the L-Arginine Pathway with Thrombo-Inflammation May Contribute to the Outcome of Acute Ischemic Stroke

DEFF Research Database (Denmark)

Molnar, Tihamer; Pusch, Gabriella; Nagy, Lajos

2016-01-01

BACKGROUND: Immune responses contribute to secondary injury after acute ischemic stroke (AIS), and metabolites of the L-arginine pathway are associated with stroke outcome. Here, we analyzed the relationship of the L-arginine pathway with thrombo-inflammatory biomarkers in AIS and their additive...... and independent associations to outcome. METHODS: Serial changes in P-selectin, tPA, MCP-1, sCD40L, IL-6, IL-8, L-arginine, and asymmetric and symmetric dimethylarginine (ADMA, SDMA) were investigated in 55 patients with AIS and without infection within 6 and 72 hours after stroke onset. Outcomes were assessed...... as National Institutes of Health Stroke Scale (NIHSS) worsening by 24 hours, poststroke infection, and death by 1 month. RESULTS: Serum levels of L-arginine showed negative correlation, whereas ADMA and SDMA showed positive correlation with thrombo-inflammatory biomarkers in the hyperacute phase. Most...

A study on the influence of corona on currents and electromagnetic fields predicted by a nonlinear lightning return-stroke model

Science.gov (United States)

De Conti, Alberto; Silveira, Fernando H.; Visacro, Silvério

2014-05-01

This paper investigates the influence of corona on currents and electromagnetic fields predicted by a return-stroke model that represents the lightning channel as a nonuniform transmission line with time-varying (nonlinear) resistance. The corona model used in this paper allows the calculation of corona currents as a function of the radial electric field in the vicinity of the channel. A parametric study is presented to investigate the influence of corona parameters, such as the breakdown electric field and the critical electric field for the stable propagation of streamers, on predicted currents and electromagnetic fields. The results show that, regardless of the assumed corona parameters, the incorporation of corona into the nonuniform and nonlinear transmission line model under investigation modifies the model predictions so that they consistently reproduce most of the typical features of experimentally observed lightning electromagnetic fields and return-stroke speed profiles. In particular, it is shown that the proposed model leads to close vertical electric fields presenting waveforms, amplitudes, and decay with distance in good agreement with dart leader electric field changes measured in triggered lightning experiments. A comparison with popular engineering return-stroke models further confirms the model's ability to predict consistent electric field waveforms in the close vicinity of the channel. Some differences observed in the field amplitudes calculated with the different models can be related to the fact that current distortion, while present in the proposed model, is ultimately neglected in the considered engineering return-stroke models.

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.

Independent Prognostic Value of Stroke Volume Index in Patients With Immunoglobulin Light Chain Amyloidosis.

Science.gov (United States)

2018-05-01

Heart involvement is the most important prognostic determinant in AL amyloidosis patients. Echocardiography is a cornerstone for the diagnosis and provides important prognostic information. We studied 754 patients with AL amyloidosis who underwent echocardiographic assessment at the Mayo Clinic, including a Doppler-derived measurement of stroke volume (SV) within 30 days of their diagnosis to explore the prognostic role of echocardiographic variables in the context of a well-established soluble cardiac biomarker staging system. Reproducibility of SV, myocardial contraction fraction, and left ventricular strain was assessed in a separate, yet comparable, study cohort of 150 patients from the Pavia Amyloidosis Center. The echocardiographic measures most predictive for overall survival were SV index <33 mL/min, myocardial contraction fraction <34%, and cardiac index <2.4 L/min/m 2 with respective hazard ratios (95% confidence intervals) of 2.95 (2.37-3.66), 2.36 (1.96-2.85), and 2.32 (1.91-2.80). For the subset that had left ventricular strain performed, the prognostic cut point was -14% (hazard ratios, 2.70; 95% confidence intervals, 1.84-3.96). Each parameter was independent of systolic blood pressure, Mayo staging system (NT-proBNP [N-terminal pro-B-type natriuretic peptide] and troponin), and ejection fraction on multivariable analysis. Simple predictive models for survival, including biomarker staging along with SV index or left ventricular strain, were generated. SV index prognostic performance was similar to left ventricular strain in predicting survival in AL amyloidosis, independently of biomarker staging. Because SV index is routinely calculated and widely available, it could serve as the preferred echocardiographic measure to predict outcomes in AL amyloidosis patients. © 2018 American Heart Association, Inc.

Predicting Age Using Neuroimaging: Innovative Brain Ageing Biomarkers.

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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.

Histopathologic composition of cerebral thrombi of acute stroke patients is correlated with stroke subtype and thrombus attenuation.

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Joris M Niesten

Full Text Available INTRODUCTION: We related composition of cerebral thrombi to stroke subtype and attenuation on non-contrast CT (NCCT to gain more insight in etiopathogenesis and to validate thrombus attenuation as a new imaging biomarker for acute stroke. METHODS: We histopathologically investigated 22 thrombi retrieved after mechanical thrombectomy in acute stroke patients. First, thrombi were classified as fresh, lytic or organized. Second, percentages of red blood cells (RBCs, platelets and fibrin and number of red, white (respectively RBCs or platelets outnumbering other components with ≥ 15% or mixed thrombi were compared between large artery atherosclerosis (LAA, cardioembolism, dissection and unknown subtype. Third, correlation between attenuation and RBCs, platelets and fibrin was calculated using Pearson's correlation coefficients (r. RESULTS: Thrombi were fresh in 73% (n = 16, lytic in 18% (n = 4 and organized in 9% (n = 2. The stroke cause was LAA in eight (36%, cardioembolism in six (27%, dissection in three (14%, and unknown in five (23% patients. LAA thrombi showed the highest percentage RBCs (median 50 (range 35-90, followed by dissection (35 (20-40, p = 0.05, cardioembolism (35 (5-45, p = 0.013 and unknown subtype (25 (2-40, p = 0.006. No differences in platelets (p = 0.16 and fibrin (p = 0.52 between subtypes were found. LAA thrombi were classified as red or mixed (both n = 4, cardioembolisms as mixed (n = 5 or white (n = 1 and dissection as mixed (n = 3. There was a moderate positive correlation between attenuation and RBCs (r = 0.401, p = 0.049, and weak negative correlations with platelets (r = -0.368, p = 0.09 and fibrin (r = -0.073, p = 0.75. CONCLUSIONS: The majority of cerebral thrombi is fresh. There are no differences in age of thrombi between subtypes. LAA thrombi have highest percentages RBCs, cardioembolism and unknown subtype lowest. No relationship exists between subtype and platelets or fibrin percentages. We found a

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

Science.gov (United States)

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

2012-05-01

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

Altered Coupling between Motion-Related Activation and Resting-State Brain Activity in the Ipsilesional Sensorimotor Cortex after Cerebral Stroke

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Jianping Hu

2017-07-01

outcome of hand motion performance in the early chronic stages. Couplings between RSFC and motion-related activation were dynamically changed with stroke progression, which suggested changes in the prediction of resting-state brain activity for task-evoked brain activity in different pathological states. The changes in coupling strength between these two types of brain activity implicate a reparative mechanism of brain injury and may represent a biomarker for predicting motor recovery in cerebral stroke.

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

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

2011-01-01

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

Timing of oral anticoagulant therapy in acute ischemic stroke with atrial fibrillation: study protocol for a registry-based randomised controlled trial.

Science.gov (United States)

Åsberg, Signild; Hijazi, Ziad; Norrving, Bo; Terént, Andreas; Öhagen, Patrik; Oldgren, Jonas

2017-12-02

Oral anticoagulation therapy is recommended for the prevention of recurrent ischemic stroke in patients with atrial fibrillation (AF). Current guidelines do not provide evidence-based recommendations on optimal time-point to start anticoagulation therapy after an acute ischemic stroke. Non-vitamin K antagonist oral anticoagulants (NOACs) may offer advantages compared to warfarin because of faster and more predictable onset of action and potentially a lower risk of intracerebral haemorrhage also in the acute phase after an ischemic stroke. The TIMING study aims to establish the efficacy and safety of early vs delayed initiation of NOACs in patients with acute ischemic stroke and AF. The TIMING study is a national, investigator-led, registry-based, multicentre, open-label, randomised controlled study. The Swedish Stroke Register is used for enrolment, randomisation and follow-up of 3000 patients, who are randomised (1:1) within 72 h from ischemic stroke onset to either early (≤ 4 days) or delayed (≥ 5-10 days) start of NOAC therapy. The primary outcome is the composite of recurrent ischemic stroke, symptomatic intracerebral haemorrhage, or all-cause mortality within 90 days after randomisation. Secondary outcomes include: individual components of the primary outcome at 90 and 365 days; major haemorrhagic events; functional outcome by the modified Rankin Scale at 90 days; and health economics. In an optional biomarker sub-study, blood samples will be collected after randomisation from approximately half of the patients for central analysis of cardiovascular biomarkers after study completion. The study is funded by the Swedish Medical Research Council. Enrolment of patients started in April 2017. The TIMING study addresses the ongoing clinical dilemma of when to start NOAC after an acute ischemic stroke in patients with AF. By the inclusion of a randomisation module within the Swedish Stroke Register, the advantages of a prospective randomised study design

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

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

2017-09-07

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

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

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

2011-01-01

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

Biomarkers in Airway Diseases

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Janice M Leung

2013-01-01

Full Text Available The inherent limitations of spirometry and clinical history have prompted clinicians and scientists to search for surrogate markers of airway diseases. Although few biomarkers have been widely accepted into the clinical armamentarium, the authors explore three sources of biomarkers that have shown promise as indicators of disease severity and treatment response. In asthma, exhaled nitric oxide measurements can predict steroid responsiveness and sputum eosinophil counts have been used to titrate anti-inflammatory therapies. In chronic obstructive pulmonary disease, inflammatory plasma biomarkers, such as fibrinogen, club cell secretory protein-16 and surfactant protein D, can denote greater severity and predict the risk of exacerbations. While the multitude of disease phenotypes in respiratory medicine make biomarker development especially challenging, these three may soon play key roles in the diagnosis and management of airway diseases.

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

Science.gov (United States)

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

2014-01-01

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

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

Directory of Open Access Journals (Sweden)

Guillaume Turc

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

DNA Methylation Biomarkers: Cancer and Beyond

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Thomas Mikeska

2014-09-01

Full Text Available Biomarkers are naturally-occurring characteristics by which a particular pathological process or disease can be identified or monitored. They can reflect past environmental exposures, predict disease onset or course, or determine a patient’s response to therapy. Epigenetic changes are such characteristics, with most epigenetic biomarkers discovered to date based on the epigenetic mark of DNA methylation. Many tissue types are suitable for the discovery of DNA methylation biomarkers including cell-based samples such as blood and tumor material and cell-free DNA samples such as plasma. DNA methylation biomarkers with diagnostic, prognostic and predictive power are already in clinical trials or in a clinical setting for cancer. Outside cancer, strong evidence that complex disease originates in early life is opening up exciting new avenues for the detection of DNA methylation biomarkers for adverse early life environment and for estimation of future disease risk. However, there are a number of limitations to overcome before such biomarkers reach the clinic. Nevertheless, DNA methylation biomarkers have great potential to contribute to personalized medicine throughout life. We review the current state of play for DNA methylation biomarkers, discuss the barriers that must be crossed on the way to implementation in a clinical setting, and predict their future use for human disease.

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.

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

Science.gov (United States)

Moorman, Anthony V.

2016-01-01

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

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

OpenAIRE

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

2017-01-01

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

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

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Dang My Nhi

2016-02-01

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

[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.

Stroke Location Is an Independent Predictor of Cognitive Outcome.

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Munsch, Fanny; Sagnier, Sharmila; Asselineau, Julien; Bigourdan, Antoine; Guttmann, Charles R; Debruxelles, Sabrina; Poli, Mathilde; Renou, Pauline; Perez, Paul; Dousset, Vincent; Sibon, Igor; Tourdias, Thomas

2016-01-01

On top of functional outcome, accurate prediction of cognitive outcome for stroke patients is an unmet need with major implications for clinical management. We investigated whether stroke location may contribute independent prognostic value to multifactorial predictive models of functional and cognitive outcomes. Four hundred twenty-eight consecutive patients with ischemic stroke were prospectively assessed with magnetic resonance imaging at 24 to 72 hours and at 3 months for functional outcome using the modified Rankin Scale and cognitive outcome using the Montreal Cognitive Assessment (MoCA). Statistical maps of functional and cognitive eloquent regions were derived from the first 215 patients (development sample) using voxel-based lesion-symptom mapping. We used multivariate logistic regression models to study the influence of stroke location (number of eloquent voxels from voxel-based lesion-symptom mapping maps), age, initial National Institutes of Health Stroke Scale and stroke volume on modified Rankin Scale and MoCA. The second part of our cohort was used as an independent replication sample. In univariate analyses, stroke location, age, initial National Institutes of Health Stroke Scale, and stroke volume were all predictive of poor modified Rankin Scale and MoCA. In multivariable analyses, stroke location remained the strongest independent predictor of MoCA and significantly improved the prediction compared with using only age, initial National Institutes of Health Stroke Scale, and stroke volume (area under the curve increased from 0.697-0.771; difference=0.073; 95% confidence interval, 0.008-0.155). In contrast, stroke location did not persist as independent predictor of modified Rankin Scale that was mainly driven by initial National Institutes of Health Stroke Scale (area under the curve going from 0.840 to 0.835). Similar results were obtained in the replication sample. Stroke location is an independent predictor of cognitive outcome (MoCA) at 3

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

NARCIS (Netherlands)

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

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

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

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Jiangang Liu

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

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

Science.gov (United States)

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

2017-01-01

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

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

OpenAIRE

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

2014-01-01

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

Registration of acute stroke

DEFF Research Database (Denmark)

Wildenschild, Cathrine; Mehnert, Frank; Thomsen, Reimar Wernich

2014-01-01

BACKGROUND: The validity of the registration of patients in stroke-specific registries has seldom been investigated, nor compared with administrative hospital discharge registries. The objective of this study was to examine the validity of the registration of patients in a stroke-specific registry...... (The Danish Stroke Registry [DSR]) and a hospital discharge registry (The Danish National Patient Registry [DNRP]). METHODS: Assuming that all patients with stroke were registered in either the DSR, DNRP or both, we first identified a sample of 75 patients registered with stroke in 2009; 25 patients...... in the DSR, 25 patients in the DNRP, and 25 patients registered in both data sources. Using the medical record as a gold standard, we then estimated the sensitivity and positive predictive value of a stroke diagnosis in the DSR and the DNRP. Secondly, we reviewed 160 medical records for all potential stroke...

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...

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

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Bradley S Quon

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

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

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

2015-01-01

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

Measuring of vertical stroke Vub vertical stroke in the forthcoming decade

International Nuclear Information System (INIS)

Kim, C.S.

1997-01-01

I first introduce the importance of measuring V ub precisely. Then, from a theoretician's point of view, I review (a) past history, (b) present trials, and (c) possible future alternatives on measuring vertical stroke V ub vertical stroke and/or vertical stroke V ub /V cb vertical stroke. As of my main topic, I introduce a model-independent method, which predicts Γ(B→X u lν)/Γ(B→X c lν)≡(γ u /γ c ) x vertical stroke V ub /V cb vertical stroke 2 ≅(1.83±0.28) x vertical stroke V ub /V cb vertical stroke 2 and vertical stroke V ub /V cb vertical stroke ≡(γ c /γ u ) 1/2 x [B(B→X u lν)/B(B→ X c lν]) 1/2 ≅(0.74±0.06) x [B(B→X u lν/)B(B→X c lν)] 1/2 , based on the heavy quark effective theory I also explore the possible experimental options to separate B→X u lν from the dominant B→X c lν: the measurement of inclusive hadronic invariant mass distributions, and the 'D-π' (and 'K-π') separation conditions I also clarify the relevant experimental backgrounds. (orig.)

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

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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.

Stroke genetics: prospects for personalized medicine

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Markus Hugh S

2012-09-01

Full Text Available Abstract Epidemiologic evidence supports a genetic predisposition to stroke. Recent advances, primarily using the genome-wide association study approach, are transforming what we know about the genetics of multifactorial stroke, and are identifying novel stroke genes. The current findings are consistent with different stroke subtypes having different genetic architecture. These discoveries may identify novel pathways involved in stroke pathogenesis, and suggest new treatment approaches. However, the already identified genetic variants explain only a small proportion of overall stroke risk, and therefore are not currently useful in predicting risk for the individual patient. Such risk prediction may become a reality as identification of a greater number of stroke risk variants that explain the majority of genetic risk proceeds, and perhaps when information on rare variants, identified by whole-genome sequencing, is also incorporated into risk algorithms. Pharmacogenomics may offer the potential for earlier implementation of 'personalized genetic' medicine. Genetic variants affecting clopidogrel and warfarin metabolism may identify non-responders and reduce side-effects, but these approaches have not yet been widely adopted in clinical practice.

