Neonatal Outcomes Following Culture-negative Late-onset Sepsis Among Preterm Infants
Bibliographic record
Abstract
BACKGROUND: Culture-negative late-onset sepsis (LOS) is commonly diagnosed in neonatal intensive care units, while the outcomes of neonatal culture-negative LOS are not reported for large cohorts. This study aimed to examine the incidence and neonatal outcomes for culture-negative LOS in a contemporary multicenter cohort of preterm infants. METHODS: We performed a retrospective analysis of data from a cluster-randomized controlled study. Infants <34 weeks of gestation and admitted to 25 neonatal intensive care units between May 1, 2015, and April 30, 2018, were included. Culture-negative LOS was diagnosed if infants had abnormal manifestations and laboratory tests but negative blood cultures. The primary outcome was a composite of mortality or morbidities including periventricular leukomalacia (PVL), retinopathy of prematurity (ROP) ≥ stage 3 or bronchopulmonary dysplasia (BPD). RESULTS: Of 22,346 eligible infants, 1505 (6.7%) infants had culture-negative and 761 (3.4%) infants had culture-positive LOS. Compared with infants without LOS, infants with culture-negative LOS had higher rates of composite outcome (24.1% vs. 9.6%), death (3.8% vs. 1.8%), PVL (4.8% vs. 2.2%), severe ROP (3.3% vs. 1.1%) and BPD (18.1% vs. 7.0%). After adjustment, culture-negative LOS was independently associated with increased risk of composite outcome {adjusted odds ratio [aOR]: 1.8 [95% confidence interval (CI): 1.5-2.1]}, PVL [aOR: 2.0 (95% CI: 1.4-2.8)] and BPD [aOR: 1.8 (95% CI: 1.5-2.2)] relative to the absence of LOS. CONCLUSION: Culture-negative LOS was frequently diagnosed in preterm infants and was associated with increased risks of adverse outcomes. There is an emerging need for more precise diagnosis and treatment strategies for culture-negative LOS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".