Five percent albumin for adult burn shock resuscitation: lack of effect on daily multiple organ dysfunction score
Bibliographic record
Abstract
BACKGROUND: The effect of 5 percent human albumin on multiple organ dysfunction was investigated during the first 14 days of treatment to determine whether albumin resuscitation might benefit adult burn patients. STUDY DESIGN AND METHODS: Multicenter unblinded controlled trial with stratified block (two patients per block) randomization by center and mortality prediction at enrollment (high-risk stratum [predicted mortality, 50%-90%] and low-risk stratum [predicted mortality, <50%]). The primary outcome was the worst multiple organ dysfunction score (MODS), excluding the cardiovascular component, to Day 14. Eligible adults (>15 years) suffering from thermal injury not more than 12 hours before enrollment received fluid resuscitation with Ringer's lactate (n=23) or 5 percent human albumin plus Ringer's lactate (n=19) by protocol to achieve recommended (American Burn Association) resuscitation endpoints. RESULTS: Forty-two patients were randomly assigned. There were no significant differences (median [95% confidence intervals]) in age (36 [24-45] vs. 31 [25-39] years), burn size (39 [32-53] vs. 32 [26-34] total body surface area percentage), inhalation injury (n=12/19 vs. n=11/23), or baseline MODS (3 [1-5] vs. 1.5 [0-2]) between the treatment and control groups. In an intention-to-treat analysis, there was no significant difference between the treatment and control group in the lowest MODS from Day 0 to Day 14 (analysis of covariance, p=0.73). CONCLUSION: Treatment with 5 percent albumin from Day 0 to Day 14 does not decrease the burden of MODS in adult burn 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".