ArticleHuman reproduction open2023
Predicting serum hormone concentration by estimation of urinary hormones through a home-use device.
Article in Human reproduction open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- Association of daily perceived stress with fertility outcomes in natural and controlled ovarian stimulation cycles: a feasibility study.Journal of assisted reproduction and genetics · 2026Article
- Analysis of factors that increase serum progesterone levels on the day of hCG administration in gonadotropin-releasing hormone antagonist cycles.Frontiers in endocrinology · 2026Article
- Validating At-Home Urinary Hormone Measurements in Postpartum and Perimenopause Fertility Transitions.Women's health reports (New Rochelle, N.Y.) · 2025Article
- Comparison of Day-Specific Serum LH, Estradiol, and Progesterone with MiraMedicina (Kaunas, Lithuania) · 2024Article
- Current Ovulation and Luteal Phase Tracking Methods and Technologies for Fertility and Family Planning: A Review.Seminars in reproductive medicine · 2024Review
- Survey Analysis of Quantitative and Qualitative Menstrual Cycle Tracking Technologies.Medicina (Kaunas, Lithuania) · 2023Article
- Validation of urinary reproductive hormone measurements using a novel smartphone connected reader.Scientific reports · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
study questionCan a home-use device be used to predict serum hormone levels? SUMMARY ANSWER: A home-use device can predict urinary hormone values which are well-correlated to serum concentrations of respective hormones and hence can be used as a proxy for serum measurements. WHAT IS KNOWN ALREADY: Home-use devices that predict ovulation are calibrated against the actual day of ovulation. However, the correlation of any quantitative system to serum hormone concentrations has not been established. STUDY DESIGN SIZE DURATION: A total of 73 data points obtained from 20 participants across different phases of the menstrual cycle, i.e. bleeding days, follicular phase and luteal phase were used to establish the correlation between serum hormones and urinary metabolite values. Single data points from 20 random users were used to assess the correlation established. PARTICIPANTS/MATERIALS SETTING
methodsParticipants were women in the fertile age groups and only current users of the home-use device. Selection was done based on inclusion and exclusion criteria. Blood hormones were tested using chemiluminescent immunoassays and urinary measurements were taken on the home-use device at home. MAIN RESULTS AND THE ROLE OF CHANCE: Serum estradiol (E2), progesterone (P4) and LH were correlated with urinary estrone-3-glucuronide (E3G), pregnanediol glucuronide (PdG) and LH with an LIMITATIONS REASONS FOR CAUTION: The study was designed to include women who have normal cycle lengths regularly; therefore, the values obtained were in the normal range. Certain infertility conditions may cause the values to be higher and correlation in such cases needs to be established. WIDER IMPLICATIONS OF THE
findingsThe results of this study imply a new tool that can be used by fertility specialists as a proxy for blood tests whenever required. Extended study on this system can enable its use in assisted reproductive techniques as well. STUDY FUNDING/COMPETING INTERESTS: No funding was received for this study. S.P. and D.D. are employees of the research and development division of Samplytics Technologies Pvt. Ltd. which is a forwarder for Inito Inc., USA. A.R. and V.A.V. are co-founders of Inito Inc., USA. TRIAL REGISTRATION NUMBER: The trial was registered at the International Standard Randomised Controlled Trial Number (ISRCTN) registry (Identifier: ISRCTN15534557).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.