Long-term health related quality of life in total knee arthroplasty.

BACKGROUND: To analyze evolution and factors related with greater gains in Health Related Quality of Life (HRQOL) and with a greater probability of exceed their corresponding minimal clinically important differences (MCID) in patients with Osteoarthritis of the knee, undergoing total knee arthroplasty (TKA) at long-term. METHODS: Data were obtained from two previously recruited multicenter cohorts of patients who underwent TKA in the Basque Country. Patients were follow-up at 6 months and 10 years after surgery. Patients completed specific and generic HRQOL questionnaires plus sociodemographic, and clinical data at 10 years. Associations were analysed using linear and logistic regression models. RESULTS: A total of 471 patients responded at 10-year follow-up. The multivariable analysis showed that low preoperative HRQOL scores, higher age, higher BMI, some comorbidities and readmissions at 6 months were associated with less gains in HRQOL. Apart from aforementioned, to have a peripheral vascular disease (odd ratio 0.49 (95% CI, 0.24-0.99)), complications (odd ratio 0.31 (95% CI, 0.11-0.91)), and readmissions within 6 months of discharge (odd ratio 2.12 (95% CI, 1.18-3.80)) were associated with a lower probability of exceeding the MCID. The effect sizes (ESs) of changes from baseline to 6 months (range, 1.20-1.96) and to 10 years (range, 1.54-1.99) were large in all dimensions, nevertheless the ESs from 6 months to 10 years were not appreciable for pain (ES = 0.03) or stiffness (ES = 0.09), and small for function (ES = 0.30). CONCLUSIONS: Low preoperative HRQOL scores, to be elderly, severe obesity, the presence of some comorbidities -depression and rheumatology disease-, having readmissions or complications and not having rehabilitation of discharge, are good predictors of long-term lower gains in HRQOL. Some other non-registered parameters of the follow-up may also influence those outcomes. KEY INDEXING TERMS (MESH TERMS): Health-Related Quality of Life, Knee Arthroplasty, Total, Osteoarthritis.

Predictors of health-related quality-of-life change after total hip arthroplasty.

UNLABELLED: Various parameters have been considered as possible predictors of health-related quality-of-life outcomes after THA in patients with hip osteoarthritis. We hypothesized the preintervention health status is the main and more homogeneous predictor of changes of the different aspects of health-related quality-of-life outcomes, mental health status has an important influence on results, whereas other sociodemographic or clinical factors had only a punctual influence. All patients who fulfilled the selection criteria completed the Medical Outcomes Study SF-36 and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) before and 6 months after the intervention. Seven hundred eighty-eight patients completed the questionnaire before the intervention and 590 completed it (74.9%) at 6 months. The preintervention score in each SF-36 and WOMAC domain and the SF-36 mental health domain predicted changes after the intervention. Female gender, having comorbidities, contralateral hip osteoarthritis, or back pain predicted less improvement on some SF-36 domains. Older age, the presence of contralateral hip osteoarthritis, or back pain predicted less improvement on some of the WOMAC domains. Preintervention health status, measured by the WOMAC or SF-36, and mental health status uniformly predicted health-related quality-of-life changes, whereas some clinical parameters predicted some domains. SF-36 and WOMAC seem to be appropriate tools for predicting THA outcomes. LEVEL OF EVIDENCE: Level II, prognostic study. See Guidelines for Authors for a complete description of levels of evidence.

Health-related quality of life and appropriateness of knee or hip joint replacement.

