Relationship between total hip replacement appropriateness and surgical priority instruments
Bibliographic record
Abstract
RATIONALE: Variability in indications for total hip replacement (THR) and unequal waiting times may limit health care access. OBJECTIVE: To analyse the relationship between appropriateness and previously developed surgical priority instruments. METHOD: Multicentre cross-validation study of patients placed on the waiting list for THR. Information on surgical priority, surgeons' evaluation of priority through a visual analogue scale (VAS) and health-related quality of life (HRQOL) (Health Utilities Index mark 3, EQ-5D, Western Ontario McMaster Osteoarthritic Index) was collected. THR indications were considered appropriate, uncertain or inappropriate according to appropriateness criteria. Statistical differences and clinically important differences in surgical priority, VAS and HRQOL between appropriateness categories were analysed with the Mann-Whitney U-test and effect size (ES), respectively. Surgical priority score's ability to discriminate appropriate and inappropriate indications was evaluated through the area under the receiver-operating characteristic curve (AUC) and its 95% confidence interval (95% CI). RESULTS: 49.4% (87) of the THR indications were deemed appropriate, 39.8% (70) uncertain and 10.8% (19) inappropriate. Differences in surgical priority score, VAS and HRQOL between appropriateness categories were statistically significant. Clinically important differences were generally small (ES, 0.2-0.5) between inappropriate and uncertain, moderate (ES, 0.5-0.8) between uncertain and appropriate, and large (ES > 0.8) between inappropriate and appropriate categories. The AUC to discriminate appropriate and inappropriate indications was 0.97 (95% CI: 0.96-0.99) and 0.90 (95% CI: 0.83-0.97), respectively. CONCLUSIONS: The relationship between the surgical priority and appropriateness instruments reinforces their validity and could improve waiting list management by establishing maximum waiting periods based on patients' characteristics.
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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 | 0.008 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".