ArticleClinical epidemiology2024
Development and Validation of an Intracranial Hemorrhage Risk Score in Older Adults with Atrial Fibrillation Treated with Oral Anticoagulant.
Article in Clinical epidemiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed, 0 citations in OpenAlex.
- Utility of Risk Scores for Predicting Stroke and Intracranial Bleeding Across Levels of Kidney Function in Two Large Community-Based Cohorts of Older Adults With Atrial Fibrillation.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2026Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Background: High risk of intracranial hemorrhage (ICH) is a leading reason for withholding anticoagulation in patients with atrial fibrillation (AF). We aimed to develop a claims-based ICH risk prediction model in older adults with AF initiating oral anticoagulation (OAC). Methods: We used US Medicare claims data to identify new users of OAC aged ≥65 years with AF in 2010-2017. We used regularized Cox regression to select predictors of ICH. We compared our AF ICH risk score with the HAS-BLED bleed risk and Homer fall risk scores by area under the receiver operating characteristic curve (AUC) and assessed net reclassification improvement (NRI) when predicting 1-year risk of ICH. Results: Our study cohort comprised 840,020 patients (mean [SD] age 77.5 [7.4] years and female 52.2%) split geographically into training (3963 ICH events [0.6%] in 629,804 patients) and validation (1397 ICH events [0.7%] in 210,216 patients) sets. Our AF ICH risk score, including 50 predictors, had superior AUCs of 0.653 and 0.650 in the training and validation sets than the HAS-BLED score of 0.580 and 0.567 ( Conclusion: Our novel claims-based ICH risk prediction model outperformed the standard HAS-BLED score and can inform OAC prescribing decisions.
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Registered trials
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