65 Outcomes of Neonates Admitted to the NICU during the COVID-19 Pandemic: Comparison with a Pre-Pandemic Cohort
Bibliographic record
Abstract
Abstract Introduction/Background The effect of the COVID-19 pandemic on neonatal outcomes is not yet completely understood. Objectives To compare the neonatal outcomes of very preterm infants admitted to Canadian NICUs pre- and during the COVID-19 pandemic. Design/Methods This retrospective cohort study included infants born <33 weeks and admitted to tertiary Canadian NICUs participating in the Canadian Neonatal Network (CNN) database. The sample included 14,368 infants from two cohorts: 7,280 infants pre-pandemic (April 1, 2018 – December 31, 2019) and 7,088 infants during the pandemic (April 1, 2020 – December 31, 2021). Primary composite outcomes were mortality or major morbidity. Care practices and interventions were compared. Relative risk (RR) comparing the pandemic vs pre-pandemic periods were estimated using generalized estimated equations and adjusted for confounders. Results The characteristics of infants admitted before and during the pandemic were not significantly different. The incidence of mortality or major morbidity was similar pre- and during the pandemic (37%, 36% respectively; RR=1.01 [0.92, 1.01]; Table 1). Infant health outcomes were not significantly different between periods. There was a non-significant decrease in the exclusive receipt of mothers’ own milk (MOM) at discharge (45% pre- and 37% during; RR=0.85 [0.68, 1.06]). Conclusion There was no difference in clinical outcomes between pre-pandemic and pandemic cohorts. The possibility of lower receipt of exclusive MOM at discharge during the COVID-19 pandemic needs further study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".