A Point-Based Model to Predict Absolute Risk of Revision in Anatomic Shoulder Arthroplasty. (October 2019)

• Record Type: Journal Article
• Authors: Lapner, Peter LC; Rollins, Meaghan D; Tuna, Meltem G; Netting, Caleb; Bader Eddeen, Anan; van Walraven, Carl
• Is Part Of: Journal of shoulder and elbow arthroplasty. Volume 3(2019)
• Publication Date: 2019-10
• Subjects: shoulder arthroplasty -- revision -- risk prediction -- shoulder hemiarthroplasty -- competing risk; Arthroplasty -- Periodicals; Shoulder joint -- Surgery -- Periodicals; Elbow -- Surgery -- Periodicals; 617.57
• DOI: 10.1177/2471549219883446
• Languages: English
• ISSNs: 2471-5492

Abstract

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.