Burden of infant group B Streptococcus disease and impact of maternal screening and antibiotic prophylaxis in Ontario, Canada: a population-based cohort study
Bibliographic record
Abstract
Background: (GBS) significantly contributes to neonatal sepsis and meningitis, with varying disease rates reported globally and limited population-based data. We estimated infant GBS disease burden in Ontario, Canada and assessed the association of maternal GBS screening (35-37 weeks' gestation) and intrapartum antibiotic prophylaxis (IAP) provision with infant disease rates. Methods: Our population-based cohort study included pregnant individuals and their offspring from April 2012 to March 2018, utilising the provincial birth registry linked to health administrative data. GBS cases were ascertained through culture results and diagnostic codes. We calculated incidence rates for early-onset disease (EOD: 0-6 days), late-onset disease (LOD: 7-89 days), and ultra-LOD (ULOD: 90-365 days). Adjusted incidence rate ratios (aIRR) were derived via log-binomial regression to compare infant GBS rates according to screening and IAP-receipt. Findings: Among 776,148 liveborn infants, we identified 803 with GBS, with multiples exhibiting a threefold incidence increase. Incidence rates of EOD, LOD and ULOD were 0.49, 0.46 and 0.07 per 1000 livebirths, respectively. Of eligible pregnancies, 94% were screened; 23% screened positive, and 81% of them received IAP. Nearly 12% of term EOD infants had mothers who missed IAP despite screening positive. Maternal screening was associated with lower rates of any infant GBS disease (aIRR: 0.60; 95% CI: 0.45, 0.80). Among screen-positive births, IAP-receipt was associated with reduced rates of EOD (aIRR: 0.72, 95% CI: 0.48, 1.29) and LOD/ULOD (aIRR: 0.69; 95% CI: 0.46, 1.05), but confidence intervals included 1.0. Interpretation: Our study, the largest Canadian investigation into infant GBS disease, highlights both widespread adoption and ongoing challenges of the current prevention strategy. Funding: Canadian Institutes of Health Research.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".