Probiotics to improve the gut microbiome in premature infants: are we there yet?
Bibliographic record
Abstract
Gut microbiome maturation in infants born prematurely is uniquely influenced by the physiological, clinical, and environmental factors surrounding preterm birth and early life, leading to altered patterns of microbial succession relative to term infants during the first months of life. These differences in microbiome composition are implicated in acute clinical conditions that disproportionately affect preterm infants, including necrotizing enterocolitis (NEC) and late-onset sepsis (LOS). Probiotic supplementation initiated early in life is an effective prophylactic measure for preventing NEC, LOS, and other clinical concerns relevant to preterm infants. In parallel, reported benefits of probiotics on the preterm gut microbiome, metabolome, and immune function are beginning to emerge. This review summarizes the current literature on the influence of probiotics on the gut microbiome of preterm infants, outlines potential mechanisms by which these effects are exerted, and highlights important clinical considerations for determining the best practices for probiotic use in premature 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".