Polycystic Ovary Syndrome Clinical Trial
Official title:
An Evidence-Based Novel Subtypes of Polycystic Ovary Syndrome and Their Association With Outcomes: a Large Cohort Study
To classify subtypes of Polycystic Ovary Syndrome (PCOS) using machine-learning algorithms, and compare the reproductive and metabolic characteristics and IVF outcomes across these identified subtypes.
In this study, we've developed a machine-learning model to classify PCOS patients into four subtypes based on nine clinical characteristics. The goal of this observational study is to: - Learn about different PCOS subtypes using our classification model. - Compare the reproductive and metabolic features of these subtypes. - Assess the outcomes of IVF among different PCOS subtypes. - Prospective 6.5-year follow-up data will be collected. Participants will: - Undergo a telephone interview to gather details on: 1. Current physical stats like height and weight. 2. Reproductive history, including pregnancies and childbirths in recent years. 3. Details about any IVF treatments. 4. Current status of conditions such as PCOS, Type 2 Diabetes, hypertension, and dyslipidemia. - Be invited for a physical examination that includes: 1. Measurements such as height, weight, blood pressure, and body circumferences. 2. Laboratory tests for endocrine and metabolic conditions. 3. Ultrasound scans of the ovaries and liver. ;
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