Quantitative Hormonal Biomarkers of Menstrual Health in Normal and Abnormal Cycles

Status: Recruiting
Location: See location...
Intervention Type: Device
Study Type: Observational
SUMMARY

The Quantum Menstrual Health Monitoring Study will measure four key reproductive hormones in the urine 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 polycystic ovarian syndrome (PCOS) and athletes. Clinical signs in the menstrual cycle (e.g. menstrual bleeding, temperature) as well as vital sign and sleep patterns will also be referenced to hormonal changes.

Eligibility
Participation Requirements
Sex: Female
Minimum Age: 18
Maximum Age: 55
Healthy Volunteers: t
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• Regularly menstruating, PCOS or athlete participants aged 18-45

• Negative pregnancy test at the beginning and at the end of each cycle

• Cycle lengths 24-34 days

• Knowledge of previous 3 cycle lengths

• Able to travel to Calgary Clinic for regular ultrasounds during the study period

Locations
Other Locations
Canada
Thomas Bouchard
RECRUITING
Calgary
Contact Information
Primary
Thomas P Bouchard, MD
thomasbouchard@quantumfertility.com
4036674296
Time Frame
Start Date: 2024-05-01
Estimated Completion Date: 2026-05-01
Participants
Target number of participants: 150
Treatments
Regular cycles
To characterize quantitative hormones in the urine using the Mira monitor, along with other menstrual cycle biomarkers, and validate these in reference to serum hormonal measurements and the gold-standard of the ultrasound-day of ovulation in participants with normal menstrual cycles (cycle length 24-38 days).
Polycystic ovarian syndrome
To identify hormonal and other menstrual cycle biomarker variations in polycystic ovarian syndrome (PCOS) with oligomenorrhea.
Athletes
To identify hormonal and other menstrual cycle biomarker variations in oligomenorrheic athletes.
Sponsors
Leads: Quanovate Tech Inc.
Collaborators: Patricia Doyle-Baker

This content was sourced from clinicaltrials.gov