Construction and validation of a predictive model for preoperative lower extremity deep vein thrombosis risk in elderly hip fracture patients: An observational study

医学 观察研究 深静脉 髋部骨折 血栓形成 试验预测值 预测值 外科 放射科 内科学 骨质疏松症
作者
Chang-Song Yang,Zhe Tan
出处
期刊:Medicine [Wolters Kluwer]
卷期号:103 (38): e39825-e39825
标识
DOI:10.1097/md.0000000000039825
摘要

The aim of this study was to identify independent risk factors for preoperative lower extremity deep vein thrombosis (DVT) in elderly hip fracture patients and to construct a nomogram prediction model based on them. We collected clinical data from elderly hip fracture patients from Ya'an Hospital of Traditional Chinese Medicine (2021-2023), and used univariate and multivariate logistic regression analyses to identify independent risk factors for preoperative DVT. In this way, a nomogram prediction model was established. In addition, external validation of the model was performed by patient data from Ya'an Mingshan District Hospital of Traditional Chinese Medicine. Receiver operating characteristic curve analysis was used to calculate the area under the curve, and calibration and decision curves were plotted to assess the predictive performance of the model. Of the 223 elderly hip fracture patients, 23 (10.31%) developed DVT of the lower extremities before surgery. A total of 6 variables were identified as independent risk factors for preoperative lower extremity DVT in elderly hip fracture patients by logistic regression analysis: age > 75 years (OR = 1.932; 95% CI: 1.230-3.941), diabetes mellitus (OR = 2.139; 95% CI: 1.149-4.342), and prolonged duration of disease (OR. 2.535; 95% CI: 1.378-4.844), surgical treatment (OR = 1.564; 95% CI: 1.389-3.278), D-dimer > 0.5 mg/L (OR = 3.365; 95% CI: 1.229-7.715) fibrinogen > 4 g/L (OR = 3.473; 95% CI: 1.702-7.078). The constructed nomogram model has high accuracy in predicting the risk of preoperative DVT in elderly hip fracture patients, providing an effective tool for clinicians to identify high-risk patients and implement early intervention.

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