The goal of this observational study is to learn about the causal architecture of Polycystic Ovary Syndrome (PCOS) in women aged 18 to 45. The main questions it aims to answer are:
What does the hormonal, metabolic, and clinical architecture of PCOS look like across a diverse global population? Can the causal architecture of PCOS be reconstructed from existing lab results and clinical data? Are there distinct architectural patterns across different groups of women with PCOS? Participants who have been diagnosed with PCOS by a healthcare provider will complete an online questionnaire about their diagnosis, symptoms, clinical history, current treatment, and existing lab results. Participants will also be asked to submit copies of their most recent blood work and lab results. No intervention or treatment is involved. All data is de-identified.
Female
Aged 18 to 45 years
Diagnosed with Polycystic Ovary Syndrome (PCOS) by a licensed healthcare provider
Willing to voluntarily share existing lab results and clinical history
Under 18 years of age
Over 45 years of age
No confirmed PCOS diagnosis from a licensed healthcare provider
Unable or unwilling to provide informed consent
Women aged 18 to 45 who have been diagnosed with Polycystic Ovary Syndrome (PCOS) by a licensed healthcare provider. Participants are recruited globally with no geographic restriction. All participants must have a confirmed diagnosis and be willing to voluntarily submit existing lab results and clinical history.
Case-only
Cross-sectional
No intervention - observational data collection only
Other interventionThis is an observational study. No intervention or treatment is administered. Participants submit existing lab results and clinical history through an online questionnaire.
Computational Reconstruction of the Causal Architecture of PCOS
Reconstruction of the hormonal, metabolic, and clinical architecture of Polycystic Ovary Syndrome across the study cohort using computational analysis of participant-submitted lab results and clinical data.
Identification of Architectural Patterns Across PCOS Cohort
Identification and characterization of distinct architectural patterns across participant cohorts based on hormonal, metabolic, thyroid, lipid, and inflammatory marker profiles.
Assessment of Current Treatment Approaches Relative to Causal Architecture
Evaluation of the relationship between participants' current treatment approaches and the underlying causal architecture identified through computational reconstruction.
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