Leiva, R., Burhan, U., Kyrillos, E., Fehring, R., McLaren, R., Dalzell, C., & Tanguay, E. (2014). Use of ovulation predictor kits as adjuncts when using fertility awareness methods (FAMs): a pilot study. Journal of the American Board of Family Medicine : JABFM, 27(3), 427-429. https://doi.org/10.3122/jabfm.2014.03.130255
Leiva R, Burhan U, Kyrillos E, Fehring R, McLaren R, Dalzell C, et al. Use of ovulation predictor kits as adjuncts when using fertility awareness methods (FAMs): a pilot study. J Am Board Fam Med. 2014;27(3):427-429. doi:10.3122/jabfm.2014.03.130255
Leiva, R., et al. "Use of ovulation predictor kits as adjuncts when using fertility awareness methods (FAMs): a pilot study." Journal of the American Board of Family Medicine : JABFM, vol. 27, no. 3, 2014, pp. 427-429.
An LH kit plus FAM found the luteal phase in 23 of 23 cycles
An LH kit added to the fertility awareness method (FAM) found the luteal phase in 23 of 23 cycles. FAM alone found it in 20 of 23. This small crossover pilot followed 23 Canadian women who struggled to spot the infertile phase after ovulation.
Key Findings
The LH kit plus fertility awareness method (FAM) identified the luteal phase in 23 of 23 cycles (proportion 1.00). FAM only did so in 20 of 23 cycles (proportion 0.87).
The absolute difference (LH minus FAM) was 0.13 (95% CI 0.03 to 0.28). The relative risk of FAM versus LH was 0.87 (95% CI 0.72 to 0.97).
Among cycles with an identified luteal phase, the kit arm showed a mean of 10.3 days of infertility and the FAM-only arm showed 10 days. The difference was not statistically significant.
Each of the 23 women supplied 2 cycles, 46 in all. Mean cycle length was 29.3 days, with no significant difference between cycle lengths for each woman.
Interpretation
The pilot used a crossover design: each of 23 women used both approaches, one per cycle, in an order set by enrollment. Participants were all Canadian, mostly white (18), and all had at least a high school education. Six of the 29 women who met the criteria were lost to follow-up. Blood progesterone testing checked whether the luteal phase was identified. The outcome was luteal phase identification, and the study did not address the start of the fertile phase. The authors name breastfeeding, very long cycles without ovulation, extremely short LH surges and premenopause as situations where a kit may fail to confirm.
RRM Context
Fertility awareness methods rely on the body's own signs of ovulation. The authors describe a low-cost urine test as an additional double-check on those signs. They suggest future research combining several urinary hormone markers with signs such as cervical mucus.
Our editorial summary of this paper, not the article's abstract.
Abstract
Purpose
Difficult clinical signs such as confusing cervical mucus or erratic basal body temperature can make the use of fertility awareness methods (FAMs) difficult in some cases. The goal of this study was to assess the feasibility of using a cheap urinary luteinizing hormone (LH)-surge identification kit as an adjunct to identify the infertile phase after ovulation when facing these scenarios.
Methods
The study used a block-allocation, crossover, 2-arm methodology (LH kit/FAM vs FAM only). Comparison of the 2 arms was done with regard to the accuracy of identification (yes/no) of the luteal phase in each cycle as confirmed by serum progesterone concentrations.
Results
We recruited 23 Canadian women currently using FAM, aged 18 to 48 years, who have had menstrual cycles 25 to 35 days long for the past 3 months and perceive themselves to have difficulty with identifying the infertile phase after ovulation. LH kits identified 100% of the luteal phases, whereas FAM indentified 87% (statistically significant). In those identified cycles, LH kits provided a mean of 10.3 days of infertility, and FAM only provided 10 days of infertility (not statistically significant).
Conclusions
Among this population, LH kits may offer an adjunct for women who may wish to have an additional double-check. However, there are still clinical circumstances when even an LH kit does not provide confirmation. More research in this area is encouraged.
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.
Background,Pregnanediol glucuronide (PdG), the principal urinary metabolite of progesterone, can assess luteal progesterone exposure, but interpretation depends on appropriate timing relative to ovulation. We evaluated whether urinary luteinizing hormone (LH)-based reference points could standardize luteal urinary PdG assessment compared with ultrasound-determined ovulation (USDO).,Methods,This retrospective secondary analysis included 216 ovulatory cycles from 95 women from an original cohort of 107 women (326 cycles). Eligible cycles had ultrasound-confirmed ovulation and an LH peak before USDO+3. The retrospectively identified LH peak and first urinary LH concentrations ≥10, ≥15, ≥20, ≥25, and ≥30 mIU/mL were evaluated for timing urinary PdG measurement 6–9 days later, using a prespecified threshold of ≥15 µg/mL. PdG classifications were compared with USDO-timed classifications using area under the receiver operating characteristic curve, sensitivity, specificity, predictive values, and likelihood ratios.,Results,Agreement remained high across assessment days. The LH peak showed the highest overall agreement. Among prospectively applicable strategies, first urinary LH ≥15 mIU/mL provided the best balance between agreement and cycle availability. Positive predictive values were consistently high (98–100%), whereas negative predictive values were modest. No assessment day consistently outperformed the others.,Conclusions,Urinary LH-based timing closely reproduced USDO-guided urinary PdG classification. The LH peak showed the highest agreement, whereas first urinary LH ≥15 mIU/mL was the most practical prospective reference point. PdG ≥15 µg/mL classifications showed near-universal agreement with ultrasound-guided timing. These findings support standardized PdG timing when ultrasound is unavailable but do not establish diagnostic criteria or predict reproductive outcomes.
