Anemia at Discharge From the PICU: A Bicenter Descriptive Study
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence and risk markers of anemia at PICU discharge. DESIGN: Bicenter retrospective cohort study. SETTING: Two multidisciplinary French PICUs. PATIENTS: All children admitted during a 5-year period, staying in the PICU for at least 2 days, and for whom a hemoglobin was available at PICU discharge. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Patient, admission, and PICU stay characteristics were retrospectively collected in the electronic medical records of each participating PICU. Anemia was defined according to the World Health Organization criteria. Among the 3,170 patients included for analysis, 1,868 (58.9%) were anemic at discharge from PICU. The proportion of anemic children differed between age categories, whereas the median hemoglobin level did not exhibit significant variations according to age. After multivariate adjustment, anemia at PICU admission was the strongest predictor of anemia at PICU discharge, and the strength of this association varied according to age (interaction). Children anemic at PICU admission had a reduced risk of anemia at PICU discharge if transfused with RBCs during the PICU stay, if less than 6 months old, or if creatinine level at PICU admission was low. Children not anemic at PICU admission had an increased risk of anemia at PICU discharge if they were thrombocytopenic at PICU admission, if they had higher C-reactive protein levels, and if they received plasma transfusion, inotropic/vasopressor support, or mechanical ventilation during the PICU stay. CONCLUSIONS: Anemia is frequent after pediatric critical illness. Anemia status at PICU admission defines different subgroups of critically ill children with specific prevalence and risk markers of anemia at PICU discharge. Further studies are required to confirm our results, to better define anemia during pediatric critical illness, and to highlight the causes of post-PICU stay anemia, its course, and its association with post-PICU outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".