Predicting the risk of sarcopenia in elderly patients with patellar fracture: development and assessment of a new predictive nomogram

PeerJ

article

Yi-sheng Chen¹  Yan-xian Cai²  Xue-ran Kang³  Zi-hui Zhou¹  Xin Qi¹  Chen-ting Ying¹  Yun-peng Zhang¹  Jie Tao¹ 

[1] Department of Orthopedics, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine;Department of Plastic Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine;Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine;Ear Institute, Shanghai JiaoTong University School of Medicine;Shanghai Key Laboratory of Translational Medicine on Ear and Nose diseases

关键词: Patellar fracture;    Sarcopenia;    Nomogram prediction model;    Skeletal muscle;    Logistic regression model;   

DOI  :  10.7717/peerj.8793

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

PurposeTo develop a risk prediction model for postoperative sarcopenia in elderly patients with patellar fractures in China.Patients and methodsWe conducted a community survey of patients aged ≥55 years who underwent surgery for patellar fractures between January 2013 and October 2018, through telephone interviews, community visits, and outpatient follow-up. We established a predictive model for assessing the risk of sarcopenia after patellar fractures. We developed the prediction model by combining multivariate logistic regression analysis with the least absolute shrinkage model and selection operator regression (lasso analysis) as well as the Support Vector Machine (SVM) algorithm. The predictive quality and clinical utility of the predictive model were determined using C-index, calibration plots, and decision curve analysis. We also conducted internal sampling methods for qualitative assessment.ResultWe recruited 137 participants (53 male; mean age, 65.7 years). Various risk factors were assessed, and low body mass index and advanced age were identified as the most important risk factor (P < 0.05). The prediction rate of the model was good (C-index: 0.88; 95% CI [0.80552–0.95448]), with a satisfactory correction effect. The C index is 0.97 in the validation queue and 0.894 in the entire cohort. Decision curve analysis suggested good clinical practicability.ConclusionOur prediction model shows promise as a cost-effective tool for predicting the risk of postoperative sarcopenia in elderly patients based on the following: advanced age, low body mass index, diabetes, less outdoor exercise, no postoperative rehabilitation, different surgical methods, diabetes, open fracture, and removal of internal fixation.

【 授权许可】

CC BY