Abstract 14938: Association Between Survival and Increases in Prehospital Systolic Blood Pressure After Its Nadir in Major Traumatic Brain Injury
Bibliographic record
Abstract
Introduction: Little is known about prehospital EMS blood pressure patterns in TBI and the effect of serial trends in BP during EMS care remains entirely unclear. Using the comprehensive, linked EMS data in the Excellence in Prehospital Injury Care (EPIC) TBI Study (NIH 1R01NS071049; ClinicalTrials.gov NCT01339702), we evaluated the association between mortality and increases in EMS systolic BP (SBP) after the lowest recorded SBP in major TBI cases. Methods: We used the entire EPIC pre-implementation cohort (before TBI guideline implementation; 1/07-3/14) to assess, in detail, a previous preliminary evaluation. All moderate/severe TBI cases (CDC Barell Matrix Type 1) were evaluated [exclusions: age <10, died before ED arrival, SBP <40 or >300, missing SBP (4%)]. Logistic regression was used to determine associations between increases in EMS SBP after the lowest SBP and the probability of death, adjusted for important confounders. Results: Among 14,567 included cases, 7696 (68% male, median age 45) were in the cohort of interest (had an equal or higher SBP recorded subsequent to the lowest). Figures show the probability of death vs the increase after the nadir (and 95% CIs) in 4 cohorts of lowest SBP (40-89; 90-139; 140-159; 160-300). Conclusion: Increases in EMS SBP after the nadir revealed distinct patterns: Hypotension-Mortality drops significantly if SBP increases after the nadir (dramatic improvement with large increases). Normotension-Mortality is slightly reduced with SBP increases and even large increases were not detrimental. Mild HTN-Mortality decreases with modest SBP increases but large increases (>40mmHg) are associated with higher mortality. Severe HTN-Higher mortality with any subsequent increase. The findings in the hypotensive & normotensive cohorts support the concept of restoring/optimizing cerebral perfusion in TBI. This is further supported by the fact that, even with mild HTN, moderate SBP increases do not appear to be detrimental.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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".