Endotoxemia Following Multiple Trauma
Bibliographic record
Abstract
OBJECTIVE: To evaluate the prevalence and time course of systemic endotoxemia following severe multiple trauma, to define its risk factors, and to explore the correlation between post-trauma endotoxemia and organ dysfunction. DESIGN: Prospective single-center cohort study. SETTING: Emergency department and ICU of adult tertiary care level I trauma center. PATIENTS: Forty-eight severely injured (Injury Severity Score ≥ 16) patients, admitted to ICU within 24 hours of injury. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Endotoxemia was not evident on initial presentation, but developed subsequently in 75% of patients, even in the absence of Gram-negative infection. Nonsurviving patients had higher endotoxin levels than survivors on day 1 (endotoxemia, 0.48 vs 0.28; p = 0.048). Shock at admission, or surgery within the first 48 hours after trauma, was associated with higher endotoxin levels and predicted subsequent maximal endotoxemia, after adjusting for other significant covariates. Maximal endotoxemia levels were higher in patients who developed organ dysfunction, reflected in a cumulative Multiple Organ Dysfunction Score greater than 25, and patients with an intermediate endotoxemia level (≥ 0.4) had more cardiovascular dysfunction. CONCLUSIONS: It is the first study to detect increasing levels of endotoxemia following multiple trauma. Shock and early surgery predict the development of endotoxemia; endotoxemia is particularly associated with cardiovascular dysfunction. However, Gram-negative infections are uncommon in these patients, suggesting that the gastrointestinal tract is the dominant reservoir of endotoxin. Endotoxin may be an appropriate therapeutic target in patients who have sustained severe multiple trauma.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".