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

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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.

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

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

2018-05-09

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

Transthyretin Concentrations in Acute Stroke Patients Predict Convalescent Rehabilitation.

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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.

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

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Andrés Quesada

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

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

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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

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.

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

DEFF Research Database (Denmark)

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

2012-01-01

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

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

Science.gov (United States)

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

2017-07-01

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

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

Science.gov (United States)

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

2011-01-01

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

Stroke Rehabilitation.

Science.gov (United States)

Belagaje, Samir R

2017-02-01

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

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

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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

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

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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

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

OpenAIRE

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

2014-01-01

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

Risk prediction of major complications in individuals with diabetes: the Atherosclerosis Risk in Communities Study.

Science.gov (United States)

Parrinello, C M; Matsushita, K; Woodward, M; Wagenknecht, L E; Coresh, J; Selvin, E

2016-09-01

To develop a prediction equation for 10-year risk of a combined endpoint (incident coronary heart disease, stroke, heart failure, chronic kidney disease, lower extremity hospitalizations) in people with diabetes, using demographic and clinical information, and a panel of traditional and non-traditional biomarkers. We included in the study 654 participants in the Atherosclerosis Risk in Communities (ARIC) study, a prospective cohort study, with diagnosed diabetes (visit 2; 1990-1992). Models included self-reported variables (Model 1), clinical measurements (Model 2), and glycated haemoglobin (Model 3). Model 4 tested the addition of 12 blood-based biomarkers. We compared models using prediction and discrimination statistics. Successive stages of model development improved risk prediction. The C-statistics (95% confidence intervals) of models 1, 2, and 3 were 0.667 (0.64, 0.70), 0.683 (0.65, 0.71), and 0.694 (0.66, 0.72), respectively (p < 0.05 for differences). The addition of three traditional and non-traditional biomarkers [β-2 microglobulin, creatinine-based estimated glomerular filtration rate (eGFR), and cystatin C-based eGFR] to Model 3 significantly improved discrimination (C-statistic = 0.716; p = 0.003) and accuracy of 10-year risk prediction for major complications in people with diabetes (midpoint percentiles of lowest and highest deciles of predicted risk changed from 18-68% to 12-87%). These biomarkers, particularly those of kidney filtration, may help distinguish between people at low versus high risk of long-term major complications. © 2016 John Wiley & Sons Ltd.

Predictive cytogenetic biomarkers for colorectal neoplasia in medium risk patients.

Science.gov (United States)

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

2015-01-01

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

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

Science.gov (United States)

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

2017-02-01

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

A statistical approach to evaluate the performance of cardiac biomarkers in predicting death due to acute myocardial infarction: time-dependent ROC curve

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Karaismailoğlu, Eda; Dikmen, Zeliha Günnur; Akbıyık, Filiz; Karaağaoğlu, Ahmet Ergun

2018-04-30

Background/aim: Myoglobin, cardiac troponin T, B-type natriuretic peptide (BNP), and creatine kinase isoenzyme MB (CK-MB) are frequently used biomarkers for evaluating risk of patients admitted to an emergency department with chest pain. Recently, time- dependent receiver operating characteristic (ROC) analysis has been used to evaluate the predictive power of biomarkers where disease status can change over time. We aimed to determine the best set of biomarkers that estimate cardiac death during follow-up time. We also obtained optimal cut-off values of these biomarkers, which differentiates between patients with and without risk of death. A web tool was developed to estimate time intervals in risk. Materials and methods: A total of 410 patients admitted to the emergency department with chest pain and shortness of breath were included. Cox regression analysis was used to determine an optimal set of biomarkers that can be used for estimating cardiac death and to combine the significant biomarkers. Time-dependent ROC analysis was performed for evaluating performances of significant biomarkers and a combined biomarker during 240 h. The bootstrap method was used to compare statistical significance and the Youden index was used to determine optimal cut-off values. Results : Myoglobin and BNP were significant by multivariate Cox regression analysis. Areas under the time-dependent ROC curves of myoglobin and BNP were about 0.80 during 240 h, and that of the combined biomarker (myoglobin + BNP) increased to 0.90 during the first 180 h. Conclusion: Although myoglobin is not clinically specific to a cardiac event, in our study both myoglobin and BNP were found to be statistically significant for estimating cardiac death. Using this combined biomarker may increase the power of prediction. Our web tool can be useful for evaluating the risk status of new patients and helping clinicians in making decisions.

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

Ischemic Stroke Profile, Risk Factors, and Outcomes in India: The Indo-US Collaborative Stroke Project.

Science.gov (United States)

Sylaja, P N; Pandian, Jeyaraj Durai; Kaul, Subhash; Srivastava, M V Padma; Khurana, Dheeraj; Schwamm, Lee H; Kesav, Praveen; Arora, Deepti; Pannu, Aman; Thankachan, Tijy K; Singhal, Aneesh B

2018-01-01

The Indo-US Collaborative Stroke Project was designed to characterize ischemic stroke across 5 high-volume academic tertiary hospitals in India. From January 2012 to August 2014, research coordinators and physician coinvestigators prospectively collected data on 2066 patients with ischemic stroke admitted <2 weeks after onset. Investigator training and supervision and data monitoring were conducted by the US site (Massachusetts General Hospital, Boston). The mean age was 58.3±14.7 years, 67.2% men. The median admission National Institutes of Health Stroke Scale score was 10 (interquartile range, 5-15) and 24.5% had National Institutes of Health Stroke Scale ≥16. Hypertension (60.8%), diabetes mellitus (35.7%), and tobacco use (32.2%, including bidi/smokeless tobacco) were common risk factors. Only 4% had atrial fibrillation. All patients underwent computed tomography or magnetic resonance imaging; 81% had cerebrovascular imaging. Stroke etiologic subtypes were large artery (29.9%), cardiac (24.9%), small artery (14.2%), other definite (3.4%), and undetermined (27.6%, including 6.7% with incomplete evaluation). Intravenous or intra-arterial thrombolysis was administered in 13%. In-hospital mortality was 7.9%, and 48% achieved modified Rankin Scale score 0 to 2 at 90 days. On multivariate analysis, diabetes mellitus predicted poor 3-month outcome and younger age, lower admission National Institutes of Health Stroke Scale and small-artery etiology predicted excellent 3-month outcome. These comprehensive and novel clinical imaging data will prove useful in refining stroke guidelines and advancing stroke care in India. © 2017 American Heart Association, Inc.

Prevalence of Fabry disease in young patients with cryptogenic ischemic stroke.

Science.gov (United States)

Dubuc, Véronique; Moore, David F; Gioia, Laura C; Saposnik, Gustavo; Selchen, Daniel; Lanthier, Sylvain

2013-11-01

A German study diagnosed 4% of young cryptogenic ischemic stroke patients with Fabry disease, an X-linked lysosomal storage disease caused by mutations in the alpha-galactosidase A (α-GAL-A) gene resulting in an accumulation of glycosphingolipids. A lower prevalence was found in other geographic regions. To determine the prevalence of Fabry disease in a Canadian population of young cryptogenic ischemic stroke patients. Patients with cryptogenic ischemic stroke at age 16-55 were retrospectively identified in our institutional stroke database and underwent a focused clinical evaluation. We sequenced the α-GAL-A gene and measured the levels of blood globotriaosylsphingosine in subjects with mutations of undetermined pathogenicity. Fabry disease was diagnosed in patients with pathogenic mutations or increased levels of blood globotriaosylsphingosine. Ninety-three of 100 study subjects had normal α-GAL-A gene polymorphisms. Seven had mutations of undetermined pathogenicity, including one with increased globotriaosylsphingosine (prevalence, 1%; 95% confidence interval, ischemic stroke presentation as the first clinical manifestation of Fabry disease. Both Fabry patients experienced recurrent ischemic stroke. Fabry disease accounts for a small proportion of young Canadians with cryptogenic ischemic stroke. Identification of Fabry biomarkers remains a research priority to delineate stroke patients disserving routine screening. Copyright © 2013 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Transcranial magnetic stimulation (TMS) in stroke: Ready for clinical practice?

Science.gov (United States)

Smith, Marie-Claire; Stinear, Cathy M

2016-09-01

The use of transcranial magnetic stimulation (TMS) in stroke research has increased dramatically over the last decade with two emerging and potentially useful functions identified. Firstly, the use of single pulse TMS as a tool for predicting recovery of motor function after stroke, and secondly, the use of repetitive TMS (rTMS) as a treatment adjunct aimed at modifying the excitability of the motor cortex in preparation for rehabilitation. This review discusses recent advances in the use of TMS in both prediction and treatment after stroke. Prediction of recovery after stroke is a complex process and the use of TMS alone is not sufficient to provide accurate prediction for an individual after stroke. However, when applied in conjunction with other tools such as clinical assessment and MRI, accuracy of prediction using TMS is increased. rTMS temporarily modulates cortical excitability after stroke. Very few rTMS studies are completed in the acute or sub-acute stages after stroke and the translation of altered cortical excitability into gains in motor function are modest, with little evidence of long term effects. Although gains have been made in both of these areas, further investigation is needed before these techniques can be applied in routine clinical care. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

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.

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

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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.

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

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Seyed Ali Roudbary

2011-03-01

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

Early warning score predicts acute mortality in stroke patients

DEFF Research Database (Denmark)

Liljehult, J; Christensen, Thomas

2016-01-01

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

Computed Tomography Perfusion Alberta Stroke Program Early Computed Tomography Score Is Associated with Hemorrhagic Transformation after Acute Cardioembolic Stroke

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Lan Liu

2017-11-01

Full Text Available Alberta Stroke Program Early Computed Tomography (CT score (ASPECTS has been applied to CT perfusion (CTP with good interrater agreement to predict early ischemic stroke, and it can be useful in decision making in acute ischemic stroke. The aim of the present study was to assess the predictive value of CTP ASPECTS of hemorrhagic transformation (HT in acute cardioembolic stroke. This is a single-enter, retrospective study. All patients hospitalized with acute cardioembolic stroke from January 2008 to September 2013 were included. ASPECTS of baseline non-contrast CT, CTP maps of cerebral blood volume (CBV, cerebral blood flow, and mean transit time were collected from 52 consecutive patients with less than 12-h anterior circulation ischemic stroke. MRI scan was performed within 72 h of symptom onset after index stroke including T2*-weighted gradient echo to identify HT. For bleeding risk assessment, CTP and diffusion-weighted imaging ASPECTS were categorized into 0–7 or 8–10. Baseline characteristics, ASPCETS scores and HT were compared. Eighteen (34.6% patients had HT and four (7.7% developed symptomatic HT. On univariate analysis, the proportion of patients with CBV-ASPECTS 0–7 was significantly higher in HT patients as compared to patients without HT (44 versus 9%, P = 0.005. CBV ASPECTS 0–7 remained independent prognostic factors for HT after adjustment for clinical baseline variables. CBV ASPECTS could be of value to predict HT risk after acute cardioembolic stroke and may be a quick risk assessment approach before reperfusion therapy.

Enlarged pulmonary artery is predicted by vascular injury biomarkers and is associated with WTC-Lung Injury in exposed fire fighters: a case–control study

Science.gov (United States)

Schenck, Edward J; Echevarria, Ghislaine C; Girvin, Francis G; Kwon, Sophia; Comfort, Ashley L; Rom, William N; Prezant, David J; Weiden, Michael D; Nolan, Anna

2014-01-01

Objectives We hypothesise that there is an association between an elevated pulmonary artery/aorta (PA/A) and World Trade Center-Lung Injury (WTC-LI). We assessed if serum vascular disease biomarkers were predictive of an elevated PA/A. Design Retrospective case-cohort analysis of thoracic CT scans of WTC-exposed firefighters who were symptomatic between 9/12/2001 and 3/10/2008. Quantification of vascular-associated biomarkers from serum collected within 200 days of exposure. Setting Urban tertiary care centre and occupational healthcare centre. Participants Male never-smoking firefighters with accurate pre-9/11 forced expiratory volume in 1 s (FEV1) ≥75%, serum sampled ≤200 days of exposure was the baseline cohort (n=801). A subcohort (n=97) with available CT scans and serum biomarkers was identified. WTC-LI was defined as FEV1≤77% at the subspecialty pulmonary evaluation (n=34) and compared with controls (n=63) to determine the associated PA/A ratio. The subcohort was restratified based on PA/A≥0.92 (n=38) and PA/A<0.92(n=59) to determine serum vascular biomarkers that were predictive of this vasculopathy. Outcome measures The primary outcome of this study was to identify a PA/A ratio in a cohort of individuals exposed to WTC dust that was associated with WTC-LI. The secondary outcome was to identify serum biomarkers predictive of the PA/A ratio using logistic regression. Results PA/A≥0.92 was associated with WTC-LI, OR of 4.02 (95% CI 1.21 to 13.41; p=0.023) when adjusted for exposure, body mass index and age at CT. Elevated macrophage derived chemokine and soluble endothelial selectin were predictive of PA/A≥0.92, (OR, 95% CI 2.08, 1.05 to 4.11, p=0.036; 1.33, 1.06 to 1.68, p=0.016, respectively), while the increased total plasminogen activator inhibitor 1 was predictive of not having PA/A≥0.92 (OR 0.88, 0.79 to 0.98; p=0.024). Conclusions Elevated PA/A was associated with WTC-LI. Development of an elevated PA/A was predicted by biomarkers of

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.

Prediabetes is associated with post-stroke cognitive impairment in ischaemic stroke patients.

Science.gov (United States)

Wang, Qiongzhang; Zhao, Kai; Cai, Yan; Tu, Xinjie; Liu, Yuntao; He, Jincai

2018-05-15

Diabetes mellitus is associated with post-stroke cognitive impairment. To the best of our knowledge, no study has explored the relationship between prediabetes and post-stroke cognitive impairment. The purpose of this study is to explore the association between prediabetes and cognitive impairment in ischaemic stroke patients at 1 month. Two hundred one acute ischaemic stroke patients were consecutively recruited within the first 24 h after admission and were followed up for 1 month. Patients were divided into a diabetes mellitus group, prediabetes group and non-diabetes mellitus group by fasting glucose levels, 2-h postprandial blood glucose levels and glycosylated haemoglobin levels at admission. Cognitive function was evaluated by the Mini-Mental State Examination at 1 month after stroke. The prediabetes group had a higher risk of post-stroke cognitive impairment than the non-diabetes group (35.7% vs. 18.1%, χ 2  = 4.252, P = .039). In logistical analyses, prediabetes was associated with post-stroke cognitive impairment after adjusting for potential confounding factors (odds ratio 3.062, 95% confidence interval 1.130-8.299, P = .028). Our findings show that prediabetes is associated with post-stroke cognitive impairment and may predict its development at 1 month post-stroke. Copyright © 2018 Elsevier B.V. All rights reserved.

Recovery of slow-5 oscillations in a longitudinal study of ischemic stroke patients.

Science.gov (United States)

La, C; Nair, V A; Mossahebi, P; Stamm, J; Birn, R; Meyerand, M E; Prabhakaran, V

2016-01-01

Functional networks in resting-state fMRI are identified by characteristics of their intrinsic low-frequency oscillations, more specifically in terms of their synchronicity. With advanced aging and in clinical populations, this synchronicity among functionally linked regions is known to decrease and become disrupted, which may be associated with observed cognitive and behavioral changes. Previous work from our group has revealed that oscillations within the slow-5 frequency range (0.01-0.027 Hz) are particularly susceptible to disruptions in aging and following a stroke. In this study, we characterized longitudinally the changes in the slow-5 oscillations in stroke patients across two different time-points. We followed a group of ischemic stroke patients (n = 20) and another group of healthy older adults (n = 14) over two visits separated by a minimum of three months (average of 9 months). For the stroke patients, one visit occurred in their subacute window (10 days to 6 months after stroke onset), the other took place in their chronic window (> 6 months after stroke). Using a mid-order group ICA method on 10-minutes eyes-closed resting-state fMRI data, we assessed the frequency distributions of a component's representative time-courses for differences in regards to slow-5 spectral power. First, our stroke patients, in their subacute stage, exhibited lower amplitude slow-5 oscillations in comparison to their healthy counterparts. Second, over time in their chronic stage, those same patients showed a recovery of those oscillations, reaching near equivalence to the healthy older adult group. Our results indicate the possibility of an eventual recovery of those initially disrupted network oscillations to a near-normal level, providing potentially a biomarker for stroke recovery of the cortical system. This finding opens new avenues in infra-slow oscillation research and could serve as a useful biomarker in future treatments aimed at recovery.

