Basal body temperature assessment: is it useful to couples seeking pregnancy?

Novel Methodology for Identifying the Occurrence of Ovulation by Estimating Core Body Temperature During Sleeping: Validity and Effectiveness Study

BACKGROUND

Body temperature is the most-used noninvasive biomarker to determine menstrual cycle and ovulation. However, issues related to its low accuracy are still under discussion.

OBJECTIVE

This study aimed to improve the accuracy of identifying the presence or absence of ovulation within a menstrual cycle. We investigated whether core body temperature (CBT) estimation can improve the accuracy of temperature biphasic shift discrimination in the menstrual cycle. The study consisted of 2 parts: experiment 1 assessed the validity of the CBT estimation method, while experiment 2 focused on the effectiveness of the method in discriminating biphasic temperature shifts.

METHODS

In experiment 1, healthy women aged between 18 and 40 years had their true CBT measured using an ingestible thermometer and their CBT estimated from skin temperature and ambient temperature measured during sleep in both the follicular and luteal phases of their menstrual cycles. This study analyzed the differences between these 2 measurements, the variations in temperature between the 2 phases, and the repeated measures correlation between the true and estimated CBT. Experiment 2 followed a similar methodology, but focused on evaluating the diagnostic accuracy of these 2 temperature measurement approaches (estimated CBT and traditional oral basal body temperature [BBT]) for identifying ovulatory cycles. This was performed using urine luteinizing hormone (LH) as the reference standard. Menstrual cycles were categorized based on the results of the LH tests, and a temperature shift was identified using a specific criterion called the "three-over-six rule." This rule and the nested design of the study facilitated the assessment of diagnostic measures, such as sensitivity and specificity.

RESULTS

The main findings showed that CBT estimated from skin temperature and ambient temperature during sleep was consistently lower than directly measured CBT in both the follicular and luteal phases of the menstrual cycle. Despite this, the pattern of temperature variation between these phases was comparable for both the estimated and true CBT measurements, suggesting that the estimated CBT accurately reflected the cyclical variations in the true CBT. Significantly, the CBT estimation method showed higher sensitivity and specificity for detecting the occurrence of ovulation than traditional oral BBT measurements, highlighting its potential as an effective tool for reproductive health monitoring. The current method for estimating the CBT provides a practical and noninvasive method for monitoring CBT, which is essential for identifying biphasic shifts in the BBT throughout the menstrual cycle.

CONCLUSIONS

This study demonstrated that the estimated CBT derived from skin temperature and ambient temperature during sleep accurately captures variations in true CBT and is more accurate in determining the presence or absence of ovulation than traditional oral BBT measurements. This method holds promise for improving reproductive health monitoring and understanding of menstrual cycle dynamics.

The effectiveness of cervical mucus electrical impedance compared to basal body temperature to determine fertility window

BACKGROUND

Serial serum hormone measurements and transvaginal ultrasound are reliable measures to predict ovulation. These measures are inconvenient and expensive therefore, basal body temperature charting (BBT) and urine ovulation predictor kits (OPK) for luteinizing hormone are often used to determine the 6-day fertile window. However, BBT does not clearly change until 1-2 days after ovulation. Additionally, while OPK can indicate positivity prior to ovulation, false readings are common. A novel alternative approach involves measuring electrolyte trends in cervical mucus using electrical impedance spectroscopy. Cervical mucus electrolyte measurements are associated with hormone level changes during the menstrual cycle. The purpose of this study was to compare the effectiveness of cervical mucus electrical impedance and basal body temperature. We sought to determine if cervical mucus electrolyte measurements provided improved detection of the ovulation day and therefore, improve fertility timing for women.

METHODS

14 healthy women between 18 and 44 years of age with normal menstrual cycles were enrolled in the Observational Study. Participants measured BBT and cervical mucus electrical impedance daily for 3 menstrual cycles using Kegg (Lady Technologies Inc. San Francisco, California, USA). Ovulation date for each cycle was confirmed by measuring hormone levels in urine and serum, and by vaginal ultrasound.

RESULTS

Electrical impedance was significantly different between the follicular phase versus ovulatory date (p = 0.007) and between the luteal phase versus the ovulatory date (p = 0.007). A significant difference in the rate of change of cervical impedance measurements in the pre-ovulatory follicular phase was found compared to BBT (p = 0.0225). The sensitivity (+ 7.14%), specificity (+ 20.35%), and accuracy (+ 17.59) to determine the 1-day fertility window was significantly higher using cervical mucus impedance compared to BBT.

CONCLUSIONS

BBT is considered unreliable for evaluating ovulatory function. Cervical mucus electrical impedance offers a novel measure of electrolyte changes associated with hormone levels. We report that pre-ovulatory electrical impedance patterns demonstrated higher sensitivity, specificity, and accuracy for determining the fertility window when compared to BBT. These findings suggest that changes in electrical impedance may provide an accurate method for predicting ovulation and for measuring ovulatory function.

Knee Laxities Changes with Sex-steroids throughout the Menstrual Cycle Phases in Athlete and Non-athlete Females

Objective:  Our study investigated changes of knee laxities in athletes and non-athletes females and relationship between knee laxity and sex-steroid at menstrual cycle phases. Methods:  Forty six healthy females, twenty four athletes and twenty two non-athletes not on hormone contraceptive pills, had no previous knee injuries and with regular menstrual cycles for 3 consecutive months, participated in the study. Medial and lateral knee laxities were determined by varus-valgus tests at follicular, ovulatory and luteal phases. Serum level of relaxin, estrogen, progesterone and testosterone were determined by ELISA and radioimmunoassay. Results:  Knee laxities in athletes and non-athletes at 0° and 20° flexion were the highest in luteal phase with non-athletes possess greater laxity than athletes. Positive correlation between progesterone and relaxin levels with knee laxities were observed. Meanwhile, the levels of both hormones were highest in the luteal phase. Conclusion:  Increased medial and lateral knee laxities in athletes and non-athletes associated with high serum progesterone and relaxin levels in luteal phase may contribute toward increased risk of non-contact knee injury. However, lower knee laxity in athletes than non-athletes suggest that exercise could be a protective factor.

Establishing a Gold Standard for Quantitative Menstrual Cycle Monitoring

Background and Objectives: The Quantum Menstrual Health Monitoring Study will measure four key reproductive hormones in the urine (follicle-stimulating hormone, FSH; estrone-3-glucuronide, E13G; luteinizing hormone, LH; and pregnanediol glucuronide, PDG) to characterize patterns that predict and confirm ovulation, referenced to serum hormones and the gold standard of the ultrasound day of ovulation in participants with regular cycles. These normal cycles will provide a reference for comparison to irregular cycles in subjects with polycystic ovarian syndrome (PCOS) and athletes. Materials and Methods: Participants will track their menstrual cycles for 3 months and be provided with an at-home urine hormone monitor (Mira monitor) to predict ovulation. The day of ovulation will be confirmed with serial ultrasounds completed in a community clinic. Urine results will be compared to serum hormone values. Other markers of menstrual health, such as bleeding patterns and temperature changes, will be determined using a customized app. Three groups will be recruited. Group 1 will include those with consistent regular cycle lengths (between 24-38 days), and will be compared to two groups with irregular cycle lengths (with increased cycle length variability and longer cycles). Group 2 will include those with polycystic ovarian syndrome (PCOS) with irregular cycles and Group 3 will include individuals participating in high levels of exercise with irregular cycles. Hypothesis: The Mira monitor quantitative urine hormone pattern will accurately correlate with serum hormonal levels and will predict (with LH) and confirm (with PDG) the ultrasound day of ovulation in those with regular cycles as well as those with irregular cycles. Rationale: Once the ultrasound validation is complete, tools like the Mira monitor with a customized app may become a new standard for at-home and remote clinical monitoring of the menstrual cycle without having to use labor-intensive follicular-tracking ultrasound or follow serum hormone changes. Conclusions: Precision monitoring of the menstrual cycle is expected to impact individuals who want to increase their menstrual health literacy and guide decisions about fertility.

