Does Bathing Newborns Remove Potentially Harmful Pathogens from the Skin?
Bibliographic record
Abstract
BACKGROUND: Newborn infants are routinely bathed after birth partly to reduce the possibility of transmitting potential pathogens to others. The extent to which a mild soap reduces the quantity and type of microbes found on the skin through normal colonization has not been reported. The objective of the study was to compare colonization rates between infants bathed in soap and water and infants bathed in plain water. METHOD: One hundred and forty infants were randomly assigned to one group bathed in a mild pH neutral soap and water or to another group bathed in water alone. Microbiology swabs were taken on three occasions (before the first bath, 1 hour after the bath, and 24 hours after birth) from two sites (anterior fontanelle and umbilical area). RESULTS: No difference occurred between groups on type or quantity of organisms found at each time period. Skin colonization is a function of time, and the quantity of organisms identified increased over time (Friedman A 2 = 111.379, df = 5, p < 0.001). CONCLUSIONS: Bathing with mild soap as opposed to bathing in water alone has minimal effect on skin bacterial colonization. Skin colonization increased over time. The findings did not support the efficacy of bathing with soap and water to reduce skin colonization of bacterial pathogens. Although the incidence of potential pathogens colonizing the skin during the first day of life is low and unlikely to pose a risk to healthy newborns, health care professionals may wish to wear gloves until the infant has been bathed.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".