Relationship of Preoperative Patient-Reported Outcome Measures (PROMs) to Postoperative Success in End-Stage Ankle Arthritis
Bibliographic record
Abstract
BACKGROUND: Ankle osteoarthritis is a significant cause of pain and disability. Despite the effectiveness of treatments, a subset of patients remains with persistent pain and functional limitations. The purpose of this study was to use preoperative patient-reported outcome measures to predict which ankle osteoarthritis patients would be most likely to experience postoperative improvements in functional outcomes. METHODS: A retrospective analysis of prospectively collected data was used to evaluate 427 patients with end-stage ankle arthritis with 5-year follow-up. Demographics, comorbidities, Ankle Osteoarthritis Scale (AOS), Ankle Arthritis Score (AAS), and the physical and mental component scores of the Short Form-36 (SF-36 Physical Components Score [PCS] and Mental Components Score [MCS]) were collected. The minimal clinically important difference (MCID) was then calculated. Receiver operating characteristic (ROC) analysis was used to choose the optimal threshold values of preoperative patient-reported outcome measure and assess the prediction performance. RESULTS: Patients who scored worst at preoperative baseline made the greatest gains in function and pain relief, and they had a high chance of achieving MCID following surgical treatment. ROC curves demonstrated that preoperative AOS, AAS, and SF-36 PCS and MCS scores were predictive of postoperative improvements in physical and mental function. Patients with preoperative AOS score above 45.7 had an 83% probability of achieving an MCID (AUC = 0.67). Similarly, patients with a preoperative AAS score above 25.7 had a 78% probability of achieving an MCID (AUC = 0.63). Patients with a preoperative SF-36 PCS score below 31 had a 62% probability of achieving an MCID (AUC = 0.64). Patients with a preoperative SF-36 MCS below 52.7 had a 47% probability of achieving an MCID (AUC = 0.89). MCIDs for AOS, AAS, SF3-36 PCS, and SF-36 MCS score changes were 12.4, 10.0, 6.43, and 8.1, respectively. CONCLUSION: Preoperative patient-reported outcomes measures could predict postoperative improvement in ankle arthritis patients. The results of this study may be used to facilitate discussion between physicians and patients regarding the expected benefit of surgery. LEVEL OF EVIDENCE: Level III, prognostic comparative 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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".