Shireman Theresa I, Mahnken Jonathan D, Howard Patricia A, Kresowik Timothy F, Hou Qingjiang, Ellerbeck Edward F
Department of Preventive Medicine & Public Health, University of Kansas Medical Center, Kansas City, KS 66160, USA.
Chest. 2006 Nov;130(5):1390-6. doi: 10.1378/chest.130.5.1390.
Develop and validate a contemporary bleeding risk model to guide the clinical use of warfarin in the elderly atrial fibrillation (AF) population.
Chart-abstracted data from the National Registry of Atrial Fibrillation was combined with Medicare part A claims to identify major bleeding events requiring hospitalization. Using a split-sample technique, candidate variables that provided statistically stable relationships with major bleeding events were selected for model development. Three risk categories were created and validated. The new model was compared to existing bleeding risk models using c-statistics and Kaplan-Meier curves.
Model development and validation was conducted on 26,345 AF patients who were > 65 years of age and had been discharged from the hospital while receiving warfarin therapy. The following eight variables were included in the final risk score model: age > or = 70 years; gender; remote bleeding; recent (ie, during index hospitalization) bleeding; alcohol/drug abuse; diabetes; anemia; and antiplatelet use. Bleeding rates were 0.9%, 2.0%, and 5.4%, respectively, for the groups with low, moderate, and high risk, compared to the bleeding rates for groups with moderate risk (1.5% and 1.0%) and high risk (1.8% and 2.5%) from other models.
Using a nationally derived data set, we developed a model based on contemporary practice standards for determining major bleeding risk among AF patients receiving warfarin therapy. The larger sample size afforded the opportunity to incorporate additional risk factors. In addition, since the majority of our population was > 65 years of age, we had greater ability to stratify risk among the elderly.
开发并验证一种当代出血风险模型，以指导华法林在老年心房颤动（AF）人群中的临床应用。
将来自全国心房颤动注册中心的病历摘要数据与医疗保险A部分索赔数据相结合，以识别需要住院治疗的重大出血事件。采用分割样本技术，选择与重大出血事件具有统计学稳定关系的候选变量进行模型开发。创建并验证了三个风险类别。使用c统计量和Kaplan-Meier曲线将新模型与现有的出血风险模型进行比较。
对26345名年龄大于或等于65岁且在接受华法林治疗期间出院的AF患者进行了模型开发和验证。最终风险评分模型纳入了以下八个变量：年龄大于或等于70岁；性别；既往出血；近期（即索引住院期间）出血；酒精/药物滥用；糖尿病；贫血；以及抗血小板药物使用。低、中、高风险组的出血率分别为0.9%、2.0%和5.4%，而其他模型中中风险组（1.5%和1.0%）和高风险组（1.8%和2.5%）的出血率与之不同。
利用全国性数据集，我们基于当代实践标准开发了一个模型，用于确定接受华法林治疗的AF患者的重大出血风险。更大的样本量为纳入额外的风险因素提供了机会。此外，由于我们的大多数人群年龄大于65岁，我们有更强的能力对老年人的风险进行分层。