Changes in Heart Rate, Heart Rate Variability, Breathing Rate, and Skin Temperature throughout Pregnancy and the Impact of Emotions-A Longitudinal Evaluation Using a Sensor Bracelet

(1) Background: Basic vital signs change during normal pregnancy as they reflect the adaptation of maternal physiology. Electronic wearables like fitness bracelets have the potential to provide vital signs continuously in the home environment of pregnant women. (2) Methods: We performed a prospective observational study from November 2019 to November 2020 including healthy pregnant women, who recorded their wrist skin temperature, heart rate, heart rate variability, and breathing rate using an electronic wearable. In addition, eight emotions were assessed weekly using five-point Likert scales. Descriptive statistics and a multivariate model were applied to correlate the physiological parameters with maternal emotions. (3) Results: We analyzed data from 23 women using the electronic wearable during pregnancy. We calculated standard curves for each physiological parameter, which partially differed from the literature. We showed a significant association of several emotions like feeling stressed, tired, or happy with the course of physiological parameters. (4) Conclusions: Our data indicate that electronic wearables are helpful for closely observing vital signs in pregnancy and to establish modern curves for the physiological course of these parameters. In addition to physiological adaptation mechanisms and pregnancy disorders, emotions have the potential to influence the course of physiological parameters in pregnancy.

Effectiveness of a Postpartum Breastfeeding Protocol for Avoiding Pregnancy

The uses of cervical mucus and basal body temperature as indicators of return to fertility postpartum have resulted in high unintended pregnancy rates. In 2013, a study found that when women used urine hormone signs in a postpartum/breastfeeding protocol this resulted in fewer pregnancies. To improve the original protocol's effectiveness, three revisions were made: (1) women were to increase the number of days tested with the Clearblue Fertility Monitor, (2) an optional second luteinizing hormone test could be done in the evening, and (3) instructions were given to manage the beginning of the fertile window for the first six cycles postpartum. The purpose of this study was to determine the correct and typical use effectiveness rates to avoid pregnancy in women who used a revised postpartum/breastfeeding protocol. A cohort review of an established data set from 207 postpartum breastfeeding women who used the protocol to avoid pregnancy was completed using Kaplan-Meier survival analysis. Total pregnancy rates that included correct and incorrect use pregnancies were eighteen per one hundred women over twelve cycles of use. For the pregnancies that met a priori criteria, the correct use pregnancy rates were two per one hundred over twelve months and twelve cycles of use and typical use rates were four per one hundred women at twelve cycles of use. The protocol had fewer unplanned pregnancies than the original, however, the cost of the method increased.

Exploring relationships between autistic traits and body temperature, circadian rhythms, and age

The number of clinical diagnoses of autism spectrum disorder (ASD) is increasing annually. Interestingly, the human body temperature has also been reported to gradually decrease over the decades. An imbalance in the activation of the excitatory and inhibitory neurons is assumed to be involved in the pathogenesis of ASD. Neurophysiological evidence showed that brain activity decreases as cortical temperature increases, suggesting that an increase in brain temperature enhances the inhibitory neural mechanisms. Behavioral characteristics specific to clinical ASD were observed to be moderated when people with the diagnoses had a fever. To explore the possible relationship between ASD and body temperature in the general population, we conducted a survey study using a large population-based sample (N ~ 2000, in the age groups 20s to 70s). Through two surveys, multiple regression analyses did not show significant relationships between axillary temperatures and autistic traits measured by questionnaires (Autism Spectrum (AQ) and Empathy/Systemizing Quotients), controlling for covariates of age and self-reported circadian rhythms. Conversely, we consistently observed a negative relationship between AQ and age. People with higher AQ scores tended to have stronger eveningness. Our findings contribute to the understanding of age-related malleability and the irregularity of circadian rhythms related to autistic traits.

Current evidence shows no influence of women's menstrual cycle phase on acute strength performance or adaptations to resistance exercise training

Introduction

The bias towards excluding women from exercise science research is often due to the assumption that cyclical fluctuations in reproductive hormones influence resistance exercise performance and exercise-induced adaptations.

Methods

Hence, the purpose of this umbrella review was to examine and critically evaluate the evidence from meta-analyses and systematic reviews on the influence of menstrual cycle phase on acute performance and chronic adaptations to resistance exercise training (RET).

Results

We observed highly variable findings among the published reviews on the ostensible effects of female sex hormones on relevant RET-induced outcomes, including strength, exercise performance, and hypertrophy.

Discussion

We highlight the importance of comprehensive menstrual cycle verification methods, as we noted a pattern of poor and inconsistent methodological practices in the literature. In our opinion, it is premature to conclude that short-term fluctuations in reproductive hormones appreciably influence acute exercise performance or longer-term strength or hypertrophic adaptations to RET.

Confirmation of human ovulation in assisted reproduction using an adhesive axillary thermometer (femSense®)

Objective

Timing for sexual intercourse is important in achieving pregnancy in natural menstrual cycles. Different methods of detecting the fertile window have been invented, among them luteinization hormone (LH) to predict ovulation and biphasic body basal temperature (BBT) to confirm ovulation retrospectively. The gold standard to detect ovulation in gynecology practice remains transvaginal ultrasonography in combination with serum progesterone. In this study we evaluated a wearable temperature sensing patch (femSense®) using continuous body temperature measurement to confirm ovulation and determine the end of the fertile window.

Methods

96 participants received the femSense® system consisting of an adhesive axillary thermometer patch and a smartphone application, where patients were asked to document information about their previous 3 cycles. Based on the participants data, the app predicted the cycle length and the estimated day of ovulation. From these predictions, the most probable fertile window and the day for applying the patch were derived. Participants applied and activated the femSense® patch on the calculated date, from which the patch continuously recorded their body temperature throughout a period of up to 7 days to confirm ovulation. Patients documented their daily urinary LH test positivity, and a transvaginal ultrasound was performed on day cycle day 7, 10, 12 and 14/15 to investigate the growth of one dominant follicle. If a follicle reached 15 mm in diameter, an ultrasound examination was carried out every day consecutively until ovulation. On the day ovulation was detected, serum progesterone was measured to confirm the results of the ultrasound. The performance of femSense® was evaluated by comparing the day of ovulation confirmation with the results of ovulation prediction (LH test) and detection (transvaginal ultrasound).

