The Impact of Diagnosed Chronic Sleep Disorders on Outcomes Following Total Knee Arthroplasty

Background: Up to 20% of patients undergoing total knee arthroplasty (TKA) remain dissatisfied with their outcome, leading to the identification of risk factors for poor outcomes. The purpose of this study was to analyze the effect of chronic sleep disorders on patient-reported outcomes after primary TKA. Methods: A retrospective review of patients undergoing primary TKA was conducted using a prospectively collected database of patients from a single institution between 2018 and 2022. The cohort was split based on the presence of documented chronic sleep disorders, identified preoperatively from the electronic medical record using current procedural terminology codes. The sample was further restricted to include all patients who have sleep disorders (SDs), as well as a 3:1 propensity-matched (on age, sex, body mass index, and American Society of Anesthesiologists class) cohort of patients who had no documented SDs (NSDs) prior to surgery. The final sample included 172 patients (SD: 43; NSD: 129). Repeated-measures linear mixed model analysis was used to analyze the progression of Knee Injury and Osteoarthritis Outcome Score (KOOS) through time between groups. Results: Those who had SDs had a lower preoperative mean total KOOS score (40.2) than the NSD group (44.1); however, this was not significantly different (P = .108). At 1 year postoperatively, those who had an SD had a significantly higher mean total KOOS score (87.2) than the NSD group (80.4), P = .005. When comparing total KOOS scores by group, over each time period, the SD group showed a better progression when compared to the NSD group, P = .001. Conclusions: Compared to patients who did not have documented chronic sleep disorders, patients who had a prior history of chronic sleep disorders reported significantly greater improvements in most KOOS domains in the 12-month period following TKA. (c) 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.