A nomogram to predict postoperative deep vein thrombosis in patients with Femoral Fracture: a retrospective study

Abstract

Abstract Objective: More active anticoagulation prevention and treatment has reduced the incidence of perioperative deep vein thrombosis (DVT) in patients with bone trauma effectively, but the incidence is still relatively high. According to the Caprini score, all patients undergoing major orthopedic surgery were defined as the high-risk group for DVT. Further risk stratification of DVT high-risk groups remains a challenge. Therefore, the Caprini score most commonly used in the perioperative period is not applicable to orthopaedic patients. We attempt to establish a specialized model to predict postoperative DVT risk in patients with femoral fracture. Methods: We collected the clinical data of 513 patients undergoing femoral fracture surgery in our hospital from May 2018 to December 2019. According to the independent risk factors of DVT obtained by univariate and multivariate logistic regression analysis, the corresponding nomogram model was established and verified internally. The discriminative capacity of nomogram was evaluated by receiver operating characteristic (ROC) curve and area under the curve (AUC). The calibration curve used to verify model consistency was the fitted line between predicted and actual incidences. The clinical validity of the nomogram model was assessed using decision curve analysis (DCA) which could quantify the net benefit of different risk threshold probabilities. Bootstrap method was applied to the internal validation of the nomogram model. Furthermore, we compared the Caprini score and nomogram. Results: The Caprini scores of subjects ranged from 5 to 17 points. The incidence of DVT was not positively correlated with the Caprini score. The predictors of the nomogram model included 10 risk factors such as age, hypoalbuminemia, multiple trauma, perioperative red blood cell infusion, etc. Compared with the Caprini scale (AUC=0.571,95% CI: 0.479~0.623), the calibration accuracy and identification ability of nomogram were higher (AUC=0.865,95% CI:0.780~0.935). The decision curve analysis (DCA) indicated the clinical effectiveness of nomogram was higher than the Caprini score. Conclusions: The nomogram was established to effectively predict postoperative DVT in patients with femoral fracture. More specialized DVT risk assessment models should be established for early identification and individualized prevention strategies to further reduce the incidence.