Waiting for total knee replacement surgery: factors associated with pain, stiffness, function and quality of life
Bibliographic record
Abstract
BACKGROUND: Recent evidences show that education and rehabilitation while waiting for knee replacement have positive effects on the patients' health status. Identification of factors associated with worse pain, function and health-related quality of life (HRQoL) while waiting for surgery could help develop pre-surgery rehabilitation interventions that target specifically these factors and prioritize patients that may benefit the most from them. The objectives of this study were to measure pain, stiffness, function and HRQoL in patients at enrolment on waiting lists for knee replacement and to identify demographic, clinical, socioeconomic and psychosocial characteristics associated with these outcomes. METHODS: This study is part of a broader study measuring the effects of pre-surgery wait in patients scheduled for knee replacement. From 02/2006 to 09/2007, 197 patients newly scheduled for total knee replacement were recruited from the waiting lists of three university hospitals in Quebec City, Canada. Pain, stiffness and function were measured with the Western Ontario and McMaster Osteoarthritis Index (WOMAC) and HRQoL was measured with the SF-36 Health Survey. Stepwise multiple regression analysis was used to assess the strength of the associations between the independent variables and the WOMAC and SF-36 scores. RESULTS: The scores of all eight HRQoL physical and mental domains of the SF-36 were significantly lower than aged matched Canadian normative data (p < 0.05). Contralateral knee pain, higher psychological distress, higher body mass index (BMI) and the use of a walking aid were significantly associated with worse function (p < 0.05) and contributed to 22% of the variance of the WOMAC function score (multiple r = 0.47). A higher BMI, the use of a walking aid, contralateral knee pain and advanced age were significantly associated with worse physical function (p < 0.05) and contributed to 17% of the variance of the SF-36 HRQoL physical functioning score (multiple r = 0.41). CONCLUSION: Patients waiting for knee replacement have poor function and HRQoL. Characteristics that were found to be associated with these outcomes could help develop pre-surgery rehabilitation program and prioritize patients that may benefit the most from them. Such programs could include interventions to reduce psychological distress, therapeutic exercises targeting both knees and weight loss management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".