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Establishing a Gold Standard for Quantitative Menstrual Cycle Monitoring
Background and Objectives: The Quantum Menstrual Health Monitoring Study will measure four key reproductive hormones in the urine (follicle-stimulating hormone, FSH; estrone-3-glucuronide, E(1)3G; luteinizing hormone, LH; and pregnanediol glucuronide, PDG) to characterize patterns that predict and c...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10533176/ https://www.ncbi.nlm.nih.gov/pubmed/37763632 http://dx.doi.org/10.3390/medicina59091513 |
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author | Bouchard, Thomas Yong, Paul Doyle-Baker, Patricia |
author_facet | Bouchard, Thomas Yong, Paul Doyle-Baker, Patricia |
author_sort | Bouchard, Thomas |
collection | PubMed |
description | Background and Objectives: The Quantum Menstrual Health Monitoring Study will measure four key reproductive hormones in the urine (follicle-stimulating hormone, FSH; estrone-3-glucuronide, E(1)3G; luteinizing hormone, LH; and pregnanediol glucuronide, PDG) to characterize patterns that predict and confirm ovulation, referenced to serum hormones and the gold standard of the ultrasound day of ovulation in participants with regular cycles. These normal cycles will provide a reference for comparison to irregular cycles in subjects with polycystic ovarian syndrome (PCOS) and athletes. Materials and Methods: Participants will track their menstrual cycles for 3 months and be provided with an at-home urine hormone monitor (Mira monitor) to predict ovulation. The day of ovulation will be confirmed with serial ultrasounds completed in a community clinic. Urine results will be compared to serum hormone values. Other markers of menstrual health, such as bleeding patterns and temperature changes, will be determined using a customized app. Three groups will be recruited. Group 1 will include those with consistent regular cycle lengths (between 24–38 days), and will be compared to two groups with irregular cycle lengths (with increased cycle length variability and longer cycles). Group 2 will include those with polycystic ovarian syndrome (PCOS) with irregular cycles and Group 3 will include individuals participating in high levels of exercise with irregular cycles. Hypothesis: The Mira monitor quantitative urine hormone pattern will accurately correlate with serum hormonal levels and will predict (with LH) and confirm (with PDG) the ultrasound day of ovulation in those with regular cycles as well as those with irregular cycles. Rationale: Once the ultrasound validation is complete, tools like the Mira monitor with a customized app may become a new standard for at-home and remote clinical monitoring of the menstrual cycle without having to use labor-intensive follicular-tracking ultrasound or follow serum hormone changes. Conclusions: Precision monitoring of the menstrual cycle is expected to impact individuals who want to increase their menstrual health literacy and guide decisions about fertility. |
format | Online Article Text |
id | pubmed-10533176 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105331762023-09-28 Establishing a Gold Standard for Quantitative Menstrual Cycle Monitoring Bouchard, Thomas Yong, Paul Doyle-Baker, Patricia Medicina (Kaunas) Protocol Background and Objectives: The Quantum Menstrual Health Monitoring Study will measure four key reproductive hormones in the urine (follicle-stimulating hormone, FSH; estrone-3-glucuronide, E(1)3G; luteinizing hormone, LH; and pregnanediol glucuronide, PDG) to characterize patterns that predict and confirm ovulation, referenced to serum hormones and the gold standard of the ultrasound day of ovulation in participants with regular cycles. These normal cycles will provide a reference for comparison to irregular cycles in subjects with polycystic ovarian syndrome (PCOS) and athletes. Materials and Methods: Participants will track their menstrual cycles for 3 months and be provided with an at-home urine hormone monitor (Mira monitor) to predict ovulation. The day of ovulation will be confirmed with serial ultrasounds completed in a community clinic. Urine results will be compared to serum hormone values. Other markers of menstrual health, such as bleeding patterns and temperature changes, will be determined using a customized app. Three groups will be recruited. Group 1 will include those with consistent regular cycle lengths (between 24–38 days), and will be compared to two groups with irregular cycle lengths (with increased cycle length variability and longer cycles). Group 2 will include those with polycystic ovarian syndrome (PCOS) with irregular cycles and Group 3 will include individuals participating in high levels of exercise with irregular cycles. Hypothesis: The Mira monitor quantitative urine hormone pattern will accurately correlate with serum hormonal levels and will predict (with LH) and confirm (with PDG) the ultrasound day of ovulation in those with regular cycles as well as those with irregular cycles. Rationale: Once the ultrasound validation is complete, tools like the Mira monitor with a customized app may become a new standard for at-home and remote clinical monitoring of the menstrual cycle without having to use labor-intensive follicular-tracking ultrasound or follow serum hormone changes. Conclusions: Precision monitoring of the menstrual cycle is expected to impact individuals who want to increase their menstrual health literacy and guide decisions about fertility. MDPI 2023-08-23 /pmc/articles/PMC10533176/ /pubmed/37763632 http://dx.doi.org/10.3390/medicina59091513 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Protocol Bouchard, Thomas Yong, Paul Doyle-Baker, Patricia Establishing a Gold Standard for Quantitative Menstrual Cycle Monitoring |
title | Establishing a Gold Standard for Quantitative Menstrual Cycle Monitoring |
title_full | Establishing a Gold Standard for Quantitative Menstrual Cycle Monitoring |
title_fullStr | Establishing a Gold Standard for Quantitative Menstrual Cycle Monitoring |
title_full_unstemmed | Establishing a Gold Standard for Quantitative Menstrual Cycle Monitoring |
title_short | Establishing a Gold Standard for Quantitative Menstrual Cycle Monitoring |
title_sort | establishing a gold standard for quantitative menstrual cycle monitoring |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10533176/ https://www.ncbi.nlm.nih.gov/pubmed/37763632 http://dx.doi.org/10.3390/medicina59091513 |
work_keys_str_mv | AT bouchardthomas establishingagoldstandardforquantitativemenstrualcyclemonitoring AT yongpaul establishingagoldstandardforquantitativemenstrualcyclemonitoring AT doylebakerpatricia establishingagoldstandardforquantitativemenstrualcyclemonitoring |