Fehring, R. J., & Schlaff, W. D. (1998). Accuracy of the Ovulon fertility monitor to predict and detect ovulation. Journal of nurse-midwifery, 43(2), 117-120. https://doi.org/10.1016/s0091-2182(97)00151-1
Fehring RJ, Schlaff WD. Accuracy of the Ovulon fertility monitor to predict and detect ovulation. J Nurse Midwifery. 1998;43(2):117-120. doi:10.1016/s0091-2182(97)00151-1
Fehring, R. J., and W. D. Schlaff. "Accuracy of the Ovulon fertility monitor to predict and detect ovulation." Journal of nurse-midwifery, vol. 43, no. 2, 1998, pp. 117-120.
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The purpose of this pilot study was to correlate the three biologic markers of the Ovulon fertility monitor (a long-term predictive peak about 6 days before ovulation, a short-term predictive peak about 1 day before ovulation, and a nadir at the time of ovulation) with the peak in cervical mucus and the luteinizing hormone (LH) surge in the urine. Ten volunteer subjects (mean age 30.2 years) monitored their cervical-vaginal mucus, the surge of LH in the urine with a home assay test, and their vaginal electrical readings (with Ovulon monitors) on a daily basis for one to four menstrual cycles. In 19 of the 21 cycles that indicated a LH surge, there was a strong positive correlation between the LH surge and the peak of cervical-vaginal mucus (r = 0.96, P < or = .01), and between the LH surge and both the Ovulon nadir and Ovulon short-term predictive peak (r = 0.84, P < or = .01), and a modest positive correlation between the long-term Ovulon predictive peak and the LH surge (r = 0.62, P < or = .01). The time of optimal fertility as determined by the peak in cervical mucus, the LH surge, and the Ovulon was similar. The Ovulon has potential as a reusable device to help women determine their fertile period.
Bouchard TP et al., 2026·Journal of ovarian research·Free to read
Reproductive hormones of the fertile window are often referenced to women in regular cycles, but this may not be representative of the hormonal profiles of women in different circumstances like polycystic ovarian syndrome, the postpartum period, and the perimenopause transition. This observational cohort study sought to identify the variability in the reproductive hormones in various clinical circumstances and to establish potential thresholds for each category based on hormone measurements with the Mira urinary hormone monitor. A total of 57 women (ages 22-51) in various circumstances (regular cycles, polycystic ovarian syndrome, postpartum and perimenopause) tracked Mira urine hormone measurements (estrone-3-glucuronide, luteinizing hormone, pregnanediol glucuronide), contributing 444 cycles of data. Using additive mixed models, hormone values were stratified by the four different reproductive categories. The perimenopause and polycystic ovarian syndrome groups demonstrated relative hypoestrogenic states, while the perimenopause group showed low luteal pregnanediol glucuronide and the polycystic ovarian syndrome/polyendocrine metabolic ovarian syndrome (PCOS/PMOS) group showed high luteal pregnanediol glucuronide. The perimenopause group had significantly higher luteinizing hormone values throughout the whole cycle. The fertile window hormone thresholds vary depending on a woman's specific reproductive category. Women in different circumstances should not necessarily use the same hormonal thresholds for the fertile window and ovulation. A larger dataset with ultrasound correlation to ovulation is required to delineate the fertile window with more precision. Hormone differences across the menstrual cycle could be used for targeted treatments in polycystic ovarian syndrome and perimenopause women.
Malliou-Becher MN et al., 2026·Human reproduction (Oxford, England)
What are the variations in ovulation time and menstrual cycle characteristics among and within various individuals over the course of 12 menstrual cycles? There are considerable variations in both cycle length and ovulation time, with pronounced intra-individual variability over a 12-cycle observation period. Although it is commonly believed that healthy women have regular cycles with a predictable mid-cycle ovulation, more recent research shows a significant variation in cycle length and ovulation time. Previous studies have focused only on cycle length, often excluding cycles outside the 25-35-day range, thus limiting the understanding of natural variation; they have also lacked precise ovulation diagnostics or included small sample sizes, making it difficult to capture the full scope of cycle and ovulation variability. Similarly, a recent big data study, while valuable, was limited by a self-selected group and the absence of accurate ovulation diagnostics, reducing its generalizability. STUDY DESIGN, SIZE, This study was designed as a prospective long-term observational study, which involved collecting data from 1923 women with a total of 43 999 menstrual cycles from January 1985 to July 2019. After fulfilling the inclusion criteria, the main group consisted of 1051 women, all of whom contributed data for 12 cycles (12 612 cycles), including 420 conception cycles. PARTICIPANTS/MATERIALS, SETTING, Participants in the study were between 18 and 44 years of age at study entry and did not take any reproductive