Measurement properties of UCLA Activity Scale for hip and knee arthroplasty patients and translation and cultural adaptation into Danish.

Background and purpose - The UCLA Activity Scale (UCLA) is a questionnaire assessing physical activity level from 1 (low) to 10 (high) in patients undergoing hip or knee arthroplasty (HA/KA). After translation and cultural adaptation, we evaluated the measurement properties of the Danish UCLA.Patients and methods - After dual panel translation, cognitive interviews were performed among 55 HA/KA patients. An orthopedic surgeon and a physiotherapist estimated UCLA scores for 80 KA patients based on short interviews. Measurement properties were evaluated in 130 HA and 134 KA patients preoperatively and 1-year postoperatively.Results - To suit Danish patients of today, several adaptations were required. Prior to interviews, 4 patients were excluded, and 11 misinterpreted the answer options. Examiners rated the remaining 65 patients (mean age 67 years) 0.2-1.6 UCLA levels lower than patients themselves. The 130 HA and 134 KA patients (mean age 71/68 years) changed from 4.3 (SD 1.9)/4.5 (1.8) preoperatively to 6.6 (1.8)/6.2 (1.0) at 1-year follow-up. 103 (79%) HA and 89 (66%) KA patients reported increased activity. Effect sizes were large (1.2/0.96). Knee patients reaching minimal important change (MIC, ≥ 8 Oxford Knee Score points) had higher 1-year UCLA scores than patients not reaching MIC.Interpretation - Original scale development was undocumented. Content validity was questionable, and there was discrepancy between patient and examiner estimates. UCLA appears valuable for measuring change in self-reported physical activity on a group level. 4 out of 5 HA patients and 2 out of 3 KA patients were more physically active 1 year after joint replacement surgery.

Knee Osteoarthritis Patients Can Provide Useful Estimates of Passive Knee Range of Motion: Development and Validation of the Copenhagen Knee ROM Scale.

BACKGROUND: Knee arthroplasty does not always require extensive long-term follow-up. If knee range of motion (ROM) could be assessed reliably by patients, some follow-up visits might be replaced by patient-reported outcome measures, and this additional information could be reported directly to registers. We developed and tested the validity and reliability of a simple scale for patients to self-report their passive knee ROM. METHODS: Through an iterative process, we created a 2-item scale with 11 illustrations of knee motion in 15° increments. The validity and reliability was tested in knee osteoarthritis and arthroplasty patients at different treatment stages, many with poor ROM. Patient estimates were compared to passive goniometer measurements performed blindly by a physiotherapist and a junior orthopedic surgeon. RESULTS: The mean difference between 100 patients' (70.9 years) estimates and goniometer measurements was -0.7° (standard deviation, 12.3°) for flexion and 1.1° (standard deviation, 11.6°) for extension, both not significant. Correlation was 0.79 and 0.63, and kappa values at retest were 0.84 and 0.66. For flexion < 110°, sensitivity of patient estimates was 88% and specificity was 88%. For a limit of 100°, values were 95% and 81%. For extension deficits >10°, sensitivity was 78% and specificity 70%. Values were 100% and 66% for a 15° limit. CONCLUSION: The Copenhagen Knee ROM Scale is a patient-friendly and feasible alternative to passive ROM measurement for registers, research, and selected clinical use. This scale appears reliable and valid compared to reports of similar tools, and patient estimates are better correlated to goniometer measurements.

Development and comparison of 1-year survival models in patients with primary bone sarcomas: External validation of a Bayesian belief network model and creation and external validation of a new gradient boosting machine model.

BACKGROUND: Bone sarcomas often present late with advanced stage at diagnosis and an according, varying short-term survival. In 2016, Nandra et al. generated a Bayesian belief network model for 1-year survival in patients with bone sarcomas. The purpose of this study is: (1) to externally validate the prior 1-year Bayesian belief network prediction model for survival in patients with bone sarcomas and (2) to develop a gradient boosting machine model using Nandra et al.'s cohort and evaluate whether the gradient boosting machine model outperforms the Bayesian belief network model when externally validated in an independent Danish population cohort. MATERIAL AND METHODS: The training cohort comprised 3493 patients newly diagnosed with bone sarcoma from the institutional prospectively maintained database at the Royal Orthopaedic Hospital, Birmingham, UK. The validation cohort comprised 771 patients with newly diagnosed bone sarcoma included from the Danish Sarcoma Registry during January 1, 2000-June 22, 2016. We performed area under receiver operator characteristic curve analysis, Brier score and decision curve analysis to evaluate the predictive performance of the models. RESULTS: External validation of the Bayesian belief network 1-year prediction model demonstrated an area under receiver operator characteristic curve of 68% (95% confidence interval, 62%-73%). Area under receiver operator characteristic curve of the gradient boosting machine model demonstrated: 75% (95% confidence interval: 70%-80%), overall model performance by the Brier score was 0.09 (95% confidence interval: 0.077-0.11) and decision curve analysis demonstrated a positive net benefit for threshold probabilities above 0.5. External validation of the developed gradient boosting machine model demonstrated an area under receiver operator characteristic curve of 63% (95% confidence interval: 57%-68%), and the Brier score was 0.14 (95% confidence interval: 0.12-0.16). CONCLUSION: External validation of the 1-year Bayesian belief network survival model yielded a poor outcome based on a Danish population cohort validation. We successfully developed a gradient boosting machine 1-year survival model. The gradient boosting machine did not outperform the Bayesian belief network model based on external validation in a Danish population-based cohort.