Validation of a second-generation appropriateness classification system for total knee arthroplasty: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: To test the validity of a second-generation appropriateness system in a cohort of patients undergoing total knee arthroplasty (TKA). METHODS: We applied the RAND/UCLA Appropriateness Method to derive our second-generation system and conducted a prospective study of patients diagnosed with knee osteoarthritis in eight public hospitals in Spain. Main outcome questionnaires were the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Short-Form-12 (SF-12), and the Knee Society Score satisfaction scale (KSS), completed before and 6 months after TKA. Baseline, changes from baseline to 6 months (journey outcome), and 6-month scores (destination outcome) were compared according to appropriateness category. Percentage of patients attaining the minimal clinically important difference (MCID) and responders according to Outcome Measures in Rheumatology-Osteoarthritis Research Society (OMERACT-OARSI) criteria were also reported. RESULTS: A total of 282 patients completed baseline and 6-month questionnaires. Of these, 142 (50.4%) were classified as Appropriate, 90 (31.9%) as Uncertain, and 50 (17.7%) as Inappropriate. Patients classified as Appropriate had worse preoperative pain, function, and satisfaction (p < 0.001) and had greater improvements (i.e., journey scores) than those classified as Inappropriate (p < 0.001). At 6 months, destination scores for pain, function, or satisfaction were not significantly different across appropriateness categories. The percentage of patients meeting responder criteria (p < 0.001) and attaining MCID was statistically higher in Appropriate versus Inappropriate groups in pain (p = 0.04) and function (p = 0.004). CONCLUSIONS: The validity of our second-generation appropriateness system was generally supported. The findings highlight a critical issue in TKA healthcare: whether TKA appropriateness should be driven by the extent of improvement, by patient final state, or by both.
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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 | 0.006 | 0.002 |
| 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".