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Cardioembolic Stroke.

ABSTRACT: Cardiac embolism accounts for an increasing proportion of ischemic strokes and might multiply several-fold during the next decades. However, research points to several potential strategies to stem this expected rise in cardioembolic stroke. First, although one-third of strokes are of unclear cause, it is increasingly accepted that many of these cryptogenic strokes arise from a distant embolism rather than in situ cerebrovascular disease, leading to the recent formulation of embolic stroke of undetermined source as a distinct target for investigation. Second, recent clinical trials have indicated that embolic stroke of undetermined source may often stem from subclinical atrial fibrillation, which can be diagnosed with prolonged heart rhythm monitoring. Third, emerging evidence indicates that a thrombogenic atrial substrate can lead to atrial thromboembolism even in the absence of atrial fibrillation. Such an atrial cardiomyopathy may explain many cases of embolic stroke of undetermined source, and oral anticoagulant drugs may prove to reduce stroke risk from atrial cardiomyopathy given its parallels to atrial fibrillation. Non-vitamin K antagonist oral anticoagulant drugs have recently expanded therapeutic options for preventing cardioembolic stroke and are currently being tested for stroke prevention in patients with embolic stroke of undetermined source, including specifically those with atrial cardiomyopathy. Fourth, increasing appreciation of thrombogenic atrial substrate and the common coexistence of cardiac and extracardiac stroke risk factors suggest benefits from global vascular risk factor management in addition to anticoagulation. Finally, improved imaging of ventricular thrombus plus the availability of non-vitamin K antagonist oral anticoagulant drugs may lead to better prevention of stroke from acute myocardial infarction and heart failure.

SUBMITTER: Kamel H

PROVIDER: S-EPMC5312810 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Cardioembolic Stroke.

Kamel Hooman H Healey Jeff S JS

Circulation research 20170201 3

Cardiac embolism accounts for an increasing proportion of ischemic strokes and might multiply several-fold during the next decades. However, research points to several potential strategies to stem this expected rise in cardioembolic stroke. First, although one-third of strokes are of unclear cause, it is increasingly accepted that many of these cryptogenic strokes arise from a distant embolism rather than in situ cerebrovascular disease, leading to the recent formulation of embolic stroke of und ...[more]

PMID: 28154101

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Project description:Background and purposeOral anticoagulation is generally indicated for cardioembolic strokes, but not for other stroke causes. Consequently, subtype classification of ischemic stroke is important for risk stratification and secondary prevention. Because manual classification of ischemic stroke is time-intensive, we assessed the accuracy of automated algorithms for performing cardioembolic stroke subtyping using an electronic health record (EHR) database.MethodsWe adapted TOAST (Trial of ORG 10172 in Acute Stroke Treatment) features associated with cardioembolic stroke for derivation in the EHR. Using administrative codes and echocardiographic reports within Mass General Brigham Biobank (N=13 079), we iteratively developed EHR-based algorithms to define the TOAST cardioembolic stroke features, revising regular expression algorithms until achieving positive predictive value ≥80%. We compared several machine learning-based statistical algorithms for discriminating cardioembolic stroke using the feature algorithms applied to EHR data from 1598 patients with acute ischemic strokes from the Massachusetts General Hospital Ischemic Stroke Registry (2002-2010) with previously adjudicated TOAST and Causative Classification of Stroke subtypes.ResultsRegular expression-based feature extraction algorithms achieved a mean positive predictive value of 95% (range, 88%-100%) across 11 echocardiographic features. Among 1598 patients from the Massachusetts General Hospital Ischemic Stroke Registry, 1068 had any cardioembolic stroke feature within predefined time windows in proximity to the stroke event. Cardioembolic stroke tended to occur at an older age, with more TOAST-based comorbidities, and with atrial fibrillation (82.3%). The best model was a random forest with 92.2% accuracy and area under the receiver operating characteristic curve of 91.1% (95% CI, 87.5%-93.9%). Atrial fibrillation, age, dilated cardiomyopathy, congestive heart failure, patent foramen ovale, mitral annulus calcification, and recent myocardial infarction were the most discriminatory features.ConclusionsMachine learning-based identification of cardioembolic stroke using EHR data is feasible. Future work is needed to improve the accuracy of automated cardioembolic stroke identification and assess generalizability of electronic phenotyping algorithms across clinical settings.

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.

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Cardioembolic Stroke.

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Cardioembolic Stroke.

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