Survey on transfusion practices of pediatric intensivists*
Bibliographic record
Abstract
OBJECTIVE: To describe the red blood cell transfusion practices of pediatric intensivists. DESIGN: Cross-sectional self-administered survey. SETTING: Pediatric intensive care units. PATIENTS: Academic pediatric intensivists. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: Scenario-based survey among English- or French-speaking intensivists from Canada, France, Belgium, or Switzerland, working in tertiary-care pediatric intensive care units. Respondents were asked to report their decisions regarding transfusion practice with respect to four scenarios: cases of bronchiolitis, septic shock, trauma, and the postoperative care of a patient with Fallot's tetrad. The response rate was 71% (163 of 230). The overall baseline hemoglobin transfusion threshold that would have prompted intensivists to transfuse a patient ranged from 7 to 13 g/dL (70-130 g/L) within almost all scenarios. There was a significant difference between scenarios of the average baseline hemoglobin transfusion thresholds (p < .0001). A low Pao2, a high blood lactate concentration, a high Pediatric Risk of Mortality score, active gastric bleeding, emergency surgery, and age (2 wks) were important determinants of red blood cell transfusion, whereas none of the respondents' personal characteristics were. The average volume of packed red blood cells transfused in the four scenarios did not differ significantly. CONCLUSIONS: This survey documented a significant variation in transfusion practice patterns among pediatric critical care practitioners with respect to the threshold hemoglobin concentration for red blood cell transfusion. The volume of packed red blood cells given was not adjusted to the hemoglobin concentration.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".