Recovery of slow-5 oscillations in a longitudinal study of ischemic stroke patients

Directory of Open Access Journals (Sweden)

C. La

2016-01-01

Full Text Available Functional networks in resting-state fMRI are identified by characteristics of their intrinsic low-frequency oscillations, more specifically in terms of their synchronicity. With advanced aging and in clinical populations, this synchronicity among functionally linked regions is known to decrease and become disrupted, which may be associated with observed cognitive and behavioral changes. Previous work from our group has revealed that oscillations within the slow-5 frequency range (0.01–0.027 Hz are particularly susceptible to disruptions in aging and following a stroke. In this study, we characterized longitudinally the changes in the slow-5 oscillations in stroke patients across two different time-points. We followed a group of ischemic stroke patients (n = 20 and another group of healthy older adults (n = 14 over two visits separated by a minimum of three months (average of 9 months. For the stroke patients, one visit occurred in their subacute window (10 days to 6 months after stroke onset, the other took place in their chronic window (>6 months after stroke. Using a mid-order group ICA method on 10-minutes eyes-closed resting-state fMRI data, we assessed the frequency distributions of a component's representative time-courses for differences in regards to slow-5 spectral power. First, our stroke patients, in their subacute stage, exhibited lower amplitude slow-5 oscillations in comparison to their healthy counterparts. Second, over time in their chronic stage, those same patients showed a recovery of those oscillations, reaching near equivalence to the healthy older adult group. Our results indicate the possibility of an eventual recovery of those initially disrupted network oscillations to a near-normal level, providing potentially a biomarker for stroke recovery of the cortical system. This finding opens new avenues in infra-slow oscillation research and could serve as a useful biomarker in future treatments aimed at recovery.

Serum tenascin-C predicts severity and outcome of acute intracerebral hemorrhage.

Science.gov (United States)

Wang, Lin-Guo; Huangfu, Xue-Qin; Tao, Bo; Zhong, Guan-Jin; Le, Zhou-Di

2018-06-01

Tenascin-C is a matricellular protein related to brain injury. We studied serum tenascin-C in acute intracerebral hemorrhage (ICH) and examined the associations with severity and outcome following the acute event. Tenascin-C samples were obtained from 162 patients with acute hemorrhagic stroke and 162 healthy controls. Poor 90-day functional outcome was defined as modified Rankin Scale score > 2. Early neurological deterioration (END) and hematoma growth (HG) were recorded at 24 h. Patients had higher tenascin-C levels than controls. Tenascin-C levels were positively correlated with hematoma volume or National Institutes of Health Stroke Scale score at baseline. Elevated tenascin-C levels were independently associated with END, HG, 90-day mortality and poor functional outcome. Moreover, tenascin-C levels significantly predicted END, HG and 90-day outcomes under receiver operating characteristic curves. An increase in serum tenascin-C level is associated with an adverse outcome in ICH patients, supporting the potential role of serum tenascin-C as a prognostic biomarker for hemorrhagic stroke. Copyright © 2018 Elsevier B.V. All rights reserved.

Revised Framingham Stroke Risk Profile to Reflect Temporal Trends.

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Dufouil, Carole; Beiser, Alexa; McLure, Leslie A; Wolf, Philip A; Tzourio, Christophe; Howard, Virginia J; Westwood, Andrew J; Himali, Jayandra J; Sullivan, Lisa; Aparicio, Hugo J; Kelly-Hayes, Margaret; Ritchie, Karen; Kase, Carlos S; Pikula, Aleksandra; Romero, Jose R; D'Agostino, Ralph B; Samieri, Cécilia; Vasan, Ramachandran S; Chêne, Genevieve; Howard, George; Seshadri, Sudha

2017-03-21

Age-adjusted stroke incidence has decreased over the past 50 years, likely as a result of changes in the prevalence and impact of various stroke risk factors. An updated version of the Framingham Stroke Risk Profile (FSRP) might better predict current risks in the FHS (Framingham Heart Study) and other cohorts. We compared the accuracy of the standard (old) and of a revised (new) version of the FSRP in predicting the risk of all-stroke and ischemic stroke and validated this new FSRP in 2 external cohorts, the 3C (3 Cities) and REGARDS (Reasons for Geographic and Racial Differences in Stroke) studies. We computed the old FSRP as originally described and a new model that used the most recent epoch-specific risk factor prevalence and hazard ratios for individuals ≥55 years of age and for the subsample ≥65 years of age (to match the age range in REGARDS and 3C studies, respectively) and compared the efficacy of these models in predicting 5- and 10-year stroke risks. The new FSRP was a better predictor of current stroke risks in all 3 samples than the old FSRP (calibration χ 2 of new/old FSRP: in men: 64.0/12.1, 59.4/30.6, and 20.7/12.5; in women: 42.5/4.1, 115.4/90.3, and 9.8/6.5 in FHS, REGARDS, and 3C, respectively). In the REGARDS, the new FSRP was a better predictor among whites compared with blacks. A more contemporaneous, new FSRP better predicts current risks in 3 large community samples and could serve as the basis for examining geographic and racial differences in stroke risk and the incremental diagnostic utility of novel stroke risk factors. © 2017 American Heart Association, Inc.

Acute Predictors of Social Integration Following Mild Stroke.

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Wise, Frances M; Harris, Darren W; Olver, John H; Davis, Stephen M; Disler, Peter B

2018-04-01

Despite an acknowledged need to accurately predict stroke outcome, there is little empirical evidence regarding acute predictors of participation restriction post stroke. The current study examines prediction of social integration following mild stroke, using combinations of acute poststroke factors. In a prospective, longitudinal study, a cohort of 60 stroke survivors was followed up at 6 months post stroke. Hierarchical multiple regression analyses were employed to evaluate the value of acute poststroke variables in predicting social integration at 6 months post stroke. A combination of age, number of comorbidities, stroke severity, social support factors, and general self-efficacy in the acute poststroke period accounted for 42% of the variance in 6-month social integration. The largest amount of variance (20%) was explained by inclusion of social support factors, including number and types of support. Post hoc analysis was conducted to establish whether marital status was the mediating variable through which early poststroke social support factors exerted influence upon subsequent social integration. The new combination of acute variables accounted for 48% of the variance in 6-month social integration. Results suggested that subjects with partners perceived higher levels of functional social support and lower levels of participation restriction. Stroke survivors with partners may receive greater amounts of companionship and encouragement from their partners, which enhances self-esteem and confidence. Such individuals are possibly more able to participate in and maintain relationships, thus improving social integration. Social support factors, mediated via marital status, are the strongest predictors of subsequent social integration following mild stroke. Copyright © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Interhemispheric Pathways Are Important for Motor Outcome in Individuals with Chronic and Severe Upper Limb Impairment Post Stroke

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Kathryn S. Hayward

2017-01-01

Full Text Available Background. Severity of arm impairment alone does not explain motor outcomes in people with severe impairment post stroke. Objective. Define the contribution of brain biomarkers to upper limb motor outcomes in people with severe arm impairment post stroke. Methods. Paretic arm impairment (Fugl-Meyer upper limb, FM-UL and function (Wolf Motor Function Test rate, WMFT-rate were measured in 15 individuals with severe (FM-UL ≤ 30/66 and 14 with mild–moderate (FM-UL > 40/66 impairment. Transcranial magnetic stimulation and diffusion weight imaging indexed structure and function of the corticospinal tract and corpus callosum. Separate models of the relationship between possible biomarkers and motor outcomes at a single chronic (≥6 months time point post stroke were performed. Results. Age (ΔR20.365, p=0.017 and ipsilesional-transcallosal inhibition (ΔR20.182, p=0.048 explained a 54.7% (p=0.009 variance in paretic WMFT-rate. Prefrontal corpus callous fractional anisotropy (PF-CC FA alone explained 49.3% (p=0.007 variance in FM-UL outcome. The same models did not explain significant variance in mild–moderate stroke. In the severe group, k-means cluster analysis of PF-CC FA distinguished two subgroups, separated by a clinically meaningful and significant difference in motor impairment (p=0.049 and function (p=0.006 outcomes. Conclusion. Corpus callosum function and structure were identified as possible biomarkers of motor outcome in people with chronic and severe arm impairment.

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

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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.

Improved prediction of breast cancer outcome by identifying heterogeneous biomarkers.

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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

Large Animal Stroke Models vs. Rodent Stroke Models, Pros and Cons, and Combination?

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Cai, Bin; Wang, Ning

2016-01-01

Stroke is a leading cause of serious long-term disability worldwide and the second leading cause of death in many countries. Long-time attempts to salvage dying neurons via various neuroprotective agents have failed in stroke translational research, owing in part to the huge gap between animal stroke models and stroke patients, which also suggests that rodent models have limited predictive value and that alternate large animal models are likely to become important in future translational research. The genetic background, physiological characteristics, behavioral characteristics, and brain structure of large animals, especially nonhuman primates, are analogous to humans, and resemble humans in stroke. Moreover, relatively new regional imaging techniques, measurements of regional cerebral blood flow, and sophisticated physiological monitoring can be more easily performed on the same animal at multiple time points. As a result, we can use large animal stroke models to decrease the gap and promote translation of basic science stroke research. At the same time, we should not neglect the disadvantages of the large animal stroke model such as the significant expense and ethical considerations, which can be overcome by rodent models. Rodents should be selected as stroke models for initial testing and primates or cats are desirable as a second species, which was recommended by the Stroke Therapy Academic Industry Roundtable (STAIR) group in 2009.

Biomarkers of adverse drug reactions.

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Carr, Daniel F; Pirmohamed, Munir

2018-02-01

Adverse drug reactions can be caused by a wide range of therapeutics. Adverse drug reactions affect many bodily organ systems and vary widely in severity. Milder adverse drug reactions often resolve quickly following withdrawal of the casual drug or sometimes after dose reduction. Some adverse drug reactions are severe and lead to significant organ/tissue injury which can be fatal. Adverse drug reactions also represent a financial burden to both healthcare providers and the pharmaceutical industry. Thus, a number of stakeholders would benefit from development of new, robust biomarkers for the prediction, diagnosis, and prognostication of adverse drug reactions. There has been significant recent progress in identifying predictive genomic biomarkers with the potential to be used in clinical settings to reduce the burden of adverse drug reactions. These have included biomarkers that can be used to alter drug dose (for example, Thiopurine methyltransferase (TPMT) and azathioprine dose) and drug choice. The latter have in particular included human leukocyte antigen (HLA) biomarkers which identify susceptibility to immune-mediated injuries to major organs such as skin, liver, and bone marrow from a variety of drugs. This review covers both the current state of the art with regard to genomic adverse drug reaction biomarkers. We also review circulating biomarkers that have the potential to be used for both diagnosis and prognosis, and have the added advantage of providing mechanistic information. In the future, we will not be relying on single biomarkers (genomic/non-genomic), but on multiple biomarker panels, integrated through the application of different omics technologies, which will provide information on predisposition, early diagnosis, prognosis, and mechanisms. Impact statement • Genetic and circulating biomarkers present significant opportunities to personalize patient therapy to minimize the risk of adverse drug reactions. ADRs are a significant heath issue

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.)

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

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

2017-01-01

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

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

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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.

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

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

2017-01-01

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

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.

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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.

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

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Liao X

2018-04-01

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

Self-perceived quality of life predicts mortality risk better than a multi-biomarker panel, but the combination of both does best

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Nauck Matthias

2011-07-01

Full Text Available Abstract Background Associations between measures of subjective health and mortality risk have previously been shown. We assessed the impact and comparative predictive performance of a multi-biomarker panel on this association. Methods Data from 4,261 individuals aged 20-79 years recruited for the population-based Study of Health in Pomerania was used. During an average 9.7 year follow-up, 456 deaths (10.7% occurred. Subjective health was assessed by SF-12 derived physical (PCS-12 and mental component summaries (MCS-12, and a single-item self-rated health (SRH question. We implemented Cox proportional-hazards regression models to investigate the association of subjective health with mortality and to assess the impact of a combination of 10 biomarkers on this association. Variable selection procedures were used to identify a parsimonious set of subjective health measures and biomarkers, whose predictive ability was compared using receiver operating characteristic (ROC curves, C-statistics, and reclassification methods. Results In age- and gender-adjusted Cox models, poor SRH (hazard ratio (HR, 2.07; 95% CI, 1.34-3.20 and low PCS-12 scores (lowest vs. highest quartile: HR, 1.75; 95% CI, 1.31-2.33 were significantly associated with increased risk of all-cause mortality; an association independent of various covariates and biomarkers. Furthermore, selected subjective health measures yielded a significantly higher C-statistic (0.883 compared to the selected biomarker panel (0.872, whereas a combined assessment showed the highest C-statistic (0.887 with a highly significant integrated discrimination improvement of 1.5% (p Conclusion Adding biomarker information did not affect the association of subjective health measures with mortality, but significantly improved risk stratification. Thus, a combined assessment of self-reported subjective health and measured biomarkers may be useful to identify high-risk individuals for intensified monitoring.

Developing and validating a predictive model for stroke progression

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

2011-01-01

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

Self-Reported Stroke Risk Stratification: Reasons for Geographic and Racial Differences in Stroke Study.

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Howard, George; McClure, Leslie A; Moy, Claudia S; Howard, Virginia J; Judd, Suzanne E; Yuan, Ya; Long, D Leann; Muntner, Paul; Safford, Monika M; Kleindorfer, Dawn O

2017-07-01

The standard for stroke risk stratification is the Framingham Stroke Risk Function (FSRF), an equation requiring an examination for blood pressure assessment, venipuncture for glucose assessment, and ECG to determine atrial fibrillation and heart disease. We assess a self-reported stroke risk function (SRSRF) to stratify stroke risk in comparison to the FSRF. Participants from the REGARDS study (Reasons for Geographic and Racial Differences in Stroke) were evaluated at baseline and followed for incident stroke. The FSRF was calculated using directly assessed stroke risk factors. The SRSRF was calculated from 13 self-reported questions to exclude those with prevalent stroke and assess stroke risk. Proportional hazards analysis was used to assess incident stroke risk using the FSRF and SRSRF. Over an average 8.2-year follow-up, 939 of 23 983 participants had a stroke. The FSRF and SRSRF produced highly correlated risk scores ( r Spearman =0.852; 95% confidence interval, 0.849-0.856); however, the SRSRF had higher discrimination of stroke risk than the FSRF (c SRSRF =0.7266; 95% confidence interval, 0.7076-0.7457; c FSRF =0.7075; 95% confidence interval, 0.6877-0.7273; P =0.0038). The 10-year stroke risk in the highest decile of predicted risk was 11.1% for the FSRF and 13.4% for the SRSRF. A simple self-reported questionnaire can be used to identify those at high risk for stroke better than the gold standard FSRF. This instrument can be used clinically to easily identify individuals at high risk for stroke and also scientifically to identify a subpopulation enriched for stroke risk. © 2017 American Heart Association, Inc.

Prediction of Small for Gestational Age Infants in Healthy Nulliparous Women Using Clinical and Ultrasound Risk Factors Combined with Early Pregnancy Biomarkers.

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Lesley M E McCowan

Full Text Available Most small for gestational age pregnancies are unrecognised before birth, resulting in substantial avoidable perinatal mortality and morbidity. Our objective was to develop multivariable prediction models for small for gestational age combining clinical risk factors and biomarkers at 15±1 weeks' with ultrasound parameters at 20±1 weeks' gestation.Data from 5606 participants in the Screening for Pregnancy Endpoints (SCOPE cohort study were divided into Training (n = 3735 and Validation datasets (n = 1871. The primary outcomes were All-SGA (small for gestational age with birthweight <10th customised centile, Normotensive-SGA (small for gestational age with a normotensive mother and Hypertensive-SGA (small for gestational age with an hypertensive mother. The comparison group comprised women without the respective small for gestational age phenotype. Multivariable analysis was performed using stepwise logistic regression beginning with clinical variables, and subsequent additions of biomarker and then ultrasound (biometry and Doppler variables. Model performance was assessed in Training and Validation datasets by calculating area under the curve.633 (11.2% infants were All-SGA, 465(8.2% Normotensive-SGA and 168 (3% Hypertensive-SGA. Area under the curve (95% Confidence Intervals for All-SGA using 15±1 weeks' clinical variables, 15±1 weeks' clinical+ biomarker variables and clinical + biomarkers + biometry /Doppler at 20±1 weeks' were: 0.63 (0.59-0.67, 0.64 (0.60-0.68 and 0.69 (0.66-0.73 respectively in the Validation dataset; Normotensive-SGA results were similar: 0.61 (0.57-0.66, 0.61 (0.56-0.66 and 0.68 (0.64-0.73 with small increases in performance in the Training datasets. Area under the curve (95% Confidence Intervals for Hypertensive-SGA were: 0.76 (0.70-0.82, 0.80 (0.75-0.86 and 0.84 (0.78-0.89 with minimal change in the Training datasets.Models for prediction of small for gestational age, which combine biomarkers, clinical and

Biomarkers in DILI: one more step forward

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Mercedes Robles-Díaz

2016-08-01

Full Text Available Despite being relatively rare, drug-induced liver injury (DILI is a serious condition, both for the individual patient due to the risk of acute liver failure, and for the drug development industry and regulatory agencies due to associations with drug development attritions, black box warnings and postmarketing withdrawals. A major limitation in DILI diagnosis and prediction is the current lack of specific biomarkers. Despite refined usage of traditional liver biomarkers in DILI, reliable disease outcome predictions are still difficult to make. These limitations have driven the growing interest in developing new more sensitive and specific DILI biomarkers, which can improve early DILI prediction, diagnosis and course of action. Several promising DILI biomarker candidates have been discovered to date, including mechanistic-based biomarker candidates such as glutamate dehydrogenase, high-mobility group box 1 protein and keratin-18, which can also provide information on the injury mechanism of different causative agents. Furthermore, microRNAs have received much attention lately as potential non-invasive DILI biomarker candidates, in particular miR-122. Advances in omics technologies offer a new approach for biomarker exploration studies. The ability to screen a large number of molecules (for example metabolites, proteins or DNA simultaneously enables the identification of ‘toxicity signatures’, which may be used to enhance preclinical safety assessments and disease diagnostics. Omics-based studies can also provide information on the underlying mechanisms of distinct forms of DILI that may further facilitate the identification of early diagnostic biomarkers and safer implementation of personalized medicine. In this review we summarize recent advances in the area of DILI biomarker studies.

