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Related Concept Videos

Infertility in Females01:28

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Female infertility is defined as the inability to conceive after a year of regular, unprotected intercourse and affects about 10–15% of couples worldwide. The primary cause of female infertility is ovulatory disorders, which hinder the release of eggs. These disorders can be classified as hypothalamic amenorrhea, polycystic ovarian syndrome (PCOS), premature ovarian failure, and hyperprolactinemic anovulation disorders.
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Related Experiment Video

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Collection of Human Follicular Fluid, Follicle Somatic Cells, and Immature Oocytes from Individuals Undergoing In Vitro Fertilization
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Standardized protocols for characterizing women's fertility: A data-driven approach.

Khandis R Blake1, Barnaby J W Dixson2, Siobhan M O'Dean1

  • 1School of Psychology, Mathews Building, The University of New South Wales, UNSW, Sydney, NSW 2052, Australia.

Hormones and Behavior
|April 14, 2016
PubMed
Summary
This summary is machine-generated.

Standardized methods for tracking the fertile window in women are crucial. This study found that traditional counting methods are inaccurate for predicting ovulation, but combining them with luteinizing hormone tests improves accuracy significantly.

Keywords:
Backward-counting methodFertile windowFertilityForward-counting methodLuteinizing hormoneMenstrual cycleOvulationOvulatory shift

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Area of Science:

  • Reproductive endocrinology
  • Human fertility studies
  • Menstrual cycle research

Background:

  • Debate exists regarding menstrual cycle phase effects on female cognition and behavior.
  • Previous studies lack standardized methods for accurately identifying the fertile window.
  • Imprecise fertility tracking hinders reliable research into cycle-dependent effects.

Purpose of the Study:

  • To develop and validate a data-driven, standardized protocol for characterizing women's fertile phase.
  • To compare the accuracy of traditional fertility estimation methods against a novel approach.
  • To provide a reliable method for researchers investigating fertility effects.

Main Methods:

  • Compared self-reported and counting methods (forward/backward) against luteinizing hormone (LH) tests in 140 women.
  • Assessed accuracy in estimating ovulation and predicting the fertile window.
  • Evaluated the efficacy of combining counting methods with LH testing.

Main Results:

  • Counting methods showed less than 30% accuracy in predicting ovulation.
  • Over 39.5% of the predicted fertile window days were non-fertile using counting methods.
  • Combining counting methods with LH tests, following specific guidelines, achieved >95% fertility prediction accuracy.

Conclusions:

  • Traditional menstrual cycle counting methods are unreliable for accurately identifying the fertile window.
  • A standardized protocol combining counting methods with LH testing offers a highly accurate and cost-effective solution.
  • This validated protocol enables robust research into potential fertility effects on cognition and behavior.