Early‐onset neonatal group B streptococcus sepsis following national risk‐based prevention guidelines
Bibliographic record
Abstract
BACKGROUND: Neonatal infection with group B streptococcus (GBS) is an important cause of infant mortality. Intrapartum antibiotics reduce early-onset GBS sepsis, but recommendations vary as to whether they should be offered following antenatal screening or based on risk factors alone. We aimed to determine the incidence of early-onset GBS sepsis in New Zealand five years after the publication of national risk-based GBS prevention guidelines. MATERIALS AND METHODS: Prospective surveillance of early-onset GBS sepsis (defined as infection in the first 48 h of life) was undertaken between April 2009 and March 2011 through the auspices of the New Zealand Paediatric Surveillance Unit as part of a survey of infection presenting in the first week of life. RESULTS: There were 29 cases of confirmed early-onset GBS sepsis, including one case of meningitis, giving an incidence rate of 0.23 per 1000 (95% CI 0.16-0.33) live births. Three infants (10.3%) died. In 16 cases (55%), a maternal risk factor qualifying the mother for intrapartum antibiotics was present, but only five (31%) received this intervention. A retrospective review of the major hospital laboratory databases for this period identified two additional cases. A secondary sensitivity analysis taking account of these cases provided an estimated national incidence of 0.26 (95% CI 0.18-0.37) per 1000 live births. CONCLUSIONS: Ten years after a similar survey and five years after promoting a single, risk-based prevention protocol nationally, the incidence of early-onset GBS disease in New Zealand has more than halved, but opportunities remain to further reduce the rate.
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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 | 0.005 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".