Prehospital Fibrinogen Levels in Major Trauma Patients Transported by Helicopter Emergency Medical Service: Determining Who Might Benefit
Bibliographic record
Abstract
OBJECTIVES: Low fibrinogen contributes to poor outcomes in patients with traumatic coagulopathy. Empiric fibrinogen replacement is not supported. Early identification of patients at high risk of hypofibrinogenemia may enable targeted support. We sought to identify prehospital variables associated with hypofibrinogenemia at emergency department (ED) arrival. METHODS: We retrospectively reviewed health records (January 2015 to August 2019) of consecutive patients transported by helicopter EMS to two trauma centers who received one or more units of packed red blood cells (pRBCs) during transport. The primary outcome was first ED fibrinogen level transformed into a binomial variable (<1.6g/L or ≥1.6g/L) for the 65 patients analyzed. Direct multivariable logistic regression examined the independent variables (hypotension, shock index (SI), and systolic blood pressure). Odds ratios and 95% CIs were reported. RESULTS: Hypotension after first pRBC transfusion was significantly associated with low ED first fibrinogen level, P=.03, with 6.6 (1.1-40.15) times greater odds of fibrinogen <1.6g/L. Hypotension post-transfusion was also associated with ED first international normalized ratio (INR) >1.5, P=.013, with those cases having 17.5 (1.8-169.2) greater odds of INR >1.5. Additionally, an EDSI ≥1.5 had 8.9 (1.9-42.6) times greater odds of fibrinogen <1.6g/L than those with an EDSI <1, P=.006. Compared with the EDSI 1-1.49 group, those with an EDSI ≥1.5 had 6.9 times greater odds of having fibrinogen <1.6g/L, P=.02, OR=6.9 (1.3-36.1). CONCLUSION: In major trauma patients transported by helicopter EMS, persistent hypotension after the first blood transfusion and an initial EDSI ≥1.5 were both associated with low fibrinogen levels.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".