Modified CHADS₂ and CHA₂DS₂-VASc scores to predict atrial fibrillation in acute ischemic stroke patients

Area of Science:

• Cardiology
• Neurology
• Medical Diagnostics

Background:

• Atrial fibrillation (AF) detection post-ischemic stroke is vital for preventing secondary events.
• Current risk scores (CHADS₂ and CHA₂DS₂-VASc) have limitations in predicting new-onset AF in stroke patients.
• Extended cardiac monitoring is essential for identifying candidates requiring further management.

Purpose of the Study:

• To evaluate the predictive performance of CHADS₂ and CHA₂DS₂-VASc scores for detecting previously unknown atrial fibrillation (AF) in patients with ischemic stroke.
• To identify novel risk factors that improve AF prediction in this population.
• To assess the utility of these scores for guiding extended cardiac monitoring decisions.

Main Methods:

• Prospective trial data from 1315 ischemic stroke patients in China were analyzed.
• The predictive accuracy of CHADS₂ and CHA₂DS₂-VASc scores was assessed using the C statistic.
• Multivariate logistic regression identified independent predictors of newly detected AF.

Main Results:

• Previously unknown AF was detected in 8.4% of patients.
• CHADS₂ and CHA₂DS₂-VASc scores showed modest predictive values (C statistics 0.55 and 0.62, respectively).
• Adding age, heart failure, NIHSS, creatinine, and triglycerides significantly improved prediction (C statistics to 0.74 and 0.75).

Conclusions:

• The CHADS₂ and CHA₂DS₂-VASc scores are insufficient for optimal prediction of new-onset AF after ischemic stroke.
• Incorporating clinical factors like age, heart failure, NIHSS, creatinine, and triglycerides enhances predictive accuracy.
• These findings support refining risk stratification for extended cardiac monitoring in stroke patients.