One Size Does Not Fit All: Women Experience More Pain Than Men After Total Knee Arthroplasty

Background Multimodal pain regimens are universally applied to all patients, despite known differences in pain and responses to medication between patients of different sexes, ethnicities, and races. The purpose of this study was to understand the influence of patient sex on postoperative total knee arthroplasty pain perception as well as the efficacy of perioperative pregabalin for pain control. Methods Visual analog Scales (VASs) and Knee Injury and Osteoarthritis Outcome Junior (KOOS Jr.) scores were prospectively collected for 150 patients (64 men and 86 women). Mean pain scores, delta pain scores, time to achieve minimal clinically important differences, influence of pregabalin, and opioid consumption were recorded at baseline, day of surgery, 24 hours, 48 hours, and 72 hours postoperatively, as well as postoperatively weeks 1, 2, 6, 12, and 26, and compared between women and men cohorts. This study was registered on ClinicalTrials.gov (NCT04471233). Results The VAS pain scores for women were higher than for men at all study time points (P < 0.05). The change in VAS walking and mean KOOS Jr. scores from baseline to final follow-up at 26 weeks were not significantly different between cohorts. Both cohorts achieved VAS minimal clinically important difference by 2 weeks postoperatively. No significant differences in opioid consumption between men and women were noted during the study time periods. Women were also noted to have significantly higher raw KOOS Jr. scores than men at all-time points, except for at 26 weeks postoperatively. Interim analysis revealed no significant influence of pregabalin on VAS scores, so this arm of the study was discontinued. Conclusions Patient sex plays a role in perceived postoperative total knee arthroplasty pain, as women reported higher pain scores than men. We recommend not overly relying on standardized protocols, but rather instituting patient-specific pain management strategies. (c) 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.