Predictive model for severe thrombocytopenia after transfemoral transcatheter aortic valve replacement

Shaoman Li; Yafeng Wu; Jinju Wang; Liping She; Xuemei Zheng

doi:10.3389/fcvm.2023.1213248

Predictive model for severe thrombocytopenia after transfemoral transcatheter aortic valve replacement

Front Cardiovasc Med. 2023 Aug 9:10:1213248. doi: 10.3389/fcvm.2023.1213248. eCollection 2023.

Authors

Shaoman Li^#¹, Yafeng Wu^#¹, Jinju Wang¹, Liping She¹, Xuemei Zheng¹

Affiliation

¹ Department of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.

^# Contributed equally.

Abstract

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.

Keywords: aortic regurgitation; platelet count; predictive model; thrombocytopenia; transcatheter aortic valve replacement.