Understanding Hospital Volume–Outcome Relationship in Severe Traumatic Brain Injury
Bibliographic record
Abstract
BACKGROUND: The hospital volume-outcome relationship in severe traumatic brain injury (TBI) population remains unclear. OBJECTIVE: To examine the relationship between volume of patients with severe TBI per hospital and in-hospital mortality, major complications, and mortality following a major complication (ie, failure to rescue). METHODS: In a multicenter cohort study, data on 9255 adults with severe TBI were derived from 111 hospitals participating in the American College of Surgeons Trauma Quality Improvement Program over 2009-2011. Hospitals were ranked into quartiles based on their volume of severe TBI during the study period. Random-intercept multilevel models were used to examine the association between hospital quartile of severe TBI volume and in-hospital mortality, major complications, and mortality following a major complication after adjusting for patient and hospital characteristics. In sensitivity analyses, we examined these associations after excluding transferred cases. RESULTS: Overall mortality was 37.2% (n = 3447). Two thousand ninety-eight patients (22.7%) suffered from 1 or more major complication. Among patients with major complications, 27.8% (n = 583) died. Higher-volume hospitals were associated with lower mortality; the adjusted odds ratio of death was 0.50 (95% confidence interval: 0.29-0.85) in the highest volume quartile compared to the lowest. There was no significant association between hospital-volume quartile and the odds of a major complication or the odds of death following a major complication. After excluding transferred cases, similar results were found. CONCLUSION: High-volume hospitals might be associated with lower in-hospital mortality following severe TBI. However, this mortality reduction was not associated with lower risk of major complications or death following a major complication.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".