ArticleFrontiers in medicine2026
Menstrual cycle patterns in primary care: a structured approach using primary ovarian insufficiency as a sentinel condition.
Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Primary Ovarian Insufficiency, a condition characterized by early loss of ovarian function, illustrates the consequences of failing to act on menstrual cycle changes as early clinical signals. Menstrual disturbance is often the first presenting feature, yet diagnosis is frequently delayed despite repeated clinical encounters. For primary care clinicians, a disrupted menstrual pattern in an adolescent or young adult should prompt consideration of whether Primary Ovarian Insufficiency could be present in an early stage. This Perspective presents a structured approach to interpreting menstrual cycle patterns, an increasingly recognized vital sign, as actionable clinical signals in primary care. Using Primary Ovarian Insufficiency as a sentinel condition, menstrual changes are framed as prompts for timely decisions to evaluate, refer, or follow, based on pattern, persistence, progression, and associated clinical features. This approach integrates standard diagnostic pathways with contextual clinical information, including metabolic status, stress physiology, and environmental exposures, without adding to the burden of routine care. Extending beyond Primary Ovarian Insufficiency, the framework applies across the lifespan, including midlife hormonal transition, where menstrual changes similarly reflect underlying physiological change and are often under-interpreted. Making explicit how menstrual patterns inform clinical decision-making supports earlier recognition of change, more consistent triage, and improved alignment between patient presentation and clinical response. Strengthening the interpretation of menstrual cycle patterns in primary care, particularly within longitudinal, continuous care relationships, offers a practical opportunity to improve the timing and quality of care by leveraging information already present in routine clinical encounters.
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