Discriminating poststroke depression from stroke by nuclear magnetic resonance spectroscopy-based metabonomic analysis

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Xiao J

2016-08-01

Full Text Available Jianqi Xiao,1,* Jie Zhang,2,* Dan Sun,3,* Lin Wang,4,* Lijun Yu,5 Hongjing Wu,5 Dan Wang,5 Xuerong Qiu5 1Department of Neurosurgery, The First Hospital of Qiqihar City, Qiqihar, 2Department of Internal Medicine, Central Hospital of Jiamusi City, Jiamusi, 3Department of Geriatrics, General Hospital of Daqing Oil Field, Daqing, 4Department of Nursing, 5Department of Neurology, The First Hospital of Qiqihar City, Qiqihar, Heilongjiang, People’s Republic of China *These authors contributed equally to this work Abstract: Poststroke depression (PSD, the most common psychiatric disease that stroke survivors face, is estimated to affect ~30% of poststroke patients. However, there are still no objective methods to diagnose PSD. In this study, to explore the differential metabolites in the urine of PSD subjects and to identify a potential biomarker panel for PSD diagnosis, the nuclear magnetic resonance-based metabonomic method was applied. Ten differential metabolites responsible for discriminating PSD subjects from healthy control (HC and stroke subjects were found, and five of these metabolites were identified as potential biomarkers (lactate, α-hydroxybutyrate, phenylalanine, formate, and arabinitol. The panel consisting of these five metabolites provided excellent performance in discriminating PSD subjects from HC and stroke subjects, achieving an area under the receiver operating characteristic curve of 0.946 in the training set (43 HC, 45 stroke, and 62 PSD subjects. Moreover, this panel could classify the blinded samples from the test set (31 HC, 33 stroke, and 32 PSD subjects with an area under the curve of 0.946. These results laid a foundation for the future development of urine-based objective methods for PSD diagnosis and investigation of PSD pathogenesis. Keywords: poststroke depression, PSD, stroke, nuclear magnetic resonance, NMR, metabonomic

Clinical predictive value of the ABCD2 score for early risk of stroke in patients who have had transient ischaemic attack and who present to an Australian tertiary hospital.

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Sanders, Lauren M; Srikanth, Velandai K; Psihogios, Helen; Wong, Kitty K; Ramsay, David; Phan, Thanh G

2011-02-07

To determine the predictive value of the ABCD(2) score for early risk of stroke in Australian patients who have had transient ischaemic attack (TIA). Cohort study of 512 consecutive patients with suspected TIA referred by the emergency department to the acute stroke unit (in accordance with the TIA pathway) of an urban tertiary hospital in Melbourne, Victoria, between 1 June 2004 and 30 November 2007. Overall accuracy, estimated by the area under the curve (AUC) of receiver operating characteristic plots (of true positive rate v false positive rate), and sensitivity, specificity, predictive values and likelihood ratios at prespecified cut-off ABCD(2) scores for stroke within 2, 7 and 90 days. 24 patients were excluded because their symptoms lasted more than 24 hours. All included patients were reviewed by a stroke physician; TIA was confirmed in 301/488 (61.7%). Most (289/301; 96.0%) had complete follow-up. Stroke occurred in 4/292 patients (1.37%; 95% CI, 0.37%-3.47%) within 2 days and 7/289 (2.42%; 95% CI, 0.98%-4.93%) within 90 days; no patient had a stroke between 2 and 7 days. The AUCs for stroke in patients with confirmed TIA were 0.80 (95% CI, 0.68-0.91) and 0.62 (95% CI, 0.40-0.83) for stroke within 2 days and 90 days, respectively. At a cut-off of ≥ 5, the ABCD(2) score had modest specificity for stroke within 2 days (0.58) and 90 days (0.58), but positive predictive values (2 days, 0.03; 90 days, 0.04) and positive likelihood ratios (2 days, 2.40; 90 days, 1.71) were both poor. The score performed similarly poorly at other prespecified cut-off scores. Given its poor predictive value, the use of the ABCD(2) score alone may not be dependable for guiding clinical treatment decisions or service organisation in an Australian tertiary setting. Validation in other Australian settings is recommended before it can be applied with confidence.

An Evidence-Based Approach to the Use of Predictive Biomarkers in the Treatment of Non- Small Cell Lung Cancer (NSCLC)

International Nuclear Information System (INIS)

Quinton, Cindy; Ellis, Peter M.

2011-01-01

Recent advances in the treatment of non-small cell lung cancer (NSCLC) have led to improvements in patient survival and quality of life. It is unclear whether molecular abnormalities associated with NSCLC cell survival, growth and proliferation are useful in predicting treatment benefit. We conducted a systematic review to establish which biomarkers contribute meaningfully to the management of NSCLC. A team of researchers searched PubMed and conference proceedings (ASCO, ESMO, IASLC, USCAP) using MESH terms for NSCLC and randomized trials (RCT), plus keywords for variables of interest. Evidence from multiple RCTs confirmed that histologic subtype is prognostic for survival and predictive of treatment efficacy and/or toxicity in NSCLC. Likewise, activating mutations of the epidermal growth factor receptor (EGFR) are associated with benefit from EGFR tyrosine kinase inhibitors in patients with advanced non-squamous NSCLC and should be assessed routinely. No biomarkers to date reliably predict response to anti-Vascular Endothelial Growth Factor (VEGF) therapies. There are inconsistent data on the role of ERCC1, BRCA, Beta tubulin III, RRM1, K-RAS, or TP-53 in treatment decisions. These tests should not be routinely used in selecting treatment at this time, whereas EML4/ALK translocations predict responses to specific targeted agents, the optimal assessment of this molecular abnormality has yet to be established. Personalized care of patients with NSCLC based on biomarkers is increasingly important to both clinical practice and research

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-04-15

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

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.

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.

Microalbuminuria could improve risk stratification in patients with TIA and minor stroke.

Science.gov (United States)

Elyas, Salim; Shore, Angela C; Kingwell, Hayley; Keenan, Samantha; Boxall, Leigh; Stewart, Jane; James, Martin A; Strain, William David

2016-09-01

Transient ischemic attacks (TIA) and minor strokes are important risk factors for recurrent strokes. Current stroke risk prediction scores such as ABCD2, although widely used, lack optimal sensitivity and specificity. Elevated urinary albumin excretion predicts cardiovascular disease, stroke, and mortality. We explored the role of microalbuminuria (using albumin creatinine ratio (ACR)) in predicting recurrence risk in patients with TIA and minor stroke. Urinary ACR was measured on a spot sample in 150 patients attending a daily stroke clinic with TIA or minor stroke. Patients were followed up at day 7, 30, and 90 to determine recurrent stroke, cardiovascular events, or death. Eligible patients had a carotid ultrasound Doppler investigation. High-risk patients were defined as those who had an event within 90 days or had >50% internal carotid artery (ICA) stenosis. Fourteen (9.8%) recurrent events were reported by day 90 including two deaths. Fifteen patients had severe ICA stenosis. In total, 26 patients were identified as high risk. These patients had a higher frequency of previous stroke or hypercholesterolemia compared to low-risk patients (P = 0.04). ACR was higher in high-risk patients (3.4 [95% CI 2.2-5.2] vs. 1.7 [1.5-2.1] mg/mmol, P = 0.004), independent of age, sex, blood pressure, diabetes, and previous stroke. An ACR greater than 1.5 mg/mmol predicted high-risk patients (Cox proportional hazard ratio 3.5 (95% CI 1.3-9.5, P = 0.01). After TIA or minor stroke, a higher ACR predicted recurrent events and significant ICA stenosis. Incorporation of urinary ACR from a spot sample in the acute setting could improve risk stratification in patients with TIA and minor stroke.

Adjustment of Serum HE4 to reduced Glomerular filtration and its use in Biomarker-based prediction of deep Myometrial invasion in endometrial cancer

DEFF Research Database (Denmark)

Chovanec, Josef; Selingerova, Iveta; Greplova, Kristina

2017-01-01

Background: We investigated the efficacy of circulating biomarkers together with histological grade and age to predict deep myometrial invasion (dMI) in endometrial cancer patients. Methods: HE4ren was developed adjusting HE4 serum levels towards decreased glomerular filtration rate as quantified...... levels to reduced eGFR that enables quantification of time-dependent changes in HE4 production and elimination irrespective of age and renal function in women. Utilizing HE4ren improves performance of biomarker-based models for prediction of dMI in endometrial cancer patients....

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

NARCIS (Netherlands)

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

2015-01-01

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

Relationship between QT Interval Dispersion in acute stroke and stroke prognosis: A Systematic Review

Science.gov (United States)

Lederman, Yitzchok S.; Balucani, Clotilde; Lazar, Jason; Steinberg, Leah; Gugger, James; Levine, Steven R.

2014-01-01

Background QT dispersion (QTd) has been proposed as an indirect ECG measure of heterogeneity of ventricular repolarization. The predictive value of QTd in acute stroke remains controversial. We aimed to clarify the relationship between QTd and acute stroke and stroke prognosis. Methods A systematic review of the literature was performed using pre-specified medical subjects heading (MeSH) terms, Boolean logic and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Eligible studies (a) included ischemic or hemorrhagic stroke and (b) provided QTd measurements. Results Two independent reviewers identified 553 publications. Sixteen articles were included in the final analysis. There were a total of 888 stroke patients: 59% ischemic and 41% hemorrhagic. There was considerable heterogeneity in study design, stroke subtypes, ECG assessment-time, control groups and comparison groups. Nine studies reported a significant association between acute stroke and baseline QTd. Two studies reported that QTd increases are specifically related to hemorrhagic strokes, involvement of the insular cortex, right-side lesions, larger strokes, and increases in 3, 4-dihydroxyphenylethylene glycol in hemorrhagic stroke. Three studies reported QTd to be an independent predictor of stroke mortality. One study each reported increases in QTd in stroke patients who developed ventricular arrhythmias and cardiorespiratory compromise. Conclusions There are few well-designed studies and considerable variability in study design in addressing the significance of QTd in acute stroke. Available data suggest that stroke is likely to be associated with increased QTd. While some evidence suggests a possible prognostic role of QTd in stroke, larger and well-designed studies need to confirm these findings. PMID:25282188

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

Science.gov (United States)

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

2018-03-01

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

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

Science.gov (United States)

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

2011-11-01

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

Hyperacute Detection of Neurofilament Heavy Chain in Serum Following Stroke: A Transient Sign

NARCIS (Netherlands)

Sellner, J.; Patel, A; Dassan, P.; Brown, M.M.; Petzold, A.F.S.

2011-01-01

Serological biomarkers which enable quick and reliable diagnosis or measurement of the extent of irreversible brain injury early in the course of stroke are eagerly awaited. Neurofilaments (Nf) are a group of proteins integrated into the scaffolding of the neuronal and axonal cytoskeleton and an

Cognitive patterns in relation to biomarkers of cerebrovascular disease and vascular risk factors.

Science.gov (United States)

Miralbell, Júlia; López-Cancio, Elena; López-Oloriz, Jorge; Arenillas, Juan Francisco; Barrios, Maite; Soriano-Raya, Juan José; Galán, Amparo; Cáceres, Cynthia; Alzamora, Maite; Pera, Guillem; Toran, Pere; Dávalos, Antoni; Mataró, Maria

2013-01-01

Risk factors for vascular cognitive impairment (VCI) are the same as traditional risk factors for cerebrovascular disease (CVD). Early identification of subjects at higher risk of VCI is important for the development of effective preventive strategies. In addition to traditional vascular risk factors (VRF), circulating biomarkers have emerged as potential tools for early diagnoses, as they could provide in vivo measures of the underlying pathophysiology. While VRF have been consistently linked to a VCI profile (i.e., deficits in executive functions and processing speed), the cognitive correlates of CVD biomarkers remain unclear. In this population-based study, the aim was to study and compare cognitive patterns in relation to VRF and circulating biomarkers of CVD. The Barcelona-AsIA Neuropsychology Study included 747 subjects older than 50, without a prior history of stroke or coronary disease and with a moderate to high vascular risk (mean age, 66 years; 34.1% women). Three cognitive domains were derived from factoral analysis: visuospatial skills/speed, verbal memory and verbal fluency. Multiple linear regression was used to assess relationships between cognitive performance (multiple domains) and a panel of circulating biomarkers, including indicators of inflammation, C-reactive protein (CRP) and resistin, endothelial dysfunction, asymmetric dimethylarginine (ADMA), thrombosis, plasminogen activator inhibitor 1 (PAI-1), as well as traditional VRF, metabolic syndrome and insulin resistance (homeostatic model assessment for insulin resistance index). Analyses were adjusted for age, gender, years of education and depressive symptoms. Traditional VRF were related to lower performance in verbal fluency, insulin resistance accounted for lower performance in visuospatial skills/speed and the metabolic syndrome predicted lower performance in both cognitive domains. From the biomarkers of CVD, CRP was negatively related to verbal fluency performance and increasing ADMA

Biomarkers in spinal cord compression Ethics and perspectives

Directory of Open Access Journals (Sweden)

Iencean A.St.

2016-09-01

Full Text Available The phosphorylated form of the high-molecular-weight neurofilament subunit NF-H (pNF-H in serum or in cerebro-spinal fluid (CSF is a specific lesional biomarker for spinal cord injury. The lesional biomarkers and the reaction biomarkers are both presented after several hours post-injury. The specific predictive patterns of lesional biomarkers could be used to aid clinicians with making a diagnosis and establishing a prognosis, and evaluating therapeutic interventions. Diagnosis, prognosis, and treatment guidance based on biomarker used as a predictive indicator can determine ethical difficulties by differentiated therapies in patients with spinal cord compression. At this point based on studies until today we cannot take a decision based on biomarker limiting the treatment of neurological recovery in patients with complete spinal cord injury because we do not know the complexity of the biological response to spinal cord compression.

Collateral circulation on perfusion-computed tomography-source images predicts the response to stroke intravenous thrombolysis.

Science.gov (United States)

Calleja, A I; Cortijo, E; García-Bermejo, P; Gómez, R D; Pérez-Fernández, S; Del Monte, J M; Muñoz, M F; Fernández-Herranz, R; Arenillas, J F

2013-05-01

Perfusion-computed tomography-source images (PCT-SI) may allow a dynamic assessment of leptomeningeal collateral arteries (LMC) filling and emptying in middle cerebral artery (MCA) ischaemic stroke. We described a regional LMC scale on PCT-SI and hypothesized that a higher collateral score would predict a better response to intravenous (iv) thrombolysis. We studied consecutive ischaemic stroke patients with an acute MCA occlusion documented by transcranial Doppler/transcranial color-coded duplex, treated with iv thrombolysis who underwent PCT prior to treatment. Readers evaluated PCT-SI in a blinded fashion to assess LMC within the hypoperfused MCA territory. LMC scored as follows: 0, absence of vessels; 1, collateral supply filling ≤ 50%; 2, between> 50% and < 100%; 3, equal or more prominent when compared with the unaffected hemisphere. The scale was divided into good (scores 2-3) vs. poor (scores 0-1) collaterals. The predetermined primary end-point was a good 3-month functional outcome, while early neurological recovery, transcranial duplex-assessed 24-h MCA recanalization, 24-h hypodensity volume and hemorrhagic transformation were considered secondary end-points. Fifty-four patients were included (55.5% women, median NIHSS 10), and 4-13-23-14 patients had LMC score (LMCs) of 0-1-2-3, respectively. The probability of a good long-term outcome augmented gradually with increasing LMCs: (0) 0%; (1) 15.4%; (2) 65.2%; (3) 64.3%, P = 0.004. Good-LMCs was independently associated with a good outcome [OR 21.02 (95% CI 2.23-197.75), P = 0.008]. Patients with good LMCs had better early neurological recovery (P = 0.001), smaller hypodensity volumes (P < 0.001) and a clear trend towards a higher recanalization rate. A higher degree of LMC assessed by PCT-SI predicts good response to iv thrombolysis in MCA ischaemic stroke patients. © 2012 The Author(s) European Journal of Neurology © 2012 EFNS.

