Determinants of red blood cell transfusions in a pediatric critical care unit: A prospective, descriptive epidemiological study*
Bibliographic record
Abstract
OBJECTIVE: To determine the incidence and to characterize the determinants of red blood cell transfusions in critically ill children. DESIGN: Prospective, descriptive epidemiologic study. SETTING: A single-center, multidisciplinary, tertiary care level, university-affiliated, pediatric intensive care unit (PICU). PATIENTS: Critically ill children. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 1,047 consecutive admissions over a 1-yr period, 985 were retained for study. At least one transfusion was given in 139 cases (14%). Incidence rate of transfusion was 304 transfusions/1,000 cases. Possible determinants of red blood cell transfusions were identified and prospectively monitored during PICU stay until a first transfusion event (transfused cases) or up until the time of death or discharge from PICU (nontransfused cases). Four significant determinants of a first red blood cell transfusion event were retained in the multivariate analysis (odds ratio, 95% confidence interval, p): a hemoglobin level <9.5 g/dL during PICU stay (13.26, 8.04-21.88, p < .001), an admission diagnosis of cardiac disease (8.07, 5.14-14.65, p < .001), an admission Pediatric Risk of Mortality score >10 (4.83, 2.33-10.04, p < .001), and the presence of multiple organ dysfunction syndrome during the stay (2.06, 1.18-3.57, p = .01). CONCLUSION: A significant proportion of critically ill children receive at least one red blood cell transfusion during their PICU stay. Presence of anemia, cardiac disease, severe critical illness, and multiple organ dysfunction syndrome are the most significant determinants of red blood cell transfusions in PICU.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".