Prediction of Pulmonary Morbidity and Mortality in Patients With Femur Fracture
Bibliographic record
Abstract
BACKGROUND: We aimed to determine the effect of femur fractures on mortality, pulmonary complications, and adult respiratory distress syndrome (ARDS). In addition, we aimed to compare the effect of femur fractures with other major musculoskeletal injuries and to determine the effect of timing to surgery on these complications. METHODS: All patients were identified from the trauma registries of two Level I trauma centers. Outcomes were defined at mortality in hospital, pulmonary complications, and ARDS in hospital. Regression analysis was used to determine the effect of femur fractures, while controlling for age, Abbreviated Injury Scales, Glasgow Coma Scale, and systolic blood pressure at presentation. We compared femur fractures with other major musculoskeletal injuries in similar models. Within the patients with femur fracture, time to surgery (< 8 hours, 8 hours to 24 hours, and > 24 hours) was evaluated using similar regression analysis. RESULTS: Of the total 90,510 patients, 3,938 (4.35%) died in the hospital, 2,055 (2.27%) had a pulmonary complication, and 285 (0.31%) developed ARDS. Femur fracture is statistically predictive of mortality (odds ratio [OR], 1.606; 95% confidence interval [CI], 1.288-2.002) and pulmonary complications (OR, 1.659; 95% CI, 1.329-2.070), when controlling for other injury factors. This was comparable with the effect of pelvic fracture and other major musculoskeletal injuries. Femur fracture had a strong relationship with ARDS (OR, 2.129; 95% CI, 1.382-3.278). Patients treated in the 8 hours to 24 hours window had the lowest mortality risk (OR, 0.140; 95% CI, 0.052-0.375), and there was a trend to increased risk of ARDS in a delay to surgery of > 24 hours. CONCLUSIONS: Femur fractures are a major musculoskeletal injury and increase the risk of mortality and pulmonary complications as much as any other musculoskeletal injuries. There is a unique relationship between ARDS and femur fractures, and this must be considered carefully in treatment planning for these patients.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".