Prevention of early‐onset group B streptococcal disease: a pinch of probability is worth a pound of perhaps
Bibliographic record
Abstract
An effective screening programme identifies risk factors that increase disease likelihood, and reduces disease development through risk modification or intervention strategies tailored to the population. No screening programme exemplifies this more than the prevention of newborn early-onset group B streptococcal (EOGBS) disease. From the 1990s, guidelines advocated either a risk-based or a screening approach for intrapartum antibiotic prophylaxis. Unfortunately, no randomised trials have evaluated risk factor-based intrapartum antibiotic prophylaxis versus universal screening approaches for the prevention of perinatal GBS infection. A 2002 Centers for Disease Control and Prevention retrospective cohort observational study of more than 600 000 liveborn US infants found a significantly lower risk of EOGBS disease among infants of screened women compared with women managed with the risk-based approach (adjusted risk ratio 0.46; 95% CI 0.36–0.60; Schrag et al NEJM 2002; 347:233–39). As a result, GBS screening guidelines in the USA, Canada, and Australia were revised, and universal culture-based screening of all pregnant women at 35–37 weeks of gestation was recommended. Group B Strep Support reports several medico-legal actions on behalf of infants with GBS disease, 40% of which were due to a failure of intrapartum prophylaxis in the presence of known GBS risk factors. Currently in the UK, routine antepartum screening for GBS is not recommended (Hughes et al. BJOG 2017;124:e280–e305). Despite the implementation of a risk-based prevention approach in 2003, the incidence of EOGBS disease has not changed (0.57/1000 in 2015 versus 0.48/1000 live births in 2000). This may in part result from the fact that only a small proportion of newborns with EOGBS disease will have risk factors that trigger intrapartum GBS prophylaxis (for example, 35% in the most recent survey from the UK; British Paediatric Surveillance Unit Annual Report 2015–2016;2016:10–12). Thus even the perfect implementation of a risk-based approach is not likely to lead to decreases in the incidence of disease as pronounced as those attained with universal screening. Thus, one might conclude that more widespread antibiotic prophylaxis leads to improved prevention of neonatal GBS infection. So why is universal screening not recommended in the UK? When contemplating a therapy to prevent disease burden, the potential adverse effects of an intervention and the number of individuals to be treated are important considerations. Maternal antibiotic reactions, the development of antibiotic-resistant bacteria, the impact on the infant microbiome, and healthcare expenditure must be viewed as balancing measures when choosing prevention strategies for EOGBS disease. The number needed to treat in order to prevent a disease is inversely proportional to the baseline risk of the disease in the target population: as disease prevalence increases, fewer individuals will need to be treated to prevent one case. Thus, in the UK (EOGBS rate 0.57/1000 live births) universal screening would require approximately 2200 women be treated to prevent one EOGBS case [The UK National Screening Committee (UK NSC) recommendation on Group B Streptococcus screening in pregnancy; 2017] versus 1200 women in Australia (EOGBS rate 0.84/1000 live births; Angstetra et al. Aust NZ J Obstet Gynaecol 2007;47:378–82). National policies must balance the benefits and consequences of preventive strategies for EOGBS disease and choose which strategy best suits particular populations. The current approach in the UK is not reducing the risk of EOGBS disease, so a decision must be made about what to do next. Paraphrasing the words of the author James Thurber, both society and the individual will have to weigh whether the pinch of probability is worth the pound of perhaps. None declared. Completed disclosure of interests form available to view online as supporting information. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".