基于点的模型预测解剖肩关节置换术翻修绝对风险。

Journal of shoulder and elbow arthroplasty Pub Date : 2019-10-21 eCollection Date: 2019-01-01 DOI:10.1177/2471549219883446
Peter Lc Lapner, Meaghan D Rollins, Meltem G Tuna, Caleb Netting, Anan Bader Eddeen, Carl van Walraven
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摘要

背景:全肩关节置换术(TSA)显示出良好的长期生存率,但早期植入物可能发生失败。本研究确定了与肩关节置换术翻修相关的因素,并构建了肩关节置换术后翻修手术的风险评分。方法:采用一种经过验证的算法,使用基于人群的数据识别2002年至2012年间接受解剖性TSA的所有患者。人口统计学变量包括肩关节植入物类型、年龄和性别、Charlson合并症评分、收入五分位数、诊断和外科医生关节置换术量。在将死亡视为竞争风险并在肩关节置换术翻修风险评分(SARRS)中表达时,测量协变量与翻修时间的关联。结果:在研究期间,4079例患者接受了TSA。翻修风险随患者年龄增长和无骨关节炎呈非线性降低,不受手术类型或其他协变量的影响。SARRS范围从-21分(5年修订风险0.75%)到30分(风险11.4%)。评分判别性相对较弱,为0.55(95%可信区间:0.530.61),但校准非常好,检验统计量为5.77 (df = 8, P = .762)。讨论:SARRS模型准确预测了TSA患者的5年翻修风险。在此评分用于临床预测翻修风险之前,需要进行验证研究。需要进一步的研究来确定加入详细的临床数据,包括功能结果测量和盂肱关节的严重程度是否会增加模型的辨别能力。
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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A Point-Based Model to Predict Absolute Risk of Revision in Anatomic Shoulder Arthroplasty.

Background: Total shoulder arthroplasty (TSA) has demonstrated good long-term survivorship but early implant failure can occur. This study identified factors associated with shoulder arthroplasty revision and constructed a risk score for revision surgery following shoulder arthroplasty.

Methods: A validated algorithm was used to identify all patients who underwent anatomic TSA between 2002 and 2012 using population-based data. Demographic variables included shoulder implant type, age and sex, Charlson comorbidity score, income quintile, diagnosis, and surgeon arthroplasty volume. The associations of covariates with time to revision were measured while treating death as a competing risk and were expressed in the Shoulder Arthroplasty Revision Risk Score (SARRS).

Results: During the study period, 4079 patients underwent TSA. Revision risk decreased in a nonlinear fashion as patients aged and in the absence of osteoarthritis with no influence from surgery type or other covariables. The SARRS ranged from -21 points (5-year revision risk 0.75%) to 30 points (risk 11.4%). Score discrimination was relatively weak 0.55 (95% confidence interval: 0.530.61) but calibration was very good with a test statistic of 5.77 (df = 8, P = .762).

Discussion: The SARRS model accurately predicted the 5-year revision risk in patients undergoing TSA. Validation studies are required before this score can be used clinically to predict revision risk. Further study is needed to determine if the addition of detailed clinical data including functional outcome measures and the severity of glenohumeral arthrosis increases the model's discrimination.

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