Anemia, Blood Loss, and Blood Transfusions in North American Children in the Intensive Care Unit
Bibliographic record
Abstract
RATIONALE: Minimizing exposure of children to blood products is desirable. OBJECTIVES: We aimed to understand anemia development, blood loss, and red blood cell (RBC) transfusions in the pediatric intensive care unit (PICU). METHODS: Prospective, multicenter, 6-month observational study in 30 PICUs. Data were collected on consecutive children (<18 yr old) in the PICU for 48 hours or more. MEASUREMENTS AND MAIN RESULTS: Anemia development, blood loss, and RBC transfusions were measured. A total of 977 children were enrolled. Most (74%) children were anemic in the PICU (33% on admission, 41% developed anemia). Blood draws accounted for 73% of daily blood loss; median loss was 5.0 ml/day. Forty-nine percent of children received transfusions; 74% of first transfusions were on Days 1-2. After adjusting for age and illness severity, compared with nontransfused children, children who underwent transfusion had significantly longer days of mechanical ventilation (2.1 d, P < 0.001) and PICU stay (1.8 d, P = 0.03), and had increased mortality (odds ratio [OR], 11.6; 95% confidence interval [CI], 1.43-90.9; P = 0.02), nosocomial infections (OR, 1.9; 95% CI, 1.2-3.0; P = 0.004), and cardiorespiratory dysfunction (OR, 2.1; 95% CI, 1.5-3.0; P < 0.001). High blood loss per kilogram body weight from blood draws (OR, 1.11; 95% CI, 1.03-1.2; P = 0.01) was associated with RBC transfusion more than 48 hours after admission. The most common indication for transfusion was low hemoglobin (42%). Pretransfusion hemoglobin values varied greatly (mean, 9.7 +/- 2.7 g/dl). CONCLUSIONS: Critically ill children are at significant risk for developing anemia and receiving blood transfusions. Transfusion in the PICU was associated with worse outcomes. It is imperative to minimize blood loss from blood draws and to set clear transfusion thresholds.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".