Measuring the Operative Treatment Effect in End-Stage Ankle Arthritis: Are We Asking the Right Questions? A COFAS Multicenter Study
Bibliographic record
Abstract
BACKGROUND: Foot and ankle surgeons are increasingly relying on patient-reported outcome measures (PROMs) such as the Ankle Osteoarthritis Scale (AOS) to evaluate treatment options. The objectives of this retrospective cohort study were 2-fold: (1) to examine the AOS instrument using psychometric analysis and (2) to revise the questions on the AOS to improve the effect of questions on the score and remove redundancies. METHODS: Pre- and postoperative patient scores were obtained from AOS questionnaires in the COFAS Prospective Ankle Reconstruction Database, a cohort of patients operatively treated for end-stage ankle arthritis. A split-sample approach was used to evaluate the AOS and to propose a revised instrument. RESULTS: A total of 380 patients who had been treated with total ankle replacement or ankle arthrodesis were prospectively followed to the 2-year postoperative time point. Correlation analysis demonstrated that a number of questions on the AOS were highly correlated with other similar questions, frequently incomplete, or showed little variation between respondents. Eight of the original AOS questions were retained in the newly proposed Ankle Arthritis Score (AAS) [3 from the AOS Pain subscale and 5 from the AOS Disability subscale]. Principal components analysis (PCA) showed that these questions equally clustered into 2 domains in AAS: Basic Activity and Advanced Activity. CONCLUSIONS: The AAS is shorter and has improved psychometric properties as compared to the AOS. Further investigation is required to better characterize the clinical utility of this proposed new patient-reported outcome score. LEVEL OF EVIDENCE: Level III, retrospective cohort study.
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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 | 0.020 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".