hormones. Women who were postpartum, breastfeeding, amenorrheic, or within a 3-month period after stopping hormonal contraception were excluded. Participants agreed to keep cycle records according to the symptothermal method, 'Sensiplan'. Ovulation time was determined using an evidence-based algorithm based on evaluating cervical mucus patterns and basal body temperature shifts, with ovulation time defined as the day before the temperature rise. Data analysis was descriptive, using absolute and relative frequencies, standard deviation, percentiles, and ranges. Age dependency was assessed using unpaired sample t-tests and one-way ANOVA. Linear regression was used to assess long-term trends. MAIN In 62.4% of women, cycle lengths varied by 1 week or more within 12 cycles. Accordingly, the time of ovulation varied by 1 week or more within 12 cycles in 54.8% of women, with 96.5% experiencing fluctuations of 4 days or more over the 12 months. The median spontaneous cycle length was 28 days, with a mean of 29.66 days (SD = 7.55). Only 52.7% of women consistently had cycle lengths between 23 and 35 days across all 12 cycles. Ovulation occurred most frequently between Days 12 and 16, with almost half of conceptions (45.7%) occurring after Day 16. A one-way analysis of variance revealed a significant reduction in mean cycle length with increasing age (P < 0.001), showing the shortest median cycle length of 27 days being in women aged 40-44 years. Age also impacted ovulation time, with women aged 35-39 years showing more stable ovulation patterns compared to younger women. Over the 34-year study period, average cycle length increased slightly but significantly (β = 0.0161, P = 0.0306), corresponding to approximately half a day. Intra-individual variability also showed a slight, but non-significant, upward trend (β = 0.0262, P = 0.2173). LIMITATIONS, Comorbidities such as hyperprolactinemia, obesity, and PCOS were not systematically excluded. However, by including only women with at least 12 cycles, the study largely avoided severe hormonal disorders. This study highlights the considerable individual variation of ovulation time and cycle length over 12 menstrual cycles. These findings contribute to a better understanding of fertility awareness, and highlight the implications for family planning and reproductive health management. STUDY FUNDING/COMPETING INTEREST(S): The authors declare no conflicts of interest. No funding was provided. N/A.
Bouchard TP et al., 2025·Preprints.org·Free to read
Background/Objectives: Quantitative urine monitors are increasingly being used for a personalized approach to improve menstrual cycle knowledge and to manage fertility. Although several studies have evaluated urine fertility monitors in regular cycles, there is limited research in the use of quantitative monitors in reproductive disorders, such as polycystic ovarian syndrome (PCOS). Urine hormone data was collected with the Mira monitor from 20 participants, 10 of whom had PCOS and a matched group who had regular cycles. The main aim of this study was to evaluate the levels of luteinizing hormone (LH), estrone-3-glucuronide (E13G), and pregnanediol glucuronide (PDG) in PCOS menstrual cycles compared to regular cycles. Women with PCOS had higher BMI than regular cycling women (p=0.02). PCOS cycles were longer (p<0.05), peak day was later in the menstrual cycle (p<0.001), and luteal length was shorter (p < 0.01) compared to regular cycles. In whole cycle comparisons, E13G was found to be lower in PCOS cycles (p<0.01) and PDG was found to be higher in PCOS cycles (p<0.05). E13G was also lower in the follicular phase of and late luteal phase of PCOS cycles (p<0.00001). The results of this study demonstrate the feasibility of detecting hormonal differences in PCOS compared to regular cycles with at-home measurements with the Mira monitor. The metabolic dysregulation of PCOS is a possible factor in these hormone changes. Larger studies with different sub-types of PCOS will be needed to further clarify these changes and to understand the pathophysiology behind these hormonal changes.
Manhart MD et al., 2025·Linacre Q·Free full text on PubMed Central
A one-day meeting was held as a pre-conference to the Catholic Medical Association Annual Educational event in 2024. A panel of eighteen physicians, scientists, and researchers involved in NFP work was convened to review the available evidence in four topical areas: (i) evidence for effectiveness of NFP methods to postpone and achieve pregnancy, (ii) evidence for effectiveness in the postpartum and perimenopause transition periods, (iii) evaluate the current state of technology in NFP (specifically app and quantitative hormone monitoring), and (iv) evidence examining the impact of NFP on marital relations. In each topical area, the panel worked to reach a consensus opinion on the currently available evidence and identified priorities for further research. Results from these discussions and a set of priorities for further work are presented here.
An expert panel was convened to review the current evidence supporting use of NFP in various settings, utilization of new technology, and the impact of NFP on marital dynamics. Results from these discussions and a set of priorities for further work are presented here.