Results

The femSense® system confirmed ovulation occurrence in 60 cases (81.1%) compared to 48 predicted cases (64.9%) with the LH test (p = 0.041). Subgroup analysis revealed a positive trend for the femSense® system of specific ovulation confirmation within the fertile window of 24 h after ovulation in 42 of 74 cases (56.8%). Cycle length, therapy method or infertility reason of the patient did not influence accuracy of the femSense® system.

Conclusions

The femSense® system poses a promising alternative to the traditional BBT method and is a valuable surrogate marker to transvaginal ultrasound for confirmation of ovulation.

Training, Wellbeing and Recovery Load Monitoring in Female Youth Athletes

Participation in youth sports is ever-increasing, along with training and competition demands placed upon youth athletes. Young athletes may experience high training loads due to playing several sports, as well as participating in school physical education. Therefore, monitoring youth athlete load is an emerging area of research that may help limit non-functional overreaching, injury, or illness and assist with long-term athlete development. This narrative review highlights that multiple measures have been explored to monitor both internal and external load. However, the validity, reliability and practicality of these measures are often not fully understood in female youth populations. The most commonly used external monitoring methods are GPS tracking and TRIMP whereas common internal monitoring tools are questionnaires, perceived exertion rating and heart rate measures. The reporting of injuries and menstrual cycles is also crucial for providing completeness when monitoring an athlete. It has been suggested that the combination of training load, recovery and wellbeing monitoring variables is the optimal way to monitor an athlete's fatigue levels. Whichever monitoring method is applied, in a youth population it is important that the protocol can be individualised, is inexpensive and can be easily implemented and reported so that the monitoring is sustainable.

AACC Guidance Document on the Use of Point-of-Care Testing in Fertility and Reproduction

Background

The AACC Academy revised the reproductive testing section of the Laboratory Medicine Practice Guidelines: Evidence-Based Practice for Point-of-Care Testing (POCT) published in 2007.

Methods

A panel of Academy members with expertise in POCT and laboratory medicine was formed to develop guidance for the use of POCT in reproductive health, specifically ovulation, pregnancy, premature rupture of membranes (PROM), and high-risk deliveries. The committee was supplemented with clinicians having Emergency Medicine and Obstetrics/Gynecology training.

Results

Key recommendations include the following. First, urine luteinizing hormone (LH) tests are accurate and reliable predictors of ovulation. Studies have shown that the use of ovulation predicting kits may improve the likelihood of conception among healthy fertile women seeking pregnancy. Urinary LH point-of-care testing demonstrates a comparable performance among other ovulation monitoring methods for timing intrauterine insemination and confirming sufficient ovulation induction before oocyte retrieval during in vitro fertilization. Second, pregnancy POCT should be considered in clinical situations where rapid diagnosis of pregnancy is needed for treatment decisions, and laboratory analysis cannot meet the required turnaround time. Third, PROM testing using commercial kits alone is not recommended without clinical signs of rupture of membranes, such as leakage of amniotic fluid from the cervical opening. Finally, fetal scalp lactate is used more than fetal scalp pH for fetal acidosis due to higher success rate and low volume of sample required.

Conclusions

This revision of the AACC Academy POCT guidelines provides recommendations for best practice use of POCT in fertility and reproduction.

Tracking of menstrual cycles and prediction of the fertile window via measurements of basal body temperature and heart rate as well as machine-learning algorithms

BACKGROUND

Fertility awareness and menses prediction are important for improving fecundability and health management. Previous studies have used physiological parameters, such as basal body temperature (BBT) and heart rate (HR), to predict the fertile window and menses. However, their accuracy is far from satisfactory. Additionally, few researchers have examined irregular menstruators. Thus, we aimed to develop fertile window and menstruation prediction algorithms for both regular and irregular menstruators.

METHODS

This was a prospective observational cohort study conducted at the International Peace Maternity and Child Health Hospital in Shanghai, China. Participants were recruited from August 2020 to November 2020 and followed up for at least four menstrual cycles. Participants used an ear thermometer to assess BBT and wore the Huawei Band 5 to record HR. Ovarian ultrasound and serum hormone levels were used to determine the ovulation day. Menstruation was self-reported by women. We used linear mixed models to assess changes in physiological parameters and developed probability function estimation models to predict the fertile window and menses with machine learning.

RESULTS

We included data from 305 and 77 qualified cycles with confirmed ovulations from 89 regular menstruators and 25 irregular menstruators, respectively. For regular menstruators, BBT and HR were significantly higher during fertile phase than follicular phase and peaked in the luteal phase (all P < 0.001). The physiological parameters of irregular menstruators followed a similar trend. Based on BBT and HR, we developed algorithms that predicted the fertile window with an accuracy of 87.46%, sensitivity of 69.30%, specificity of 92.00%, and AUC of 0.8993 and menses with an accuracy of 89.60%, sensitivity of 70.70%, and specificity of 94.30%, and AUC of 0.7849 among regular menstruators. For irregular menstruators, the accuracy, sensitivity, specificity and AUC were 72.51%, 21.00%, 82.90%, and 0.5808 respectively, for fertile window prediction and 75.90%, 36.30%, 84.40%, and 0.6759 for menses prediction.

CONCLUSIONS

By combining BBT and HR recorded by the Huawei Band 5, our algorithms achieved relatively ideal performance for predicting the fertile window and menses among regular menstruators. For irregular menstruators, the algorithms showed potential feasibility but still need further investigation.

TRIAL REGISTRATION

ChiCTR2000036556. Registered 24 August 2020.

D, R. C. M, T. G. K, A. P. Novel Technique for Confirmation of the Day of Ovulation and Prediction of Ovulation in Subsequent Cycles Using a Skin-Worn Sensor in a Population With Ovulatory Dysfunction: A Side-by-Side Comparison With Existing Basal Body Temperature Algorithm and Vaginal Core Body Temperature Algorithm

Objective: Determine the accuracy of a novel technique for confirmation of the day of ovulation and prediction of ovulation in subsequent cycles for the purpose of conception using a skin-worn sensor in a population with ovulatory dysfunction.

Methods: A total of 80 participants recorded consecutive overnight temperatures using a skin-worn sensor at the same time as a commercially available vaginal sensor for a total of 205 reproductive cycles. The vaginal sensor and its associated algorithm were used to determine the day of ovulation, and the ovulation results obtained using the skin-worn sensor and its associated algorithm were assessed for comparative accuracy alongside a number of other statistical techniques, with a further assessment of the same skin-derived data by means of the “three over six” rule. A number of parameters were used to divide the data into separate comparative groups, and further secondary statistical analyses were performed.

Results: The skin-worn sensor and its associated algorithm (together labeled “SWS”) were 66% accurate for determining the day of ovulation (±1 day) or the absence of ovulation and 90% accurate for determining the fertile window (ovulation day ±3 days) in the total study population in comparison to the results obtained from the vaginal sensor and its associated algorithm (together labeled “VS”).

