Author:
Lin Zhencan,Sun Hao,Li Deng,Cai Zhiqing,Huang Zhencheng,Liu Fangzhou,Chen Meiyi,Wang Yimin,Xu Jie,Ma Ruofan
Abstract
Abstract
Introduction
Deep venous thrombosis (DVT) prediction after total hip and knee arthroplasty remains challenging. Early diagnosis and treatment of DVT are crucial. This research aimed to develop a nomogram for early DVT prediction.
Methods
A total of 317 patients undergoing primary total hip and knee arthroplasty in Sun Yat-sen Memorial Hospital were enrolled between May 2020 and September 2022. Data from May 2020 to February 2022 were used as the development datasets to build the nomogram model (n = 238). Using multivariate logistic regression, independent variables and a nomogram for predicting the occurrence of DVT were identified. Datasets used to validate the model for internal validation ranged from March 2022 to September 2022 (n = 79). The nomogram’s capacity for prediction was also compared with the Caprini score.
Results
For both the development and validation datasets, DVT was found in a total of 38 (15.97%) and 9 patients (11.39%) on post-operative day 7 (pod7), respectively. 59.6% patients were symptomatic DVT (leg swelling). The multivariate analysis revealed that surgical site (Knee vs. Hip), leg swelling and thrombin-antithrombin complex (TAT) were associated with DVT. The previously indicated variables were used to build the nomogram, and for the development and validation datasets, respectively. In development and validation datasets, the area under the receiver operating characteristic curve was 0.836 and 0.957, respectively. In both datasets, the predictive value of the Nomogram is greater than the Caprini score.
Conclusions
A proposed nomogram incorporating surgical site (Knee vs. Hip), leg swelling, and thrombin antithrombin complex (TAT) may facilitate the identification of patients who are more prone to develop DVT on pod7.
Funder
The National Key R&D Program of China
National Natural Science Foundation of China
Science and Technology Planning Project of Guangzhou City, China
Guangdong Basic and Applied Basic Research Foundation
Publisher
Springer Science and Business Media LLC
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献