Probiotics and Prebiotics: Role in Prevention of Nosocomial Sepsis in Preterm Infants
Bibliographic record
Abstract
Nosocomial sepsis is associated with increased mortality and morbidity including neurodevelopmental impairment and prolonged hospital stay. Prevention of sepsis especially in the preterm infants in the neonatal intensive care unit remains a major challenge. The gastrointestinal tract is an important source of potential pathogens causing nosocomial sepsis as the immature intestinal epithelium can permit translocation of bacteria and yeast. The intestinal tract and its microflora play an important role in the immunity. Altering the gut microflora has been extensively studied for immunomodulation in preterm infants. Probiotics are live microorganisms which when administered in adequate amounts confer a health benefit on the host. Probiotics have been used for prevention and treatment of various medical conditions in children and adults. Studies on probiotics in premature infants have focused on normalizing intestinal flora, improvement in feeding intolerance, prevention of necrotizing enterocolitis and sepsis. In this paper, we discuss the intestinal bacterial colonization pattern; the rational for probiotics and prebiotic therapy with special focus on the prevention of nosocomial sepsis in preterm infants.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".