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.

Stroke MRI: pathophysiology, potential and perspectives

International Nuclear Information System (INIS)

Fiehler, J.; Kucinski, T.; Zeumer, H.

2004-01-01

Magnetic resonance imaging (MRT) is increasingly utilized as the primary imaging modality in major stroke centers. The ability to depict several aspects of individual pathophysiology makes the use of MRI in stroke both attractive and complex. Profound knowledge of the pathophysiology of the imaging findings is crucial for a rational diagnostic workup. The pathophysiology of MRI in stroke will be reviewed considering recent experiences in clinical application, and the potential of stroke MRI will be assessed. Further perspectives like application of 'blood oxygen level dependent' (BOLD) and the use of multiparametric prediction maps will be discussed. (orig.) [de

Critical periods after stroke study: translating animal stroke recovery experiments into a clinical trial

Science.gov (United States)

Dromerick, Alexander W.; Edwardson, Matthew A.; Edwards, Dorothy F.; Giannetti, Margot L.; Barth, Jessica; Brady, Kathaleen P.; Chan, Evan; Tan, Ming T.; Tamboli, Irfan; Chia, Ruth; Orquiza, Michael; Padilla, Robert M.; Cheema, Amrita K.; Mapstone, Mark E.; Fiandaca, Massimo S.; Federoff, Howard J.; Newport, Elissa L.

2015-01-01

Introduction: Seven hundred ninety-five thousand Americans will have a stroke this year, and half will have a chronic hemiparesis. Substantial animal literature suggests that the mammalian brain has much potential to recover from acute injury using mechanisms of neuroplasticity, and that these mechanisms can be accessed using training paradigms and neurotransmitter manipulation. However, most of these findings have not been tested or confirmed in the rehabilitation setting, in large part because of the challenges in translating a conceptually straightforward laboratory experiment into a meaningful and rigorous clinical trial in humans. Through presentation of methods for a Phase II trial, we discuss these issues and describe our approach. Methods: In rodents there is compelling evidence for timing effects in rehabilitation; motor training delivered at certain times after stroke may be more effective than the same training delivered earlier or later, suggesting that there is a critical or sensitive period for strongest rehabilitation training effects. If analogous critical/sensitive periods can be identified after human stroke, then existing clinical resources can be better utilized to promote recovery. The Critical Periods after Stroke Study (CPASS) is a phase II randomized, controlled trial designed to explore whether such a sensitive period exists. We will randomize 64 persons to receive an additional 20 h of upper extremity therapy either immediately upon rehab admission, 2–3 months after stroke onset, 6 months after onset, or to an observation-only control group. The primary outcome measure will be the Action Research Arm Test (ARAT) at 1 year. Blood will be drawn at up to 3 time points for later biomarker studies. Conclusion: CPASS is an example of the translation of rodent motor recovery experiments into the clinical setting; data obtained from this single site randomized controlled trial will be used to finalize the design of a Phase III trial. PMID

Critical Periods after Stroke Study: Translating animal stroke recovery experiments into a clinical trial

Directory of Open Access Journals (Sweden)

Alexander W Dromerick

2015-04-01

Full Text Available Introduction: 795,000 Americans will have a stroke this year, and half will have a chronic hemiparesis. Substantial animal literature suggests that the mammalian brain has much potential to recover from acute injury using mechanisms of neuroplasticity, and that these mechanisms can be accessed using training paradigms and neurotransmitter manipulation. However, most of these findings have not been tested or confirmed in the rehabilitation setting, in large part because of the challenges in translating a conceptually straightforward laboratory experiment into a meaningful and rigorous clinical trial in humans. Through presentation of methods for a Phase II trial, we discuss these issues and describe our approach. Methods: In rodents there is compelling evidence for timing effects in rehabilitation; motor training delivered at certain times after stroke may be more effective than the same training delivered earlier or later, suggesting that there is a critical or sensitive period for strongest rehabilitation training effects. If analogous critical/sensitive periods can be identified after human stroke, then existing clinical resources can be better utilized to promote recovery. The Critical Periods after Stroke Study (CPASS is a phase II randomized, controlled trial designed to explore whether such a sensitive period exists. We will randomize 64 persons to receive an additional 20 hours of upper extremity therapy either immediately upon rehab admission, 2-3 months after stroke onset, 6 months after onset, or to an observation-only control group. The primary outcome measure will be the Action Research Arm Test at one year. Blood will be drawn at up to 3 time points for later biomarker studies. Conclusion: CPASS is an example of the translation of rodent motor recovery experiments into the clinical setting; data obtained from this single site randomized controlled trial will be used to finalize the design of a Phase III trial.

Hemostasis biomarkers and incident cognitive impairment: the REGARDS study.

Science.gov (United States)

Gillett, S R; McClure, L A; Callas, P W; Thacker, E L; Unverzagt, F W; Wadley, V G; Letter, A J; Cushman, M

2018-05-07

Vascular risk factors are associated with cognitive impairment, a condition with substantial public health burden. We hypothesized that hemostasis biomarkers related to vascular disease would be associated with risk of incident cognitive impairment. We performed a nested case control study including 1,082 participants with 3.5 years of follow-up in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, a longitudinal cohort study of 30,239 black and white Americans ≥45 years old. Participants were free of stroke or cognitive impairment at baseline. Baseline D-dimer, fibrinogen, factor VIII, and protein C were measured in 495 cases who developed cognitive impairment during follow-up (based on abnormal scores on ≥2 of 3 cognitive tests) and 587 controls. Unadjusted ORs for incident cognitive impairment were 1.32 (95% CI 1.02, 1.70) for D-dimer >0.50 μg/mL, 1.83 (CI 1.24, 2.71) for fibrinogen >90 th percentile, 1.63 (CI 1.11, 2.38) for factor VIII >90 th percentile and 1.10 (CI 0.73, 1.65) for protein C impairment, with an adjusted OR 1.73 (CI 1.10, 2.69). Elevated D-dimer, fibrinogen, and factor VIII were not associated with occurrence of cognitive impairment after multivariable adjustment; however, having at least 2 abnormal biomarkers was associated, suggesting the burden of these biomarkers is relevant. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

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

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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.

Recurrent Stroke: The Value of the CHA2DS2VASc Score and the Essen Stroke Risk Score in a Nationwide Stroke Cohort.

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Andersen, Søren Due; Gorst-Rasmussen, Anders; Lip, Gregory Y H; Bach, Flemming W; Larsen, Torben Bjerregaard

2015-09-01

The CHA2DS2VASc score and the Essen Stroke Risk Score are respectively used for risk stratification in patients with atrial fibrillation and in patients with cerebrovascular incidents. We aimed to test the ability of the 2 scores to predict stroke recurrence, death, and cardiovascular events (stroke, transient ischemic attack, myocardial infarction, or arterial thromboembolism) in a nationwide Danish cohort study, among patients with incident ischemic stroke and no atrial fibrillation. We conducted a registry-based study in patients with incident ischemic stroke and no atrial fibrillation. Patients were stratified according to the CHA2DS2VASc score and the Essen Stroke Risk Score and were followed up until stroke recurrence or death. We estimated stratified incidence rates and hazard ratios and calculated the cumulative risks. 42 182 patients with incident ischemic stroke with median age 70.1 years were included. The overall 1-year incidence rates of recurrent stroke, death, and cardiovascular events were 3.6%, 10.5%, and 6.7%, respectively. The incidence rates, the hazard ratios, and the cumulative risk of all outcomes increased with increasing risk scores. C-statistics for both risk scores were around 0.55 for 1-year stroke recurrence and cardiovascular events and correspondingly for death around 0.67 for both scores. In this cohort of non-atrial fibrillation patients with incident ischemic stroke, increasing CHA2DS2VASc score and Essen Stroke Risk Score was associated with increasing risk of recurrent stroke, death, and cardiovascular events. Their discriminatory performance was modest and further refinements are required for clinical application. © 2015 American Heart Association, Inc.

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

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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

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

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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...

Exploring the Experiences of Living With Stroke Through Narrative: Stroke Survivors' Perspectives.

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Nasr, Nasrin; Mawson, Susan; Wright, Peter; Parker, Jack; Mountain, Gail

2016-01-01

Chronic illness models are normally used to explain and predict the experience of living with a long-term condition. The aim of this study was to present the findings of narrative interviews with stroke survivors and their family carers to understand their experiences of stroke. We interviewed five people with stroke and three family carers from the United Kingdom. We used thematic analysis to generate themes from their narrative accounts and then linked them to broader theoretical perspectives while influenced by the concept of reinterpretation of life. The narrative accounts of participants are mainly structured based on how their changed bodies poststroke changed their identities and roles and consequently their relationships with others. In this study, we underline the need for using methods like narrative to explain strategies that people use to make sense of their experiences of living with a long-term condition such as stroke.

Blood biomarkers are helpful in the prediction of response to chemoradiation in rectal cancer: A prospective, hypothesis driven study on patients with locally advanced rectal cancer

International Nuclear Information System (INIS)

Buijsen, Jeroen; Stiphout, Ruud G. van; Menheere, Paul P.C.A.; Lammering, Guido; Lambin, Philippe

2014-01-01

Purpose/objective: Chemoradiation (CRT) has been shown to lead to downsizing of an important portion of rectal cancers. In order to tailor treatment at an earlier stage during treatment, predictive models are being developed. Adding blood biomarkers may be attractive for prediction, as they can be collected very easily and determined with excellent reproducibility in clinical practice. The hypothesis of this study was that blood biomarkers related to tumor load, hypoxia and inflammation can help to predict response to CRT in rectal cancer. Material/methods: 295 patients with locally advanced rectal cancer who were planned to undergo CRT were prospectively entered into a biobank protocol ( (NCT01067872)). Blood samples were drawn before start of CRT. Nine biomarkers were selected, based on a previously defined hypothesis, and measured in a standardized way by a certified lab: CEA, CA19-9, LDH, CRP, IL-6, IL-8, CA IX, osteopontin and 25-OH-vitamin D. Outcome was analyzed in two ways: pCR vs. non-pCR and responders (defined as ypT0-2N0) vs. non-responders (all other ypTN stages). Results: 276 patients could be analyzed. 20.7% developed a pCR and 47.1% were classified as responders. In univariate analysis CEA (p = 0.001) and osteopontin (p = 0.012) were significant predictors for pCR. Taking response as outcome CEA (p < 0.001), IL-8 (p < 0.001) and osteopontin (p = 0.004) were significant predictors. In multivariate analysis CEA was the strongest predictor for pCR (OR 0.92, p = 0.019) and CEA and IL-8 predicted for response (OR 0.97, p = 0.029 and OR 0.94, p = 0.036). The model based on biomarkers only had an AUC of 0.65 for pCR and 0.68 for response; the strongest model included clinical data, PET-data and biomarkers and had an AUC of 0.81 for pCR and 0.78 for response. Conclusion: CEA and IL-8 were identified as predictive biomarkers for tumor response and PCR after CRT in rectal cancer. Incorporation of these blood biomarkers leads to an additional accuracy of

Risk Factors and Biomarkers of Age-Related Macular Degeneration

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Lambert, Nathan G.; Singh, Malkit K.; ElShelmani, Hanan; Mansergh, Fiona C.; Wride, Michael A.; Padilla, Maximilian; Keegan, David; Hogg, Ruth E.; Ambati, Balamurali K.

2016-01-01

A biomarker can be a substance or structure measured in body parts, fluids or products that can affect or predict disease incidence. As age-related macular degeneration (AMD) is the leading cause of blindness in the developed world, much research and effort has been invested in the identification of different biomarkers to predict disease incidence, identify at risk individuals, elucidate causative pathophysiological etiologies, guide screening, monitoring and treatment parameters, and predict disease outcomes. To date, a host of genetic, environmental, proteomic, and cellular targets have been identified as both risk factors and potential biomarkers for AMD. Despite this, their use has been confined to research settings and has not yet crossed into the clinical arena. A greater understanding of these factors and their use as potential biomarkers for AMD can guide future research and clinical practice. This article will discuss known risk factors and novel, potential biomarkers of AMD in addition to their application in both academic and clinical settings. PMID:27156982

Transcranial Direct Current Stimulation in Stroke Rehabilitation: A Review of Recent Advancements

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Gomez Palacio Schjetnan, Andrea; Faraji, Jamshid; Metz, Gerlinde A.; Tatsuno, Masami; Luczak, Artur

2013-01-01

Transcranial direct current stimulation (tDCS) is a promising technique to treat a wide range of neurological conditions including stroke. The pathological processes following stroke may provide an exemplary system to investigate how tDCS promotes neuronal plasticity and functional recovery. Changes in synaptic function after stroke, such as reduced excitability, formation of aberrant connections, and deregulated plastic modifications, have been postulated to impede recovery from stroke. However, if tDCS could counteract these negative changes by influencing the system's neurophysiology, it would contribute to the formation of functionally meaningful connections and the maintenance of existing pathways. This paper is aimed at providing a review of underlying mechanisms of tDCS and its application to stroke. In addition, to maximize the effectiveness of tDCS in stroke rehabilitation, future research needs to determine the optimal stimulation protocols and parameters. We discuss how stimulation parameters could be optimized based on electrophysiological activity. In particular, we propose that cortical synchrony may represent a biomarker of tDCS efficacy to indicate communication between affected areas. Understanding the mechanisms by which tDCS affects the neural substrate after stroke and finding ways to optimize tDCS for each patient are key to effective rehabilitation approaches. PMID:23533955

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

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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.

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

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

2018-03-05

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

Volume-based predictive biomarkers of sequential FDG-PET/CT for sunitinib in cancer of unknown primary: identification of the best benefited patients

International Nuclear Information System (INIS)

Ma, Yifei; Xu, Wei; Xiao, Jianru; Bai, Ruojing; Li, Yiming; Yu, Hongyu; Yang, Chunshan; Shi, Huazheng; Zhang, Jian; Li, Jidong; Wang, Chenguang

2017-01-01

To test the performance of sequential "1"8F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) in predicting survival after sunitinib therapies in patients with cancer of unknown primary (CUP). CUP patients were enrolled for sequential PET/CT scanning for sunitinib and a control group. Univariate and multivariate analysis were applied to test the efficacy of sunitinib therapy in CUP patients. Next, sequential analyses involving PET/CT parameters were performed to identify and validate sensitive PET/CT biomarkers for sunitinib therapy. Finally, time-dependent receiver operating characteristic (TDROC) analyses were performed to compare the predictive accuracy. Multivariate analysis proved that sunitinib group had significantly improved survival (p < 0.01) as compared to control group. After cycle 2 of therapy, multivariate analysis identified volume-based PET/CT parameters as sensitive biomarkers for sunitinib (p < 0.01). TDROC curves demonstrated whole-body total lesion glycolysis reduction (Δ WTLG) and follow-up WTLG to have good accuracy for efficacy prediction. This evidence was validated after cycle 4 of therapy with the same method. Sunitinib therapy proved effective in treatment of CUP. PET/CT volume-based parameters may help predict outcome of sunitinib therapy, in which Δ WTLG and follow-up WTLG seem to be sensitive biomarkers for sunitinib efficacy. Patients with greater reduction and lower WTLG at follow-up seem to have better survival outcome. (orig.)

Volume-based predictive biomarkers of sequential FDG-PET/CT for sunitinib in cancer of unknown primary: identification of the best benefited patients

Energy Technology Data Exchange (ETDEWEB)

Ma, Yifei [Second Military Medical University, Department of Orthorpedic Oncology, Changzheng Hospital, Shanghai (China); Second Military Medical University, Department of Pathology, Changzheng Hospital, Shanghai (China); Xu, Wei; Xiao, Jianru [Second Military Medical University, Department of Orthorpedic Oncology, Changzheng Hospital, Shanghai (China); Bai, Ruojing [Geriatrics Institute, Department of Geriatrics, Tianjin Medical University General Hospital, Laboratory of Neuro-Trauma and Neurodegenerative Disorder, Tianjin (China); Li, Yiming [Neurosurgery Institute, Department of Neuro-oncology, Beijing (China); Yu, Hongyu [Second Military Medical University, Department of Pathology, Changzheng Hospital, Shanghai (China); Yang, Chunshan [Panorama Medical Imaging Center, Department of PET/CT Radiology, Shanghai (China); Department of PET/CT Radiology Center, Shanghai (China); Shi, Huazheng; Zhang, Jian [Department of PET/CT Radiology Center, Shanghai (China); Li, Jidong [The First People' s Hospital of Shangqiu, Department of Stomatology, Shangqiu, Henan Province (China); Wang, Chenguang [Second Military Medical University, Department of Radiology, Changzheng Hospital, Shanghai (China)

2017-02-15

To test the performance of sequential {sup 18}F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) in predicting survival after sunitinib therapies in patients with cancer of unknown primary (CUP). CUP patients were enrolled for sequential PET/CT scanning for sunitinib and a control group. Univariate and multivariate analysis were applied to test the efficacy of sunitinib therapy in CUP patients. Next, sequential analyses involving PET/CT parameters were performed to identify and validate sensitive PET/CT biomarkers for sunitinib therapy. Finally, time-dependent receiver operating characteristic (TDROC) analyses were performed to compare the predictive accuracy. Multivariate analysis proved that sunitinib group had significantly improved survival (p < 0.01) as compared to control group. After cycle 2 of therapy, multivariate analysis identified volume-based PET/CT parameters as sensitive biomarkers for sunitinib (p < 0.01). TDROC curves demonstrated whole-body total lesion glycolysis reduction (Δ WTLG) and follow-up WTLG to have good accuracy for efficacy prediction. This evidence was validated after cycle 4 of therapy with the same method. Sunitinib therapy proved effective in treatment of CUP. PET/CT volume-based parameters may help predict outcome of sunitinib therapy, in which Δ WTLG and follow-up WTLG seem to be sensitive biomarkers for sunitinib efficacy. Patients with greater reduction and lower WTLG at follow-up seem to have better survival outcome. (orig.)

