Effect of osteoarthritis and its surgical treatment on patients’ quality of life: a longitudinal study
Bibliographic record
Abstract
BACKGROUND: Osteoarthritis (OA) is one of the primary causes of pain and disability worldwide leading to patients having some of the worst health-related quality of life (QOL). The purpose of our study was to investigate the progression of the generic and disease-specific QOL of osteoarthritic patients going through total hip or knee replacement surgery and the factors that might alter the effect of surgery on QOL. METHODS: A longitudinal study was performed based on data collected from 120 OA patients who filled in the short version of the WHO's generic measure of quality of life (WHOQOL-BREF) and the disease-specific Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) before and after surgery. RESULTS: Domains related to physical health status showed relatively lower scores in patients before surgery. Patients reported a significant increase of QOL after surgery in the WHOQOL-BREF physical domain, especially if they were from the younger group (< 65 years, p = 0.022) or had a manual job (p = 0.008). Disease-specific QOL outcome results indicate that overall patients gained significantly better QOL in all domains of the WOMAC score. Patients with hip OA seemed to have the most benefit of their operation as they reported better outcome in WOMAC pain (p = 0.019), stiffness (p = 0.010), physical function domains (p = 0.011) and total score (p = 0.007) compared to knee OA patients. CONCLUSION: There was a statistically significant improvement in all domains concerning physical functions in the study population. Patients also reported significant improvement in the social relationship domain, which indicates that OA itself as well as its management might have a profound effect on patients' life beyond the reduction of their pain.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".