Predictors of outcomes of recovery following total hip replacement surgery
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: To investigate psychosocial and biomedical outcomes following total hip replacement (THR) and to identify predictors of recovery from THR. METHODS: Patients with osteoarthritis (OA) on the waiting list for primary THR in North West England were assessed pre-operatively and at six and 12 months post-operatively to investigate psychosocial and biomedical outcomes. Psychosocial outcomes were anxiety and depression, social support and health-related quality of life (HRQoL). Biomedical outcomes were pain, physical function and stiffness. The primary outcome was the Short-Form 36 (SF-36) Health Survey Total Physical Function. Potential predictors of outcome were age, sex, body mass index, previous joint replacement, involvement in the decision for THR, any comorbidities, any complications, type of medication, and pre-operative ENRICHD Social Support Instrument score, Hospital Anxiety and Depression scores and Western Ontario and McMaster Universities osteoarthritis index score. RESULTS: The study included 206 patients undergoing THR. There were 88 men and 118 women with a mean age of 66.3 years (sd 10.4;36 to 89). Pain, stiffness and physical function, severity of OA, HRQoL, anxiety and depression all improved significantly from pre-operative to 12-month assessment (all p < 0.001), with the greatest improvement occurring in the first six months (all p < 0.001). The predictors that were found to influence recovery six months after THR were: pain (p < 0.001), anxiety (p = 0.034), depression (p = 0.001), previous joint replacement (p = 0.006) and anti-inflammatory drugs (p = 0.012). CONCLUSIONS: The study identified the key psychosocial and biomedical predictors of recovery following THR. By identifying these predictors, we are able to identify and provide more support for patients at risk of poor recovery following THR. Cite this article: Bone Joint Res 2013;2:248-54.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it