Recommendations on RBC Transfusion in General Critically Ill Children Based on Hemoglobin and/or Physiologic Thresholds From the Pediatric Critical Care Transfusion and Anemia Expertise Initiative
Bibliographic record
Abstract
OBJECTIVES: To present the consensus recommendations and supporting literature for RBC transfusions in general critically ill children from the Pediatric Critical Care Transfusion and Anemia Expertise Initiative. DESIGN: Consensus conference series of international, multidisciplinary experts in RBC transfusion management of critically ill children. METHODS: The panel of 38 experts developed evidence-based and, when evidence was lacking, expert-based recommendations and research priorities regarding RBC transfusions in critically ill children. The subgroup on RBC transfusion in general critically ill children included six experts. Electronic searches were conducted using PubMed, EMBASE, and Cochrane Library databases from 1980 to May 30, 2017, using a combination of keywords to define concepts of RBC transfusion and critically ill children. Recommendation consensus was obtained using the Research and Development/UCLA Appropriateness Method. The results were summarized using the Grading of Recommendations Assessment, Development, and Evaluation method. RESULTS: Three adjudicators reviewed 4,399 abstracts; 71 papers were read, and 17 were retained. Three papers were added manually. The general Transfusion and Anemia Expertise Initiative subgroup developed, and all Transfusion and Anemia Expertise Initiative members voted on two good practice statements, six recommendations, and 11 research questions; in all instances, agreement was reached (> 80%). The good practice statements suggest a framework for RBC transfusion in PICU patients. The good practice statements and recommendations focus on hemoglobin as a threshold and/or target. The research questions focus on hemoglobin and physiologic thresholds for RBC transfusion, alternatives, and risk/benefit ratio of transfusion. CONCLUSIONS: Transfusion and Anemia Expertise Initiative developed pediatric-specific good practice statements and recommendations regarding RBC transfusion management in the general PICU population, as well as recommendations to guide future research priorities. Clinical recommendations emphasized relevant hemoglobin thresholds, and research recommendations emphasized a need for further understanding of physiologic thresholds, alternatives to RBC transfusion, and hemoglobin thresholds in populations with limited pediatric literature.
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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 | 0.067 | 0.214 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.011 |
| Bibliometrics | 0.018 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.008 | 0.005 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".