Red Blood Cell Transfusion Practices in Pediatric Critical Care
Bibliographic record
Abstract
Summary In this paper, we review all published papers on the practice patterns of pediatric intensivists with respect to the transfusion of red blood cells to critically ill children. In order to achieve this task, we address three questions: (1) What do pediatric intensivists think about RBC transfusion? (2) What do they do in practice? (3) What should be done? A review of the available evidence in the medical literature was undertaken, and the results reported. We concluded that there is a large variation in stated and observed practice patterns in pediatric intensive care. The hemoglobin concentration, as well as many other host‐specific factors, modulate the decision to prescribe a RBC transfusion in critically ill children. Hard data that support the prevalent practice pattern are scarce. Clearly, more clinical studies are required to better define the best red blood cell transfusion strategy in pediatric intensive care units.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".