A nomogram to predict postoperative deep vein thrombosis in patients with femoral fracture: a retrospective study

作者全名："Wu, Linqin; Cheng, Bo"

作者地址："[Wu, Linqin; Cheng, Bo] Chongqing Med Univ, Affiliated Hosp 1, Dept Anesthesiol, Chongqing, Peoples R China"

通信作者："Cheng, B (通讯作者)，Chongqing Med Univ, Affiliated Hosp 1, Dept Anesthesiol, Chongqing, Peoples R China."

来源：JOURNAL OF ORTHOPAEDIC SURGERY AND RESEARCH

ESI学科分类：CLINICAL MEDICINE

WOS号：WOS:001020893300001

JCR分区：Q1

影响因子：2.8

年份：2023

卷号：18

期号：1

开始页：　

结束页：　

文献类型：Article

关键词：Deep venous thrombosis; Risk factor; Femoral fracture; Nomogram model; The Caprini score

摘要："ObjectiveThe implementation of more active anticoagulant prevention and treatment measures has indeed led to a significant reduction in the incidence of perioperative deep vein thrombosis (DVT) among patients with bone trauma. However, it is important to note that despite these efforts, the incidence of DVT still remains relatively high. According to the Caprini score, all patients undergoing major orthopedic surgery were defined as the high-risk group for DVT. Stratifying the risk further within high-risk groups for DVT continues to present challenges. As a result, the commonly used Caprini score during the perioperative period is not applicable to orthopedic patients. We attempt to establish a specialized model to predict postoperative DVT risk in patients with femoral fracture.MethodsWe 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, a comparison was made between the Caprini score and the developed nomogram model.ResultsThe 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.ConclusionsThe nomogram was established to effectively predict postoperative DVT in patients with femoral fracture. To further reduce the incidence, more specialized risk assessment models for DVT should take into account the unique risk factors and characteristics associated with specific patient populations."

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