BACKGROUND: We studied the association between explicit appropriateness criteria for total hip joint replacement (THR) and total knee replacement (TKR) with changes in health-related quality of life of patients undergoing these procedures. METHODS: Prospective observational study of 1576 consecutive patients with diagnoses of osteoarthritis on waiting lists to undergo THR or TKR. Explicit appropriateness criteria using the RAND appropriateness method were applied. Patients completed 2 questionnaires that measured health-related quality of life, the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), before the procedure and 6 months afterward. RESULTS: Patients who were considered appropriate candidates for these procedures had greater improvements than those who were considered inappropriate candidates in all 3 WOMAC domains (pain, functional limitation, and stiffness; THR: 43.0, 40.6, and 40.4 vs 14.7, 19.1, and 15.9; TKR: 34.9, 32.5, and 30.2 vs 23.2, 18.9, and 17.1; P<.001 for all comparisons). Patients who underwent THR and were judged to be appropriate candidates had greater improvements in the physical function, role-physical, bodily pain, and social function domains of the SF-36 than those judged to be inappropriate candidates (34.4, 35.1, 33.1, and 26.6 vs 19.6, 9.2, 5.7, and 7.0; P = .04, P = .03, P < .001, and P < .001, respectively). Appropriate candidates for TKR demonstrated greater improvement in the social function domain of the SF-36 after the procedure than those deemed inappropriate candidates (19.9 vs 7.9; P = .004) but not in the other domains of functional status. CONCLUSIONS: These results suggest a direct relationship between explicit appropriateness criteria and better health-related quality-of-life outcomes after THR and TKR surgery. Our results support the use of these criteria for clinical guidelines or evaluation purposes.

Validation of a screening questionnaire for hip and knee osteoarthritis in old people.

BACKGROUND: To develop a sensitive and specific screening tool for knee and hip osteoarthritis in the general population of elderly people. METHODS: The Knee and Hip OsteoArthritis Screening Questionnaire (KHOA-SQ) was developed based on previous studies and observed data and sent to 11,002 people aged 60 to 90 years, stratified by age and gender, who were selected by random sampling. Algorithms of the KHOA-SQ were created. Respondents positive for knee or hip OA on the KHOA-SQ were invited to be evaluated by an orthopedic surgeon. A sample of 300 individuals negative for knee or hip OA on the KHOA-SQ were also invited for evaluation. Sensitivity and specificity were determined for the KHOA-SQ, as well as for KHOA-SQ questions. Classification and Regression Tree analysis was used to find alternative screening algorithms from the questionnaire. RESULTS: Of 11,002 individuals contacted, 7,577 completed the KHOA-SQ. Of 1,115 positive for knee OA, on the KHOA-SQ, 710 (63.6%) were diagnosed with it. For hip OA, 339 of the 772 who screened positive (43.9%) were diagnosed it. Sensitivity for the hip algorithm was 87.4% and specificity 59.8%; for the knee, sensitivity was 94.5% and specificity 43.8%. Two alternative algorithms provided lower specificity. CONCLUSION: The KHOA-SQ offers high sensitivity and moderate specificity. Although this tool correctly identifies individuals with knee or hip OA, the high false positive rate could pose problems. Based on our questions, no better algorithm was found.

Development of explicit criteria for prioritization of hip and knee replacement.

RATIONALE AND AIMS: Among the problems to the publicly funded national health services are the waiting lists. Patients who need elective surgery generally have long waiting times before treatment. We aimed to develop a new prioritization tool for primary hip and knee replacement. METHODS: Criteria were developed using a modified Delphi panel process. We convened a panel of nine members who scored the scenarios created by the research team and by patient focus groups. We studied the level of agreement among the panelists and the contribution of the variables to the ratings of the panel using linear and logistic regression models. The priority scores of the variables and their levels were synthesized using the optimal scaling and standard linear regression methods. RESULTS: Seven variables, pain on motion, walking functional limitations, abnormal findings on physical examination, pain at rest, other functional limitations, social role, and other pathologies that could improve with joint replacement, were considered to create the different scenarios. The panel scored 192 scenarios. The disagreement among the panelists was very low (1%) with an intra-class correlation coefficient of 0.72. Of the 192 scenarios, 45.8% were scored as urgent, 35.4% as preferred and 18.8% as ordinary. The variables that contributed most to the scores were pain on motion and walking functional limitations. When optimal scaling and regression techniques were applied, similar results were obtained. CONCLUSION: This tool can evaluate and prioritize patients on a waiting list for hip or knee replacement. We also provide a simple and easy way to use an algorithm to estimate the treatment priority for individual patients.