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.
Fertility awareness based methods (FABMs) can be used to ameliorate the likelihood to conceive. A literature search was performed to evaluate the relationship of cervical mucus monitoring (CMM) and the day-specific -pregnancy rate, in case of subfertility. A MEDLINE search revealed a total of 3331 articles. After excluding articles based on their relevance, 10 studies and were selected. The observed studies demonstrated that the cervical mucus monitoring (CMM) can identify the days with the highest pregnancy rate. According to the literature, the quality of the vaginal discharge correlates well with the cycle-specific probability of pregnancy in normally fertile couples but less in subfertile couples. The results indicate an urgent need for more prospective randomised trials and -prospective cohort studies on CMM in a subfertile population to evaluate the effectiveness of CMM in the subfertile couple.
Leiva R et al., 2019·BMJ Open·Free full text on PubMed Central
Ovulation confirmation is a fundamental component of the evaluation of infertility. To inform the design of a larger clinical trial to determine the effectiveness of a new home-based pregnanediol glucuronide (PDG) urine test to confirm ovulation when compared with the standard of serum progesterone. In this observational prospective cohort study (single group assignment) in an urban setting (stage 1), a convenience sample of 25 women (aged 18-42 years) collected daily first morning urine for luteinisinghormone (LH), PDG and kept a daily record of their cervical mucus for one menstrual cycle. Serum progesterone levels were measured to confirm ovulation. Sensitivity and specificity were used as the main outcome measures. Estimation of number of ultrasound (US)-monitored cycles needed for a future study was done using an exact binomial CI approach. Recruitment over 3 months was achieved (n=28) primarily via natural fertility regulation social groups. With an attrition rate of 22%, specificity of the test was 100% for confirming ovulation. Sensitivity varied depending on whether a peak-fertility mucus day or a positive LH test was observed during the cycle (85%-88%). Fifty per cent of participants found the test results easy to determine. A total of 73 US-monitored cycles would be needed to offer a narrow CI between 95% and 100%. This is first study to clinically evaluate this test when used as adjunct to the fertility awareness methods. While this pilot study was not powered to validate or test efficacy, it helped to provide information on power, recruitment and retention, acceptability of the procedures and ease of its use by the participants. Given this test had a preliminary result of 100% specificity, further research with a larger clinical trial (stage 2) is recommended to both improve this technology and incorporate additional approaches to confirm ovulation. NCT03230084.
Stanford JB et al., 2019·Fertil Steril·Free full text on PubMed Central
To quantify the frequency of use of selected fertility awareness indicators and to assess their influence on fecundability. Web-based prospective cohort study. Not applicable. PATIENT(S): Female pregnancy planners, aged 21-45 years, attempting conception for ≤6 cycles at study entry. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): We ascertained time to pregnancy, in menstrual cycles, with bimonthly questionnaires. We estimated adjusted fecundability ratios (FRs) and confidence intervals (CIs) using proportional probabilities models, controlling for age, income, education, smoking, intercourse frequency, and other lifestyle and reproductive factors. RESULT(S): A total of 5,688 women were analyzed, with a mean age of 29.9 years and mean time trying of 2.1 cycles at baseline; 30% had ever been pregnant. At baseline, 75% were using one or more fertility indicators (counting days or charting menstrual cycles [71%], measuring basal body temperature [BBT, 21%], monitoring cervical fluid [39%], using urine LH tests [32%], or feeling for changes in position of the cervix [12%]). Women using any fertility indicator at baseline had higher subsequent fecundability (adjusted FR 1.25, 95% CI 1.16-1.35) than those not using any fertility indicators. For each individual indicator, adjusted FRs ranged from 1.28-1.36, where 1.00 would indicate no relation with fecundability. The adjusted FR for women using a combination of charting days, cervical fluid, and urine LH was 1.48 (95% CI 1.31-1.67) relative to women using no fertility indicators. CONCLUSION(S): In a North American preconception cohort study, use of fertility indicators indicating the fertile window was common, and was associated with greater fecundability.
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.
Rene Leiva, Elizabeth Tanguay, Ula Burhan, Catherine Dalzell, Richard J Fehring, Edmond Kyrillos
R Leiva, Liz Tanguay, Beth Tanguay, Betsy Tanguay, E Tanguay, U Burhan, Cathy Dalzell, Kate Dalzell, C Dalzell, Rick Fehring, Dick Fehring, Rich Fehring, R Fehring, E Kyrillos
PMID 24808123 24808123 DOI 10.3122/jabfm.2014.03.130255 10.3122/jabfm.2014.03.130255 Leiva et al. 2014, Leiva 2014
Cite this article
Leiva, R., Burhan, U., Kyrillos, E., Fehring, R., McLaren, R., Dalzell, C., & Tanguay, E. (2014). Use of ovulation predictor kits as adjuncts when using fertility awareness methods (FAMs): a pilot study. Journal of the American Board of Family Medicine : JABFM, 27(3), 427-429. https://doi.org/10.3122/jabfm.2014.03.130255
Leiva R, Burhan U, Kyrillos E, Fehring R, McLaren R, Dalzell C, et al. Use of ovulation predictor kits as adjuncts when using fertility awareness methods (FAMs): a pilot study. J Am Board Fam Med. 2014;27(3):427-429. doi:10.3122/jabfm.2014.03.130255
Leiva, R., et al. "Use of ovulation predictor kits as adjuncts when using fertility awareness methods (FAMs): a pilot study." Journal of the American Board of Family Medicine : JABFM, vol. 27, no. 3, 2014, pp. 427-429.
