Bacterial Load and Molecular Markers Associated With Early-onset Group B Streptococcus: A Systematic Review and Meta-analysis.
journal contributionposted on 24.04.2019, 11:46 by F Seedat, CS Brown, C Stinton, J Patterson, J Geppert, K Freeman, B Tan, SA Johnson, H Fraser, OA Uthman, ER Robinson, ND McCarthy, A Clarke, S Taylor-Phillips
BACKGROUND: The natural history of neonatal group B Streptococcus (GBS) is poorly understood. Little is known about the bacterial factors influencing the transmission of GBS from mother to neonate, or the development of invasive early-onset GBS disease (EOGBS) in colonized neonates. We reviewed whether bacterial load and molecular markers are associated with GBS vertical transmission and progression to EOGBS. METHODS: We searched Medline, Embase, Cochrane and Web of Science from inception to October 10, 2016, for observational studies in English. We also hand-searched reference lists of relevant publications and experts cross-checked included studies. Two reviewers independently screened studies, extracted data and appraised the quality of included studies using the Quality in Prognosis Studies tool. We conducted random-effects meta-analyses where possible and narratively synthesized the evidence in text and tables. RESULTS: Seventeen studies were included from 1107 records retrieved from electronic databases and publication references. Meta-analyses of 3 studies showed that neonates colonized by serotype III had a higher risk of developing EOGBS than serotype Ia (pooled risk ratio: 1.51, 95% confidence interval: 1.12-2.03) and serotype II (risk ratio: 1.95, 95% confidence interval: 1.10-3.45). Eleven studies showed that in heavily colonized mothers, 2-3 times more neonates were colonized, and in heavily colonized neonates, up to 15 times more neonates had EOGBS, compared with light colonization. Most evidence was published before 2000 and was at risk of bias. CONCLUSIONS: Acknowledging the difficulty of natural history studies, well-controlled studies are needed to assess the predictive value of pathogen subtype and heavy load; they may be useful for better-targeted prevention.