The PAFIS score for risk stratification of atrial fibrillation detected after stroke: a multicenter cohort study

Risk-Adapted Atrial Fibrillation Monitoring after Embolic Stroke of Undetermined Source: A Population-Based Study

Refining Residual Ischemic Stroke Risk in Anticoagulated Atrial Fibrillation Using Index Outpatient LA Diameter: The CHA2DS2-VALa Score.

The CHA2DS2-VALa score significantly improves stroke risk stratification in AF by integrating LA diameter into conventional scoring, as echocardiographic measurement is widely available and reproducible.

Predictive value of acute atrial fibrillation for short-term mortality after ischemic stroke

Background Atrial fibrillation (AF) is an important risk factor for ischemic stroke. However, the prognostic impact of acute atrial fibrillation (AAF) at the onset of acute ischemic stroke (AIS) remains unclear. Methods This retrospective study categorized 417 patients with AIS into the AAF (n = 72), other AF (n = 142), and non-AF (n = 203) groups. Multivariate logistic regression analysis of associations with 30-day all-cause mortality and severe early neurological deficit (7-day NIHSS ≥16). Results The AAF group demonstrated significantly worse outcomes than the other AF and non-AF groups. In the multivariable analysis, AAF was identified as an independent risk predictor for severe 7-day neurological deficit [odds ratio (OR): 10.09; 95% CI: 3.87−27.36; P < 0.001] and all-cause mortality within 30 days (OR: 4.11; 95% CI: 2.28−7.43; P < 0.001). Conclusions AAF at the onset of AIS is an independent risk predictor for early neurological deterioration and short-term mortality, establishing it as a crucial prognostic indicator that warrants vigilant management.

Artificial intelligence shows comparable or improved performance to traditional risk models in predicting atrial fibrillation after cryptogenic stroke

In patients with cryptogenic stroke receiving an ICM, the ECG-AI score showed modest discrimination for AF detection, outperforming CHA2DS2-VA and HAVOC, but not Brown ESUS-AF, which indicates a possible role for AI-driven ECG analysis in risk stratification.

Development and Validation of the GLORIA-AF Stroke Weighted Risk Score for Patients with Atrial Fibrillation.

BACKGROUND AND AIMS Accurate stroke-risk stratification is central to anticoagulation decision-making in patients with atrial fibrillation (AF), but conventional scores may not fully capture risk heterogeneity. We aimed to develop and externally validate an interpretable weighted score using a time-to-event framework. METHODS GLORIA-AF Phase II/III data were used to evaluate 17 baseline predictors using LASSO-penalized Cox regression with stability selection; coefficients were converted into integer weights. Performance was assessed using discrimination, calibration, integrated discrimination improvement (IDI), continuous net reclassification improvement (NRI), and decision-curve analysis. External validation was performed in EORP-AF and APHRS-AF registries. RESULTS Among 20,517 patients included in the derivation cohort (mean [SD] age, 69.9 [10.3] years; 9,196 women [44.8%]), 487 (2.4%) had stroke, and 17,397 (84.8%) were receiving anticoagulation at baseline. Ten selected predictors formed a 0-23-point score. The derived score achieved a C-index of 0.661 (95% CI, 0.636-0.685), higher than CHA2DS2-VA (0.626; P < 0.001), CHA2DS2-VASc (0.615; P < 0.001), and the unweighted score (P = 0.016), with no significant difference from the full Cox or machine learning models. In external validation (8,309 patients; 147 strokes), the C-index was 0.652 (95% CI, 0.614-0.690) versus 0.616 for CHA2DS2-VA (95%CI, 0.598-0.634; P < 0.001). IDI/NRI, calibration, and decision-curve analyses supported improved risk differentiation, close calibration, and generally greater net benefit than CHA2DS2-VA. The score retained higher discrimination than CHA2DS2-VA among patients without baseline anticoagulation (P < 0.001). CONCLUSION The GLORIA-AF Stroke Weighted Risk Score provides risk refinement beyond CHA2DS2-VA while retaining discrimination consistent with more complex models. External validation supports its transportability and potential adjunctive role in guideline-directed thromboembolic risk assessment.

Predictors of ischemic stroke severity and long-term functional outcomes in patients with and without atrial fibrillation.

BACKGROUND Ischemic stroke patients with atrial fibrillation (AF) may have different mechanisms and prognostic determinants than those without AF. We investigated predictors of initial stroke severity and 3-month functional outcome in first-ever ischemic stroke, stratified by AF status. METHODS Consecutive patients with first-ever acute ischemic stroke admitted within 7 days of onset to Taitung MacKay Memorial Hospital from December 31, 2014, to December 31, 2020, were analyzed. Admission National Institutes of Health Stroke Scale (NIHSS) and 3-month modified Rankin Scale (mRS) scores were evaluated using multivariable general linear models stratified by AF status. The 3-month mRS models assessed whether associations persisted after adjustment for admission NIHSS. RESULTS Overall, 1256 patients were included (non-AF, n = 955; AF, n = 301). Patients with AF were older and had higher admission NIHSS and 3-month mRS scores than those without AF. In the non-AF group, age ≥75 years, betel nut chewing, and sedentary lifestyle were associated with higher admission NIHSS, whereas dyslipidemia was associated with lower admission NIHSS. In the AF group, sedentary lifestyle was associated with higher admission NIHSS, whereas obesity and pre-stroke anticoagulant therapy were associated with lower admission NIHSS. After adjustment for admission NIHSS, type 2 diabetes was independently associated with higher 3-month mRS in both groups. Age ≥75 years and sedentary lifestyle remained associated with higher 3-month mRS only in the non-AF group. CONCLUSION Predictors of initial stroke severity and 3-month functional outcome differ by AF status. Stratified prognostic assessment may guide individualized secondary prevention and post-stroke management.