Factors Associated With Health-Related Quality of Life in Patients With Open Fractures
Bibliographic record
Abstract
OBJECTIVES: To analyze FLOW data to identify baseline patient, injury, fracture, and treatment factors associated with lower health-related quality of life (HRQoL) at 12-month postfracture. DESIGN: Prognostic study using data from a prospective randomized controlled trial. SETTING: Thirty-one clinical centers in the United States, Canada, Australia, and India. PATIENTS/PARTICIPANTS: One thousand four hundred twenty-seven patients with open fracture from the FLOW trial with complete 12-month Short Form-12 (SF-12) follow-up assessment and no missing data for selected baseline factors. INTERVENTION: Not applicable. MAIN OUTCOME MEASUREMENT: Physical Component Score (PCS) and the Mental Component Score (MCS) of the SF-12 at 12-month postfracture. RESULTS: One thousand four hundred twenty-seven patients were included in the SF-12 PCS and MCS linear regression models. Smoking, lower preinjury SF-12 PCS and MCS, and work-related injuries were significantly associated with lower SF-12 PCS and MCS at 12-month postfracture. A lower extremity fracture and a wound that was not closed at initial irrigation and debridement were significantly associated with lower 12-month SF-12 PCS but not MCS. Only the adjusted mean difference for lower extremity fractures approached the minimally important difference for the SF-12 PCS. CONCLUSIONS: We identified a number of statistically significant baseline factors associated with lower HRQoL; however, only the presence of a lower extremity fracture approached clinical significance. More research is needed to quantify the impact of these factors on patients and to determine whether changes to modifiable factors at baseline will lead to clinically significant improvements in HRQoL after open fractures. LEVEL OF EVIDENCE: Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".