Clinical Tool to Identify Patients Who Are Most Likely to Achieve Long-Term Improvement in Physical Function After Total Hip Arthroplasty

Objective. To develop a clinical risk prediction tool to identify patients most likely to experience long-term clinically meaningful functional improvement following total hip arthroplasty (THA). Methods. We studied 282 patients from 2 health districts in England (Portsmouth and North Staffordshire) who were >= 45 years of age and undergoing THA for primary osteoarthritis. Baseline data on age, sex, comorbidity, body mass index (BMI), functional status (Short Form 36 [SF-36]), and preoperative radiographic severity were collected by interview and examination. The outcome was a clinically significant (30-point) improvement in SF-36 physical function score assessed similar to 8 years after THA. Logistic regression modeling was used to identify predictors of functional improvement. Results. Improvement in physical function was less likely in patients with better preoperative functioning (odds ratio [OR] 0.73 [95% confidence interval (95% CI) 0.60, 0.89]), older people (OR 0.94 [95% CI 0.90, 0.98]), women (OR 0.37 [95% CI 0.19, 0.72]), those with a previous hip injury (OR 0.14 [95% CI 0.03, 0.74]), and those with a greater number of painful joint sites (OR 0.61 [95% CI 0.46, 0.80]). Patients with worse radiographic grades were most likely to improve (OR 2.15 [95% CI 1.17, 3.93]). We found no influence of BMI or patient comorbidity on functional outcome. Predictors of good outcomes were the same as those of bad outcomes, acting in the opposite direction. A clinical risk prediction tool was developed to identify patients who are most likely to receive functional improvement following THA. Conclusion. This prediction tool has the potential to inform health care professionals and patients about functional improvement following THA (as distinct from driving rationing or commissioning decisions regarding who should have surgery); it requires introduction into clinical practice under research conditions to investigate its impact on decisions made by patients and clinicians.