Prevalence of Group B Streptococcus maternal colonization, serotype distribution, and antimicrobial resistance in Sub-Saharan Africa: A systematic review and meta-analysis
Bibliographic record
Abstract
Group B Streptococcus (GBS)-associated maternal, perinatal, and neonatal mortality and morbidity disproportionately affects Sub-Saharan Africa (SSA). This systematic review and meta-analysis aimed to address the estimated prevalence, antimicrobial susceptibility, and serotype distribution of GBS isolates in SSA. This study was done according to PRISMA guidelines. MEDLINE/PubMed, CINAHL (EBSCO), Embase, SCOPUS, Web of Sciences databases, and Google Scholar were used to retrieve both published and unpublished articles. STATA software version 17 was used for data analysis. Forest plots using the random-effect model were used to present the findings. Heterogeneity was assessed using Cochrane chi-square (I2) statistics, while the Egger intercept was used to assess publication bias. Fifty-eight studies that fulfilled the eligibility criteria were included for meta-analysis. The pooled prevalence of maternal rectovaginal colonization and vertical transmission of GBS were 16.06, 95% CI [13.94, 18.30] and 43.31%, 95% CI [30.75, 56.32], respectively. The highest pooled proportion of antibiotic resistance to GBS was observed in gentamicin (45.58%, 95% CI [4.12%, 91.23]), followed by erythromycin, (25.11%, 95% CI [16.70, 34.49]). The lowest antibiotic resistance was observed in vancomycin (3.84%, 95% CI [0.48, 9.22]). Our findings indicate that serotypes Ia/Ib/II/ III/and V cover almost 88.6% of serotypes in SSA. The estimated high prevalence and resistance to different antibiotic classes observed in GBS isolates from SSA suggests the need for implementation of effective intervention efforts.
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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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.042 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".