Comparison of Demographics and Oxford Knee Score in Total Knee Arthroplasty Patients Between the United Kingdom and Saudi Arabia: A Cohort Study

Background/Objectives: Total knee arthroplasty (TKA) is considered as important final line of treatment for several conditions such as knee osteoarthritis. Interestingly, culture, demographics, and health care systems may differ between countries, leading to different outcomes. Understanding this variation can help in enhancing patient care and rehabilitation therapy. This study aimed to compare primary TKA patients from the Kingdom of Saudi Arabia (KSA) and the United Kingdom (UK) pre- and post-surgery, representing two different populations and cultural backgrounds. Methods: A retrospective cohort sample was collected from the UK and one prospective cohort sample was collected in the KSA. Demographic characteristics and the Oxford knee score (OKS) were compared preoperatively and 6 and 12 months postoperatively. Results: A total of 259 patients were included in the study. Significant differences were observed in demographic characteristics. Patients in the UK cohort were five years older and 7 kg/m2 lower in body mass index (BMI) than those in the KSA cohort. The proportion of male patients was higher in the UK cohort (37%) compared to the KSA cohort (17%). Preoperatively, the OKS was significantly (p = 0.001) worse in the Saudi cohort (15 +/- 4) compared to the UK cohort (19 +/- 6). After 6 months postoperatively, both groups improved; however, there was a significant difference, with a higher value for the KSA cohort compared to the UK cohort. By 12 months post-TKA, the difference in OKS between the populations no longer existed. Conclusions: Although there are notable differences in demographics and preoperative OKS, the functional outcomes at 12 months post-TKA were comparable between the two populations. These findings suggest that while cultural and demographic factors may influence early postoperative recovery, 12-month outcomes tend to converge across different populations.