Age, Gender, Work Capability, and Worker's Compensation in Patients With Displaced Intraarticular Calcaneal Fractures
Bibliographic record
Abstract
OBJECTIVES: To determine which demographic variables are linked with outcome in displaced intraarticular calcaneal fractures. The variables studied were age, gender, work capability, Workers' Compensation Board (WCB) support, and injury type. DESIGN: A prospective cohort study with a minimum of two years of follow-up. SETTING: A university-affiliated Level I trauma hospital. PATIENTS: One hundred sixty-nine patients who required treatment for displaced intraarticular calcaneal fractures treated by a single surgeon. To be included in the study, patients had to be aged between fifteen and sixty-five years at the time of the injury, have closed injuries, and have posterior facet displacement greater than two millimeters. INTERVENTION: Patients were treated nonoperatively or operatively, using a lateral approach to the calcaneus. MAIN OUTCOME MEASUREMENTS: Outcome was measured by return of patients to full-time work, change in work capability after treatment, the SF-36 health survey, and visual analog scales. RESULTS: Male gender, medium and heavy labor, presence of WCB support, and presence of bilateral intraarticular fractures all proved to be associated with a poorer prognosis. Female patients did well when treated nonoperatively and operatively, whereas male patients always were less able to return to work at the same level as before the injury. Operatively treated patients returned to work quicker (average, eighty-seven days). CONCLUSIONS: Males, multiply injured patients, and heavy laborers may have better outcomes with operative treatment, whereas females and non-WCB patients may do better with nonoperative treatment.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".