Department of Cardiology and Clinical Research, Nordsjællands Hospital, University of Copenhagen, Hillerød, Denmark.
The Danish Heart Foundation, Copenhagen, Denmark.
PLoS One. 2024 Nov 14;19(11):e0312294. doi: 10.1371/journal.pone.0312294. eCollection 2024.
Anticoagulation in atrial fibrillation (AF) increases the risk of major bleeding. No predictive model has hitherto provided estimates of the absolute risk for individual patients.
To predict the individual 1-year risk of major bleeding in patients with AF taking anticoagulants and evaluate the importance of individual risk factors.
A nationwide register-based cohort study.
Danish patients with first-time non-valvular AF who redeemed anticoagulants within 7 days after diagnosis.
The individual absolute risk of major bleeding was estimated from a logistic regression model (the Calculator of Absolute Bleeding Risk/CABS model) utilising the same risk factors as HAS-BLED, except allowing non-linear age effects, and allowing effect modification of all factors according to history of bleeding. The logistic regression was assessed in term of discrimination using the Area Under the ROC curve (AUC) and calibration.
Among 76,102 patients with AF redeeming anticoagulants, 2,406 suffered a major bleeding within 1 year. History of bleeding was the strongest predictor, and age significantly modified the risk. The CABS model superseded HAS-BLED score with regards to discrimination (AUC 0.646 vs 0.615, p<0.001) and calibrated well. A typical male patient was 70-years old without any risk factors and he had a 1-year bleeding risk of 1.4% (1.2; 1.6) while a typical female patient was 73-years old, had hypertension and a 1-year bleeding risk of 2.2% (1.9;2.6).
We propose CABS as a tool for prediction of individual absolute risks of major bleeding in patients with AF taking anticoagulant. The predicted absolute risk can be used for patient counselling.
在心房颤动(AF)患者中使用抗凝药物会增加大出血的风险。迄今为止,尚无预测模型可以为个体患者提供大出血的绝对风险估计。
预测服用抗凝药物的 AF 患者的个体 1 年大出血风险,并评估个体危险因素的重要性。
一项全国范围内基于登记的队列研究。
丹麦首次诊断为非瓣膜性 AF 并在诊断后 7 天内服用抗凝药物的患者。
使用逻辑回归模型(绝对出血风险计算器/CABS 模型)从同一风险因素估计个体大出血风险(除了允许非线性年龄效应,并且根据出血史允许所有因素的效应修饰)。使用 ROC 曲线下面积(AUC)和校准来评估逻辑回归的判别能力。
在 76102 例服用抗凝药物的 AF 患者中,有 2406 例在 1 年内发生大出血。出血史是最强的预测因素,年龄显著改变了风险。CABS 模型在判别能力(AUC 0.646 与 0.615,p<0.001)和校准方面优于 HAS-BLED 评分。一位典型的男性患者 70 岁,没有任何危险因素,他的 1 年出血风险为 1.4%(1.2;1.6),而一位典型的女性患者 73 岁,患有高血压,1 年出血风险为 2.2%(1.9;2.6)。
我们提出 CABS 作为预测服用抗凝药物的 AF 患者大出血个体绝对风险的工具。预测的绝对风险可用于患者咨询。