Nosocomial Rotavirus Infections: A Meta-analysis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Nosocomial rotavirus (nRV) infections represent an important part of rotavirus (RV)-associated morbidity. The incidence of nRV influences the estimated total RV disease burden, an important determinant of cost-effectiveness of RV vaccination programs. Our aim is to summarize the existing evidence and produce reliable estimates of nRV incidence, in pediatric settings in Europe and North America. METHODS: We searched electronic databases for studies on nRV incidence among pediatric inpatients. To ascertain complete case reporting, only studies describing active nRV surveillance in their methodology were included. Random effects meta-analysis was performed. Meta-regression was used to obtain results adjusted for important study characteristics. RESULTS: Twenty surveillance studies met the quality criteria for inclusion. The pooled unadjusted nRV incidence was 2.9 per 100 hospitalizations (95% confidence interval [CI]: 1.6-4.4). Incidence was significantly influenced by studies' seasonality-months (RV epidemic season only or year-round) and the age range of included patients. Highest nRV incidence was found for children <2 years of age, hospitalized during the epidemic months (8.1/100 hospitalizations; 95% CI: 6.4-9.9). The adjusted year-round nRV incidence estimate without age restriction was 0.4/100 hospitalizations (95% CI: 0.1-2.1) and 0.7 (95% CI: 0.0-1.8) for children <5 years of age. CONCLUSIONS: This is the first meta-analysis to summarize results of surveillance studies on nRV incidence. nRV is an important problem among hospitalized infants during the winter months. The lower season and age-adjusted nRV incidence estimate seems more appropriate for application in population-based burden of disease analysis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".