关节镜下肩袖修复术后肩关节僵硬预测模型的更新。

IF 5.4 Q1 MEDICINE, RESEARCH & EXPERIMENTAL
Thomas Stojanov, Soheila Aghlmandi, Andreas Marc Müller, Philipp Moroder, Alexandre Lädermann, Cornelia Baum, Laurent Audigé
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引用次数: 0

摘要

背景:关节镜下肩袖修复(ARCR)是一种常见的手术,术后肩僵硬(POSS)是其最常见的不良事件之一,可能需要个体化治疗。我们的目的是更新并内部验证一个预测ARCR患者POSS发生的模型。方法:我们前瞻性地纳入了973例接受原发性ARCR的患者,纳入了ARCR_Pred数据集。对53名外科医生进行了两轮德尔菲调查,建立了术后6个月内POSS的共识定义和候选预后因素排名。治疗外科医生在手术后立即估计POSS风险。我们从外部验证了现有的POSS模型,并使用完整案例和多个输入数据集开发了更新的多变量逻辑回归模型。结果:我们在44位应答肩外科医生中对POSS的定义达成了高度共识(88%),他们还对71个因素的预后相关性进行了预测POSS。新开发的ARCR_Pred-POSS包括7个因素(年龄、肩肱骨距离、症状持续时间、基线外旋、基线主动外展、基线牛津肩评分和手术持续时间),与原始POSS模型(AUC = 0.581,斜率= 0.508)相比,具有更好的识别(AUC = 0.735)和校准(斜率= 1.022)。外科医生倾向于高估患者POSS的风险(AUC = 0.563,斜率= 1.241)。结论:这些发现支持了预测模型的持续发展,并为优化手术时机、适应证和个性化康复提供了有价值的产出。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Update of a prediction model for postoperative shoulder stiffness after arthroscopic rotator cuff repair.

Background: Arthroscopic rotator cuff repair (ARCR) is a common procedure, and postoperative shoulder stiffness (POSS) is one of its most frequent adverse events, potentially necessitating individualized therapy. Our objectives were to update and internally validate a model predicting the occurrence of POSS for patients undergoing an ARCR.

Methods: We prospectively enrolled 973 patients undergoing primary ARCR included in the ARCR_Pred dataset. A two-round Delphi survey with 53 surgeons established a consensus definition of POSS within 6 months postoperatively and a ranking of candidate prognostic factors. Treating surgeons estimated POSS risk immediately after surgery. We externally validated an existing POSS model and developed updated multivariable logistic regression models using complete-case and multiple imputed datasets.

Results: We achieved a high consensus (88%) on the POSS definition among 44 responding shoulder surgeons, who also ranked the prognostic relevance of 71 factors for the prediction of POSS. The newly developed ARCR_Pred-POSS included 7 factors (age, acromiohumeral distance, symptom duration, baseline external rotation, active baseline abduction, baseline Oxford Shoulder Score, and surgery duration) and demonstrated superior discrimination (AUC = 0.735) and calibration (slope = 1.022) compared to the original POSS model (AUC = 0.581, slope = 0.508). Surgeons tended to overestimate the risk of POSS in their patients (AUC = 0.563, slope = 1.241).

Conclusions: These findings support the continued development of prediction models and provide valuable outputs for optimizing surgical timing, indications, and personalized rehabilitation.

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