Statistical Model for Vaginal Microflora and GBS Risk
Author Information
Author(s): Mei-Ling T. Lee, Robin A. Ross, Andrew B. Onderdonk
Primary Institution: Brigham and Women's Hospital and Harvard Medical School
Hypothesis
Can a statistical model relate human microflora to the risk of vaginal colonization by group B Streptococcus (GBS)?
Conclusion
The statistical model identifies risk factors for GBS colonization, which may be important for detection and prevention.
Supporting Evidence
- 84% sensitivity and 79% specificity were achieved in predicting GBS colonization.
- 117 out of 536 observations were identified as GBS positive.
- The model uses concentrations of Corynebacterium sp., Streptococcus spp., and total anaerobic bacteria as risk factors.
Takeaway
This study created a model to help predict which women might carry a bacteria called GBS based on their vaginal bacteria.
Methodology
Longitudinal observations of bacterial concentrations were taken from healthy women using a duplicate swab technique and analyzed using generalized estimating equations.
Potential Biases
The data set is biased toward normal healthy vaginal microflora due to strict exclusion criteria.
Limitations
The model may not detect low levels of GBS colonization due to the nature of the microbiologic cultures used.
Participant Demographics
Non-pregnant, menarcheal women who volunteered for the study.
Statistical Information
P-Value
0.0001
Statistical Significance
p<0.05
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