Nanchang University, Nanchang, Jiangxi province, China.
Department of Sports Medicine, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi province, China.
BMC Musculoskelet Disord. 2024 Oct 2;25(1):775. doi: 10.1186/s12891-024-07831-1.
The factors influencing the clinical outcome of arthroscopic rotator cuff repair are not fully understood.
To explore the factors related to the postoperative outcome of arthroscopic single-row rivet rotator cuff repair in patients with rotator cuff injury and to construct the related nomogram risk prediction model.
207 patients with rotator cuff injury who underwent arthroscopic single-row rivet rotator cuff repair were reviewed. The differences of preoperative and postoperative Visual Analogue Score (VAS) scores and University of California, Los Angeles (UCLA) scores were analyzed and compared. The postoperative UCLA score of 29 points was taken as the critical point, and the patients were divided into good recovery group and poor recovery group, and binary logstic regression analysis was performed. According to the results of multivariate logistic regression analysis, the correlation nomogram model was constructed, and the calibration chart was used, AUC, C-index. The accuracy, discrimination and clinical value of the prediction model were evaluated by decision curve analysis. Finally, internal validation is performed using self-random sampling.
The mean follow-up time was 29.92 ± 17.20 months. There were significant differences in VAS score and UCLA score between preoperative and final follow-up (p < 0.05); multivariate regression analysis showed: Combined frozen shoulder (OR = 3.890, 95% CI: 1.544 ∼ 9.800), massive rotator cuff tear (OR = 3.809, 95%CI: 1.218 ∼ 11.908), More rivets number (OR = 2.118, 95%CI: 1.386 ∼ 3.237), lower preoperative UCLA score (OR = 0.831, 95%CI: 0.704-0.981) were adverse factors for the postoperative effect of arthroscopic rotator cuff repair. Use these factors to build a nomogram. The nomogram showed good discriminant and predictive power, with AUC of 0.849 and C-index of 0.900 (95% CI: 0.845 ∼ 0.955), and the corrected C index was as high as 0.836 in internal validation. Decision curve analysis also showed that the nomogram could be used clinically when intervention was performed at a threshold of 2%∼91%.
Combined frozen shoulders, massive rotator cuff tears, and increased number of rivets during surgery were all factors associated with poor outcome after arthroscopic rotator cuff repair, while higher preoperative UCLA scores were factors associated with good outcome after arthroscopic rotator cuff repair. This study provides clinicians with a new and relatively accurate nomogram model.
关节镜肩袖修复术后临床结果的影响因素尚不完全清楚。
探讨影响肩袖损伤患者关节镜下单排铆钉肩袖修复术后疗效的相关因素，并构建相关列线图风险预测模型。
回顾性分析 207 例肩袖损伤患者行关节镜下单排铆钉肩袖修复术的临床资料，分析比较患者术前、术后视觉模拟评分（VAS）和加州大学洛杉矶分校（UCLA）评分的差异，以术后 UCLA 评分 29 分为界点，将患者分为恢复良好组和恢复不良组，行二项 Logistic 回归分析。根据多因素 Logistic 回归分析结果，构建相关性列线图模型，并用校准图、AUC、C 指数评估预测模型的准确性、判别力和临床价值，最后采用自抽样法进行内部验证。
患者平均随访时间为 29.92±17.20 个月，术前与末次随访时 VAS 评分和 UCLA 评分比较差异均有统计学意义（P<0.05）；多因素回归分析显示：合并冻结肩（OR=3.890，95%CI：1.544∼9.800）、巨大肩袖撕裂（OR=3.809，95%CI：1.218∼11.908）、铆钉数量较多（OR=2.118，95%CI：1.386∼3.237）、术前 UCLA 评分较低（OR=0.831，95%CI：0.704∼0.981）是影响关节镜肩袖修复术后疗效的不利因素。利用这些因素构建列线图，该列线图显示出良好的判别和预测能力，AUC 为 0.849，C 指数为 0.900（95%CI：0.845∼0.955），内部验证校正 C 指数高达 0.836。决策曲线分析也表明，当干预阈值为 2%∼91%时，该列线图可在临床上使用。
合并冻结肩、巨大肩袖撕裂、术中铆钉数量增加均是影响关节镜肩袖修复术后疗效的不利因素，而术前较高的 UCLA 评分是影响关节镜肩袖修复术后疗效的有利因素。本研究为临床医生提供了一种新的、相对准确的列线图模型。
