Functional Outcomes Following Displaced Talar Neck Fractures
Bibliographic record
Abstract
OBJECTIVES: To determine the outcome of displaced talar neck fractures at long-term follow-up in terms of functional outcome and secondary reconstructive surgery. DESIGN: Retrospective cohort study. SETTING: Academic level 1 trauma center. PATIENTS: Seventy patients with displaced talar neck fractures. INTERVENTION: All patients were treated with open reduction and screw fixation. MAIN OUTCOME MEASUREMENTS: Functional outcome of patients who did not require secondary surgery was assessed using the Short Musculoskeletal Function Assessment, Ankle Osteoarthritis Scale score, and the American Orthopedic Foot and Ankle Society Ankle-Hindfoot Score. The incidence of secondary reconstructive hindfoot surgery, including arthrodesis or talectomy, was measured using life table analysis. RESULTS: Mean Short Musculoskeletal Function Assessment score was 20 +/- 18 out of 100, with a lower score indicative of better outcome; mean Ankle Osteoarthritis Scale score was 3.8 +/- 2.4 out of 10 (lower score better); and mean Ankle Society Ankle-Hindfoot Score was 71 +/- 19 out of 100 points (higher score better). The incidence of secondary reconstructive surgery increased from 24 +/- 5% at 1 year to 48 +/- 10% at 10 years postinjury. CONCLUSIONS: Functional outcome varied and was most dependent upon the development of complications. The incidence of secondary reconstructive surgery following talar neck fractures increased over time and was most commonly performed to treat subtalar arthritis or misalignment.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".