Routine screening of abnormal vaginal flora during pregnancy reduces the odds of preterm birth: a systematic review and meta-analysis.

Prematurity is the leading cause of perinatal mortality and the morbidity among children under the age of 5. The prevalence of preterm birth is between 5 and 18% worldwide. Approximately 30% of preterm deliveries occur as a consequence of fetal or maternal infections. Bacterial vaginosis can increase the risk of ascending infections. However, there is no recommendation or protocol for screening of abnormal vaginal flora. The aim of this systematic review was to investigate the effectiveness of routine screening of abnormal vaginal flora during pregnancy care. We conducted our systematic search in the following databases: MEDLINE via PubMed, Embase, and Cochrane Library. Studies reporting on pregnant women with no symptoms of bacterial vaginosis were included in our analysis if they provided data on the outcome of their pregnancy. The intervention group went through screening of abnormal vaginal flora in addition to routine pregnancy care. Odds ratio (OR) with 95% confidence intervals (CIs) was used as effect size measure. From each study the total number of patients and number of events was extracted in both the intervention and control arm to calculate OR. Altogether we included 13 trials with 143,534 patients. The screening methods were Gram stain, pH screening, pH self-screening and pH screening combined with Gram stain. Regular screening of vaginal flora compared to no screening significantly reduces the odds of preterm birth before 37 weeks (8.98% vs 9.42%; OR 0.71, CI 0.57-0.87), birthweight under 2500 g (6.53% vs 7.24%; OR 0.64, CI 0.50-0.81), preterm birth before 32 weeks (1.35% vs 2.03%; OR 0.51, CI 0.31-0.85) and birthweight under 1000 g (0.86% vs 2.2%; OR 0.33, CI 0.19-0.57). In conclusion, the routine screening of abnormal vaginal flora might prevent preterm birth, extreme preterm birth, low birthweight deliveries and very low birthweight deliveries. Further research is needed to assess the problem more accurately.