Validation of a prioritization tool for patients on the waiting list for total hip and knee replacements
Bibliographic record
Abstract
RATIONALE AND AIMS: Total hip and knee replacements, usually, have long waiting lists. There are several prioritization tools for these kind of patients. A new tool should undergo a standardized validation process. The aim of the present study was to validate a new prioritization tool for primary hip and knee replacements. METHODS: We carried out a prospective study. Consecutive patients placed on the waiting list were eligible for the study. Patients included were mailed a questionnaire which included, among other questions, the seven items of the priority tool and the Western Ontario and McMasters Universities Arthritis Index (WOMAC) specific questionnaire. The priority tool gives a score from 0 to 100 points, and three categories (urgent, preferent and ordinary). We studied the content and construct validity. We used Student's t-test or one-way analysis of variance. Correlational analysis was used to evaluate convergent and discriminate validity. RESULTS: The sample consisted of 838 patients (62.3% were female), with mean age of 70.2 years (SD 8.4). A total of 55.5% patients underwent knee replacement. Given that the tool was elaborated by patients and orthopaedic surgeons, it shows a good content validity. The priority score was statistically different (P < 0.001) among the three urgency categories created. The scores of the three WOMAC dimensions showed differences (P < 0.001) by the three urgency categories created. The correlations between the priority score and WOMAC dimensions were 0.79 (function), 0.69 (pain) and 0.51 (stiffness). The correlations between WOMAC items and items from priority tool were greater (0.47-0.69) between items measuring similar constructs than those measuring different constructs (0.27-0.49). These data are similar in both joints. CONCLUSIONS: Results support the validity of the prioritization tool to be used with patients waiting for hip or knee replacement.
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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 | 0.010 | 0.136 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".