Dataset Information

Atrial Fibrillation Is Associated With a Worse 90-Day Outcome Than Other Cardioembolic Stroke Subtypes.

ABSTRACT: Patients with a cardioembolic stroke (CES) have worse outcomes than stroke patients with other causes of stroke. Among patients with CES, atrial fibrillation (AF) is a common comorbidity. Mounting data indicate that AF may be related to stroke pathogenesis beyond acute cerebral thromboembolism. We sought to determine whether AF represents an independent risk factor for stroke severity and outcome among patients with CES.We retrospectively analyzed patients with acute hemispheric CES included in an academic medical center's stroke registry. CES was determined using the Causative Classification System of ischemic stroke. Multivariable logistic regression was used to determine whether AF was associated with 90-day outcome functional status.Our cohort included 140 patients. Of these, 52 had prevalent AF and 28 had incident AF diagnosed during their index hospitalization or within 90 days of hospital discharge. After adjustment for potential confounders or mediators, any AF (odds ratio, 2.51; 95% confidence interval, 1.03-6.33; P=0.049), infarct volume (odds ratio, 1.03; 95% confidence interval, 1.01-1.06; P=0.005), preadmission modified Rankin Scale score (odds ratio, 2.58; 95% confidence interval, 1.66-4.01; P<0.001), and admission National Institutes of Health Stroke Scale score (odds ratio, 1.17; 95% confidence interval, 1.08-1.28; P<0.001) remained associated with an unfavorable 90-day outcome (modified Rankin Scale score, 2-6).AF is associated with an unfavorable 90-day outcome among patients with a CES independent of established risk factors and initial stroke severity. This suggests that AF-specific mechanisms affect CES severity and functional status after CES. If confirmed in future studies, further investigation into the underlying pathophysiological mechanisms may provide novel avenues to AF detection and treatment.

SUBMITTER: Henninger N

PROVIDER: S-EPMC4880452 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Atrial Fibrillation Is Associated With a Worse 90-Day Outcome Than Other Cardioembolic Stroke Subtypes.

Henninger Nils N Goddeau Richard P RP Karmarkar Ameeta A Helenius Johanna J McManus David D DD

Stroke 20160505 6

<h4>Background and purpose</h4>Patients with a cardioembolic stroke (CES) have worse outcomes than stroke patients with other causes of stroke. Among patients with CES, atrial fibrillation (AF) is a common comorbidity. Mounting data indicate that AF may be related to stroke pathogenesis beyond acute cerebral thromboembolism. We sought to determine whether AF represents an independent risk factor for stroke severity and outcome among patients with CES.<h4>Methods</h4>We retrospectively analyzed p ...[more]

PMID: 27217503

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Project description:Background and Purpose- Classification of stroke as cardioembolic in etiology can be challenging, particularly since the predominant cause, atrial fibrillation (AF), may not be present at the time of stroke. Efficient tools that discriminate cardioembolic from noncardioembolic strokes may improve care as anticoagulation is frequently indicated after cardioembolism. We sought to assess and quantify the discriminative power of AF risk as a classifier for cardioembolism in a real-world population of patients with acute ischemic stroke. Methods- We performed a cross-sectional analysis of a multi-institutional sample of patients with acute ischemic stroke. We systematically adjudicated stroke subtype and examined associations between AF risk using CHA2DS2-VASc, Cohorts for Heart and Aging Research in Genomic Epidemiology-AF score, and the recently developed Electronic Health Record-Based AF score, and cardioembolic stroke using logistic regression. We compared the ability of AF risk to discriminate cardioembolism by calculating C statistics and sensitivity/specificity cutoffs for cardioembolic stroke. Results- Of 1431 individuals with ischemic stroke (age, 65±15; 40% women), 323 (22.6%) had cardioembolism. AF risk was significantly associated with cardioembolism (CHA2DS2-VASc: odds ratio [OR] per SD, 1.69 [95% CI, 1.49-1.93]; Cohorts for Heart and Aging Research in Genomic Epidemiology-AF score: OR, 2.22 [95% CI, 1.90-2.60]; electronic Health Record-Based AF: OR, 2.55 [95% CI, 2.16-3.04]). Discrimination was greater for Cohorts for Heart and Aging Research in Genomic Epidemiology-AF score (C index, 0.695 [95% CI, 0.663-0.726]) and Electronic Health Record-Based AF score (0.713 [95% CI, 0.681-0.744]) versus CHA2DS2-VASc (C index, 0.651 [95% CI, 0.619-0.683]). Examination of AF scores across a range of thresholds indicated that AF risk may facilitate identification of individuals at low likelihood of cardioembolism (eg, negative likelihood ratios for Electronic Health Record-Based AF score ranged 0.31-0.10 at sensitivity thresholds 0.90-0.99). Conclusions- AF risk scores associate with cardioembolic stroke and exhibit moderate discrimination. Utilization of AF risk scores at the time of stroke may be most useful for identifying individuals at low probability of cardioembolism. Future analyses are warranted to assess whether stroke subtype classification can be enhanced to improve outcomes in undifferentiated stroke.

