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Assessment of anovulation in eumenorrheic women: comparison of ovulation detection algorithms
Kristine E Lynch1, Sunni L Mumford2, Karen C Schliep2
1Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, US Department of Health & Human Services, Bethesda, Maryland; Department of Public Health and Nursing, Westminster College, Salt Lake City, Utah.
Objective:
To compare previously used algorithms to identify anovulatory menstrual cycles in women self-reporting regular menses.
Design:
Prospective cohort study.
Setting:
Western New York.
Patient(S):
Two hundred fifty-nine healthy, regularly menstruating women followed for one (n=9) or two (n=250) menstrual cycles (2005-2007).
Intervention(S):
None.
Main Outcome Measure(S):
Prevalence of sporadic anovulatory cycles identified using 11 previously defined algorithms that use E2, P, and LH concentrations.
Result(S):
Algorithms based on serum LH, E2, and P levels detected a prevalence of anovulation across the study period of 5.5%-12.8% (concordant classification for 91.7%-97.4% of cycles). The prevalence of anovulatory cycles varied from 3.4% to 18.6% using algorithms based on urinary LH alone or with the primary E2 metabolite, estrone-3-glucuronide, levels.
Conclusion(S):
The prevalence of anovulatory cycles among healthy women varied by algorithm. Mid-cycle LH surge urine-based algorithms used in over-the-counter fertility monitors tended to classify a higher proportion of anovulatory cycles compared with luteal-phase P serum-based algorithms. Our study demonstrates that algorithms based on the LH surge, or in conjunction with estrone-3-glucuronide, potentially estimate a higher percentage of anovulatory episodes. Addition of measurements of postovulatory serum P or urine pregnanediol may aid in detecting ovulation.
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