Course and predictors of pain and physical functioning in patients with hip osteoarthritis: Systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To systematically summarize the literature on: (i) the course of pain and physical functioning; and (ii) predictors of deterioration of pain and physical functioning in patients with osteoarthritis of the hip. METHODS: A literature search was conducted in PubMed, CINAHL, Embase, PsychINFO and SPORTDiscus up to July 2015. Meta-analyses and qualitative data syntheses were performed. RESULTS: Eleven of the 15 included studies were of high quality. With regard to the course of pain and physical functioning, high heterogeneity was found across studies (I² > 71%) and within study populations (reflected by large standard deviations (SDs) of change scores). Therefore, the course of pain and physical functioning was interpreted to be indistinct. Clinical characteristics (higher comorbidity count and presence of knee osteoarthritis), health behaviour factors (no supervised exercise and physical inactivity) and socio-demographics (lower education) were found to predict deterioration of pain (weak evidence). Higher comorbidity count and lower vitality were found to predict deterioration of physical functioning (strong evidence). For several other predictive factors weak evidence was found (e.g. bilateral hip pain, increase in hip pain (change), bilateral knee pain, presence of knee osteoarthritis). CONCLUSION: Because of high heterogeneity across studies and within study populations, no conclusions can be drawn with regard to the course of pain and physical functioning. Several clinical characteristics, health behaviours and psychosocial factors prognosticate deterioration of pain and physical functioning. These findings may guide future research aimed at the identification of subgroups of patients with hip osteoarthritis.
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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 | 0.013 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.033 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".