Conclusion: SWS is a useful tool for confirming the fertile window and absence of ovulation (anovulation) in a population with ovulatory dysfunction, both known and determined by means of the timing of ovulation. The body site where the skin-worn sensor was worn (arm or wrist) did not appear to affect the accuracy. Prior diagnosis of known causes of ovulatory dysfunction appeared to affect the accuracy to a lesser extent than those cycles grouped into late ovulation and “early and normal ovulation” groups. SWS is a potentially useful tool for predicting ovulation in subsequent cycles, with greater accuracy obtained for the “normal ovulation” group.

Descriptive analysis of the relationship between progesterone and basal body temperature across the menstrual cycle

OBJECTIVE

Describe the relationship between basal body temperature (BBT) and pregnanediol-3 alpha-glucuronide (PDG, the urine metabolite of progesterone) across the menstrual cycle.

DESIGN

Observational study.

SETTING

Study carried out from 1996 to 1997 in eight European family planning clinics.

PARTICIPANT(S)

One hundred and seven normally fertile and cycling women.

MAIN OUTCOME MEASURE(S)

BBT and PDG level on each day of 283 cycles and ultrasound determination of the day of ovulation.

RESULT

(s): In comparison with previous end-of-cycle levels, decreases in PDG and BBT on the first day of menses were seen in nearly 90% and 80% of cycles, respectively. In a non-negligible percentage of cycles, luteolysis would continue during menses: between the second and the third day after menses, small but significant decreases in PDG and BBT were seen in 76% and 48% of cycles, respectively. During the peri-ovulatory phase, between the third and the second day before ovulation, PDG and BBT began to rise in 56% and 41% of cycles, respectively. There was a medium degree of correlation between PDG levels and BBT (r = 0.53; 7,279 days with available measurements). The relationship between PDG levels and BBT was linear at low PDG levels but BBT increased no longer when PDG levels continued to rise above a threshold of nearly 10 mcg/mg Cr.

CONCLUSION

(s): PDG and BBT had parallel increases at low PDG rates but diverged at higher rates.

Mimicking the temperature gradient between the sow's oviduct and uterus improves in vitro embryo culture output

This work was designed to determine temperature conditions within the reproductive tract of the female pig and study their impact on ARTs. Temperatures were recorded using a laparo-endoscopic single-site surgery assisted approach and a miniaturized probe. Sows and gilts were used to address natural cycle and ovarian stimulation treatments, respectively. According to in vivo values, IVF was performed at three temperature conditions (37.0°C, 38.5°C and 39.5°C) and presumptive zygotes were cultured in these conditions for 20 h, while further embryo culture (EC) (21-168 h post-insemination) was maintained at 38.5°C. After 20 h, different fertility parameters were assessed. During EC, cleavage and blastocyst stages were evaluated. Sperm membrane fluidity at the experimental temperatures was studied by using differential scanning calorimetry and fluorescence recovery after photobleaching techniques. An increasing temperature gradient of 1.5°C was found between the oviduct and uterus of sows (P < 0.05) and when this gradient was transferred to pig in vitro culture, the number of poly-nuclear zygotes after IVF was reduced and the percentage of blastocysts was increased. Moreover, the temperature transition phase for the boar sperm membrane (37.0°C) coincided with the temperature registered in the sow oviduct, and sperm membranes were more fluid at 37.0°C compared with those of sperm incubated at higher temperatures (38.5°C and 39.5°C). These data suggest that there may be an impact of physiological temperature gradients on human embryo development.

The Accuracy of Wrist Skin Temperature in Detecting Ovulation Compared to Basal Body Temperature: Prospective Comparative Diagnostic Accuracy Study

Background

As a daily point measurement, basal body temperature (BBT) might not be able to capture the temperature shift in the menstrual cycle because a single temperature measurement is present on the sliding scale of the circadian rhythm. Wrist skin temperature measured continuously during sleep has the potential to overcome this limitation.

Objective

This study compares the diagnostic accuracy of these two temperatures for detecting ovulation and to investigate the correlation and agreement between these two temperatures in describing thermal changes in menstrual cycles.

Methods

This prospective study included 193 cycles (170 ovulatory and 23 anovulatory) collected from 57 healthy women. Participants wore a wearable device (Ava Fertility Tracker bracelet 2.0) that continuously measured the wrist skin temperature during sleep. Daily BBT was measured orally and immediately upon waking up using a computerized fertility tracker with a digital thermometer (Lady-Comp). An at-home luteinizing hormone test was used as the reference standard for ovulation. The diagnostic accuracy of using at least one temperature shift detected by the two temperatures in detecting ovulation was evaluated. For ovulatory cycles, repeated measures correlation was used to examine the correlation between the two temperatures, and mixed effect models were used to determine the agreement between the two temperature curves at different menstrual phases.

Results

Wrist skin temperature was more sensitive than BBT (sensitivity 0.62 vs 0.23; P<.001) and had a higher true-positive rate (54.9% vs 20.2%) for detecting ovulation; however, it also had a higher false-positive rate (8.8% vs 3.6%), resulting in lower specificity (0.26 vs 0.70; P=.002). The probability that ovulation occurred when at least one temperature shift was detected was 86.2% for wrist skin temperature and 84.8% for BBT. Both temperatures had low negative predictive values (8.8% for wrist skin temperature and 10.9% for BBT). Significant positive correlation between the two temperatures was only found in the follicular phase (rmcorr correlation coefficient=0.294; P=.001). Both temperatures increased during the postovulatory phase with a greater increase in the wrist skin temperature (range of increase: 0.50 °C vs 0.20 °C). During the menstrual phase, the wrist skin temperature exhibited a greater and more rapid decrease (from 36.13 °C to 35.80 °C) than BBT (from 36.31 °C to 36.27 °C). During the preovulatory phase, there were minimal changes in both temperatures and small variations in the estimated daily difference between the two temperatures, indicating an agreement between the two curves.

Conclusions

For women interested in maximizing the chances of pregnancy, wrist skin temperature continuously measured during sleep is more sensitive than BBT for detecting ovulation. The difference in the diagnostic accuracy of these methods was likely attributed to the greater temperature increase in the postovulatory phase and greater temperature decrease during the menstrual phase for the wrist skin temperatures.

Development of a Permanent Device for Fertility Period Detection by Basal Body Temperature and Analysis of the Cervical Mucus Potential of Hydrogen

Background

Sometimes, women find it difficult to conceive a baby and others use contraceptives that often have side effects. Researchers have already established the importance of measuring basal body temperature (BBT) and the potential of hydrogen (pH).

Method

We have designed and realized a device that allows the simultaneous measurement of the BBT and the pH. We used an Arduino Uno board, a pH sensor, and a temperature sensor. The device communicates with a smartphone, can be integrated into all e-health platforms, and can be used at home. We validated our ovulation detector by a measurement campaign on a group of twenty women. If the pH is >7 and at the same time, the BBT is minimum and <36.5°C, the women is in ovulation phase. If the pH is ≤7 and in the same time, the BBT is between 36.5°C and 37°C, the women are in preovulation or follicular phase. If the pH is ≤7 and in the same time, the BBT is >36.5°C, the women are in postovulation or luteal phase.

