Oova, Inc., 335 Madison Avenue, New York, NY 10017, USA.
Department of Obstetrics and Gynecology, Drexel University College of Medicine, Philadelphia, PA 19129, USA.
Medicina (Kaunas). 2023 Jul 23;59(7):1348. doi: 10.3390/medicina59071348.
: Menstrual cycle tracking is essential for reproductive health and overall well-being. However, there is still an over-reliance on estimations that standard cycles are 28 days long, divided evenly between the follicular and luteal phases. Due to the variability of cycle length and cycle phase lengths, common methods of identifying where an individual is in their cycle are often inaccurate. This study used daily hormone monitoring obtained through a remote hormone-monitoring platform to evaluate hormone levels across a menstrual cycle to identify nuances in the follicular and luteal phases in individuals of different age groups. : This study used a remote fertility testing system that quantitatively tracks luteinizing hormone (LH) and pregnanediol-3-glucuronide (PdG) through urine tests read by an AI-powered smartphone app. The study analyzed cycle data from 1233 users with a total of 4123 evaluated cycles. Daily levels for LH and PdG were monitored across multiple cycles. : This study determined that calculated cycle lengths tended to be shorter than user-reported cycle lengths. Significant differences were observed in cycle phase lengths between age groups, indicating that follicular phase length declines with age while luteal phase length increases. Finally, the study found that if an individual's age, first cycle day, and current hormone levels are known, population-level hormone data can be used to pinpoint which cycle phase and cycle day they are in with 95% confidence. : At-home hormone monitoring technologies can allow patients and clinicians to track their cycles with greater precision than when relying on textbook estimations. The study's findings have implications for fertility planning, clinical management, and general health monitoring. Prior to this study, no standard existed for pinpointing where a person was in their cycle through only one measure of LH and PdG. These findings have the potential to fill significant gaps within reproductive healthcare and beyond.
: 月经周期跟踪对于生殖健康和整体健康至关重要。然而，人们仍然过于依赖标准周期为 28 天且滤泡期和黄体期平均分配的估计值。由于周期长度和周期阶段长度的可变性，确定个体所处周期阶段的常用方法往往不够准确。本研究使用通过远程激素监测平台获得的日常激素监测来评估整个月经周期中的激素水平，以识别不同年龄组个体滤泡期和黄体期的细微差别。 : 本研究使用了一种远程生育测试系统，该系统通过尿液测试定量跟踪黄体生成素 (LH) 和孕烷二醇-3-葡糖苷酸 (PdG)，并由人工智能智能手机应用程序读取。该研究分析了来自 1233 名用户的 4123 个评估周期的周期数据。在多个周期中监测 LH 和 PdG 的日常水平。 : 本研究发现，计算出的周期长度往往比用户报告的周期长度短。年龄组之间观察到周期阶段长度的显著差异，表明滤泡期长度随年龄增长而下降，而黄体期长度增加。最后，研究发现，如果个体的年龄、第一个周期日和当前激素水平已知，那么可以使用人群水平的激素数据，以 95%的置信度准确确定他们所处的周期阶段和周期日。 : 家庭激素监测技术可以让患者和临床医生比依赖教科书估计更精确地跟踪他们的周期。该研究的结果对生育计划、临床管理和一般健康监测都有影响。在本研究之前，没有标准可以通过仅测量 LH 和 PdG 来确定一个人在其周期中的位置。这些发现有可能填补生殖保健乃至更广泛领域的重大空白。
