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Periodontal Disease and Risk of Preeclampsia: A Meta-Analysis of Observational Studies

BACKGROUND: Many epidemiological studies have found a positive association between periodontal disease (PD) and the risk of preeclampsia, but the magnitude of this association varies and independent studies have reported conflicting findings. We performed a meta-analysis to ascertain the relationshi...

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Detalles Bibliográficos
Autores principales: Wei, Ben-Juan, Chen, Yi-Jun, Yu, Li, Wu, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3741358/
https://www.ncbi.nlm.nih.gov/pubmed/23951033
http://dx.doi.org/10.1371/journal.pone.0070901
Descripción
Sumario:BACKGROUND: Many epidemiological studies have found a positive association between periodontal disease (PD) and the risk of preeclampsia, but the magnitude of this association varies and independent studies have reported conflicting findings. We performed a meta-analysis to ascertain the relationship between PD and preeclampsia. METHODS: The PubMed database was searched up to January 12, 2013, for relevant observational studies on an association between PD and the risk of preeclampsia. Data were extracted and analyzed independently by two authors. The meta-analysis was performed using comprehensive meta-analysis software. RESULTS: Thirteen observational case-control studies and two cohort studies, involving 1089 preeclampsia patients, were identified. Based on a random-effects meta-analysis, a significant association between PD and preeclampsia was identified (odds ratio = 2.79, 95% confidence interval CI, 2.01–3.01, P<0.0001). CONCLUSIONS: Although the causality remains unclear, the association between PD and preeclampsia may reflect the induction of PD by the preeclamptic state, or it may be part of an overall exaggerated inflammatory response to pregnancy. Larger randomized controlled trials with preeclampsia as the primary outcome and pathophysiological studies are required to explore causality and to dissect the biological mechanisms involved.