Results

We tested the contraceptive aspect of our ovulometer on a set of seven women. We also tested the help of conceiving babies by having intercourse during the ovulation period fixed by our ovulation detector. The results are satisfactory.

Conclusions

In the final version of our device, we displayed just in "fertility period" if the pH is ≥7 and the BBT is <36.5°C else we displayed in "nonfertility period."

Use of fertility awareness methods as a component of safer conception for women in HIV-serodifferent relationships in Kenya

Background

For couples affected by HIV, and serodifferent couples in particular, pregnancy desire is often juxtaposed against the risk of HIV transmission between the couple and the potential neonate leading to thinking about measures to minimize risk of HIV transmission. We assess the use of fertility awareness methods [FAM] and evaluate the drivers of alignment between indicators of fertility and sexual behavior among HIV-serodifferent couples desiring pregnancy.

Methods

HIV-serodifferent couples from Thika, Kenya were enrolled into an open-label pilot evaluation of safer conception strategies. Women responded to daily 7-item short message service [SMS] surveys on FAM and sexual activity. Menstrual cycles were categorized as having condomless sex aligned, not aligned, or partially aligned to the predicted peak fertility. We used binomial logit models with generalized estimating equations to assess alignment between condomless sex during peak fertility days and FAM results. We used Cox proportional hazards to compare pregnancy incidence among months with sex and peak fertility aligned and mis-aligned.

Results

A total of 6929 SMS surveys across 252 menstrual cycles of 65 women were included. Reporting “sticky” cervical mucus (adjusted odds ratio [aOR]: 2.25, 95% confidence interval [95% CI]: 1.30, 3.90) and positive ovulation prediction kit [OPK] result (aOR: 2.07, 95% CI: 1.11, 3.86) were associated with increased likelihood of alignment of condomless sex during peak fertility. Pregnancy incidence was statistically similar among periods with sex aligned and not aligned with peak fertility.

Conclusions

Among women engaged in a comprehensive safer conception program, a moderate percentage of women aligned condomless sex and predicted peak fertility days at least once. While FAM, particularly cervical mucus and OPK, are an inexpensive option for couples to consider using as a component of their safer conception strategies, antiretroviral-based strategies remain important to minimize risk.

The Effects of Menstrual Cycle Phase on Exercise Performance in Eumenorrheic Women: A Systematic Review and Meta-Analysis

Background

Concentrations of endogenous sex hormones fluctuate across the menstrual cycle (MC), which could have implications for exercise performance in women. At present, data are conflicting, with no consensus on whether exercise performance is affected by MC phase.

Objective

To determine the effects of the MC on exercise performance and provide evidence-based, practical, performance recommendations to eumenorrheic women.

Methods

This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Four databases were searched for published experimental studies that investigated the effects of the MC on exercise performance, which included at least one outcome measure taken in two or more defined MC phases. All data were meta-analysed using multilevel models grounded in Bayesian principles. The initial meta-analysis pooled pairwise effect sizes comparing exercise performance during the early follicular phase with all other phases (late follicular, ovulation, early luteal, mid-luteal and late luteal) amalgamated. A more comprehensive analysis was then conducted, comparing exercise performance between all phases with direct and indirect pairwise effect sizes through a network meta-analysis. Results from the network meta-analysis were summarised by calculating the Surface Under the Cumulative Ranking curve (SUCRA). Study quality was assessed using a modified Downs and Black checklist and a strategy based on the recommendations of the Grading of Recommendations Assessment Development and Evaluation (GRADE) working group.

Results

Of the 78 included studies, data from 51 studies were eligible for inclusion in the initial pairwise meta-analysis. The three-level hierarchical model indicated a trivial effect for both endurance- and strength-based outcomes, with reduced exercise performance observed in the early follicular phase of the MC, based on the median pooled effect size (ES_0.5 = − 0.06 [95% credible interval (CrI): − 0.16 to 0.04]). Seventy-three studies had enough data to be included in the network meta-analysis. The largest effect was identified between the early follicular and the late follicular phases of the MC (ES_0.5 = − 0.14 [95% CrI: − 0.26 to − 0.03]). The lowest SUCRA value, which represents the likelihood that exercise performance is poor, or among the poorest, relative to other MC phases, was obtained for the early follicular phase (30%), with values for all other phases ranging between 53 and 55%. The quality of evidence for this review was classified as “low” (42%).

Conclusion

The results from this systematic review and meta-analysis indicate that exercise performance might be trivially reduced during the early follicular phase of the MC, compared to all other phases. Due to the trivial effect size, the large between-study variation and the number of poor-quality studies included in this review, general guidelines on exercise performance across the MC cannot be formed; rather, it is recommended that a personalised approach should be taken based on each individual's response to exercise performance across the MC.

Electronic supplementary material

The online version of this article (10.1007/s40279-020-01319-3) contains supplementary material, which is available to authorized users.

Predictive Factors of Conception and the Cumulative Pregnancy Rate in Subfertile Couples Undergoing Timed Intercourse With Ultrasound

The aim of this study was to determine predictive factors for pregnancy and assess the cumulative pregnancy rate (CPR) and live birth rate (CLBR) in subfertile couples undergoing timed intercourse (TI) using ultrasound. This retrospective cohort study included 285 women (854 cycles) who started TI with ultrasound between January 2017 and October 2019. The overall clinical pregnancy rate was 28.1% (80/285) per couple and 9.4% (80/854) per cycle. Pregnant women had a higher body mass index (BMI), higher percentage of irregular menstrual cycles, a shorter duration of subfertility, lower serum follicle-stimulating hormone levels, and higher anti-Müllerian hormone levels than non-pregnant women. A longer duration of subfertility (≥24 months vs. <12 months; odds ratio: 0.193; 95% confidence interval: 0.043-0.859) and endometriosis (vs. ovulatory factors; odds ratio: 0.282; 95% confidence interval: 0.106-0.746) as causes of subfertility were unfavorable factors that independently affected clinical pregnancy. In subgroup analysis, old age ≥ 35 years [vs. < 35 years; odds ratio: 0.279; 95% confidence interval: 0.083-0.938), a longer duration of infertility ≥24 months (vs. <24 months; odds ratio: 0.182; 95% confidence interval: 0.036-0.913) and a higher BMI ≥ 25 kg/m²(vs. >25 kg/m²; odds ratio: 3.202; 95% confidence interval: 1.020-10.046) in couples with ovulatory factor and a longer duration of infertility ≥24 months (vs. <24 months; odds ratio: 0.185; 95% confidence interval: 0.042-0.819) in couples with non-ovulatory factors were significant independent predictive factors for pregnancy. No significant differences were found in the cycle characteristics between pregnant and non-pregnant women. The CPR substantially increased during the first three cycles and significantly increased until the sixth cycle. No significant increase was observed in the CPR after the sixth cycle. The CLBRs substantially increased during the first three cycles and significantly increased until the fourth cycle. No significant increase was observed in the CLBRs after the fifth cycle. When comparing CPRs and CLBRs according to subfertile causes, CRPs was significantly different and CLBRs was different with borderline significance. Our findings may indicate that women with a longer duration of subfertility or subfertility due to endometriosis have poor outcomes during TI with ultrasound. Women who failed to achieve conception by the fourth or fifth cycle of TI with ultrasound may be encouraged to consider advancing to the next treatment strategy.

