The impact of jaundice in newborn infants on the length of breastfeeding
Bibliographic record
Abstract
OBJECTIVES: To examine the breastfeeding prevalence among infants aged three and six months who were previously hospitalized because of hyperbilirubinemia, and to determine whether jaundice in newborn infants increases the risk of breastfeeding discontinuation. METHOD: Surveys were mailed to mothers of all eligible infants admitted over a two-and-a-half year period to the paediatric ward of a tertiary care children's hospital with a diagnosis of hyperbilirubinemia. A total of 127 mother-patient pairs were included in the study. Breastfeeding rates at three and six months were compared with those of a city-wide survey (Infant Care Survey) conducted by Ottawa's Public Health Department. Risk factors for early breastfeeding discontinuation were examined. RESULTS: Breastfeeding rates at three and six months were not different between the study group and those reported in the Infant Care Survey (75.5% in the study group versus 71.2% in the Infant Care Survey group, at three months; and 59.1% in the study group versus 50.8% of the Infant Care Survey group, at six months). None of the previously reported risk factors for early weaning had an impact on breastfeeding duration in the study population. CONCLUSION: Breastfeeding rates following the discharge of infants diagnosed with jaundice were not significantly different from those reported for the general population. Different patient characteristics may have inflated the breastfeeding rates in the study population, as evidenced by a very high education level among the mothers of enrolled patients. Larger prospective studies in diverse populations are needed to determine the rates of early breastfeeding discontinuation in jaundiced infants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".