Determinants of red blood cell transfusion in pediatric trauma patients admitted to the intensive care unit
Bibliographic record
Abstract
BACKGROUND: There are no well-designed prospective studies evaluating transfusion practices in pediatric trauma. We sought to describe red blood cell (RBC) transfusion practices in trauma patients who were admitted to a pediatric intensive care unit (PICU). STUDY DESIGN AND METHODS: This study is a post-hoc analysis of a prospective, 6-month observational study in 30 PICUs. We studied a total of 580 patients aged less than 18 years who had been admitted to a PICU for more than 48 hours, including 95 who were trauma patients. RESULTS: Trauma patients more frequently received transfusion before PICU admission (p < 0.001), were older (p < 0.0001), and more frequently were mechanically ventilated (p = 0.05). In the PICU, trauma patients received more transfusions (55% vs. 37%; p < 0.001), although admission hemoglobin levels were similar in both groups (p = 0.86). The mean (± standard deviation) pretransfusion hemoglobin level in the PICU was 9.0 ± 2.4 g/dL for trauma patients compared with 8.3 ± 2.4 g/dL for nontrauma patients (p = 0.09). Among the trauma patients, transfusion was associated with younger age, higher Pediatric Logistic Organ Regression scores, mechanical ventilation, bleeding, and transfusion before PICU admission. Multivariate regression demonstrated that receiving an RBC transfusion before admission was strongly associated with receiving a blood transfusion in the PICU (p = 0.008). CONCLUSION: Trauma patients are at high risk for receiving an RBC transfusion both before and during their PICU stay, despite a similar transfusion threshold compared with nontrauma patients. Transfusion before PICU admission is a strong determinant, suggesting ongoing bleeding that will require re-transfusion. Further studies are needed to evaluate whether a restrictive transfusion strategy can safely be considered in these 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".