Impact of Rotavirus Vaccine on Premature Infants
Bibliographic record
Abstract
Infants born preterm are at a higher risk of complications and hospitalization in cases of rotavirus diarrhea than children born at term. We evaluated the impact of a rotavirus vaccination campaign (May 2007 to May 2010) on hospitalizations for rotavirus gastroenteritis in a population of children under 3 years old born prematurely (before 37 weeks of gestation) in the Brest University Hospital birth zone. Active surveillance from 2002 to 2006 and a prospective collection of hospitalizations for rotavirus diarrhea were initiated in the pediatric units of Brest University Hospital until May 2010. Numbers of hospitalizations for rotavirus diarrhea among the population of children born prematurely, before and after the start of the vaccination program, were compared using a Poisson regression model controlling for epidemic-to-epidemic variation. A total of 217 premature infants were vaccinated from 2007 to 2010. Vaccine coverage for a complete course of three doses was 41.9%. The vaccine safety in premature infants was similar to that in term infants. The vaccination program led to a division by a factor of 2.6 (95% confidence interval [CI], 1.3 to 5.2) in the number of hospitalizations for rotavirus diarrhea during the first two epidemic seasons following vaccine introduction and by a factor of 11 (95% CI, 3.5 to 34.8) during the third season. We observed significant effectiveness of the pentavalent rotavirus vaccine on the number of hospitalizations in a population of prematurely born infants younger than 3 years of age. A multicenter national study would provide better assessment of this impact. (This study [Impact of Systematic Infants Vaccination Against Rotavirus on Gastroenteritis Hospitalization: a Prospective Study in Brest District, France (IVANHOE)] has been registered at ClinicalTrials.gov under registration no. NCT00740935.).
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".