Predicting Outcomes after Hip Fracture Repair
Bibliographic record
Abstract
OBJECTIVE: To compare the activities of daily living before and after hip fracture and construct a statistical model for discharge destination and independent walking. The classification accuracy of the model was determined from an independent sample. DESIGN: Prospective study: FIM prefracture, at discharge, and at 6-mo follow-up were obtained from 63 patients who underwent operations for acute hip fractures. A statistical model for discharge destination and independent walking was made and classification accuracy was checked using 78 independent samples. RESULTS: The motor FIM scores at prefracture decreased significantly at discharge (P < 0.0001) and at 6-mo follow-up (P < 0.0001), but at 6-mo follow-up, they had increased significantly compared with those at discharge (P = 0.0103). A mobility subscale was used to predict discharge destination, and mobility and social cognition subscales were related to independent walking. The predictive accuracy was 87%. CONCLUSIONS: Motor FIM scores increase for at least 6 mos after hip fracture, and discharge destination and independent walking were highly predictable from FIM mobility and social cognition subscales.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".