The (PD) peak day of cervical mucus is an important biologic marker for the self-determination of the optimal time of fertility in a woman's menstrual cycle. The purpose of this article is to provide evidence (literature and empiric) for the accuracy of the PD of cervical mucus as a biologic marker of peak fertility and the estimated day of ovulation. An analysis of data from four published studies that compared the self-determination of the PD of cervical mucus with the urinary luteinizing hormone (LH) surge was conducted. The four studies yielded 108 menstrual cycle charts from 53 women participants. The 108 cycles ranged in length from 22 to 75 days (mean 29.4 SD 6.0). Ninety-three of the 108 cycles had both an identified PD and LH surge. Data charts showed that 97.8% of the PD fell within +/-4 days of the estimated day of ovulation. Use of a standardized mucus cycle scoring system indicated that the peak in cervical mucus ratings was highest on the day of the LH surge. Self-determination of the PD of cervical mucus is a very accurate means of determining peak fertility and a fairly accurate means of determining the day of ovulation and the beginning of the end of the fertile time.
Mu Q et al., 2023·Medicina (Kaunas)·Free full text on PubMed Central
Background and
Accuracy in detecting ovulation and estimating the fertile window in the menstrual cycle is essential for women to avoid or achieve pregnancy. There has been a rapid growth in fertility apps and home ovulation testing kits in recent years. Nevertheless, there lacks information on how well these apps perform in helping users understand their fertility in the menstrual cycle. This pilot study aimed to evaluate and compare the beginning, peak, and length of the fertile window as determined by a new luteinizing hormone (LH) fertility tracking app with the Clearblue Fertility Monitor (CBFM). A total of 30 women were randomized into either a quantitative Premom or a qualitative Easy@Home (EAH) LH testing system. The results of the two testing systems were compared with the results from the CBFM over three menstrual cycles of use. Potential LH levels for estimating the beginning of the fertile window were calculated along with user acceptability and satisfaction. The estimates of peak fertility by the Premom and EAH LH testing were highly correlated with the CBFM peak results (R = 0.99, p < 0.001). The participants had higher satisfaction and ease-of-use ratings with the CBFM compared to the Premom and EAH LH testing systems. LH 95% confidence levels for estimating the beginning of the fertile window were provided for both the Premom and EAH LH testing results. Our pilot study findings suggest that the Premom and EAH LH fertility testing app can accurately detect impending ovulation for women and are easy to use at home. However, successful utilization of these low-cost LH testing tools and apps for fertility self-monitoring and family planning needs further evaluation with a large and more diverse population.
The purpose of this study was to compare the CUE Ovulation Predictor with the ovulation method in determining the fertile period. Eleven regularly ovulating women measured their salivary and vaginal electrical resistance (ER) with the CUE, observed their cervical-vaginal mucus, and measured their urine for a luteinizing hormone (LH) surge on a daily basis. Data from 21 menstrual cycles showed no statistical difference (T = 0.33, p = 0.63) between the CUE fertile period, which ranged from 5 to 10 days (mean = 6.7 days, SD = 1.6), and the fertile period of the ovulation method, which ranged from 4 to 9 days (mean = 6.5 days, SD = 2.0). The CUE has potential as an adjunctive device in the learning and use of natural family planning methods.
Fehring RJ et al., 2004·Contraception·Free to read
The purpose of this study was to compare the fertile phase of the menstrual cycle as determined by the Clearplan Easy Fertility Monitor (CPEFM) with self-monitoring of cervical mucus. One-hundred women (mean age = 29.4 years) observed their cervical mucus and monitored their urine for estrogen and luteinizing hormone metabolites with the CPEFM on a daily basis for 2-6 cycles and generated 378 cycles of data; of these, 347 (92%) had a CPEFM peak. The beginning of the fertile window was, on average, day 11.8 (SD = 3.4) by the monitor and day 9.9 (SD = 3.0) by cervical mucus (r = 0.43, p < 0.001). The average first day of peak fertility by the monitor was 16.5 (SD = 3.6) and by cervical mucus 16.3 (SD = 3.7) (r = 0.85, p < 0.001). The mean length of the fertile phase by the monitor was 7.7 days (SD = 3.1) and by cervical mucus 10.9 days (SD = 3.7) (t = 12.7, p < 0.001). The peak in fertility as determined by the monitor and by self-assessment of cervical mucus is similar but the monitor tends to underestimate and self-assessment of cervical mucus tends to overestimate the actual fertile phase.
Rick Fehring, Dick Fehring, Rich Fehring, R Fehring
PMID 9581098 9581098 DOI 10.1016/s0091-2182(97)00151-1 10.1016/s0091-2182(97)00151-1 Fehring et al. 1998, Fehring 1998
Cite this article
Fehring, R. J., & Schlaff, W. D. (1998). Accuracy of the Ovulon fertility monitor to predict and detect ovulation. Journal of nurse-midwifery, 43(2), 117-120. https://doi.org/10.1016/s0091-2182(97)00151-1
Fehring RJ, Schlaff WD. Accuracy of the Ovulon fertility monitor to predict and detect ovulation. J Nurse Midwifery. 1998;43(2):117-120. doi:10.1016/s0091-2182(97)00151-1
Fehring, R. J., and W. D. Schlaff. "Accuracy of the Ovulon fertility monitor to predict and detect ovulation." Journal of nurse-midwifery, vol. 43, no. 2, 1998, pp. 117-120.
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