Clinical trial · Observational
Ovarian Ultrasonography for the Clinical Evaluation of Polycystic Ovary Syndrome
NCT03547453CI-TRIAL-00063888completedClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
The investigators would like to determine how aspects of adiposity and age influence ultrasound features of the ovaries which are used to diagnose polycystic ovarian syndrome (PCOS). The study will also compare anti-Müllerian hormone (AMH) levels against ultrasound features of the ovary to predict PCOS.
Conditions
Conditions (3)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Menstrual Irregularity | — | UNRESOLVED | — |
| Overweight and Obesity | — | UNRESOLVED | — |
| Polycystic Ovary Syndrome (PCOS) | — | UNRESOLVED | — |
Interventions
Interventions (0)
Data not yet available
No intervention recorded.
Design
Arms and outcomes
Arms (2)
- label
- Regular Menstrual Cycles
- description
- Women will be assigned to this category if they report a history of regular menstrual cycles (every 21 to 35 days). Recruitment will be targeted to obtain 20 lean (BMI\<25 kg/m2) and 20 overweight or obese (BMI\>24.9kg/m2) women in each of the following age groups: 18-24y (early), 25-34y (mid), ≥35y (later adulthood).
- label
- Polycystic Ovarian Syndrome
- description
- Women will be assigned to this category if they have clinical or biochemical androgen excess and report a history of irregular menstrual cycles (\<21 days or \>35 days), including women with a pre-existing diagnosis of PCOS. Recruitment will be targeted to obtain 20 lean (BMI\<25kg/m2) and 20 overweight or obese (BMI\>24.9kg/m2) women in each of the following age groups: 18-24y (early), 25-34y (mid), ≥35y (later adulthood).
Primary outcomes (1)
- measure
- Follicle number per ovary
- timeFrame
- 1 day
- description
- The number of follicles in each ovary will be assessed by ultrasonography
Secondary outcomes (12)
Eligibility
Eligibility (as posted)
- Sex
- Female
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Aged \>18 years * At least 2y post-menarche * BMI \>18.5kg/m2 * Good visibility of the ovaries on ultrasound * Pelvic exam with normal results within the last 2 years Either: * Regular menstrual cycles (21-35 days); * Irregular menstrual cycles (\>36 days); or * Previous diagnosis of PCOS from a primary care provider Exclusion Criteria: * Use of medication(s) known or suspected to interfere with reproductive function, metabolism, and/or appetite (e.g., oral contraceptives) within the past 3 months * Use of fertility medications in the past 2 months (e.g., Clomid) * Current use of a non-copper intrauterine device for contraception (e.g., Mirena) * Diagnosis of premature ovarian failure, endometriosis, or another disease/disorder (other than PCOS) known or suspected to interfere with reproductive function * History of ovarian surgery * Missing uterus or an ovary * Pregnant or breastfeeding * Diagnosis of a bleeding disorder * Regular use of blood thinners/anticoagulants * Skin allergy/condition that might be aggravated by alcohol application * Currently being treated for a vaginal infection, cervical infection, sexually transmitted infection, or disease either with antibiotics, antifungals, or anti-viral medication * Abnormal vaginal discharge, pelvic pain, and/or blisters/lesions/warts/skin growths in the genital/anal area, which have not been examined by a medical professional. * Vaginal abnormality (e.g., vaginal atresia/hypoplasia, vaginal septation, Mullerian agenesis, vulvar/vaginal malignancy). * Not otherwise healthy
References
Publications (1)
- DERIVEDEvans AT, Rehani E, Smith B, Hong MD, Lewin Z, Hiroshige K, Spandorfer SD, Hajirasouliha I, Lujan ME, Hoeger KM. Diagnosis of Polycystic Ovary Syndrome With Predictive Modeling of Select Clinical Features. O G Open. 2026 Mar 19;3(2):e161. doi: 10.1097/og9.0000000000000161. eCollection 2026 Apr. PMID 41868592