Comparison of Generic, Musculoskeletal-Specific, and Foot and Ankle–Specific Outcome Measures Over Time in Tibial Plafond Fractures
Bibliographic record
Abstract
Background: This study performed a psychometric analysis assessing and comparing the responsiveness of the relevant components of a generic (Short Form–36 [SF36]), a musculoskeletal-specific (Short Musculoskeletal Functional Assessment [SMFA]), and a foot and ankle–specific (Foot and Ankle Outcome Score [FAOS]) outcome score when evaluating surgically treated tibial plafond fractures over time. Methods: Fifty-one patients were followed for 12 months after their tibial plafond fracture. Responsiveness, or the ability to detect clinical change in a disease, was evaluated through the standardized response mean (SRM), the proportion meeting a minimal clinically important difference (MCID), and floor and ceiling effects. Results: The SRM of the SF36–Physical Component Summary (PCS) was significantly greater than the SMFA–dysfunction index (DI) ( P < .01) and FAOS–Activities of Daily Living (ADL) ( P = .01) between baseline and 6 months, whereas the SRMs of only SF36-PCS and FAOS-ADL differed ( P = .01) between 6 and 12 months. The proportion of patients achieving an MCID for SF36-PCS was higher than FAOS-ADL ( P = .03) between baseline and 6 months and higher than SMFA-DI ( P = .04) between 6 and 12 months. The FAOS-ADL showed substantial ceiling effects at baseline (88.2%) but much less at 6 months (5.9%) and 12 months (9.8%). Smaller ceiling effects were observed for the SMFA-DI (11.8%) at baseline, whereas none were observed for the SF36-PCS. Conclusions: This study found that the SF36-PCS had greater responsiveness in assessing tibial plafond fractures compared to the SMFA-DI and FAOS-ADL, particularly in the first 6 months after surgery. In addition, limitations were revealed in the SMFA-DI and FAOS-ADL. This study illustrates the necessary diligence required for selection of outcome measures, as musculoskeletal and anatomy specific scores are not necessarily superior. Level of Evidence: Level II, prospective 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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".