Impact of Blood Sampling on Anemia in the PICU: A Prospective Cohort Study
Bibliographic record
Abstract
OBJECTIVES: Fifty percent of children are anemic after a critical illness. Iatrogenic blood testing may be a contributor to this problem. The objectives of this study were to describe blood sampling practice in a PICU, determine patient factors associated with increased sampling, and examine the association among blood sampling volume, anemia at PICU discharge, and change in hemoglobin from PICU entry to PICU discharge. DESIGN: Prospective observational cohort study. SETTING: PICU of Sainte-Justine University Hospital. PATIENTS: All children consecutively admitted during a 4-month period. MEASUREMENTS AND MAIN RESULTS: Four hundred twenty-three children were enrolled. Mean blood volume sampled was 3.9 (±19) mL/kg/stay, of which 26% was discarded volume. Children with central venous or arterial access were sampled more than those without access (p < 0.05). Children with sepsis, shock, or cardiac surgery were most sampled, those with a primary respiratory diagnosis; the least (p < 0.001). We detected a strong association between blood sample volume and mechanical ventilation (H, 81.35; p < 0.0001), but no association with severity of illness (Worst Pediatric Logistic Organ Dysfunction score) (R, -0.044; p = 0.43). Multivariate analysis (n = 314) showed a significant association between the volume of blood sampled (as continuous variable) and anemia at discharge (adjusted OR, 1.63; 95% CI, 1.18-2.45; p = 0.003). We lacked power to detect an association between blood sampling and change in hemoglobin from PICU admission to PICU discharge. CONCLUSIONS: Diagnostic blood sampling in PICU is associated with anemia at discharge. Twenty-five percent of blood losses from sampling is wasted. Volumes are highest for patients with sepsis, shock, or cardiac surgery, and in patients with vascular access or ventilatory support.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".