Variability of indication criteria in knee and hip replacement: an observational study
Bibliographic record
Abstract
BACKGROUND: Total knee (TKR) and hip (THR) replacement (arthroplasty) are effective surgical procedures that relieve pain, improve patients' quality of life and increase functional capacity. Studies on variations in medical practice usually place the indications for performing these procedures to be highly variable, because surgeons appear to follow different criteria when recommending surgery in patients with different severity levels. We therefore proposed a study to evaluate inter-hospital variability in arthroplasty indication. METHODS: The pre-surgical condition of 1603 patients included was compared by their personal characteristics, clinical situation and self-perceived health status. Patients were asked to complete two health-related quality of life questionnaires: the generic SF-12 (Short Form) and the specific WOMAC (Western Ontario and Mcmaster Universities) scale. The type of patient undergoing primary arthroplasty was similar in the 15 different hospitals evaluated.The variability in baseline WOMAC score between hospitals in THR and TKR indication was described by range, mean and standard deviation (SD), mean and standard deviation weighted by the number of procedures at each hospital, high/low ratio or extremal quotient (EQ5-95), variation coefficient (CV5-95) and weighted variation coefficient (WCV5-95) for 5-95 percentile range. The variability in subjective and objective signs was evaluated using median, range and WCV5-95. The appropriateness of the procedures performed was calculated using a specific threshold proposed by Quintana et al for assessing pain and functional capacity. RESULTS: The variability expressed as WCV5-95 was very low, between 0.05 and 0.11 for all three dimensions on WOMAC scale for both types of procedure in all participating hospitals. The variability in the physical and mental SF-12 components was very low for both types of procedure (0.08 and 0.07 for hip and 0.03 and 0.07 for knee surgery patients). However, a moderate-high variability was detected in subjective-objective signs. Among all the surgeries performed, approximately a quarter of them could be considered to be inappropriate. CONCLUSIONS: A greater inter-hospital variability was observed for objective than for subjective signs for both procedures, suggesting that the differences in clinical criteria followed by surgeons when indicating arthroplasty are the main responsible factors for the variation in surgery rates.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".