Symptom and Disability Measurement by Common Foot and Ankle–Specific Outcome Rating Scales
Bibliographic record
Abstract
BACKGROUND: Well-designed foot and ankle clinical outcomes research requires region-specific subjective outcome measures. Many foot and ankle-specific instruments are now available. Determining which instruments to choose is daunting. We present a patient survey to determine the most relevant questions pertaining to them. METHODS: Sixteen foot and ankle-specific outcome instruments were chosen based on popularity, emphasizing valid, reliable, responsive scores. Subjective portions were consolidated and given to 109 patients with osteochondral lesion of the talus (OLT) (39), ankle instability (35), and ankle arthritis (35). Outcome instruments were measured according to 4 criteria: number of questions endorsed by 51%, number with high mean importance, number with low mean importance, and number with the highest-ranking frequency importance product. Instruments were then ranked based on relative score, with the highest scores indicating the instrument was the most useful for that sample. RESULTS: The Foot and Ankle Outcome Score (FAOS) achieved the highest score in all 4 categories for OLT, followed by Foot and Ankle Ability Measure (FAAM) and American Academy of Orthopaedic Surgeons (AAOS) Foot and Ankle Score. The FAOS achieved the highest score in all 4 categories for ankle instability, followed by FAAM and AAOS. For osteoarthritis, the FAOS achieved the highest relative score followed by FAAM and AAOS. The AOF, Ankle Osteoarthritis Score, and AAS are instruments commonly used that had lower relative scores. CONCLUSION: The FAOS, FAAM, and AAOS Foot and Ankle Score contain several items important to patients with osteochondral lesions of the talus, ankle instability, and ankle osteoarthritis. LEVEL OF EVIDENCE: Level II, prospective 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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".