Catecholamines as outcome markers in isolated traumatic brain injury: the COMA-TBI study
Bibliographic record
Abstract
BACKGROUND: Elevated catecholamine levels might be associated with unfavorable outcome after traumatic brain injury (TBI). We investigated the association between catecholamine levels in the first 24 h post-trauma and functional outcome in patients with isolated moderate-to-severe TBI. METHODS: A cohort of 174 patients who sustained isolated blunt TBI was prospectively enrolled from three Level-1 Trauma Centers. Epinephrine (Epi) and norepinephrine (NE) concentrations were measured at admission (baseline), 6, 12 and 24 h post-injury. Outcome was assessed at 6 months by the extended Glasgow Outcome Scale (GOSE) score. Fractional polynomial plots and logistic regression models (fixed and random effects) were used to study the association between catecholamine levels and outcome. Effect size was reported as the odds ratio (OR) associated with one logarithmic change in catecholamine level. RESULTS: At 6 months, 109 patients (62.6%) had an unfavorable outcome (GOSE 5-8 vs. 1-4), including 51 deaths (29.3%). Higher admission levels of Epi were associated with a higher risk of unfavorable outcome (OR, 2.04, 95% CI: 1.31-3.18, p = 0.002) and mortality (OR, 2.86, 95% CI: 1.62-5.01, p = 0.001). Higher admission levels of NE were associated with higher risk of unfavorable outcome (OR, 1.59, 95% CI: 1.07-2.35, p = 0.022) but not mortality (OR, 1.45, 95% CI: 0.98-2.17, p = 0.07). There was no relationship between the changes in Epi levels over time and mortality or unfavorable outcome. Changes in NE levels with time were statistically associated with a higher risk of mortality, but the changes had no relation to unfavorable outcome. CONCLUSIONS: Elevated circulating catecholamines, especially Epi levels on hospital admission, are independently associated with functional outcome and mortality after isolated moderate-to-severe TBI.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".