Multilingual Validation of the Questionnaire for Verifying Stroke-Free Status in West Africa.

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Sarfo, Fred; Gebregziabher, Mulugeta; Ovbiagele, Bruce; Akinyemi, Rufus; Owolabi, Lukman; Obiako, Reginald; Akpa, Onoja; Armstrong, Kevin; Akpalu, Albert; Adamu, Sheila; Obese, Vida; Boa-Antwi, Nana; Appiah, Lambert; Arulogun, Oyedunni; Mensah, Yaw; Adeoye, Abiodun; Tosin, Aridegbe; Adeleye, Osimhiarherhuo; Tabi-Ajayi, Eric; Phillip, Ibinaiye; Sani, Abubakar; Isah, Suleiman; Tabari, Nasir; Mande, Aliyu; Agunloye, Atinuke; Ogbole, Godwin; Akinyemi, Joshua; Laryea, Ruth; Melikam, Sylvia; Uvere, Ezinne; Adekunle, Gregory; Kehinde, Salaam; Azuh, Paschal; Dambatta, Abdul; Ishaq, Naser; Saulson, Raelle; Arnett, Donna; Tiwari, Hemnant; Jenkins, Carolyn; Lackland, Dan; Owolabi, Mayowa

2016-01-01

The Questionnaire for Verifying Stroke-Free Status (QVSFS), a method for verifying stroke-free status in participants of clinical, epidemiological, and genetic studies, has not been validated in low-income settings where populations have limited knowledge of stroke symptoms. We aimed to validate QVSFS in 3 languages, Yoruba, Hausa and Akan, for ascertainment of stroke-free status of control subjects enrolled in an on-going stroke epidemiological study in West Africa. Data were collected using a cross-sectional study design where 384 participants were consecutively recruited from neurology and general medicine clinics of 5 tertiary referral hospitals in Nigeria and Ghana. Ascertainment of stroke status was by neurologists using structured neurological examination, review of case records, and neuroimaging (gold standard). Relative performance of QVSFS without and with pictures of stroke symptoms (pictograms) was assessed using sensitivity, specificity, positive predictive value, and negative predictive value. The overall median age of the study participants was 54 years and 48.4% were males. Of 165 stroke cases identified by gold standard, 98% were determined to have had stroke, whereas of 219 without stroke 87% were determined to be stroke-free by QVSFS. Negative predictive value of the QVSFS across the 3 languages was 0.97 (range, 0.93-1.00), sensitivity, specificity, and positive predictive value were 0.98, 0.82, and 0.80, respectively. Agreement between the questionnaire with and without the pictogram was excellent/strong with Cohen k=0.92. QVSFS is a valid tool for verifying stroke-free status across culturally diverse populations in West Africa. © 2015 American Heart Association, Inc.

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

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Yasser E Nassef

2013-11-01

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

A Revised Framingham Stroke Risk Profile to Reflect Temporal Trends

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Dufouil, Carole; Beiser, Alexa; McLure, Leslie A.; Wolf, Philip A.; Tzourio, Christophe; Howard, Virginia J; Westwood, Andrew J.; Himali, Jayandra J.; Sullivan, Lisa; Aparicio, Hugo J.; Kelly-Hayes, Margaret; Ritchie, Karen; Kase, Carlos S.; Pikula, Aleksandra; Romero, Jose R.; D’Agostino, Ralph B.; Samieri, Cécilia; Vasan, Ramachandran S.; Chêne, Genevieve; Howard, George; Seshadri, Sudha

2017-01-01

Background Age-adjusted stroke incidence has decreased over the past 50 years, likely due to changes in the prevalence and impact of various stroke risk factors. An updated version of the Framingham Stroke Risk Profile (FSRP) might better predict current risks in the Framingham Heart Study (FHS) and other cohorts. We compared the accuracy of the standard (Old), and of a revised (New) version of the FSRP in predicting the risk of all-stroke and ischemic stroke, and validated this new FSRP in two external cohorts, the 3 Cities (3C) and REGARDS studies. Methods We computed the old FSRP as originally described, and a new model that used the most recent epoch-specific risk factors' prevalence and hazard-ratios for persons ≥ 55 years and for the subsample ≥ 65 years (to match the age range in REGARDS and 3C studies respectively), and compared the efficacy of these models in predicting 5- and 10-year stroke risks. Results The new FSRP was a better predictor of current stroke risks in all three samples than the old FSRP (Calibration chi-squares of new/old FSRP: in men 64.0/12.1, 59.4/30.6 and 20.7/12.5; in women 42.5/4.1, 115.4/90.3 and 9.8/6.5 in FHS, REGARDS and 3C, respectively). In the REGARDS, the new FSRP was a better predictor among whites compared to blacks. Conclusions A more contemporaneous, new FSRP better predicts current risks in 3 large community samples and could serve as the basis for examining geographic and racial differences in stroke risk and the incremental diagnostic utility of novel stroke risk factors. PMID:28159800

Value of the CHA2DS2-VASc score and Fabry-specific score for predicting new-onset or recurrent stroke/TIA in Fabry disease patients without atrial fibrillation.

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Liu, Dan; Hu, Kai; Schmidt, Marie; Müntze, Jonas; Maniuc, Octavian; Gensler, Daniel; Oder, Daniel; Salinger, Tim; Weidemann, Frank; Ertl, Georg; Frantz, Stefan; Wanner, Christoph; Nordbeck, Peter

2018-05-24

To evaluate potential risk factors for stroke or transient ischemic attacks (TIA) and to test the feasibility and efficacy of a Fabry-specific stroke risk score in Fabry disease (FD) patients without atrial fibrillation (AF). FD patients often experience cerebrovascular events (stroke/TIA) at young age. 159 genetically confirmed FD patients without AF (aged 40 ± 14 years, 42.1% male) were included, and risk factors for stroke/TIA events were determined. All patients were followed up over a median period of 60 (quartiles 35-90) months. The pre-defined primary outcomes included new-onset or recurrent stroke/TIA and all-cause death. Prior stroke/TIA (HR 19.97, P TIA in FD patients without AF. A Fabry-specific score was established based on above defined risk factors, proving somehow superior to the CHA 2 DS 2 -VASc score in predicting new-onset or recurrent stroke/TIA in this cohort (AUC 0.87 vs. 0.75, P = .199). Prior stroke/TIA, angiokeratoma, renal dysfunction, left ventricular hypertrophy, and global systolic dysfunction are independent risk factors for new-onset or recurrent stroke/TIA in FD patients without AF. It is feasible to predict new or recurrent cerebral events with the Fabry-specific score based on the above defined risk factors. Future studies are warranted to test if FD patients with high risk for new-onset or recurrent stroke/TIA, as defined by the Fabry-specific score (≥ 2 points), might benefit from antithrombotic therapy. Clinical trial registration HEAL-FABRY (evaluation of HEArt invoLvement in patients with FABRY disease, NCT03362164).

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

Science.gov (United States)

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

2017-03-01

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

Value of Combining Left Atrial Diameter and Amino-terminal Pro-brain Natriuretic Peptide to the CHA2DS2-VASc Score for Predicting Stroke and Death in Patients with Sick Sinus Syndrome after Pacemaker Implantation

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Bin-Feng Mo

2017-01-01

Conclusions: CHA2DS2-VASc score is valuable for predicting stroke and death risk in patients with SSS after pacemaker implantation. The addition of LAD and NT-proBNP to the CHA2DS2-VASc score improved its predictive power for stroke and death, respectively, in this patient cohort. Future prospective studies are warranted to validate the benefit of adding LAD and NT-proBNP to the CHA2DS2-VASc score for predicting stroke and death risk in non-AF populations.

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

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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.

Novel biomarkers in primary breast core biopsies to predict poor response to neoadjuvant chemotherapy and appearance of metastases.

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Novell, Anna; Morales, Serafin; Valls, Joan; Panadés, Maria José; Salud, Antonieta; Iglesias, Edelmiro; Vilardell, Felip; Matias-Guiu, Xavier; Llombart-Cussac, Antonio

2017-09-01

Drug resistance has been one of the major obstacles limiting the success of cancer chemotherapy. In two thirds of breast cancer patients, large (>1cm) residual tumors are present after neoadjuvant chemotherapy (NCT). The residual tumor and involved nodes have been indicators of relapse and survival very important in breast cancer. The goal of this preliminary study was to assess the predictive significance of a panel of molecular biomarkers, related with the response to treatment or drug resistance to NCT, as determined on the diagnostic tumor. The expression of 22 proteins was examined using immunohistochemistry in tissue microarrays (TMA) from 115 patients of stage II-III breast cancer, treated with NCT. Among studied proteins, there are some that are anti-apoptotic, pro-proliferative, cancer stem cell markers and the Vitamin D Receptor. Other proteins are involved in the identification of molecular subtype, cell cycle regulation or DNA repair. Next, a predictive signature of poor response was generated from independent markers of predictive value. Tumors that expressed four or five conditions (biomarkers of chemoresistance with a determinated cutoff) were associated with a 9-fold increase in the chances of these patients of having a poor response to NCT. Additionally, we also found a worse prognostic signature, generated from independent markers of prognostic value. Tumors which expressed two or three conditions of worst prognostic, were associated with a 6-fold reduction in Distant Disease Free Survival. In conclusion, finding biomarkers of chemoresitance (ypTNM II-III) and metastases can become a stepping stone for future studies that will need to be assessed in a bigger scale.

WONOEP appraisal: Biomarkers of epilepsy-associated comorbidities.

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Ravizza, Teresa; Onat, Filiz Y; Brooks-Kayal, Amy R; Depaulis, Antoine; Galanopoulou, Aristea S; Mazarati, Andrey; Numis, Adam L; Sankar, Raman; Friedman, Alon

2017-03-01

Neurologic and psychiatric comorbidities are common in patients with epilepsy. Diagnostic, predictive, and pharmacodynamic biomarkers of such comorbidities do not exist. They may share pathogenetic mechanisms with epileptogenesis/ictogenesis, and as such are an unmet clinical need. The objectives of the subgroup on biomarkers of comorbidities at the XIII Workshop on the Neurobiology of Epilepsy (WONOEP) were to present the state-of-the-art recent research findings in the field that highlighting potential biomarkers for comorbidities in epilepsy. We review recent progress in the field, including molecular, imaging, and genetic biomarkers of comorbidities as discussed during the WONOEP meeting on August 31-September 4, 2015, in Heybeliada Island (Istanbul, Turkey). We further highlight new directions and concepts from studies on comorbidities and potential new biomarkers for the prediction, diagnosis, and treatment of epilepsy-associated comorbidities. The activation of various molecular signaling pathways such as the "Janus Kinase/Signal Transducer and Activator of Transcription," "mammalian Target of Rapamycin," and oxidative stress have been shown to correlate with the presence and severity of subsequent cognitive abnormalities. Furthermore, dysfunction in serotonergic transmission, hyperactivity of the hypothalamic-pituitary-adrenocortical axis, the role of the inflammatory cytokines, and the contributions of genetic factors have all recently been regarded as relevant for understanding epilepsy-associated depression and cognitive deficits. Recent evidence supports the utility of imaging studies as potential biomarkers. The role of such biomarker may be far beyond the diagnosis of comorbidities, as accumulating clinical data indicate that comorbidities can predict epilepsy outcomes. Future research is required to reveal whether molecular changes in specific signaling pathways or advanced imaging techniques could be detected in the clinical settings and correlate

Elevation of brain-enriched miRNAs in cerebrospinal fluid of patients with acute ischemic stroke

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Sorensen, Sofie Solvsten; Nygaard, Ann-Britt; Carlsen, Anting Liu

2017-01-01

BackgroundThe purpose of this study was to investigate the potential of cerebrospinal fluid miRNAs as diagnostic biomarkers of acute ischemic stroke using three different profiling techniques in order to identify and bypass any influence from technical variation. MethodsCerebrospinal fluid (CSF) ...

Effect of pre-stroke use of ACE inhibitors on ischemic stroke severity

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Caplan Louis

2005-06-01

Full Text Available Abstract Background Recent trials suggest that angiotensin-converting enzyme inhibitors (ACEI are effective in prevention of ischemic stroke, as measured by reduced stroke incidence. We aimed to compare stroke severity between stroke patients who were taking ACEI before their stroke onset and those who were not, to examine the effects of pretreatment with ACEI on ischemic stroke severity. Methods We retrospectively studied 126 consecutive patients presenting within 24 hours of ischemic stroke onset, as confirmed by diffusion-weighted magnetic resonance imaging (DWI. We calculated the NIHSS score at presentation, as the primary measure of clinical stroke severity, and categorized stroke severity as mild (NIHSS [less than or equal to] 7, moderate (NIHSS 8–13 or severe (NIHSS [greater than or equal to] 14. We analyzed demographic data, risk-factor profile, blood pressure (BP and medications on admissions, and determined stroke mechanism according to TOAST criteria. We also measured the volumes of admission diffusion- and perfusion-weighted (DWI /PWI magnetic resonance imaging lesions, as a secondary measure of ischemic tissue volume. We compared these variables among patients on ACEI and those who were not. Results Thirty- three patients (26% were on ACE-inhibitors. The overall median baseline NIHSS score was 5.5 (range 2–21 among ACEI-treated patients vs. 9 (range 1–36 in non-ACEI patients (p = 0.036. Patients on ACEI prior to their stroke had more mild and less severe strokes, and smaller DWI and PWI lesion volumes compared to non-ACEI treated patients. However, none of these differences were significant. Predictably, a higher percentage of patients on ACEI had a history of heart failure (p = 0.03. Age, time-to-imaging or neurological evaluation, risk-factor profile, concomitant therapy with lipid lowering, other antihypertensives or antithrombotic agents, or admission BP were comparable between the two groups. Conclusion Our results

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

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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.

Protein consumptions in stroke patients

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Zahra Maghsoudi

2013-01-01

Full Text Available Background : Stroke is one of the most common causes of disabilities and death all over the world. The mortality rate of stroke is predicted to be doubled by 2030 in the Middle East countries. Nutrition is an effective strategy in prevention and management of stroke. This study assessed the relationship between various protein types and stroke risk. Materials and Methods: This hospital-based case-control study was performed in a University hospital. The data regarding consumption of usual food intake of 69 cases (46 men and 23 women and 60 controls (30 men and 30 women was collected with a food frequency questionnaire (FFQ. The mean consumption of red and white meat and vegetable and processed proteins consumption were compared between two groups. Results: The percent of total of daily protein intake were lower in patients with stroke in both sexes (25.92% vs 30.55% in men and 30.7% vs 31.14% in women. Conclusion: Lower protein consumption may be observed in patients with stroke patients in both sex.

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

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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.

Prognostic biomarkers in osteoarthritis

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Attur, Mukundan; Krasnokutsky-Samuels, Svetlana; Samuels, Jonathan; Abramson, Steven B.

2013-01-01

Purpose of review Identification of patients at risk for incident disease or disease progression in osteoarthritis remains challenging, as radiography is an insensitive reflection of molecular changes that presage cartilage and bone abnormalities. Thus there is a widely appreciated need for biochemical and imaging biomarkers. We describe recent developments with such biomarkers to identify osteoarthritis patients who are at risk for disease progression. Recent findings The biochemical markers currently under evaluation include anabolic, catabolic, and inflammatory molecules representing diverse biological pathways. A few promising cartilage and bone degradation and synthesis biomarkers are in various stages of development, awaiting further validation in larger populations. A number of studies have shown elevated expression levels of inflammatory biomarkers, both locally (synovial fluid) and systemically (serum and plasma). These chemical biomarkers are under evaluation in combination with imaging biomarkers to predict early onset and the burden of disease. Summary Prognostic biomarkers may be used in clinical knee osteoarthritis to identify subgroups in whom the disease progresses at different rates. This could facilitate our understanding of the pathogenesis and allow us to differentiate phenotypes within a heterogeneous knee osteoarthritis population. Ultimately, such findings may help facilitate the development of disease-modifying osteoarthritis drugs (DMOADs). PMID:23169101

Cardiovascular biomarkers and sex: the case for women.

