Development and validation of a newly developed nomogram for predicting the risk of deep vein thrombosis after surgery for lower limb fractures in elderly patients

Frontiers in Surgery

Surgery

Dapeng Feng¹  Jiaqi Wang¹  Shufeng Li²  Kai Li³  Jun Zhang³  Jian Wang³  Yongmin Qiu³  Juhong Ding³  Kun Jiao³  Shuai Han³  Yunpeng Bai³  Jingyun Hu⁴  Haihan Song⁴ 

[1] Central Lab, Shanghai Key Laboratory of Pathogenic Fungi Medical Testing, Shanghai Pudong New Area People's Hospital, Shanghai, China;Department of Orthopedic Surgery, Shandong, Key Laboratory of Rheumatic Disease and Translational Medicine, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China;Department of Orthopedics, Shanghai Pudong New Area People's Hospital, Shanghai, China;Department of Orthopedics, The Second Hospital of Dalian Medical University, Dalian, China;

关键词: nomograms;    deep vein thrombosis;    lower limb fractures;    elderly patients;    predictive factors;   

DOI  :  10.3389/fsurg.2023.1095505

 received in 2022-11-11, accepted in 2023-04-13,  发布年份 2023

来源: Frontiers

【 摘 要 】

BackgroundPrevention of deep vein thrombosis (DVT) is indispensable in the treatment of lower limb fractures during the perioperative period. This study aimed to develop and validate a novel model for predicting the risk of DVT in elderly patients after orthopedic surgeries for lower limb fractures.MethodsThis observational study included 576 elderly patients with lower limb fractures who were surgically treated from January 2016 to December 2018. Eleven items affecting DVT were optimized by least absolute shrinkage and selection operator regression analysis. Multivariable logistic regression analysis was performed to construct a predictive model incorporating the selected features. C-index was applied to evaluate the discrimination. Decision curve analysis was employed to determine the clinical effectiveness of this model and calibration plot was applied to evaluate the calibration of this nomogram. The internal validation of this model was assessed by bootstrapping validation.ResultsPredictive factors that affected the rate of DVT in this model included smoking, time from injury to surgery, operation time, blood transfusion, hip replacement arthroplasty, and D-dimer level after operation. The nomogram showed significant discrimination with a C-index of 0.919 (95% confidence interval: 0.893–0.946) and good calibration. Acceptable C-index value could still be reached in the interval validation. Decision curve analysis indicated that the DVT risk nomogram was useful within all possibility threshold.ConclusionThis newly developed nomogram could be used to predict the risk of DVT in elderly patients with lower limb fractures during the perioperative period.

【 授权许可】

Unknown   
© 2023 Han, Bai, Jiao, Qiu, Ding, Zhang, Hu, Song, Wang, Li, Feng, Wang and Li.