Probiotic supplementation – does it prevent or cause neonatal sepsis?
Bibliographic record
Abstract
Probiotic supplementation in preterm infants is one of the most extensively studied interventions in neonatal medicine, with over 50 randomised controlled trials. This paper examines the relationship between probiotic supplementation and late onset sepsis (LOS), considering mechanistic pathways, clinical evidence, and safety profile. Multiple systematic reviews and meta-analyses consistently show that probiotics reduce necrotising enterocolitis (NEC) incidence and all-cause mortality in preterm infants, establishing them as one of the most beneficial interventions in neonatology. Current evidence suggests modest effects on LOS, with Cochrane systematic reviews reporting relative risk 0.89 (95 % CI 0.82-0.97) but with low certainty. Mechanisms supporting LOS reduction include competitive pathogen exclusion, enhanced epithelial barrier function, improved immune responses, and reduced time to full enteral feeding with decreased intravenous access requirements. The safety profile of probiotics is reassuring, with serious adverse events being exceptionally rare. Probiotic-induced sepsis probably occurs in less than 0.5 % of treated infants, representing a very low risk that must be weighed against the likely substantial benefits for NEC and mortality reduction. Product contamination and other quality issues exist but appear manageable with appropriate quality control. Given the robust evidence for NEC and mortality reduction, probiotics represent a valuable intervention for preterm infants but may have limited, if any impact on sepsis. While their specific role in LOS prevention and impacts on the resistome requires further investigation, the overall benefit-risk profile strongly favors their use. Future research will further refine understanding of optimal strain selection and implementation strategies for maximizing clinical benefits while maintaining safety.
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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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".