Using Circadian Rhythm Patterns of Continuous Core Body Temperature to Improve Fertility and Pregnancy Planning

Objective

Review relationships among circadian clocks, core body temperature (CBT), and fertility in women.

Methods

Scoping literature review.

Results

Circadian clocks are a ubiquitous adaptation to the most predictable environmental events - the daily cycles of light and dark. Core body temperature (CBT) also follows a circadian rhythm. Additionally, CBT is tightly controlled by a combination of neuronal circuits that begin in the hypothalamus and involve many other portions of the brain as well as a wide range of peripheral mechanisms. In women with normal reproductive function, the diurnal temperature pattern for CBT is strongly influenced by the menstrual cycle of reproductive hormones, primarily estradiol and progesterone, which modulate the activity of hypothalamic neural circuits involved in body temperature control, resulting in an infradian CBT rhythm.

Conclusions

Analysis of CBT via continuous recording reveals patterns in the interactions of circadian and infradian CBT rhythms capable of accurately predicting the fertility window and hormonal patterns suggesting oligo-ovulation and subfertility. New wearable technologies can facilitate employment of hormone-associated changes in CBT for pregnancy planning and offer clinical insight to infertility and menopause.

Temperature regulation in women: Effects of the menstrual cycle

Core body temperature changes across the ovulatory menstrual cycle, such that it is 0.3°C to 0.7°C higher in the post-ovulatory luteal phase when progesterone is high compared with the pre-ovulatory follicular phase. This temperature difference, which is most evident during sleep or immediately upon waking before any activity, is used by women as a retrospective indicator of an ovulatory cycle. Here, we review both historical and current literature aimed at characterizing changes in core body temperature across the menstrual cycle, considering the assessment of the circadian rhythm of core body temperature and thermoregulatory responses to challenges, including heat and cold exposure, exercise, and fever. We discuss potential mechanisms for the thermogenic effect of progesterone and the temperature-lowering effect of estrogen, and discuss effects on body temperature of exogenous formulations of these hormones as contained in oral contraceptives. We review new wearable temperature sensors aimed at tracking daily temperature changes of women across multiple menstrual cycles and highlight the need for future research on the validity and reliability of these devices. Despite the change in core body temperature across the menstrual cycle being so well identified, there remain gaps in our current understanding, particularly about the underlying mechanisms and microcircuitry involved in the temperature changes.

Pilot Evaluation of a New Urine Progesterone Test to Confirm Ovulation in Women Using a Fertility Monitor

Background: Progesterone rises ~24–36 h after ovulation. Past studies using ultrasound-confirmed ovulation have shown that three consecutive tests with a threshold of 5μg/mL of urine progesterone (pregnanediol-3-glucuronide, PDG), taken after the luteinizing hormone (LH) surge, confirmed ovulation with 100% specificity.

Purpose: The purpose of this study was to a evaluate a new urine PDG self-test to retrospectively confirm ovulation in women who were monitoring ovulation using a hormonal fertility monitor.

Methods: Thirteen women of reproductive age were recruited to test urine PDG while using their home hormonal fertility monitor. The monitor measured the rise in estrogen (estrone-3-glucuronide, E3G) and LH to estimate the fertile phase of the menstrual cycle. The women used an online menstrual cycle charting system to track E3G, LH and PDG levels for four menstrual cycles.

Results: The participants (Mean age 33.6) produced 34 menstrual cycles of data (Mean length 28.4 days), 17 of which used a PDG test with a threshold of 7μg/mL and 17 with a threshold of 5μg/mL. In the cycles that used the 7μg/mL test strips, 59% had a positive confirmation of ovulation, and with the 5μg/mL test strips, 82% of them had a positive confirmation of ovulation.

Conclusion: The 5μg/mL PDG test confirmed ovulation in 82% of cycles and could assist women in the evaluation of the luteal progesterone rise of their menstrual cycle.

Development of Ovulatory Menstrual Cycles in Adolescent Girls

Irregular menstrual cycles due to anovulation are well described in the first few years after menarche, but the normal developmental trajectory from anovulatory to mature ovulatory cycles during adolescence remains undefined. In this article we review the very limited understanding of this final stage of female reproductive axis development and discuss why additional research in this area is critical to the health of women.

A self-excited threshold autoregressive state-space model for menstrual cycles: Forecasting menstruation and identifying within-cycle stages based on basal body temperature

The menstrual cycle is divided into hypothermic and hyperthermic phases based on the periodic shift in the basal body temperature (BBT), reflecting events occurring in the ovary. In the present study, we proposed a state-space model that explicitly incorporates the biphasic nature of the menstrual cycle, in which the probability density distributions for the advancement of the menstrual phase and that for the BBT switch depending on a latent state variable. Our model derives the predictive distribution of the day of the next menstruation onset that is adaptively adjusted by accommodating new observations of the BBT sequentially. It also enables us to obtain conditional probabilities of the woman being in the early or late stages of the cycle, which can be used to identify the duration of hypothermic and hyperthermic phases, possibly as well as the day of ovulation. By applying the model to real BBT and menstruation data, we show that the proposed model can properly capture the biphasic characteristics of menstrual cycles, providing a good prediction of the menstruation onset in a wide range of age groups. The application of the proposed model to a large data set containing 25 622 cycles provided by 3533 women further highlighted the between-age differences in the population characteristics of menstrual cycles, suggesting its wide applicability.

Wearable Sensors Reveal Menses-Driven Changes in Physiology and Enable Prediction of the Fertile Window: Observational Study

Background

Previous research examining physiological changes across the menstrual cycle has considered biological responses to shifting hormones in isolation. Clinical studies, for example, have shown that women’s nightly basal body temperature increases from 0.28 to 0.56 ˚C following postovulation progesterone production. Women’s resting pulse rate, respiratory rate, and heart rate variability (HRV) are similarly elevated in the luteal phase, whereas skin perfusion decreases significantly following the fertile window’s closing. Past research probed only 1 or 2 of these physiological features in a given study, requiring participants to come to a laboratory or hospital clinic multiple times throughout their cycle. Although initially designed for recreational purposes, wearable technology could enable more ambulatory studies of physiological changes across the menstrual cycle. Early research suggests that wearables can detect phase-based shifts in pulse rate and wrist skin temperature (WST). To date, previous work has studied these features separately, with the ability of wearables to accurately pinpoint the fertile window using multiple physiological parameters simultaneously yet unknown.

Objective

In this study, we probed what phase-based differences a wearable bracelet could detect in users’ WST, heart rate, HRV, respiratory rate, and skin perfusion. Drawing on insight from artificial intelligence and machine learning, we then sought to develop an algorithm that could identify the fertile window in real time.

