Patient Acceptable Symptom State for the Oxford Elbow Score After Primary Elbow Arthroplasty Due to Acute Distal Humeral Fracture.

Background: Patient Acceptable Symptom State (PASS) describes the highest level of symptom beyond which patients consider themselves well. PASS can be used to establish what patients' view as an acceptable outcome after surgery. The Oxford Elbow Score (OES) is one of the most used elbow-specific patient-reported outcome measure (PROM), but a PASS-value has not yet been established for the OES after elbow arthroplasty. The primary purpose of this study was to determine the PASS for the OES after primary elbow arthroplasty due to acute distal humeral fracture. Methods: This is a retrospective multi-center cohort study. All nationwide patients treated with elbow arthroplasty due to acute distal humeral fracture from January 1, 2008, until December 1, 2021, were invited to participate. Data were collected retrospectively using electronic health records. Study participants answered the OES, and a PASS-anchor question was used to assess if patients were in an acceptable state at follow-up. Logistic modelling was used to determine the PASS-value, defined as the value of OES needed to achieve an acceptable postoperative result with at least 95% probability. A PASS-value was estimated for the total population, for patients with <5 years of follow-up, and patients with ≥5 years of follow-up. Results: The OES and PASS-anchor was answered by 159 (62%) patients. Median OES was 41 (0-48) in the total population. One hundred and thirty-nine patients (87%) reported an acceptable result. The 95% PASS-value for the OES was 33 (95% CI 29.6-38.5) in the total population. Conclusion: The PASS-value for the OES after elbow arthroplasty due to acute distal humeral fracture was 33 for the total population and similar for patients with short-term and long-term follow-up. We recommend using the PASS-value to aid in interpretation of clinical trials and registry-based studies as well as identifying clinical failures in registries.