Risk Factors and Outcomes of Late-Onset Bacterial Sepsis in Preterm Neonates Born at < 32 Weeks' Gestation
Bibliographic record
Abstract
OBJECTIVE: This study aims to identify the incidence, risk factors, and outcomes of late-onset sepsis in preterm neonates in Canadian neonatal intensive care units (NICUs). STUDY DESIGN: This retrospective analysis included preterm infants born at < 32 weeks' gestation and admitted to 29 NICUs in the Canadian Neonatal Network during the years 2010 and 2011. Infants were classified into three groups: no infection, gram-positive infection, and gram-negative infection. Late-onset sepsis was defined as positive blood and/or spinal fluid cultures after 3 days of birth. Risk factors and the primary outcome of mortality or bronchopulmonary dysplasia (BPD) were compared between the groups. RESULTS: Out of the 7,509 neonates, 6,405 (85%) had no infection, 909 (12%) had gram-positive, and 195 (3%) had gram-negative infections. Lower gestation, higher Score for Neonatal Acute Physiology, version II scores, the presence of central catheters for > 4 days, parenteral nutrition for > 7 days, and prolonged duration of nothing by mouth were associated with late-onset sepsis. After controlling for confounders, the odds ratio (OR) of mortality/BPD were higher in infants who had gram-negative (OR 2.79, 95% confidence interval [CI] 1.96-3.97) and gram-positive (OR 1.44, 95% CI 1.21-1.71) sepsis as compared with no infection. CONCLUSIONS: Bacterial late-onset sepsis in very preterm neonates was associated with mortality and BPD. Neonates with gram-negative sepsis had the highest risk of adverse outcomes as compared with gram-positive sepsis or no sepsis.
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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 | 0.000 | 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 | 0.000 | 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".