Development and validation of a prognostic nomogram for open elbow arthrolysis: the Shanghai Prediction model for Elbow Stiffness Surgical Outcome. (4th April 2022)

• Record Type: Journal Article
• Authors: Liu, Weixuan; Sun, Ziyang; Xiong, Hao; Liu, Junjian; Lu, Jiuzhou; Cai, Bin; Wang, Wei; Fan, Cunyi
• Is Part Of: Bone & joint journal. Volume 104B:Number 4(2022)
• Page Start: 486
• Page End: 494
• Publication Date: 2022-04-04
• Subjects: Elbow -- Nomogram -- Open arthrolysis -- Post-traumatic elbow stiffness -- Predictors -- Range of motion -- Prediction model -- Nomograms -- elbow -- arthrolysis -- post-traumatic stiffness -- stiffness -- open arthrolysis -- post-traumatic osteoarthritis -- elbow stiffness -- clinicians -- clinical outcome; Bones -- Surgery -- Periodicals; Joints -- Surgery -- Periodicals; Orthopedic surgery -- Periodicals; 617.47005
• DOI: 10.1302/0301-620X.104B4.BJJ-2021-1326.R2
• Languages: English
• ISSNs: 2049-4394

Abstract

Abstract : 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°) 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 (SPESSO) 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. Cite this article: Bone Joint J 2022;104-B(4):486–494.