Prioritization of patients on scheduled waiting lists: validation of a scoring system for hip and knee arthroplasty.
Bibliographic record
Abstract
INTRODUCTION: The hip and knee replacement priority criteria tool (HKPT) is 1 of 5 tools developed by the Western Canada Waiting List Project for setting priorities among patients awaiting elective procedures. We set out to assess the validity of the HKPT priority criteria score (PCS) and map the maximum acceptable waiting times (MAWTs) for patients to levels of urgency. METHODS: Two studies were used to assess convergent and discriminant validity. In study 1, consecutive patients on a waiting list for hip or knee arthroplasty were assessed by orthopedic surgeons from the 4 provinces in Western Canada, using the HKPT and data on patient age, gender, joint site, type of surgery (primary or revision), 2 measures of surgeon-rated patient urgency, and diagnosis. In study 2, 6 patients were videotaped during a consultation interview with the surgeon and were assessed by a group of experts. We measured function with the PCS and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). RESULTS: In study 1, we assessed 394 patients, and in study 2, 19 raters assessed the 6 patients. Correlations between the PCS and other measures of physician-rated urgency were strong, ranging from 0.78 to 0.89. For a subgroup of 60 patients, correlation between the PCS and function as measured with the WOMAC was 0.48, and correlation was greater (0.45-0.56) between items measuring similar constructs (e.g., pain at rest) than those measuring different constructs (0.21-0.40). In study 2, median MAWTs ranged from 4 to 24 weeks for 5 levels of urgency based on PCS percentiles. CONCLUSIONS: Results from this study support the validity of the PCS as a measure of surgeon-rated urgency for hip or knee arthroplasty. Evaluative studies are needed to assess the validity and acceptability of the tools and the establishment of MAWTs in clinical practice.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".