Blood component ratios in children with non‐traumatic life‐threatening bleeding
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: In paediatric trauma patients, there are limited prospective data regarding blood components and mortality, with some literature suggesting decreased mortality with high ratios of plasma and platelets to red blood cells (RBCs) in massive transfusions; however, most paediatric massive transfusions occur for non-traumatic aetiologies and few studies assess blood product ratios in these children. This study's objective was to evaluate whether high blood product ratios or low deficits conferred a survival benefit in children with non-traumatic life-threatening bleeding. MATERIALS AND METHODS: This is a secondary analysis of the five-year, multicentre, prospective, observational massive transfusion epidemiology and outcomes in children study of children with life-threatening bleeding from US, Canadian and Italian medical centres. Primary interventions were plasma:RBC and platelets:RBC (high ratio ≥1:2 ml/kg) and plasma and platelet deficits. The primary outcome was mortality at 6 h, 24 h and 28 days. Multivariate logistic regression models were used to determine independent associations with mortality. RESULTS: A total of 222 children were included from 24 medical centres: 145 children (median [interquartile range] age 2.1 years [0.3-11.8]) with operative bleeding and 77 (8.0 years [1.2-14.7]) with medical bleeding. In adjusted analyses, neither blood product ratios nor deficits were associated with mortality at 6 h, 24 h or 28 days. CONCLUSION: This paper addresses a lack of prospective data in children regarding optimal empiric massive transfusion strategies in non-traumatic massive haemorrhage and in finding no decrease in mortality with high plasma or platelet to RBC ratios or lower deficits supports an exploratory analysis for mortality.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".