Optimal diagnosis of polycystic ovary syndrome, natural history, and relationships between diagnostic features and long-term cardiometabolic outcomes

My research focused on improving the diagnosis of polycystic ovary syndrome (PCOS), which is a risk factor for infertility, cardiometabolic and psychological disorders in women. 70% PCOS cases go undetected due to unclear parameter values to differentiate women with PCOS from those without PCOS. I defined normal and abnormal PCOS parameter values in adolescents, and observed values that are lower than the currently used ones. I further established a PCOS dataset from across the world to re-define PCOS diagnosis. Additionally, my research demonstrated that irregular menstrual cycles may predict heart disease and diabetes over 20-years in adult women from Australia.