Development and validation of a prognostic nomogram for open elbow arthrolysis the Shanghai Prediction model for Elbow Stiffness Surgical Outcome

被引:0
|
作者
Liu, W. [1 ,2 ]
Sun, Z. [1 ,2 ]
Xiong, H. [1 ,2 ]
Liu, J. [3 ]
Lu, J. [4 ]
Cai, B. [5 ]
Wang, W. [1 ,2 ]
Fan, C. [1 ,2 ]
机构
[1] Shanghai Jiao Tong Univ Affiliated Peoples Hosp 6, Dept Orthopaed, Shanghai, Peoples R China
[2] Shanghai Engn Res Ctr Orthoped Mat Innovat & Tiss, Shanghai, Peoples R China
[3] Tongji Univ, Sch Med, Shanghai Tenth Peoples Hosp, Dept Orthoped, Shanghai, Peoples R China
[4] Fudan Univ, Huashan Hosp, Dept Hand Surg, Shanghai, Peoples R China
[5] Shanghai Jiao Tong Univ, Sch Med, Shanghai Ninth Peoples Hosp, Dept Rehabil Med, Shanghai, Peoples R China
来源
BONE & JOINT JOURNAL | 2022年 / 104B卷 / 04期
基金
中国国家自然科学基金;
关键词
HETEROTOPIC OSSIFICATION; SURVIVAL; CLASSIFICATION; OSTEOARTHRITIS; COMPLICATIONS; ARTHRITIS; RESECTION; EXCISION; RANGE; INDEX;
D O I
暂无
中图分类号
R826.8 [整形外科学]; R782.2 [口腔颌面部整形外科学]; R726.2 [小儿整形外科学]; R62 [整形外科学(修复外科学)];
学科分类号
摘要
Aims The aim of this study was to develop and internally validate a prognostic nomogram to predict the probability of gaining a functional range of motion (ROM >= 120 degrees) after open arthrolysis of the elbow in patients with post-traumatic stiffness of the elbow. Methods We developed the Shanghai Prediction Model for Elbow Stiffness Surgical Outcome (SPES-SO) based on a dataset of 551 patients who underwent open arthrolysis of the elbow in four institutions. Demographic and clinical characteristics were collected from medical records. The least absolute shrinkage and selection operator regression model was used to optimize the selection of relevant features. Multivariable logistic regression analysis was used to build the SPESSO. Its prediction performance was evaluated using the concordance index (C-index) and a calibration graph. Internal validation was conducted using bootstrapping validation. Results BMI, the duration of stiffness, the preoperative ROM, the preoperative intensity of pain, and grade of post-traumatic osteoarthritis of the elbow were identified as predictors of outcome and incorporated to construct the nomogram. SPESSO displayed good discrimination with a C-index of 0.73 (95% confidence interval 0.64 to 0.81). A high C-index value of 0.70 could still be reached in the interval validation. The calibration graph showed good agreement between the nomogram prediction and the outcome. Conclusion The newly developed SPESSO is a valid and convenient model which can be used to predict the outcome of open arthrolysis of the elbow. It could assist clinicians in counselling patients regarding the choice and expectations of treatment.
引用
收藏
页码:486 / 494
页数:9
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