Project description:Background and purposeLarge-scale observational studies of acute ischemic stroke (AIS) promise to reveal mechanisms underlying cerebral ischemia. However, meaningful quantitative phenotypes attainable in large patient populations are needed. We characterize a dynamic metric of AIS instability, defined by change in National Institutes of Health Stroke Scale score (NIHSS) from baseline to 24 hours baseline to 24 hours (NIHSSbaseline - NIHSS24hours = ΔNIHSS6-24h), to examine its relevance to AIS mechanisms and long-term outcomes.MethodsPatients with NIHSS prospectively recorded within 6 hours after onset and then 24 hours later were enrolled in the GENISIS study (Genetics of Early Neurological Instability After Ischemic Stroke). Stepwise linear regression determined variables that independently influenced ΔNIHSS6-24h. In a subcohort of tPA (alteplase)-treated patients with large vessel occlusion, the influence of early sustained recanalization and hemorrhagic transformation on ΔNIHSS6-24h was examined. Finally, the association of ΔNIHSS6-24h with 90-day favorable outcomes (modified Rankin Scale score 0-2) was assessed. Independent analysis was performed using data from the 2 NINDS-tPA stroke trials (National Institute of Neurological Disorders and Stroke rt-PA).ResultsFor 2555 patients with AIS, median baseline NIHSS was 9 (interquartile range, 4-16), and median ΔNIHSS6-24h was 2 (interquartile range, 0-5). In a multivariable model, baseline NIHSS, tPA-treatment, age, glucose, site, and systolic blood pressure independently predicted ΔNIHSS6-24h (R2=0.15). In the large vessel occlusion subcohort, early sustained recanalization and hemorrhagic transformation increased the explained variance (R2=0.27), but much of the variance remained unexplained. ΔNIHSS6-24h had a significant and independent association with 90-day favorable outcome. For the subjects in the 2 NINDS-tPA trials, ΔNIHSS3-24h was similarly associated with 90-day outcomes.ConclusionsThe dynamic phenotype, ΔNIHSS6-24h, captures both explained and unexplained mechanisms involved in AIS and is significantly and independently associated with long-term outcomes. Thus, ΔNIHSS6-24h promises to be an easily obtainable and meaningful quantitative phenotype for large-scale genomic studies of AIS.

