Dataset Information

Who should undergo a comprehensive cognitive assessment after a stroke? A cognitive risk score.

ABSTRACT:

Objective

To validate the ability of a specifically developed cognitive risk score to identify patients at risk of poststroke neurocognitive disorders (NCDs) who are eligible for a comprehensive cognitive assessment.

Methods

After assessing 404 patients (infarct 91.3%) in the Groupe de Réflexion pour l'Evaluation Cognitive VASCulaire (GRECogVASC) cross-sectional study with the National Institute of Neurological Disorders and Stroke-Canadian Stroke Network battery 6 months after stroke, we used multivariable logistic regression and bootstrap analyses to determine factors associated with NCDs. Independent, internally validated factors were included in a cognitive risk score.

Results

Cognitive impairment was present in 170 of the 320 patients with a Rankin Scale score ≥1. The backward logistic regression selected 4 factors (≥73% of the permutations): NIH Stroke Scale score on admission ≥7 (odds ratio [OR] 2.73, 95% confidence interval [CI] 1.29-4.3, p = 0.005), multiple strokes (OR 3.78, 95% CI 1.6-8, p = 0.002), adjusted Mini-Mental State Examination (MMSEadj) score ≤27 (OR 6.69, 95% CI 3.9-11.6, p = 0.0001), and Fazekas score ≥2 (OR 2.34, 95% CI 1.3-4.2, p = 0.004). The cognitive risk score computed with these 4 factors provided good calibration, discrimination (overoptimism-corrected C = 0.793), and goodness of fit (Hosmer-Lemeshow test p = 0.99). A combination of Rankin Scale score ≥1, cognitive risk score ≥1, and MMSEadj score ≥21 selected 230 (56.9%) of the 404 patients for a comprehensive assessment. This procedure yielded good sensitivity (96.5%) and moderate specificity (43%; positive predictive value 0.66, negative predictive value 0.91) and was more accurate (p ≤ 0.03 for all) than the sole use of screening tests (MMSE or Montréal Cognitive Assessment).

Conclusion

The GRECogVASC cognitive risk score comprises 4 easily documented factors; this procedure helps to identify patients at risk of poststroke NCDs who must therefore undergo a comprehensive assessment.

Clinicaltrialsgov identifier

NCT01339195.

SUBMITTER: Godefroy O

PROVIDER: S-EPMC6260202 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Publications

Who should undergo a comprehensive cognitive assessment after a stroke? A cognitive risk score.

Godefroy Olivier O Yaïche Hugo H Taillia Hervé H Bompaire Flavie F Nédélec-Ciceri Claudine C Bonnin Camille C Bonnin Camille C Varvat Jérôme J Vincent-Grangette Françoise F Diouf Momar M Mas Jean-Louis JL Canaple Sandrine S Lamy Chantal C Arnoux Audrey A Leclercq Claire C Tasseel-Ponche Sophie S Roussel Martine M Barbay Mélanie M

Neurology 20181017 21

<h4>Objective</h4>To validate the ability of a specifically developed cognitive risk score to identify patients at risk of poststroke neurocognitive disorders (NCDs) who are eligible for a comprehensive cognitive assessment.<h4>Methods</h4>After assessing 404 patients (infarct 91.3%) in the Groupe de Réflexion pour l'Evaluation Cognitive VASCulaire (GRECogVASC) cross-sectional study with the National Institute of Neurological Disorders and Stroke-Canadian Stroke Network battery 6 months after st ...[more]

PMID: 30333160

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Project description:Stroke, a major global health concern often rooted in cardiac dynamics, demands precise risk evaluation for targeted intervention. Current risk models, like the CHA2DS2-VASc score, often lack the granularity required for personalized predictions. In this study, we present a nuanced and thorough stroke risk assessment by integrating functional insights from cardiac magnetic resonance (CMR) with patient-specific computational fluid dynamics (CFD) simulations. Our cohort, evenly split between control and stroke groups, comprises eight patients. Utilizing CINE CMR, we compute kinematic features, revealing smaller left atrial volumes for stroke patients. The incorporation of patient-specific atrial displacement into our hemodynamic simulations unveils the influence of atrial compliance on the flow fields, emphasizing the importance of LA motion in CFD simulations and challenging the conventional rigid wall assumption in hemodynamics models. Standardizing hemodynamic features with functional metrics enhances the differentiation between stroke and control cases. While standalone assessments provide limited clarity, the synergistic fusion of CMR-derived functional data and patient-informed CFD simulations offers a personalized and mechanistic understanding, distinctly segregating stroke from control cases. Specifically, our investigation reveals a crucial clinical insight: normalizing hemodynamic features based on ejection fraction fails to differentiate between stroke and control patients. Differently, when normalized with stroke volume, a clear and clinically significant distinction emerges and this holds true for both the left atrium and its appendage, providing valuable implications for precise stroke risk assessment in clinical settings. This work introduces a novel framework for seamlessly integrating hemodynamic and functional metrics, laying the groundwork for improved predictive models, and highlighting the significance of motion-informed, personalized risk assessments.

Project description:Background and purposeLimited data exist on the performance of the revised Framingham Stroke Risk Score (R-FSRS) and the R-FSRS in conjunction with nontraditional risk markers. We compared the R-FSRS, original FSRS, and the Pooled Cohort Equation for stroke prediction and assessed the improvement in discrimination by nontraditional risk markers.MethodsSix thousand seven hundred twelve of 6814 participants of the MESA (Multi-Ethnic Study of Atherosclerosis) were included. Cox proportional hazard, area under the curve, net reclassification improvement, and integrated discrimination increment analysis were used to assess and compare each stroke prediction risk score. Stroke was defined as fatal/nonfatal strokes (hemorrhagic or ischemic).ResultsAfter mean follow-up of 10.7 years, 231 of 6712 (3.4%) strokes were adjudicated (2.7% ischemic strokes). Mean stroke risks using the R-FSRS, original FSRS, and Pooled Cohort Equation were 4.7%, 5.9%, and 13.5%. The R-FSRS had the best calibration (Hosmer-Lemeshow goodness-of-fit, χ2=6.55; P=0.59). All risk scores were predictive of incident stroke. C statistics of R-FSRS (0.716) was similar to Pooled Cohort Equation (0.716), but significantly higher than the original FSRS (0.653; P=0.01 for comparison with R-FSRS). Adding nontraditional risk markers individually to the R-FSRS did not improve discrimination of the R-FSRS in the area under the curve analysis, but did improve category-less net reclassification improvement and integrated discrimination increment for incident stroke. The addition of coronary artery calcium to R-FSRS produced the highest category-less net reclassification improvement (0.36) and integrated discrimination increment (0.0027). Similar results were obtained when ischemic strokes were used as the outcome.ConclusionsThe R-FSRS downgraded stroke risk but had better calibration and discriminative ability for incident stroke compared with the original FSRS. Nontraditional risk markers modestly improved the discriminative ability of the R-FSRS, with coronary artery calcium performing the best.

Dataset Information

Who should undergo a comprehensive cognitive assessment after a stroke? A cognitive risk score.

Objective

Methods

Results

Conclusion

Clinicaltrialsgov identifier

Publications

Who should undergo a comprehensive cognitive assessment after a stroke? A cognitive risk score.

Similar Datasets

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