Comparison of Health-Related Quality of Life, Work Status, and Health Care Utilization and Costs According to Hip and Knee Joint Disease Severity: A National Australian Study
Bibliographic record
Abstract
BACKGROUND: No population-based studies have investigated how the impact of hip and knee joint disease may vary with increasing severity. OBJECTIVE: The purpose of this study was to evaluate health-related quality of life (HRQoL), work status, and health service utilization and costs according to severity of hip and knee joint disease. DESIGN: A national cross-sectional survey was conducted. METHODS: Five thousand individuals were randomly selected from the Australian electoral roll and invited to complete a questionnaire to screen for doctor-diagnosed hip arthritis, hip osteoarthritis (OA), knee arthritis, and knee OA. Severity was classified by means of Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores (range=0-100): <7=asymptomatic, 7-38=mild-moderate, and ≥39=severe. Health-related quality of life was evaluated by means of the Assessment of Quality of Life (AQoL) instrument (range=-0.04 to 1.00; scored worst-best). Self-reported data on work status and health service utilization were collected, with health care costs estimated with the use of government data. RESULTS: Data were available for 1,157 participants, with 237 (20%) reporting hip or knee joint disease. Of these, 16% (n=37) were classified as asymptomatic, 51% (n=120) as mild-moderate, and 27% (n=64) as severe. The severe group reported very low HRQoL (adjusted mean AQoL=0.43, 95% confidence interval [95% CI]=0.38-0.47) compared with the mild-moderate group (adjusted mean AQoL=0.72, 95% CI=0.69-0.75) and the asymptomatic group (adjusted mean AQoL=0.80, 95% CI=0.74-0.86). Compared with the asymptomatic group, the severe group was >3 times less likely to undertake paid work (adjusted odds ratio=0.28, 95% CI=0.09-0.88) and >4 times less likely to undertake unpaid work (adjusted odds ratio=0.24, 95% CI=0.10-0.62). Although physical therapy services were used infrequently, primary and specialist care utilization and costs were highest for the severe group. LIMITATIONS: Other costs (including physical therapy consultations) were unavailable. CONCLUSIONS: A clear pattern of worsening HRQoL, reduced work participation, and higher medical care utilization was seen with increasing severity of joint disease.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".