Department of Nursing, Chung-Ang University, Seoul, South Korea.
Medicine (Baltimore). 2021 May 14;100(19):e25875. doi: 10.1097/MD.0000000000025875.
Available classification tools and risk factors predicting bleeding events in elderly patients after mechanical valve replacement may not be suitable in Asian populations. Thus, we aimed to identify an accurate model for predicting bleeding in elderly patients receiving warfarin after mechanical valve replacement in a Korean population. In this retrospective cohort study, a random forest model was used to determine factors predicting bleeding events among 598 participants. Twenty-two descriptors were selected as predictors for bleeding. Steroid use was the most important predictor of bleeding events, followed by labile international normalized ratio, history of stroke, history of myocardial infarction, and cancer. The random forest model was sensitive (80.77%), specific (87.67%), and accurate (85.86%), with an area under the curve of 0.87, suggesting fair prediction. In the elderly, drug interactions with steroids and overall physical condition had a significant effect on bleeding. Elderly patients taking warfarin for life require lifelong management.
现有的用于预测机械瓣膜置换术后老年患者出血事件的分类工具和风险因素可能并不适用于亚洲人群。因此，我们旨在确定一个准确的模型，以预测韩国老年人群接受华法林治疗后机械瓣膜置换术后出血的情况。在这项回顾性队列研究中，我们使用随机森林模型来确定 598 名参与者出血事件的预测因素。22 个描述符被选为出血的预测因子。类固醇的使用是出血事件的最重要预测因子，其次是不稳定的国际标准化比值、中风史、心肌梗死史和癌症。随机森林模型的敏感性为 80.77%，特异性为 87.67%，准确性为 85.86%，曲线下面积为 0.87，提示具有良好的预测能力。在老年人中，与类固醇的药物相互作用和整体身体状况对出血有显著影响。需要终生服用华法林的老年患者需要终身管理。
