Prehospital traumatic cardiac arrest
Bibliographic record
Abstract
BACKGROUND: Traumatic arrests have historically had poor survival rates. Identifying salvageable patients and ideal management is challenging. We aimed to (1) describe the management and outcomes of prehospital traumatic arrests; (2) determine regional variation in survival; and (3) identify Advanced Life Support (ALS) procedures associated with survival. METHODS: This was a secondary analysis of cases from the Resuscitation Outcomes Consortium Epistry-Trauma and Prospective Observational Prehospital and Hospital Registry for Trauma (PROPHET) registries. Patients were included if they had a blunt or penetrating injury and received cardiopulmonary resuscitation. Logistic regression analyses were used to determine the association between ALS procedures and survival. RESULTS: We included 2,300 patients who were predominately young (Epistry mean [SD], 39 [20] years; PROPHET mean [SD], 40 [19] years), males (79%), injured by blunt trauma (Epistry, 68%; PROPHET, 67%), and treated by ALS paramedics (Epistry, 93%; PROPHET, 98%). A total of 145 patients (6.3%) survived to hospital discharge. More patients with blunt (Epistry, 8.3%; PROPHET, 6.5%) vs. penetrating injuries (Epistry, 4.6%; PROPHET, 2.7%) survived. Most survivors (81%) had vitals on emergency medical services arrival. Rates of survival varied significantly between the 12 study sites (p = 0.048) in the Epistry but not PROPHET (p = 0.14) registries.Patients in the PROPHET registry who received a supraglottic airway insertion or intubation experienced decreased odds of survival (adjusted OR, 0.27; 95% confidence interval, 0.08-0.93; and 0.37; 95% confidence interval, 0.17-0.78, respectively) compared to those receiving bag-mask ventilation. No other procedures were associated with survival. CONCLUSIONS: Survival from traumatic arrest may be higher than expected, particularly in blunt trauma and patients with vitals on emergency medical services arrival. Although limited by confounding and statistical power, no ALS procedures were associated with increased odds of survival. LEVEL OF EVIDENCE: Prognostic study, level IV.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".