Inhalation Injury Does Not Influence the Amount of Blood Transfused to Major Burn Patients: A Secondary Analysis from the Transfusion Requirement in Burn Care Evaluation Study
Bibliographic record
Abstract
Patients with major burn injuries typically require numerous blood transfusions. It is not known if an inhalation injury (INHI) directly influences the need for blood transfusion. The purpose of this study was to determine whether INHI increases the amount of blood transfused to major burn patients. A secondary analysis from the Transfusion Requirement in Burn Care Evaluation (TRIBE) study was conducted. Patients with INHI were compared with patients without INHI. The number of red blood cell (RBC) transfusions per day (RBC per day) between INHI and No INHI was analyzed with a multivariable regression. Patients with INHI (n = 78) had significantly larger burns (P = .0004), larger full-thickness burns (P = .0007), greater admission APACHE score (P < .0001), higher admission multiple organ dysfunction scores (P < .0001), and were transfused more RBC per day (P = .009) than No INHI patients (n = 267). In the multivariable regression analysis, RBC per day was significantly associated with the %TBSA burn (P < .0001), age of the patient (P = .004), the need for more than 1 day of mechanical ventilation (P < .0001), the occurrence of at least one blood stream infection (BSI; P = .044), and being assigned to the liberal transfusion arm of TRIBE (P < .001) but not the presence of INHI (P = .056). The null hypothesis that INHI exerts no influence on the amount of blood transfused could not be rejected. Larger burn size, advanced patient age, mechanical ventilation, and BSIs are important determinants of the blood transfusion rate in major 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".