A Nomogram Model to Predict Deep Vein Thrombosis Risk After Surgery in Patients with Hip Fractures

用于预测髋部骨折患者术后深静脉血栓形成风险的列线图模型

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Abstract

AIMS: This study aimed to establish a nomogram model for predicting the probability of postoperative deep vein thrombosis (DVT) risk in patients with hip fractures. METHODS: 504 patients were randomly assigned to the training set and validation set, and then divided into a DVT group and a non-DVT group. The study analysed the risk factors for DVT using univariate and multivariate analyses. Based on these parameters, a nomogram model was constructed and validated. The predicting performance of nomogram was evaluated by discrimination, calibration, and clinical usefulness. RESULTS: The predictors contained in the nomogram model included age, surgical approach, 1-day postoperative D-dimer value and admission ultrasound diagnosis of the lower limb vein. Furthermore, the area under the ROC curve (AUC) for the specific DVT risk-stratification nomogram model (0.815; 95% CI 0.746-0.884) was significantly higher than the current model (Caprini) (0.659; 95% CI 0.572-0.746, P < 0.05). According to the calibration plots, the prediction and actual observation were in good agreement. In the range of threshold probabilities of 0.2-0.8, the predictive performance of the model on DVT risk could be maximized. CONCLUSIONS: The current predictive model could serve as a reliable tool to quantify the possibility of postoperative DVT in hip fractures patients.

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