Project description:Atrial fibrillation (AF) is a major risk factor for ischemic stroke. We aimed to identify novel potential biomarkers with diagnostic value in patients with atrial fibrillation-related cardioembolic stroke (AF-CE).Publicly available gene expression profiles related to AF, cardioembolic stroke (CE), and large artery atherosclerosis (LAA) were downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified and then functionally annotated. The support vector machine recursive feature elimination (SVM-RFE) and least absolute shrinkage and selection operator (LASSO) regression analysis were conducted to identify potential diagnostic AF-CE biomarkers. Furthermore, the results were validated by using external data sets, and discriminability was measured by the area under the ROC curve (AUC). In order to verify the predictive results, the blood samples of 13 healthy controls, 20 patients with CE, and 20 patients with LAA stroke were acquired for RT-qPCR, and the correlation between biomarkers and clinical features was further explored. Lastly, a nomogram and the companion website were developed to predict the CE-risk rate. Three feature genes (C1QC, VSIG4, and CFD) were selected and validated in the training and the external datasets. The qRT-PCR evaluation showed that the levels of blood biomarkers (C1QC, VSIG4, and CFD) in patients with AF-CE can be used to differentiate patients with AF-CE from normal controls (P < 0.05) and can effectively discriminate AF-CE from LAA stroke (P < 0.05). Immune cell infiltration analysis revealed that three feature genes were correlated with immune system such as neutrophils. Clinical impact curve, calibration curves, ROC, and DCAs of the nomogram indicate that the nomogram had good performance. Our findings showed that C1QC, VSIG4, and CFD can potentially serve as diagnostic blood biomarkers of AF-CE; novel nomogram and the companion website can help clinicians to identify high-risk individuals, thus helping to guide treatment decisions for stroke patients.

Project description:ObjectiveTo determine whether altered metabolic profiles represent a link between atrial dysfunction and cardioembolic (CE) stroke, and thus whether underlying dysfunctional atrial substrate may contribute to thromboembolism risk in CE stroke.MethodsA total of 144 metabolites were measured using liquid chromatography-tandem mass spectrometry in plasma samples collected within 9 hours of stroke onset in 367 acute stroke patients. Stroke subtype was assigned using the Causative Classification of Stroke System, and CE stroke (n = 181) was compared to non-CE stroke (n = 186). Markers of left atrial dysfunction included abnormal atrial function (P-wave terminal force in lead V1, PTFV1 >4,000 μV·ms), left atrial enlargement on echocardiography, and frank atrial fibrillation on ECG. Stroke recurrence risk was assessed using CHADS2 and CHA2DS2-VASc scores. Associations between metabolites and CE stroke, atrial dysfunction, and stroke recurrence risk were evaluated using logistic regression models.ResultsThree tricarboxylic acid metabolites-succinate (odds ratio [OR] 1.71, 95% confidence interval [CI] 1.36-2.15, p = 1.37 × 10-6), α-ketoglutarate (OR 1.62, 95% CI 1.29-2.04, p = 1.62 × 10-5), and malate (OR 1.58, 95% CI 1.26-1.97, p = 2.57 × 10-5)-were associated with CE stroke. Succinate (OR 1.36, 95% CI 1.31-1.98, p = 1.22 × 10-6), α-ketoglutarate (OR 2.14, 95% CI 1.60-2.87, p = 2.08 × 10-8), and malate (OR 2.02, 95% CI 1.53-2.66, p = 1.60 × 10-7) were among metabolites also associated with subclinical atrial dysfunction. Of these, succinate was also associated with left atrial enlargement (OR 1.54, 95% CI 1.23-1.94, p = 1.06 × 10-4) and stroke recurrence based on dichotomized CHADS2 (OR 2.63, 95% CI 1.68-4.13, p = 3.00 × 10-6) and CHA2DS2-VASc (OR 2.43, 95% CI 1.60-3.68, p = 4.25 × 10-6) scores.ConclusionsMetabolite profiling identified changes in succinate associated with CE stroke, atrial dysfunction, and stroke recurrence, revealing a putative underlying link between CE stroke and energy metabolism.

Dataset Information

Atrial Fibrillation Is Associated With a Worse 90-Day Outcome Than Other Cardioembolic Stroke Subtypes.

Publications

Atrial Fibrillation Is Associated With a Worse 90-Day Outcome Than Other Cardioembolic Stroke Subtypes.

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