Updated Clinical Consensus and Measurement Gaps in Self-Monitoring Fertility Tracking Technologies for Polyendocrine Metabolic Ovarian Syndrome.

Self-monitoring fertility tracking technologies are widely used by women with polyendocrine metabolic ovarian syndrome (PMOS; until recently referred to as polycystic ovary syndrome) to track menstrual cycles and guide conception planning. However, the performance of these tools remains unclear. Most self-monitoring fertility technologies rely on single-domain physiologic signals and predictive algorithms developed in populations with regular ovulatory cycles, which limits their applicability in the setting of ovulatory dysfunction, endocrine variability, and metabolic heterogeneity characteristic of PMOS. In this column, I describe commonly used self-monitoring fertility tracking technologies and the physiologic signals they capture. I summarize available evidence on their accuracy in predicting ovulation among women with PMOS and examine differences between self-monitoring approaches and clinical fertility monitoring. Finally, I discuss implications for clinicians in ambulatory care settings, including interpretation of patient-generated fertility data, communication strategies, and gaps in current evidence guiding use of these technologies in populations with irregular menstrual cycles and endocrine dysfunction.