ArticleClinical cardiology2024
Incidence Rate and Predictors of Intracranial Hemorrhage in Patients With Atrial Fibrillation: A Report From the Nationwide COOL-AF Registry.
Article in Clinical cardiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Asian Perspectives on Atrial Fibrillation Management: Lessons Learned From the COOL-AF Registry.JACC. Asia · 2026Article
- Cerebral Microbleeds, Anemia, and Estimated Net Benefit of DOACs versus Warfarin in Older Atrial Fibrillation: A Single-Center MRI-Selected Cohort.Clinical interventions in aging · 2026Observational
- How to Apply Predictive Model in Real-World Practice: The Standard of Model Validation.Clinical cardiology · 2025Article
- The Applicability of Novel Predictor of Intracranial Hemorrhage in Patients With Atrial Fibrillation in the Contemporary Real-World Clinical Practice.Clinical cardiology · 2025Article
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5 authors.
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Abstract
backgroundSpecific risk predictor scores of intracranial hemorrhage (ICH) risk in Asian subjects are lacking. We determined the incidence rate and predictors of ICH in patients with non-valvular atrial fibrillation (AF).
methodsA prospective nationwide registry of patients with AF was conducted from 27 hospitals in Thailand. The adjudicated primary outcome was the development of ICH during follow-up. Multivariable Cox proportional hazard model was performed to identify the independent predictors for ICH. A predictive model for ICH risk was developed and validated by bootstrap, calibration plot, C-statistics, and decision curve analysis using our own data.
resultsWe studied a total of 3405 patients (mean age 67.8 years; 58.2% male) with an average follow-up duration of 31.8 ± 8.7 months, during which ICH developed in 70 patients (2.06%). The incidence rate of ICH was 0.78 (0.61-0.98) per 100 person-years. Predictors of ICH were chosen from the theory-driven approaches in combination with the results of the univariable analysis. The predictive risk model had a c-index of 0.717 (0.702-0.732) with good calibration, internal validation, and clinical usefulness using decision curve analysis. The probability of ICH at 3 years for an individual patient derived from the prediction model was compared with the probability derived from HAS-BLED score by using the C-statistics. The ICH probability from the COOL-AF model was superior to the HAS-BLED score in the prediction of ICH.
conclusionThe incidence rate of ICH was 0.78 (0.61-0.98) per 100 person-years. Predictors of ICH were older age, male sex, nonsmoking, renal replacement therapy, and use of oral anticoagulants.
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