Human Reproduction, Vol. 16, No. 11, 2278-2282,
November 2001
© 2001 European Society of Human Reproduction and Embryology
The relationship between cervical secretions and the daily probabilities of pregnancy: effectiveness of the TwoDay Algorithm
1 Biostatistics Branch, MD A3-03, National Institute of Environmental Health Sciences, PO Box 12233, Research Triangle Park, NC 27709, 2 Institute for Reproductive Health, Georgetown University, Washington, DC, USA and 3 Department of Statistics, University of Padua, Padua, Italy
BACKGROUND: The TwoDay Algorithm is a simple method for identifying the fertile window. It classifies a day as fertile if cervical secretions are present on that day or were present on the day before. This approach may be an effective alternative to the ovulation and symptothermal methods for populations and programmes that find current natural family planning methods difficult to implement. METHODS: We used data on secretions from a large multinational European fecundability study to assess the relationship between the days predicted to be potentially fertile by the TwoDay Algorithm and the day-specific probabilities of pregnancy based on intercourse patterns in 434 conception cycles from the study. RESULTS: The days around ovulation that had the highest fecundability were the days most likely to be classified as fertile by the TwoDay Algorithm. In addition, intercourse on a particular day in the fertile interval was twice as likely to result in a pregnancy if cervical secretions were present on that day or the day before. CONCLUSIONS: The TwoDay Algorithm is effective, both in identifying the fertile days of the cycle and in predicting days within the fertile interval that have a high pregnancy rate. Our data provide the first direct evidence that cervical secretions are associated with higher fecundability within the fertile window.
Key words: Bayesian/cervical secretions/fecundability/fertile interval/natural family planning
4 To whom correspondence should be addressed. E-mail: dunson1{at}niehs.nih.gov
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