Early Life Antimicrobial Exposure: Impact on Clostridioides difficile Colonization in Infants
Bibliographic record
Abstract
The relationship between antibiotic use and Clostridioides difficile (C. difficile) has been well established in adults and older children but remains unclear and is yet to be fully examined in infant populations. This study aimed to determine the separate and cumulative impact from antibiotics and household cleaning products on C. difficile colonization in infants. This study included 1429 infants at 3–4 months of age and 1728 infants at 12 months of age from the Canadian Healthy Infant Longitudinal Development (CHILD) birth cohort. The levels of infant antimicrobial exposure were obtained from hospital birth charts and standardized questionnaires. Infant gut microbiota was characterized by Illumina 16S ribosomal ribonucleic acid (rRNA) gene sequencing. Analysis of C. difficile was performed using a quantitative polymerase chain reaction (qPCR). Overall, C. difficile colonized 31% and 46% of infants at 3–4 months and 12 months, respectively. At 3–4 months, C. difficile colonization was significantly higher in infants exposed to both antibiotics and higher (above average) usage of household cleaning products (adjusted odds ratio (aOR) 1.50, 95% CI 1.03–2.17; p = 0.032) than in infants who had the least antimicrobial exposure. This higher colonization persisted up to 12 months of age. Our study suggests that cumulative exposure to systemic antibiotics and higher usage of household cleaning products facilitates C. difficile colonization in infants. Further research is needed to understand the future health impacts.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".