Methods

We conducted a prospective longitudinal study, recruiting 237 conception-seeking Swiss women. Participants wore the Ava bracelet (Ava AG) nightly while sleeping for up to a year or until they became pregnant. In addition to syncing the device to the corresponding smartphone app daily, women also completed an electronic diary about their activities in the past 24 hours. Finally, women took a urinary luteinizing hormone test at several points in a given cycle to determine the close of the fertile window. We assessed phase-based changes in physiological parameters using cross-classified mixed-effects models with random intercepts and random slopes. We then trained a machine learning algorithm to recognize the fertile window.

Results

We have demonstrated that wearable technology can detect significant, concurrent phase-based shifts in WST, heart rate, and respiratory rate (all P<.001). HRV and skin perfusion similarly varied across the menstrual cycle (all P<.05), although these effects only trended toward significance following a Bonferroni correction to maintain a family-wise alpha level. Our findings were robust to daily, individual, and cycle-level covariates. Furthermore, we developed a machine learning algorithm that can detect the fertile window with 90% accuracy (95% CI 0.89 to 0.92).

Conclusions

Our contributions highlight the impact of artificial intelligence and machine learning’s integration into health care. By monitoring numerous physiological parameters simultaneously, wearable technology uniquely improves upon retrospective methods for fertility awareness and enables the first real-time predictive model of ovulation.

Modern fertility awareness methods: wrist wearables capture the changes in temperature associated with the menstrual cycle

Core and peripheral body temperatures are affected by changes in reproductive hormones during the menstrual cycle. Women worldwide use the basal body temperature (BBT) method to aid and prevent conception. However, prior research suggests that taking one's daily temperature can prove inconvenient and subject to environmental factors. We investigate whether a more automatic, non-invasive temperature measurement system can detect changes in temperature across the menstrual cycle. We examined how wrist skin temperature (WST), measured with wearable sensors, correlates with urinary tests of ovulation and may serve as a new method of fertility tracking. One hundred and thirty-six eumenorrheic, non-pregnant women participated in an observational study. Participants wore WST biosensors during sleep and reported their daily activities. An at-home luteinizing hormone (LH) test was used to confirm ovulation. WST was recorded across 437 cycles (mean cycles/participant = 3.21, S.D. = 2.25). We tested the relationship between the fertile window and WST temperature shifts, using the BBT three-over-six rule. A sustained 3-day temperature shift was observed in 357/437 cycles (82%), with the lowest cycle temperature occurring in the fertile window 41% of the time. Most temporal shifts (307/357, 86%) occurred on ovulation day (OV) or later. The average early-luteal phase temperature was 0.33°C higher than in the fertile window. Menstrual cycle changes in WST were impervious to lifestyle factors, like having sex, alcohol, or eating prior to bed, that, in prior work, have been shown to obfuscate BBT readings. Although currently costlier than BBT, the present study suggests that WST could be a promising, convenient parameter for future multiparameter fertility awareness methods.

The forecasting of menstruation based on a state-space modeling of basal body temperature time series

Women's basal body temperature (BBT) shows a periodic pattern that associates with menstrual cycle. Although this fact suggests a possibility that daily BBT time series can be useful for estimating the underlying phase state as well as for predicting the length of current menstrual cycle, little attention has been paid to model BBT time series. In this study, we propose a state-space model that involves the menstrual phase as a latent state variable to explain the daily fluctuation of BBT and the menstruation cycle length. Conditional distributions of the phase are obtained by using sequential Bayesian filtering techniques. A predictive distribution of the next menstruation day can be derived based on this conditional distribution and the model, leading to a novel statistical framework that provides a sequentially updated prediction for upcoming menstruation day. We applied this framework to a real data set of women's BBT and menstruation days and compared prediction accuracy of the proposed method with that of previous methods, showing that the proposed method generally provides a better prediction. Because BBT can be obtained with relatively small cost and effort, the proposed method can be useful for women's health management. Potential extensions of this framework as the basis of modeling and predicting events that are associated with the menstrual cycles are discussed. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Detection of ovulation, a review of currently available methods

The ability to identify the precise time of ovulation is important for women who want to plan conception or practice contraception. Here, we review the current literature on various methods for detecting ovulation including a review of point‐of‐care device technology. We incorporate an examination of methods to detect ovulation that have been developed and practiced for decades and analyze the indications and limitations of each—transvaginal ultrasonography, urinary luteinizing hormone detection, serum progesterone and urinary pregnanediol 3‐glucuronide detection, urinary follicular stimulating hormone detection, basal body temperature monitoring, and cervical mucus and salivary ferning analysis. Some point‐of‐care ovulation detection devices have been developed and commercialized based on these methods, however previous research was limited by small sample size and an inconsistent standard reference to true ovulation.

Pulse Rate Measurement During Sleep Using Wearable Sensors, and its Correlation with the Menstrual Cycle Phases, A Prospective Observational Study

An affordable, user-friendly fertility-monitoring tool remains an unmet need. We examine in this study the correlation between pulse rate (PR) and the menstrual phases using wrist-worn PR sensors. 91 healthy, non-pregnant women, between 22-42 years old, were recruited for a prospective-observational clinical trial. Participants measured PR during sleep using wrist-worn bracelets with photoplethysmographic sensors. Ovulation day was estimated with "Clearblue Digital-Ovulation-urine test". Potential behavioral and nutritional confounders were collected daily. 274 ovulatory cycles were recorded from 91 eligible women, with a mean cycle length of 27.3 days (±2.7). We observed a significant increase in PR during the fertile window compared to the menstrual phase (2.1 beat-per-minute, p < 0.01). Moreover, PR during the mid-luteal phase was also significantly elevated compared to the fertile window (1.8 beat-per-minute, p < 0.01), and the menstrual phase (3.8 beat-per-minute, p < 0.01). PR increase in the ovulatory and mid-luteal phase was robust to adjustment for the collected confounders. There is a significant increase of the fertile-window PR (collected during sleep) compared to the menstrual phase. The aforementioned association was robust to the inter- and intra-person variability of menstrual-cycle length, behavioral, and nutritional profiles. Hence, PR monitoring using wearable sensors could be used as one parameter within a multi-parameter fertility awareness-based method.

Basal Temperature Measurement Using a Multi-Sensor Armband in Australian Young Women: A Comparative Observational Study

BACKGROUND

The menstrual cycle is a key marker of health in women of reproductive age. Monitoring ovulation is useful in health studies involving young women. The upward shift in basal body temperature, which occurs shortly after ovulation and continues until the next menses, is a potentially useful marker of ovulation, which has been exploited in clinical and research settings.

OBJECTIVE

We investigated the utility of BodyMedia SenseWear (BMSW) in monitoring ovulation in young women by analyzing the correlation and agreement of basal temperatures measured using BMSW and a digital oral thermometer.

METHODS

Kappa statistics were used to determine the agreement in ovulation detection between the two devices, for each participant, under each form of analysis. Participants also completed an online questionnaire assessing the acceptability of both devices.