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Daniels, Lori B; Maisel, Alan S

2015-10-01

Measurement of biomarkers is a critical component of cardiovascular care. Women and men differ in their cardiac physiology and manifestations of cardiovascular disease. Although most cardiovascular biomarkers are used by clinicians without taking sex into account, sex-specific differences in biomarkers clearly exist. Baseline concentrations of many biomarkers (including cardiac troponin, natriuretic peptides, galectin-3, and soluble ST2) differ in men versus women, but these sex-specific differences do not generally translate into a need for differential sex-based cut-off points. Furthermore, most biomarkers are similarly diagnostic and prognostic, regardless of sex. Two potential exceptions are cardiac troponins measured by high-sensitivity assay, and proneurotensin. Troponin levels are lower in women than in men and, with the use of high-sensitivity assays, sex-specific cut-off points might improve the diagnosis of myocardial infarction. Proneurotensin is a novel biomarker that was found to be predictive of incident cardiovascular disease in women, but not men, and was also predictive of incident breast cancer. If confirmed, proneurotensin might be a unique biomarker of disease risk in women. With any biomarker, an understanding of sex-specific differences might improve its use and might also lead to an enhanced understanding of the physiological differences between the hearts of men and women.

Development of the Stroke-unit Discharge Guideline: choice of assessment instruments for prediction in the subacute phase post-stroke

NARCIS (Netherlands)

Meijer, Ronald; van Limbeek, Jacques; de Haan, Rob

2006-01-01

The purpose of this paper is to present the design of an evidence-based dataset of assessment instruments for the prognostic factors of the Stroke-unit Discharge Guideline (SDG), a consensus based guideline for the decision of the discharge destination from the hospital stroke unit. In our

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

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

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Liou, Li-Min; Lin, Hsiu-Fen; Huang, I-Fang; Chang, Yang-Pei; Lin, Ruey-Tay; Lai, Chiou-Lian

2013-12-01

Vertigo can be a major presentation of posterior circulation stroke and can be easily misdiagnosed because of its complicated presentation. We thus prospectively assessed the predictive value of vertebral artery extracranial color-coded duplex sonography (ECCS) for the prediction of ischemic stroke-related vertigo. The inclusion criteria were: (1) a sensation of whirling (vertigo); (2) intractable vertigo for more than 1 hour despite appropriate treatment; and (3) those who could complete cranial magnetic resonance imaging (MRI) and vertebral artery (V2 segment) ECCS studies. Eventually, 76 consecutive participants with vertigo were enrolled from Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung, Taiwan between August 2010 and August 2011. Demographic data, neurological symptoms, neurologic examinations, and V2 ECCS were assessed. We chose the parameters of peak systolic velocity (PSV), end diastolic velocity (EDV), PSV/EDV, mean velocity (MV), resistance index (RI), and pulsatility index (PI) to represent the hemodynamics. Values from both sides of V2 segments were averaged. We then calculated the average RI (aRI), average PI (aPI), average PSV (aPSV)/EDV, and average (aMV). Axial and coronal diffusion-weighted MRI findings determined the existence of acute ischemic stroke. We grouped and analyzed participants in two ways (way I and way II analyses) based on the diffusion-weighted MRI findings (to determine whether there was acute stroke) and neurological examinations. Using way I analysis, the "MRI (+)" group had significantly higher impedance (aRI, aPI, and aPSV/EDV ratio) and lower velocity (aPSV, aEDV, and aMV(PSV + EDV/2)), compared to the "MRI (-)" group. The cutoff value/sensitivity/specificity of aPSV, aEDV, aMV, aPI, aRI, and aPSV/EDV between the MRI (+) and MRI (-) groups were 41.15/61.5/66.0 (p = 0.0101), 14.55/69.2/72.0 (p = 0.0003), 29.10/92.1/38.0 (p = 0.0013), 1.07/76.9/64.0 (p = 0.0066), 0.62/76.9/64.0 (p = 0.0076), and 2.69/80.8/66.0 (p = 0

Genetic View To Stroke Occurrence

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Sadegh Yoosefee

2017-02-01

Full Text Available Stroke is the third leading cause of death. The role of genetics in the etiology and development of this disease is undeniable. As a result of inadequate previous research, more and more studies in the field of genetics are necessary to identify pathways involved in the pathogenesis of stroke, which in turn, may lead to new therapeutic approaches. However, due to the multifactorial nature of stroke and the few studies conducted in this field, genetic diversity is able to predict only a small fraction of the risk of disease. On the other hand, studies have shown genetically different architecture for different types of stroke, and finally pharmacogenomics as an important part of personalized medicine approach, is influenced by genetic studies, all of which confirm the need of addressing the topic by researchers.

Predicting the Grade of Disability 1 Year After Stroke Following Rehabilitation

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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.

Personal exposure to benzene from fuel emissions among commercial fishers: comparison of two-stroke, four-stroke and diesel engines.

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Kirrane, Ellen; Loomis, Dana; Egeghy, Peter; Nylander-French, Leena

2007-03-01

Commercial fishers are exposed to unburned hydrocarbon vapors and combustion products present in the emissions from their boat engines. The objective of this study was to measure personal exposure to benzene as a marker of fuel exposure, and to predict exposure levels across categories of carbureted two-stroke, four-stroke and diesel engines. A self-monitoring approach, employing passive monitors, was used to obtain measurements of personal exposure to benzene over time. Mixed-effect linear regression models were used to predict exposure levels, identify significant effects and determine restricted maximum likelihood estimates for within- and between-person variance components. Significant fixed effects for engine type and refueling a car or truck were identified. After controlling for refueling, predicted benzene exposure levels to fishers on boats equipped with two-stroke, four-stroke and diesel engines were 58.4, 38.9 and 15.7 microg/m3, respectively. The logged within-person variance component was 1.43, larger than the between-person variance component of 1.13, indicating that the total variation may be attributable to monitor placement, environmental conditions and other factors that change over time as well as differences between individual work practices. The health consequences of exposure to marine engine emissions are not known. The predicted levels are well below those at which health effects have been attributed, however.

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

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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.

A risk score for in-hospital death in patients admitted with ischemic or hemorrhagic stroke.

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Smith, Eric E; Shobha, Nandavar; Dai, David; Olson, DaiWai M; Reeves, Mathew J; Saver, Jeffrey L; Hernandez, Adrian F; Peterson, Eric D; Fonarow, Gregg C; Schwamm, Lee H

2013-01-28

We aimed to derive and validate a single risk score for predicting death from ischemic stroke (IS), intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH). Data from 333 865 stroke patients (IS, 82.4%; ICH, 11.2%; SAH, 2.6%; uncertain type, 3.8%) in the Get With The Guidelines-Stroke database were used. In-hospital mortality varied greatly according to stroke type (IS, 5.5%; ICH, 27.2%; SAH, 25.1%; unknown type, 6.0%; Pmortality and to assign point scores for a prediction model in the overall population and in the subset with the National Institutes of Health Stroke Scale (NIHSS) recorded (37.1%). The c statistic, a measure of how well the models discriminate the risk of death, was 0.78 in the overall validation sample and 0.86 in the model including NIHSS. The model with NIHSS performed nearly as well in each stroke type as in the overall model including all types (c statistics for IS alone, 0.85; for ICH alone, 0.83; for SAH alone, 0.83; uncertain type alone, 0.86). The calibration of the model was excellent, as demonstrated by plots of observed versus predicted mortality. A single prediction score for all stroke types can be used to predict risk of in-hospital death following stroke admission. Incorporation of NIHSS information substantially improves this predictive accuracy.

Stroke in women - from evidence to inequalities

DEFF Research Database (Denmark)

Cordonnier, Charlotte; Sprigg, Nikola; Sandset, Else Charlotte

2017-01-01

Stroke is the second largest cause of disability-adjusted life-years lost worldwide. The prevalence of stroke in women is predicted to rise rapidly, owing to the increasing average age of the global female population. Vascular risk factors differ between women and men in terms of prevalence, and ...

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

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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

Clinical study on HAT and SEDAN score scales and related risk factors for predicting hemorrhagic transformation following thrombolysis in acute ischemic stroke

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Heng WEI

2015-03-01

Full Text Available Objective To investigate the value of HAT and SEDAN score scales in predicting hemorrhagic transformation (HT following the recombinant tissue-type plasminogen activator (rt-PA intravenous thrombolysis in acute ischemic stroke patients and risk factors affecting HT.  Methods A total of 143 patients with acute ischemic stroke underwent rt-PA intravenous thrombolysis within 4.50 h of onset and their clinical data were collected. According to head CT after thrombolysis, patients were divided into HT group (18 cases and non-HT group (125 cases. Single factor analysis was used to assess differences in HAT and SEDAN score scales and related risk factors of ischemic stroke in 2 groups, and further Logistic regression analysis was used to investigate independent predictors of HT. Receiver operating characteristic (ROC curve was used to evaluate the sensitivity and specificity of HAT and SEDAN score scales in predicting HT.  Results Univariate Logistic regression analysis showed that history of atrial fibrillation (AF, admission systolic blood pressure (SBP, admission blood glucose level, early low density of head CT, thrombolytic time window, National Institute of Health Stroke Scale (NIHSS, HAT and SEDAN scores were all risk factors for HT after thrombolysis (P < 0.05, for all. Multivariate Logistic regression analysis showed that history of AF (OR = 1.677, 95% CI: 1.332-2.111; P = 0.000, admission SBP (OR = 1.102, 95% CI: 1.009-1.204; P = 0.031, admission blood glucose level (OR = 1.870, 95% CI: 1.119-3.125; P = 0.017, thrombolysis time window (OR = 1.030, 95%CI: 1.009-1.052; P = 0.005, NIHSS score (OR = 1.574, 95%CI: 1.186-2.090; P = 0.002, HAT score (OR = 2.515, 95%CI: 1.273-4.970;P = 0.008 and SEDAN score (OR = 2.413, 95%CI: 1.123-5.185; P = 0.024 were risk factors for HT after thrombolysis. ROC curve analysis showed that HAT score could predict HT with 94.40% sensitivity and 41.60% specificity, and area under curve (AUC was 0.70. SEDAN

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

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

2013-11-08

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

Resting-State Functional Connectivity-Based Biomarkers and Functional MRI-Based Neurofeedback for Psychiatric Disorders: A Challenge for Developing Theranostic Biomarkers.

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Yamada, Takashi; Hashimoto, Ryu-Ichiro; Yahata, Noriaki; Ichikawa, Naho; Yoshihara, Yujiro; Okamoto, Yasumasa; Kato, Nobumasa; Takahashi, Hidehiko; Kawato, Mitsuo

2017-10-01

Psychiatric research has been hampered by an explanatory gap between psychiatric symptoms and their neural underpinnings, which has resulted in poor treatment outcomes. This situation has prompted us to shift from symptom-based diagnosis to data-driven diagnosis, aiming to redefine psychiatric disorders as disorders of neural circuitry. Promising candidates for data-driven diagnosis include resting-state functional connectivity MRI (rs-fcMRI)-based biomarkers. Although biomarkers have been developed with the aim of diagnosing patients and predicting the efficacy of therapy, the focus has shifted to the identification of biomarkers that represent therapeutic targets, which would allow for more personalized treatment approaches. This type of biomarker (i.e., "theranostic biomarker") is expected to elucidate the disease mechanism of psychiatric conditions and to offer an individualized neural circuit-based therapeutic target based on the neural cause of a condition. To this end, researchers have developed rs-fcMRI-based biomarkers and investigated a causal relationship between potential biomarkers and disease-specific behavior using functional MRI (fMRI)-based neurofeedback on functional connectivity. In this review, we introduce a recent approach for creating a theranostic biomarker, which consists mainly of 2 parts: (1) developing an rs-fcMRI-based biomarker that can predict diagnosis and/or symptoms with high accuracy, and (2) the introduction of a proof-of-concept study investigating the relationship between normalizing the biomarker and symptom changes using fMRI-based neurofeedback. In parallel with the introduction of recent studies, we review rs-fcMRI-based biomarker and fMRI-based neurofeedback, focusing on the technological improvements and limitations associated with clinical use. © The Author 2017. Published by Oxford University Press on behalf of CINP.

Application of bio-marker to study on tumor radiosensitivity

International Nuclear Information System (INIS)

Guo Wanfeng; Ding Guirong; Han Liangfu

2001-01-01

To definite tumor radiosensitivity is important for applying the schedules of individualization of patient radiotherapy. Many laboratories were carrying on the research which predict the tumor radiosensitivity with one bio-marker or/and multi-bio-marker in various levels. At present has not witnessed the specific bio-marker, but it provides an excellent model for predicting tumor radiosensitivity

Risk prediction in stable cardiovascular disease using a high-sensitivity cardiac troponin T single biomarker strategy compared to the ESC-SCORE.

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Biener, Moritz; Giannitsis, Evangelos; Kuhner, Manuel; Zelniker, Thomas; Mueller-Hennessen, Matthias; Vafaie, Mehrshad; Stoyanov, Kiril M; Neumann, Franz-Josef; Katus, Hugo A; Hochholzer, Willibald; Valina, Christian Marc

2018-01-01

To evaluate the prognostic performance of high-sensitivity cardiac troponin T (hs-cTnT) compared with the ESC-SCORE. We included low-risk outpatients with stable cardiovascular (CV) disease categorised into need for non-secondary and secondary prevention. The prognostication of hs-cTnT at index visit was compared with the European Society of Cardiology-Systematic COronary Risk Evaluation (ESC-SCORE) with respect to all-cause mortality (ACM) and two composite endpoints (ACM, acute myocardial infarction (AMI) and stroke and ACM, AMI, stroke and rehospitalisation for acute coronary syndrome (ACS) and decompensated heart failure (DHF)). Within a median follow-up of 796 days, a total of 16 deaths, 32 composite endpoints of ACM, AMI and stroke and 83 composite endpoints of ACM, AMI, stroke, rehospitalisation for ACS and DHF were observed among 693 stable low-risk outpatients. Using C-statistics, measurement of hs-cTnT alone outperformed the ESC-SCORE for the prediction of ACM in the entire study population (Δarea under the curve (AUC) 0.221, p=0.0039) and both prevention groups (non-secondary: ΔAUC 0.164, p=0.0208; secondary: ΔAUC 0.264, p=0.0134). For the prediction of all other secondary endpoints, hs-cTnT was at least as effective as the ESC-SCORE, both in secondary and non-secondary prevention. Using continuous and categorical net reclassification improvement and integrated discrimination improvement, hs-cTnT significantly improved reclassification regarding all endpoints in the entire population and in the secondary prevention cohort. In non-secondary prevention, hs-cTnT improved reclassification only for ACM. The results were confirmed in an independent external cohort on 2046 patients. Hs-cTnT is superior to the multivariable ESC-SCORE for the prediction of ACM and a composite endpoint in stable outpatients with and without relevant CV disease. NCT01954303; Pre-results.

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

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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.

Unfulfilled rehabilitation needs and dissatisfaction with care 12 months after a stroke

DEFF Research Database (Denmark)

Tistad, Malin; Tham, Kerstin; von Koch, Lena

2012-01-01

a questionnaire. Stroke severity, domains of the Stroke Impact Scale (SIS), the Sense of Coherence scale (SOC) and socio demographic factors were used as independent variables in four logistic regression analyses. RESULTS: Unfulfilled needs for rehabilitation at 12 months were predicted by strength (SIS) (odds......BACKGROUND: People who have suffered a stroke commonly report unfulfilled need for rehabilitation. Using a model of patient satisfaction, we examined characteristics in individuals that at 3 months after stroke predicted, or at 12 months were associated with unmet need for rehabilitation...... or dissatisfaction with health care services at 12 months after stroke. METHODS: The participants (n = 175) received care at the stroke units at the Karolinska University Hospital, Sweden. The dependent variables "unfulfilled needs for rehabilitation" and "dissatisfaction with care" were collected using...

