Prevalence and determinants of anemia at discharge in pediatric intensive care survivors
Bibliographic record
Abstract
BACKGROUND: Restrictive transfusion practices are increasingly being followed in pediatric intensive care units (PICU); consequently, more patients are discharged anemic from PICU. Given the possible impact of anemia on long-term neurodevelopmental outcomes, we aim to describe the epidemiology of anemia at PICU discharge in a mixed (pediatric and cardiac) cohort of PICU survivors and to characterize risk factors for anemia. STUDY DESIGN AND METHODS: We performed a retrospective cohort study in the PICU of a multidisciplinary tertiary-care university-affiliated center. All consecutive PICU survivors for whom a hemoglobin level was available at PICU discharge were included. Baseline characteristics and hemoglobin levels were extracted from an electronic medical records database. RESULTS: From January 2013 to January 2018, 4750 patients were admitted to the PICU (97.1% survival); discharge hemoglobin levels were available for 4124 patients. Overall, 50.9% (n = 2100) were anemic at PICU discharge. Anemia at PICU discharge was also common in the cardiac surgery population (53.3%), mainly in acyanotic patients; only 24.6% of cyanotic patients were anemic according to standard definitions of anemia. Cardiac surgery patients were transfused more often and at higher hemoglobin levels than medical and non-cardiac surgery patients. Anemia at admission was the strongest predictor of anemia at discharge (odds ratios (OR): 6.51, 95% confidence interval (CI:5.40;7.85)). DISCUSSION: Half of PICU survivors are anemic at discharge. Further studies are required to determine the course of anemia after discharge and to ascertain whether anemia is associated with adverse long-term 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".