Li Shaoman, Wu Yafeng, Wang Jinju, She Liping, Zheng Xuemei
Department of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
Front Cardiovasc Med. 2023 Aug 9;10:1213248. doi: 10.3389/fcvm.2023.1213248. eCollection 2023.
The aim of this study was to develop a predictive model for severe thrombocytopenia after transfemoral transcatheter aortic valve replacement (TAVR). A total of 155 patients treated with TAVR at our center were retrospectively enrolled in this study. The incidence of severe thrombocytopenia after TAVR was 25.16%, and most patients suffered from severe thrombocytopenia on 4 days after procedure. Multivariate regression analysis showed that weight <60 kg, New York Heart Association Functional Classification (NYHAFC IV), major vascular complications, and lower first post-procedural platelet count were independent risk factors for severe thrombocytopenia after TAVR. The c-statistic for the area under the curve was 0.758, the sensitivity was 0.744, the specificity was 0.784, and the negative predictive value of the model was 91.38%. The overall predictive value was 76.77%. The predictive model developed from this cohort data could effectively identify patients at high risk of severe thrombocytopenia after TAVR, and might be applicable to patients with aortic regurgitation (AR) and severe thrombocytopenia with different definitions.
本研究的目的是建立经股动脉经导管主动脉瓣置换术(TAVR)后严重血小板减少症的预测模型。本研究回顾性纳入了在我们中心接受TAVR治疗的155例患者。TAVR后严重血小板减少症的发生率为25.16%,大多数患者在术后4天出现严重血小板减少症。多因素回归分析显示,体重<60 kg、纽约心脏协会功能分级(NYHAFC IV级)、主要血管并发症以及术后首次血小板计数较低是TAVR后严重血小板减少症的独立危险因素。曲线下面积的c统计量为0.758,敏感性为0.744,特异性为0.784,模型的阴性预测值为91.38%。总体预测值为76.77%。从该队列数据建立的预测模型可以有效识别TAVR后严重血小板减少症的高危患者,并且可能适用于不同定义的主动脉瓣反流(AR)和严重血小板减少症患者。