1-year trajectories of patients undergoing primary total hip arthroplasty: Patient reported outcomes and resource needs according to education level
Bibliographic record
Abstract
BACKGROUND: Objectives were first to evaluate by education level one-year trajectories of pain, function and general health, as well as hospital resource and medication needs in patients undergoing primary total hip arthroplasty (THA); and second, to evaluate whether outcome differences are related to existing baseline differences in health and disease severity. METHODS: We included all primary THAs from a public hospital-based prospective arthroplasty registry, performed in a high-income country 2010 to 2017. Education was classified in three levels: ≤8years of schooling (low), 9-12years (medium), and ≥13years (high). Pain and function prior to and one-year after surgery were assessed with the Western Ontario McMaster Universities score (WOMAC) and general health with the 12-item short-form health survey (SF-12). RESULTS: Overall 963 patients were included, 340 (35.3%) with low, 306 (31.8%) with medium, and 317 (32.9%) with high education. With increasing educational level preoperative scores for pain, function and SF-12 mental health component increased. One year after surgery improvement was observed in all education categories for WOMAC pain and function, SF-12 mental and physical component. However, absolute postoperative scores remained lower in all four domains for the low education group. After adjustment for baseline characteristics differences were much attenuated and no longer significant. There was also greater resource need in low educated patients. CONCLUSIONS: The inferior absolute results one year after surgery in less educated patients were largely due to older age, worse preoperative health and greater symptom severity calling for greater attention to timely and equal management, for more targeted perioperative care and increased support for the lower education group.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".