Prehospital hypotension that persists on arrival at the emergency department is a powerful predictor of mortality following major trauma
Bibliographic record
Abstract
Outcome following major injury is time dependent. Early identification of high-risk patients allows rapid decision-making and correction of life-threatening disorders. Complex scoring systems are of limited value during major trauma resuscitation. Our aim was to evaluate the utility of a single blood pressure during the prehospital phase in combination with the blood pressure on arrival at the emergency department. Data were collected prospectively on 1,111 patients admitted to a Level 1 South African trauma unit over a 1-year period. Patients were subdivided into two groups according to the combination of their prehospital (PH) and emergency department (ED) blood pressure. Hypotension was defined as a systolic blood pressure less than 90 mmHg. Mortality was defined as death within 30 days. The mortality in patients ( n = 1,031) with normal PH and ED blood pressure was 5.4%. The mortality in patients ( n = 80) with PH and ED hypotension was significantly higher at 45% ( P < 0.0001, chi-square test) (Table 1 ). The combination of prehospital and emergency department systolic blood pressure is a simple yet extremely powerful predictor of mortality following major trauma and should be used as a triage tool to rapidly identify the highest risk patients.
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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 | 0.006 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".