Microalbuminuria indicates long-term vascular risk in patients after acute stroke undergoing in-patient rehabilitation

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Sander Dirk

2012-09-01

Full Text Available Abstract Background Patients in neurologic in-patient rehabilitation are at risk of cardio- and cerebrovascular events. Microalbuminuria (MAU is frequent and an important risk predictor but has not been validated in in-patient rehabilitation. We therefore aimed to examine MAU as an indicator of risk and predictor of vascular events in a prospective study. Methods The INSIGHT (INvestigation of patients with ischemic Stroke In neuroloGic reHabiliTation registry is the first to provide large scale data on 1,167 patients with acute stroke (χ2 or Mann–Whitney-U Test. Relative risks (RR with 95% confidence intervals (CI were estimated using log-binominal models. To evaluate the association between MAU and new vascular events as well as mortality, we calculated hazard ratios (HR using Cox proportional hazard regression. Results A substantial proportion of patients was MAU positive at baseline (33.1%. Upon univariate analysis these patients were about 4 years older (69 vs. 65 years; p 2; p = 0.03 and increased waist circumference (79.5 vs. 50.4% for women [p  Conclusions INSIGHT demonstrated a significant association between MAU and polyvascular disease and further supports previous findings that MAU predicts cardio-/cerebrovascular events in patients recovering from ischemic stroke. This biomarker may also be used in patients during neurologic in-patient rehabilitation, opening a window of opportunity for early intervention in this patient group at increased risk for recurrent events.

The Biomarker GlycA Is Associated with Chronic Inflammation and Predicts Long-Term Risk of Severe Infection.

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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.

Biomarkers, Trauma, and Sepsis in Pediatrics: A Review

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Marianne Frieri

2016-01-01

Full Text Available Context: There is a logical connection with biomarkers, trauma, and sepsis. This review paper provides new information and clinical practice implications. Biomarkers are very important especially in pediatrics. Procalcitonin and other biomarkers are helpful in identifying neonatal sepsis, defense mechanisms of the immune system. Pediatric trauma and sepsis is very important both in infants and in children. Stress management both in trauma is based upon the notion that stress causes an immune imbalance in susceptible individuals. Evidence Acquisition: Data sources included studies indexed in PubMed, a meta- analysis, predictive values, research strategies, and quality assessments. A recent paper by one of the authors stated marked increase in serum procalcitonin during the course of a septic process often indicates an exacerbation of the illness, and a decreasing level is a sign of improvement. A review of epidemiologic studies on pediatric soccer patients was also addressed. Keywords for searching included biomarkers, immunity, trauma, and sepsis. Results: Of 50 reviewed articles, 34 eligible articles were selected including biomarkers, predictive values for procalcitonin, identifying children at risk for intra-abdominal injuries, blunt trauma, and epidemiology, a meta-analysis. Of neonatal associated sepsis, the NF-kappa B pathway by inflammatory stimuli in human neutrophils, predictive value of gelsolin for the outcomes of preterm neonates, a meta-analysis interleukin-8 for neonatal sepsis diagnosis. Conclusions: Biomarkers are very important especially in pediatrics. Procalcitonin and other biomarkers are helpful in identifying neonatal sepsis, defense mechanisms, and physiological functions of the immune system. Pediatric trauma and sepsis is very important both in infants and in children. Various topics were covered such as biomarkers, trauma, sepsis, inflammation, innate immunity, role of neutrophils and IL-8, reactive oxygen species

Biomarkers for equine joint injury and osteoarthritis.

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McIlwraith, C Wayne; Kawcak, Christopher E; Frisbie, David D; Little, Christopher B; Clegg, Peter D; Peffers, Mandy J; Karsdal, Morten A; Ekman, Stina; Laverty, Sheila; Slayden, Richard A; Sandell, Linda J; Lohmander, L S; Kraus, Virginia B

2018-03-01

We report the results of a symposium aimed at identifying validated biomarkers that can be used to complement clinical observations for diagnosis and prognosis of joint injury leading to equine osteoarthritis (OA). Biomarkers might also predict pre-fracture change that could lead to catastrophic bone failure in equine athletes. The workshop was attended by leading scientists in the fields of equine and human musculoskeletal biomarkers to enable cross-disciplinary exchange and improve knowledge in both. Detailed proceedings with strategic planning was written, added to, edited and referenced to develop this manuscript. The most recent information from work in equine and human osteoarthritic biomarkers was accumulated, including the use of personalized healthcare to stratify OA phenotypes, transcriptome analysis of anterior cruciate ligament (ACL) and meniscal injuries in the human knee. The spectrum of "wet" biomarker assays that are antibody based that have achieved usefulness in both humans and horses, imaging biomarkers and the role they can play in equine and human OA was discussed. Prediction of musculoskeletal injury in the horse remains a challenge, and the potential usefulness of spectroscopy, metabolomics, proteomics, and development of biobanks to classify biomarkers in different stages of equine and human OA were reviewed. The participants concluded that new information and studies in equine musculoskeletal biomarkers have potential translational value for humans and vice versa. OA is equally important in humans and horses, and the welfare issues associated with catastrophic musculoskeletal injury in horses add further emphasis to the need for good validated biomarkers in the horse. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:823-831, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

A Contemporary Review of the Treatment Landscape and the Role of Predictive and Prognostic Biomarkers in Pancreatic Adenocarcinoma

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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.

Diagnostic and prognostic epigenetic biomarkers in cancer.

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Costa-Pinheiro, Pedro; Montezuma, Diana; Henrique, Rui; Jerónimo, Carmen

2015-01-01

Growing cancer incidence and mortality worldwide demands development of accurate biomarkers to perfect detection, diagnosis, prognostication and monitoring. Urologic (prostate, bladder, kidney), lung, breast and colorectal cancers are the most common and despite major advances in their characterization, this has seldom translated into biomarkers amenable for clinical practice. Epigenetic alterations are innovative cancer biomarkers owing to stability, frequency, reversibility and accessibility in body fluids, entailing great potential of assay development to assist in patient management. Several studies identified putative epigenetic cancer biomarkers, some of which have been commercialized. However, large multicenter validation studies are required to foster translation to the clinics. Herein we review the most promising epigenetic detection, diagnostic, prognostic and predictive biomarkers for the most common cancers.

Novel biomarker-based model for the prediction of sorafenib response and overall survival in advanced hepatocellular carcinoma: a prospective cohort study.

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Kim, Hwi Young; Lee, Dong Hyeon; Lee, Jeong-Hoon; Cho, Young Youn; Cho, Eun Ju; Yu, Su Jong; Kim, Yoon Jun; Yoon, Jung-Hwan

2018-03-20

Prediction of the outcome of sorafenib therapy using biomarkers is an unmet clinical need in patients with advanced hepatocellular carcinoma (HCC). The aim was to develop and validate a biomarker-based model for predicting sorafenib response and overall survival (OS). This prospective cohort study included 124 consecutive HCC patients (44 with disease control, 80 with progression) with Child-Pugh class A liver function, who received sorafenib. Potential serum biomarkers (namely, hepatocyte growth factor [HGF], fibroblast growth factor [FGF], vascular endothelial growth factor receptor-1, CD117, and angiopoietin-2) were tested. After identifying independent predictors of tumor response, a risk scoring system for predicting OS was developed and 3-fold internal validation was conducted. A risk scoring system was developed with six covariates: etiology, platelet count, Barcelona Clinic Liver Cancer stage, protein induced by vitamin K absence-II, HGF, and FGF. When patients were stratified into low-risk (score ≤ 5), intermediate-risk (score 6), and high-risk (score ≥ 7) groups, the model provided good discriminant functions on tumor response (concordance [c]-index, 0.884) and 12-month survival (area under the curve [AUC], 0.825). The median OS was 19.0, 11.2, and 6.1 months in the low-, intermediate-, and high-risk group, respectively (P functions on tumor response (c-index, 0.825) and 12-month survival (AUC, 0.803), and good calibration functions (all P > 0.05 between expected and observed values). This new model including serum FGF and HGF showed good performance in predicting the response to sorafenib and survival in patients with advanced HCC.

Biomarkers of the Dementia

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Mikio Shoji

2011-01-01

Full Text Available Recent advances in biomarker studies on dementia are summarized here. CSF Aβ40, Aβ42, total tau, and phosphorylated tau are the most sensitive biomarkers for diagnosis of Alzheimer's disease (AD and prediction of onset of AD from mild cognitive impairment (MCI. Based on this progress, new diagnostic criteria for AD, MCI, and preclinical AD were proposed by National Institute of Aging (NIA and Alzheimer's Association in August 2010. In these new criteria, progress in biomarker identification and amyloid imaging studies in the past 10 years have added critical information. Huge contributions of basic and clinical studies have established clinical evidence supporting these markers. Based on this progress, essential therapy for cure of AD is urgently expected.

Adipose tissue and metabolic and inflammatory responses to stroke are altered in obese mice

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Michael J. Haley

2017-10-01

Full Text Available Obesity is an independent risk factor for stroke, although several clinical studies have reported that obesity improves stroke outcome. Obesity is hypothesised to aid recovery by protecting against post-stroke catabolism. We therefore assessed whether obese mice had an altered metabolic and inflammatory response to stroke. Obese ob/ob mice underwent a 20-min middle cerebral artery occlusion and 24-h reperfusion. Lipid metabolism and expression of inflammatory cytokines were assessed in the plasma, liver and adipose tissue. The obese-specific metabolic response to stroke was assessed in plasma using non-targeted ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS metabolomics coupled with univariate and multivariate analysis. Obesity had no effect on the extent of weight loss 24 h after stroke but affected the metabolic and inflammatory responses to stroke, predominantly affecting lipid metabolism. Specifically, obese mice had increases in plasma free fatty acids and expression of adipose lipolytic enzymes. Metabolomics identified several classes of metabolites affected by stroke in obese mice, including fatty acids and membrane lipids (glycerophospholipids, lysophospholipids and sphingolipids. Obesity also featured increases in inflammatory cytokines in the plasma and adipose tissue. Overall, these results demonstrate that obesity affected the acute metabolic and inflammatory response to stroke and suggest a potential role for adipose tissue in this effect. These findings could have implications for longer-term recovery and also further highlight the importance of considering comorbidities in preclinical stroke research, especially when identifying biomarkers for stroke. However, further work is required to assess whether these changes translate into long-term effects on recovery.

Biomarkers for Response to Neoadjuvant Chemoradiation for Rectal Cancer

International Nuclear Information System (INIS)

Kuremsky, Jeffrey G.; Tepper, Joel E.; McLeod, Howard L. Phar

2009-01-01

Locally advanced rectal cancer (LARC) is currently treated with neoadjuvant chemoradiation. Although approximately 45% of patients respond to neoadjuvant therapy with T-level downstaging, there is no effective method of predicting which patients will respond. Molecular biomarkers have been investigated for their ability to predict outcome in LARC treated with neoadjuvant chemotherapy and radiation. A literature search using PubMed resulted in the initial assessment of 1,204 articles. Articles addressing the ability of a biomarker to predict outcome for LARC treated with neoadjuvant chemotherapy and radiation were included. Six biomarkers met the criteria for review: p53, epidermal growth factor receptor (EGFR), thymidylate synthase, Ki-67, p21, and bcl-2/bax. On the basis of composite data, p53 is unlikely to have utility as a predictor of response. Epidermal growth factor receptor has shown promise as a predictor when quantitatively evaluated in pretreatment biopsies or when EGFR polymorphisms are evaluated in germline DNA. Thymidylate synthase, when evaluated for polymorphisms in germline DNA, is promising as a predictive biomarker. Ki-67 and bcl-2 are not useful in predicting outcome. p21 needs to be further evaluated to determine its usefulness in predicting outcome. Bax requires more investigation to determine its usefulness. Epidermal growth factor receptor, thymidylate synthase, and p21 should be evaluated in larger prospective clinical trials for their ability to guide preoperative therapy choices in LARC.

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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...

Value of Combining Left Atrial Diameter and Amino-terminal Pro-brain Natriuretic Peptide to the CHA2DS2-VASc Score for Predicting Stroke and Death in Patients with Sick Sinus Syndrome after Pacemaker Implantation.

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Mo, Bin-Feng; Lu, Qiu-Fen; Lu, Shang-Biao; Xie, Yu-Quan; Feng, Xiang-Fei; Li, Yi-Gang

2017-08-20

The CHA2DS2-VASc score is used clinically for stroke risk stratification in patients with atrial fibrillation (AF). We sought to investigate whether the CHA2DS2-VASc score predicts stroke and death in Chinese patients with sick sinus syndrome (SSS) after pacemaker implantation and to evaluate whether the predictive power of the CHA2DS2-VASc score could be improved by combining it with left atrial diameter (LAD) and amino-terminal pro-brain natriuretic peptide (NT-proBNP). A total of 481 consecutive patients with SSS who underwent pacemaker implantation from January 2004 to December 2014 in our department were included. The CHA2DS2-VASc scores were retrospectively calculated according to the hospital medical records before pacemaker implantation. The outcome data (stroke and death) were collected by pacemaker follow-up visits and telephonic follow-up until December 31, 2015. During 2151 person-years of follow-up, 46 patients (9.6%) suffered stroke and 52 (10.8%) died. The CHA2DS2-VASc score showed a significant association with the development of stroke (hazard ratio [HR] 1.45, 95% confidence interval [CI] 1.20-1.75, Ppacemaker implantation. The addition of LAD and NT-proBNP to the CHA2DS2-VASc score improved its predictive power for stroke and death, respectively, in this patient cohort. Future prospective studies are warranted to validate the benefit of adding LAD and NT-proBNP to the CHA2DS2-VASc score for predicting stroke and death risk in non-AF populations.

Multi-site laser Doppler flowmetry for assessing collateral flow in experimental ischemic stroke: Validation of outcome prediction with acute MRI.

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Cuccione, Elisa; Versace, Alessandro; Cho, Tae-Hee; Carone, Davide; Berner, Lise-Prune; Ong, Elodie; Rousseau, David; Cai, Ruiyao; Monza, Laura; Ferrarese, Carlo; Sganzerla, Erik P; Berthezène, Yves; Nighoghossian, Norbert; Wiart, Marlène; Beretta, Simone; Chauveau, Fabien

2017-06-01

High variability in infarct size is common in experimental stroke models and affects statistical power and validity of neuroprotection trials. The aim of this study was to explore cerebral collateral flow as a stratification factor for the prediction of ischemic outcome. Transient intraluminal occlusion of the middle cerebral artery was induced for 90 min in 18 Wistar rats. Cerebral collateral flow was assessed intra-procedurally using multi-site laser Doppler flowmetry monitoring in both the lateral middle cerebral artery territory and the borderzone territory between middle cerebral artery and anterior cerebral artery. Multi-modal magnetic resonance imaging was used to assess acute ischemic lesion (diffusion-weighted imaging, DWI), acute perfusion deficit (time-to-peak, TTP), and final ischemic lesion at 24 h. Infarct volumes and typology at 24 h (large hemispheric versus basal ganglia infarcts) were predicted by both intra-ischemic collateral perfusion and acute DWI lesion volume. Collateral flow assessed by multi-site laser Doppler flowmetry correlated with the corresponding acute perfusion deficit using TTP maps. Multi-site laser Doppler flowmetry monitoring was able to predict ischemic outcome and perfusion deficit in good agreement with acute MRI. Our results support the additional value of cerebral collateral flow monitoring for outcome prediction in experimental ischemic stroke, especially when acute MRI facilities are not available.

Comparison of Medicare claims versus physician adjudication for identifying stroke outcomes in the Women's Health Initiative.

Science.gov (United States)

Lakshminarayan, Kamakshi; Larson, Joseph C; Virnig, Beth; Fuller, Candace; Allen, Norrina Bai; Limacher, Marian; Winkelmayer, Wolfgang C; Safford, Monika M; Burwen, Dale R

2014-03-01

Many studies use medical record review for ascertaining outcomes. One large, longitudinal study, the Women's Health Initiative (WHI), ascertains strokes using participant self-report and subsequent physician review of medical records. This is resource-intensive. Herein, we assess whether Medicare data can reliably assess stroke events in the WHI. Subjects were WHI participants with fee-for-service Medicare. Four stroke definitions were created for Medicare data using discharge diagnoses in hospitalization claims: definition 1, stroke codes in any position; definition 2, primary position stroke codes; and definitions 3 and 4, hemorrhagic and ischemic stroke codes, respectively. WHI data were randomly split into training (50%) and test sets. A concordance matrix was used to examine the agreement between WHI and Medicare stroke diagnosis. A WHI stroke and a Medicare stroke were considered a match if they occurred within ±7 days of each other. Refined analyses excluded Medicare events when medical records were unavailable for comparison. Training data consisted of 24 428 randomly selected participants. There were 577 WHI strokes and 557 Medicare strokes using definition 1. Of these, 478 were a match. With regard to algorithm performance, specificity was 99.7%, negative predictive value was 99.7%, sensitivity was 82.8%, positive predictive value was 85.8%, and κ=0.84. Performance was similar for test data. Whereas specificity and negative predictive value exceeded 99%, sensitivity ranged from 75% to 88% and positive predictive value ranged from 80% to 90% across stroke definitions. Medicare data seem useful for population-based stroke research; however, performance characteristics depend on the definition selected.

The Impact of Conscious Sedation versus General Anesthesia for Stroke Thrombectomy on the Predictive Value of Collateral Status: A Post Hoc Analysis of the SIESTA Trial.