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Bone & Joint Open
Vol. 5, Issue 11 | Pages 1041 - 1048
19 Nov 2024
Delgado C Martínez-Rodríguez JM Candura D Valencia M Martínez-Catalán N Calvo E

Aims

The Bankart and Latarjet procedures are two of the most common surgical techniques to treat anterior shoulder instability with satisfactory clinical and functional outcomes. However, the outcomes in the adolescent population remain unclear, and there is no information regarding the arthroscopic Latarjet in this population. The purpose of this study was to evaluate the outcomes of the arthroscopic Bankart and arthroscopic Latarjet procedures in the management of anterior shoulder instability in adolescents.

Methods

We present a retrospective, matched-pair study of teenagers with anterior glenohumeral instability treated with an arthroscopic Bankart repair (ABR) or an arthroscopic Latarjet (AL) procedure with a minimum two-year follow-up. Preoperative demographic and clinical features, factors associated with dislocation, and complications were collected. Recurrence, defined as dislocation or subluxation, was established as the primary outcome. Clinical and functional outcomes were analyzed using objective (Rowe), and subjective (Western Ontario Shoulder Instability Index (WOSI) and Single Assessment Numeric Evaluation (SANE)) scores. Additionally, the rate of return to sport was assessed.


The Bone & Joint Journal
Vol. 104-B, Issue 4 | Pages 486 - 494
4 Apr 2022
Liu W Sun Z Xiong H Liu J Lu J Cai B Wang W Fan C

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.