Key result
BANQMR score predicts paroxysmal AF in acute ischemic stroke with AUC ~0.79, outperforming existing tools.
Why the study?
Paroxysmal atrial fibrillation can cause embolic stroke but is often asymptomatic and may resolve before detection, requiring practical scoring systems to improve detection.
Does the BANQMR score accurately predict paroxysmal atrial fibrillation in patients with acute ischemic stroke?
Cohort (n=1,232)
Yes
Does the BANQMR score accurately predict paroxysmal atrial fibrillation in patients with acute ischemic stroke?
The BANQMR score is a simple and accurate tool for predicting paroxysmal atrial fibrillation in patients with acute ischemic stroke, aiding in early detection and potential stroke prevention.
Answers are grounded in this paper and cite their sources.
May aid PAF stratification in acute ischemic stroke; leaves open prospective validation before practice change.
BACKGROUND AND PURPOSE: Paroxysmal atrial fibrillation (PAF) can cause embolic stroke but is often asymptomatic and may resolve before it can be detected. We developed a simple, practical scoring system to improve the detection of PAF in stroke patients. METHODS: Patients with acute ischemic stroke hospitalized in three stroke centers between 2014 and 2021 were retrospectively examined. Multivariate logistic regression analysis was used to identify independent risk factors for PAF in a derivation cohort. Using these factors, a scoring system was developed and validated in a separate cohort. RESULTS: The derivation and validation cohorts included 649 and 583 patients, respectively. Median follow-up was 606 and 101 days, respectively. The independent risk factors for PAF were brain natriuretic peptide (BNP) ≥55 pg/mL, atrial premature contractions (APCs), National Institutes of Health Stroke Scale (NIHSS) score ≥11, corrected QT interval (QTc) ≥0.46 seconds, and multiple acute cerebral infarcts (MACIs). The BANQMR score assigns points based on these factors (BNP=3, APC=3, NIHSS score=2, QTc=1, and MACIs=1) and classifies patients into three risk grades based on points: low (0-2), moderate (3-5), and high (6-10). PAF was actually detected in 53.4% of high-risk patients, 15.0% of moderate-risk patients, and 4.6% of low-risk patients. The BANQMR score outperformed other existing scoring systems in terms of PAF prediction. CONCLUSIONS: The BANQMR score is a simple, accurate tool for predicting PAF in ischemic stroke patients shortly after hospitalization, providing a clinically applicable method for early detection.
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Suzuki et al. (2025) conducted a cohort in Acute ischemic stroke (n=1,232). BANQMR score vs. Existing scoring systems (STAF, Fujii's simple score, iPAB, AS5F, AF-ESUS, Brown ESUS-AF) was evaluated on Detection of undiagnosed paroxysmal atrial fibrillation (AUC in validation cohort) (AUC 0.791, 95% CI 0.735-0.847). The BANQMR score accurately predicted paroxysmal atrial fibrillation in patients with acute ischemic stroke with an AUC of 0.791, outperforming other existing scoring systems.
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