Key result
Specific DVT risk nomogram outperforms the Caprini score for predicting thrombosis in hip fracture patients.
Why the study?
The study aimed to establish a nomogram model to predict the probability of postoperative deep vein thrombosis risk in patients with hip fractures.
Does a novel nomogram model improve the prediction of postoperative DVT compared to the Caprini score in patients with hip fractures?
Observational (n=504)
No
Does a novel nomogram model improve the prediction of postoperative DVT compared to the Caprini score in patients with hip fractures?
A novel nomogram incorporating age, surgical approach, postoperative D-dimer, and admission ultrasound provides superior prediction of postoperative DVT risk in hip fracture patients compared to the Caprini score.
Answers are grounded in this paper and cite their sources.
Nomogram may aid DVT risk prediction in hip fracture patients; hypothesis-generating and requires prospective validation before practice change.
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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Bo et al. (2024) conducted an observational in Hip fractures (n=504). Nomogram model vs. Caprini score was evaluated on Area under the ROC curve (AUC) for predicting postoperative deep vein thrombosis (95% CI 0.746–0.884, p=< 0.05). The specific DVT risk-stratification nomogram model demonstrated a higher predictive performance compared to the Caprini score in patients with hip fractures.
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