Fungal infection and neurodevelopmental outcomes at 18–30 months in preterm infants
Bibliographic record
Abstract
Background: Invasive fungal infection (IFI) is associated with significant mortality and morbidity among preterm infants but there has been no population-based study of long-term neurodevelopmental outcomes. The objective of this study was to examine population-based incidence trends as well as mortality, short term in-hospital morbidity and long-term neurodevelopmental outcomes among preterm infants with IFI, non-fungal infections (NFI) and no infections in Canada. Methods: We conducted a retrospective cohort study of 8,408 infants born at <29 weeks gestational age (GA), admitted to Canadian Neonatal Network neonatal intensive care units (NICU) from April 2009 to December 2017, and followed up at 18-30 months corrected age (CA) in Canadian Neonatal Follow-Up Network clinics. We compared mortality, long term neurodevelopmental outcomes and short term in-hospital morbidity among 3 groups of infants (IFI, NFI, and no infections). Results: < 0.01) less likely to have IFI. Among infants with IFI, NFI and no infections, the incidence of the significant neurodevelopmental impairment (sNDI) was 44.26%, 21.63% and 14.84% respectively, while mortality was 50%, 25.35% and 22.25% respectively. Even after risk adjustment for confounders (GA, Score for Neonatal Acute Physiology Version II, ruptured membranes >24 h, maternal antibiotic treatment, antenatal steroid use, cesarean section), infants with IFI had significantly higher odds of sNDI than NFI (aOR: 2.19; 95% CI: 1.23, 3.91) or no infections (aOR: 2.97; 95% CI: 1.55, 5.71), and higher odds of mortality than NFI (aOR: 1.55; 95% CI: 1.07, 2.26) or no infections (aOR: 1.45; 95% CI: 0.97, 2.17). Conclusions: Preterm infants with invasive fungal infections have significantly higher incidence of mortality and adverse neurodevelopmental outcomes than those with non-invasive fungal infections and no infections.
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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 | 0.000 |
| 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 | 0.001 | 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".