Interhospital Variation in Operative Intervention for Firearm-Related Penetrating Traumatic Brain Injury and Associations With Inpatient Mortality
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Firearm-related penetrating traumatic brain injury (pTBI) carries a high mortality risk and grim prognosis. This study aimed to quantify interhospital variation in operative intervention for this patient population and assess whether cranial surgery tendency is associated with inpatient mortality. METHODS: We conducted a retrospective cohort study using the American College of Surgeons Trauma Quality Improvement Program (TQIP) data set to identify adult patients presenting with firearm-related pTBI. Risk-adjusted hierarchical regression evaluated associations with cranial surgery. Hospitals were stratified into quartiles based on surgical tendency (lowest, quartile 1; highest, quartile 4 [Q4]). Propensity score matching was performed across quartiles, and a multivariable regression model was constructed to investigate associations between hospital quartile and inpatient mortality. Effect modification by pupillary reactivity was tested. RESULTS: Cranial surgery rates for 4895 patients (median age, 31 years) varied widely across 309 hospitals (0%-71%; median, 21%; median odds ratio, 1.33). After matching, treatment at Q4 hospitals was associated with significantly reduced odds of mortality compared with treatment at quartile 1 hospitals (odds ratio, 0.61; 95% CI, 0.47-0.78). Patients presenting with one (interaction P = .03) or both (interaction P = .03) unreactive pupils experienced amplified survival benefits from treatment at Q4 hospitals. CONCLUSION: Substantial interhospital variation exists in operative intervention for firearm-related pTBI. Hospitals with higher surgical tendency were associated with improved survival, and this effect was amplified for patients presenting with unreactive pupils. These findings suggest a need to standardize operative decision-making for patients with firearm-related pTBI, aligning with ongoing efforts by organizations such as the Brain Trauma Foundation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".