Late-Onset Sepsis among Extremely Preterm Infants of 24–28 Weeks Gestation: An International Comparison in 10 High-Income Countries
Bibliographic record
Abstract
INTRODUCTION: Despite advances in neonatal care, late-onset sepsis remains an important cause of preventable morbidity and mortality. Neonatal late-onset sepsis rates have decreased in some countries, while in others they have not. Our objective was to compare trends in late-onset sepsis rates in 9 population-based networks from 10 countries and to assess the associated mortality within 7 days of late-onset sepsis. METHODS: We performed a retrospective population-based cohort study. Infants born at 24-28 weeks' gestation between 2007 and 2019 were eligible for inclusion. Late-onset sepsis was defined as a positive blood or cerebrospinal fluid culture. Late-onset sepsis rates were calculated for 3 epochs (2007-11, 2012-15, and 2016-19). Adjusted risk ratios (aRRs) for late-onset sepsis were calculated for each network. RESULTS: Of a total of 82,850 infants, 16,914 (20.4%) had late-onset sepsis, with Japan having the lowest rate (7.1%) and Spain the highest (44.6%). Late-onset sepsis rates decreased in most networks and remained unchanged in a few. Israel, Sweden, and Finland showed the largest decrease in late-onset sepsis rates. The aRRs for late-onset sepsis showed wide variations between networks. The rate of mortality temporally related to late-onset sepsis was 10.9%. The adjusted mean length of stay for infants with late-onset sepsis was increased by 5-18 days compared to infants with no late-onset sepsis. CONCLUSIONS: One in 5 neonates of 24-28 weeks' gestation develops late-onset sepsis. Wide variability in late-onset sepsis rates exists between networks with most networks exhibiting improvement. Late-onset sepsis was associated with increased mortality and length of stay.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".