Development and validation of a nomogram for predicting a forgotten joint in patients one year after robotic-assisted total knee arthroplasty.

IF 2.2 3区 医学 Q2 ORTHOPEDICS
Chengshuai Zhang, Zhaolun Wang, Jianzeng Zhang, Qi Wang, Dejin Yang, Yixin Zhou
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引用次数: 0

Abstract

Purpose: The Forgotten Joint Score (FJS-12) was designed to assess the extent to which patients were unaware of their artificial joints during daily activities, representing an ideal outcome of TKA. This study aimed to identify the individual predictors and develop a nomogram to predict a forgotten joint in patients 1 year after robotic-assisted total knee arthroplasty (RA-TKA).

Methods: This retrospective study involved 199 patients with knee osteoarthritis who underwent RA-TKA. All participants completed the FJS-12 questionnaire at 1-year follow-up, with scores above 77.1 considered indicative of a forgotten joint. The demographic data, surgical data, preoperative and postoperative imaging data were collected for analysis. Univariate and multivariate logistic regression analyses were conducted to determine predictors and establish a predictive model. The receiver operating characteristic curve, calibration curve analysis and decision curve analysis (DCA) were used to evaluate the discriminatory ability, calibration and clinical usefulness of the model.

Results: Overall, 44.22% (88/199) of knees achieved a forgotten joint 1 year after RA-TKA. Five variables were identified as independent predictors, including age, sex, prothesis type, operative time and changes in the arithmetic hip-knee-ankle angle (aHKA). The area under the curve (AUC) of the nomogram was 0.726 and 0.725 (95% CI 0.660-0.788) using 500 bootstrap resampling. The Hosmer-Lemeshow test showed that the model was of goodness-of-fit (p = 0.886). And the DCA showed net benefits when the threshold probability was between 20 and 75%.

Conclusions: A nomogram was developed and internally validated for predicting a forgotten joint 1 year after RA-TKA. Its implementation may enhance patient selection, refine preoperative counseling, and optimize surgical decision-making, potentially improving functional outcomes. Further external validation in broader populations is required to confirm its generalizability.

Clinical trial number: Not applicable.

机器人辅助全膝关节置换术一年后患者遗忘关节的nomogram预测方法的开发与验证。
目的:遗忘关节评分(FJS-12)旨在评估患者在日常活动中不知道其人工关节的程度,代表TKA的理想结果。本研究旨在确定个体预测因素,并开发一种nomogram方法来预测机器人辅助全膝关节置换术(RA-TKA)后1年患者的遗忘关节。方法:对199例行RA-TKA的膝关节骨性关节炎患者进行回顾性研究。所有参与者在1年的随访中完成了FJS-12问卷,得分超过77.1被认为是遗忘关节的标志。收集人口学资料、手术资料、术前和术后影像学资料进行分析。采用单因素和多因素logistic回归分析确定预测因子,建立预测模型。采用受试者工作特征曲线、校正曲线分析和决策曲线分析(DCA)评价模型的判别能力、校正和临床应用。结果:总体而言,44.22%(88/199)的膝关节在RA-TKA术后1年实现了遗忘关节。确定年龄、性别、假体类型、手术时间和算术髋关节-膝关节-踝关节角(aHKA)的变化为独立预测因素。使用500次bootstrap重采样,nomogram曲线下面积(AUC)分别为0.726和0.725 (95% CI为0.660-0.788)。Hosmer-Lemeshow检验表明模型具有拟合优度(p = 0.886)。当阈值概率在20%到75%之间时,DCA显示出净收益。结论:开发并内部验证了一种nomogram,用于预测RA-TKA术后1年的遗忘关节。它的实施可以加强患者选择,完善术前咨询,优化手术决策,潜在地改善功能预后。需要在更广泛的人群中进行进一步的外部验证,以确认其普遍性。临床试验号:不适用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Musculoskeletal Disorders
BMC Musculoskeletal Disorders 医学-风湿病学
CiteScore
3.80
自引率
8.70%
发文量
1017
审稿时长
3-6 weeks
期刊介绍: BMC Musculoskeletal Disorders is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of musculoskeletal disorders, as well as related molecular genetics, pathophysiology, and epidemiology. The scope of the Journal covers research into rheumatic diseases where the primary focus relates specifically to a component(s) of the musculoskeletal system.
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