Pelvic Ring Injury Mortality: Are We Getting Better?
Bibliographic record
Abstract
OBJECTIVES: To determine if changes in pelvic trauma care and treatment protocols have affected overall mortality rates after pelvic ring injury. DESIGN: Retrospective cohort study. SETTING: Level I trauma center. PATIENTS/PARTICIPANTS: A total of 3314 patients with pelvic ring injuries who presented to a single referral center from 1999 to 2018 were included in the study. INTERVENTION: Pelvic ring management, years 1999-2006 versus years 2007-2018. MAIN OUTCOME MEASUREMENTS: In hospital mortality. Other examined variables included change in patient demographics, fracture characteristics, date of injury, associated injuries, length of hospital stay, Abbreviated Injury Severity Score. RESULTS: The composite mortality rate was 6.5% (214/3314). The earliest cohort presented a mortality rate of 9.1% [111/1224; 95% confidence interval (CI), 7.6%-10.8%] compared with the more recent cohort mortality rate of 4.9% (103/2090; 95% CI, 4.1%-5.9%). Overall mortality was significantly lower in the more recent period, a risk difference of 4.1% (95% CI, 2.3%-6.1%; P < 0.01). After adjusting for age and Abbreviated Injury Severity Score of the brain, chest, and abdomen, the mortality reduction was more pronounced with an adjusted risk difference of 6.4% (95% CI, 4.7%-8.1%; P < 0.01). CONCLUSION: Significant improvement in the mortality rate of pelvic ring injuries has been demonstrated in recent years (4.9% vs. 9.1%) and the difference is even large when accounting for known confounders. Improvement appears to coincide chronologically with changes in trauma resuscitation and implementation of adjuvant treatments for managing patients with severe hemorrhagic shock. Although the exact benefit of each treatment awaits further research, these data might indicate improved care over time for these difficult patients. LEVEL OF EVIDENCE: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.
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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 | 0.011 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".