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欧若手环作为排卵检测工具:验证分析

Oura Ring as a Tool for Ovulation Detection: Validation Analysis.

作者信息

Thigpen Nina, Patel Shyamal, Zhang Xi

机构信息

Oura Ring, San Francisco, CA, United States.

出版信息

J Med Internet Res. 2025 Jan 31;27:e60667. doi: 10.2196/60667.

DOI:10.2196/60667
PMID:39889300
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11829181/
Abstract

BACKGROUND

Oura Ring is a wearable device that estimates ovulation dates using physiology data recorded from the finger. Estimating the ovulation date can aid fertility management for conception or nonhormonal contraception and provides insights into follicular and luteal phase lengths. Across the reproductive lifespan, changes in these phase lengths can serve as a biomarker for reproductive health.

OBJECTIVE

We assessed the strengths, weaknesses, and limitations of using physiology from the Oura Ring to estimate the ovulation date. We compared performance across cycle length, cycle variability, and participant age. In each subgroup, we compared the algorithm's performance with the traditional calendar method, which estimates the ovulation date based on an individual's last period start date and average menstrual cycle length.

METHODS

The study sample contained 1155 ovulatory menstrual cycles from 964 participants recruited from the Oura Ring commercial database. Ovulation prediction kits served as a benchmark to evaluate the performance. The Fisher test was used to determine an odds ratio to assess if ovulation detection rate significantly differed between methods or subgroups. The Mann-Whitney U test was used to determine if the accuracy of the estimated ovulation date differed between the estimated and reference ovulation dates.

RESULTS

The physiology method detected 1113 (96.4%) of 1155 ovulations with an average error of 1.26 days, which was significantly lower (U=904942.0, P<.001) than the calendar method's average error of 3.44 days. The physiology method had significantly better accuracy across all cycle lengths, cycle variability groups, and age groups compared with the calendar method (P<.001). The physiology method detected fewer ovulations in short cycles (odds ratio 3.56, 95% CI 1.65-8.06; P=.008) but did not differ between typical and long or abnormally long cycles. Abnormally long cycle lengths were associated with decreased accuracy (U=22,383, P=.03), with a mean absolute error of 1.7 (SEM .09) days compared with 1.18 (SEM .02) days. The physiology method was not associated with differences in accuracy across age or typical cycle variability, while the calendar method performed significantly worse in participants with irregular cycles (U=21,643, P<.001).

CONCLUSIONS

The physiology method demonstrated superior accuracy over the calendar method, with approximately 3-fold improvement. Calendar-based fertility tracking could be used as a backup in cases of insufficient physiology data but should be used with caution, particularly for individuals with irregular menstrual cycles. Our analyses suggest the physiology method can reliably estimate ovulation dates for adults aged 18-52 years, across a variety of cycle lengths, and in users with regular or irregular cycles. This method may be used as a tool to improve fertile window estimation, which can aid in conceiving or preventing pregnancies. This method also offers a low-effort solution for follicular and luteal phase length tracking, which are key biomarkers for reproductive health.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec89/11829181/2f4b85e6d8ec/jmir_v27i1e60667_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec89/11829181/c1fee7a0fe8d/jmir_v27i1e60667_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec89/11829181/2f4b85e6d8ec/jmir_v27i1e60667_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec89/11829181/c1fee7a0fe8d/jmir_v27i1e60667_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec89/11829181/2f4b85e6d8ec/jmir_v27i1e60667_fig2.jpg
摘要

背景

欧若环(Oura Ring)是一种可穿戴设备,它利用从手指记录的生理数据来估算排卵日期。估算排卵日期有助于进行生育管理以实现受孕或采用非激素避孕方法,还能深入了解卵泡期和黄体期的时长。在整个生殖寿命中,这些阶段时长的变化可作为生殖健康的生物标志物。

目的

我们评估了使用欧若环的生理数据估算排卵日期的优点、缺点和局限性。我们比较了不同周期长度、周期变异性和参与者年龄的性能。在每个亚组中,我们将该算法的性能与传统日历法进行了比较,传统日历法根据个人上次月经开始日期和平均月经周期长度来估算排卵日期。

方法

研究样本包括从欧若环商业数据库招募的964名参与者的1155个排卵性月经周期。排卵预测试剂盒用作评估性能的基准。使用费舍尔检验确定优势比,以评估不同方法或亚组之间的排卵检测率是否存在显著差异。使用曼 - 惠特尼U检验确定估算的排卵日期与参考排卵日期之间的估算排卵日期准确性是否存在差异。

结果

生理数据法检测到了1155次排卵中的1113次(96.4%),平均误差为1.26天,这显著低于(U = 904942.0,P <.001)日历法的平均误差3.44天。与日历法相比,生理数据法在所有周期长度、周期变异性组和年龄组中的准确性均显著更高(P <.001)。生理数据法在短周期中检测到的排卵较少(优势比3.56,95%置信区间1.65 - 8.06;P =.008),但在典型周期与长周期或异常长周期之间没有差异。异常长的周期长度与准确性降低相关(U = 22383,P =.03),平均绝对误差为1.7(标准误0.09)天,而相比之下为1.18(标准误0.02)天。生理数据法与年龄或典型周期变异性的准确性差异无关,而日历法在周期不规律的参与者中表现明显更差(U = 21643,P <.001)。

结论

生理数据法的准确性优于日历法,提高了约3倍。在生理数据不足的情况下,基于日历的生育追踪可作为备用方法,但应谨慎使用,特别是对于月经周期不规律的个体。我们的分析表明,生理数据法可以可靠地估算18至52岁成年人在各种周期长度以及周期规律或不规律的用户中的排卵日期。该方法可作为一种工具来改善易受孕窗口的估算,有助于受孕或预防怀孕。该方法还为卵泡期和黄体期时长追踪提供了一种省力的解决方案,而卵泡期和黄体期时长是生殖健康的关键生物标志物。

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2
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Contracept X. 2023 Nov 28;5:100103. doi: 10.1016/j.conx.2023.100103. eCollection 2023.
3
The Impact of Irregular Menstruation on Health: A Review of the Literature.
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Cureus. 2023 Nov 20;15(11):e49146. doi: 10.7759/cureus.49146. eCollection 2023 Nov.
4
Interrogating the pill: Rising distrust and the reshaping of health risk perceptions in the social media age.质疑药丸:社交媒体时代不断上升的不信任和健康风险认知的重塑。
Soc Sci Med. 2023 Aug;331:116081. doi: 10.1016/j.socscimed.2023.116081. Epub 2023 Jul 7.
5
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6
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7
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9
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Reasons for rejecting hormonal contraception in Western countries: A systematic review.拒绝使用激素避孕的西方国家原因:系统评价。
Soc Sci Med. 2021 Sep;284:114247. doi: 10.1016/j.socscimed.2021.114247. Epub 2021 Jul 20.