RESULTS

We recruited 16 participants with 15 of them providing analyzable data (11 OCP non-users, 4 OCP users). Weak to moderate correlations were observed between thermometer and BMSW temperature measurements averaged over 5 different time intervals. However, no agreement between methods was observed using Bland-Altman plots. There was a significant difference in the range of temperatures that each device recorded (thermometer: 35.3-37.2°C, BMSW: 29.7-36.7°C) with BMSW temperatures significantly lower than thermometer temperatures: mean 34.6°C (SD 1.2) versus 36.4°C (SD 0.3) respectively, P<.001. Poor agreement was observed between devices under quantitative analysis of ovulation while fair agreement was observed under visual analysis. Under both quantitative and visual analysis, there was 0% agreement for evidence of ovulation.

CONCLUSIONS

This study demonstrated the importance of evaluating biomeasures collected using mobile monitoring devices by comparison with standard methods. It revealed a relatively poor correlation between BMSW and oral thermometer temperature readings and suggested that BMSW is unlikely to detect an upward shift in basal body temperature. Participant behavior suggested poor compliance in the use of BMSW for basal temperature measurement and that the basal body temperature method may not be suitable for use in unselected samples of young women. There is a need for research tools for monitoring ovulation that are simple, self-administered, and inexpensive, yet appealing to young women.

Reclaiming fertility awareness methods to inform timed intercourse for HIV serodiscordant couples attempting to conceive

INTRODUCTION

Increased life expectancy of HIV-positive individuals during recent years has drawn attention to their quality of life, which includes fulfillment of fertility desires. In particular, heterosexual HIV serodiscordant couples constitute a special group for whom the balance between desired pregnancy and the risk of viral transmission should be carefully considered and optimized. Although advanced assisted reproductive technologies are available, such treatments are expensive and are often unavailable. Moreover, standard viral load testing and antiretroviral therapy may not be accessible due to structural or individual barriers. To reduce the risk of HIV transmission, a lower cost alternative is timed condomless sex combined with other risk-reduction strategies. However, timed condomless sex requires specific knowledge of how to accurately predict the fertile window in a menstrual cycle. The aim of this study was to summarize inexpensive fertility awareness methods (FAMs) that predict the fertile window and may be useful for counselling HIV-positive couples on lower cost options to conceive.

METHODS

Original English-language research articles were identified by a detailed Medline and Embase search in July 2014. Relevant citations in the included articles were also retrieved.

RESULTS AND DISCUSSION

Calendar method, basal body temperature and cervicovaginal mucus secretions are the most accessible and sensitive FAMs, although poor specificity precludes their independent use in ovulation detection. In contrast, urinary luteinizing hormone testing is highly specific but less sensitive, and more expensive. To maximize the chance of conception per cycle, the likelihood of natural conception needs to be assessed with a basic fertility evaluation of both partners and a combination of FAMs should be offered. Adherence to other risk-reduction strategies should also be advised, and timely referral to reproductive medicine specialists is necessary when sub/infertility is suspected.

CONCLUSIONS

FAMs provide effective, economical and accessible options for HIV serodiscordant couples to conceive while minimizing unnecessary viral exposure. It is important for health care providers to initiate conversations about fertility desires in HIV-positive couples and to educate identified couples on safer conception strategies.

Physiological signs of ovulation and fertility readily observable by women

INTRODUCTION

Confirmation of ovulation can be difficult in clinical practice, as gold standard methods including serial transvaginal ultrasonography, serum luteinizing hormone (LH) measurements, or laparoscopic follicular observation are impractical. Numerous surrogate markers have been proposed and evaluated in relation to these gold standards that have more practical clinical applications.

PURPOSE

To review the evidence on physiological signs of ovulation timing and fertility in order to determine valid markers that can be easily identified by women.

METHODS

A literature review of primary resources in Ovid Medline was undertaken to identify studies examining physiological signs as they relate to gold standard assessment of ovulation. Studies examining the efficacy/effectiveness of different types of natural family planning were excluded.

RESULTS

The most commonly encountered physiological signs were urine LH, cervical mucus, and basal body temperature (BBT). Urine LH as assessed by home monitoring systems indicated ovulation 91 percent of the time during the 2 days of peak fertility on the monitor and 97 percent during the 2 peak days plus 1. Cervical mucus peak characteristics were identified 78 percent of the time ±1 day, and 91 percent of the time ±2 days of LH surge indicating ovulation. Further research supports the importance of cervical mucus in overall fertility, as conception rates were more closely related to mucus quality than to timing of intercourse related to ovulation. As a lone indicator of ovulation, BBT is at best a retrospective marker, and functions best in conjunction with other signs of ovulation. Additionally, salivary ferning, salivary and vaginal fluid electrical potential, finger-finger electrical potential, and differential skin temperature were postulated as possible indicators, but were not found to be temporally related to ovulation. The research on differential skin temperature is promising, but minimal thus far in number, and has not been evaluated as an adjunct to BBT as yet.

CONCLUSION

Home urinary LH monitors are becoming more widely available and less expensive giving women the potential to assess the ovulatory status of their cycle in real time. Cervical mucus observation is an effective and cost-efficient method, but requires some teaching to increase the confidence of users. In conjunction, LH monitors and cervical mucus can give the best indication of fertility and ovulation timing.

Infertility: evaluation and initial management

Treating the infertile client with competence and compassion is within the scope of practice for advanced practice clinicians. However, due to both a lack of emphasis on infertility treatment in many advanced practice education programs and confusion regarding diagnosis and treatment by many practitioners, infertility is often undertreated by these providers. A basic infertility evaluation, patient counseling, and prescriptive therapy with oral ovulation-inducing agents by a knowledgeable practitioner is cost-effective and may result in successful pregnancy in women who otherwise may not be adequately and quickly treated prior to referral to a reproductive endocrinologist. A diagnosis of infertility is often stressful and frustrating for a couple. Midwives and advanced practice nurses are uniquely qualified to provide both compassionate care and competent treatment during this time. This article provides the clinician with an overview of infertility diagnosis, evaluation, and initial management with lifestyle modifications and oral ovulation-inducing agents.

Isometric knee-extension and knee-flexion torque production during early follicular and postovulatory phases in recreationally active women

CONTEXT

Acute decreases in strength have been associated with risky biomechanical strategies that might predispose one to injury. Whether acute changes in thigh muscle torque occur across the menstrual cycle remains equivocal.

OBJECTIVE

We compared maximal voluntary isometric contraction (MVIC) torque of the knee flexors and extensors between the early follicular (EF) and either the early luteal (EL) or midluteal (ML) phases, which were confirmed by serum hormone concentrations. We expected that MVIC torques would increase from the EF to the EL phase after estradiol peaked and before increased exposure to progesterone.

DESIGN

Cohort study.

SETTING

Applied Neuromechanics Research Laboratory.

PATIENTS OR OTHER PARTICIPANTS

Seventy-one recreationally active women (age range, 18-30 years).

INTERVENTION(S)

The MVICs were measured 1 day during menses and 1 day during the 8 days after ovulation. Participants were grouped by the hormone profile of their luteal test days as EL phase, ML phase, or anovulatory cycle.

MAIN OUTCOME MEASURE(S)

The MVIC torque of knee flexors and extensors (Nm/kg), estradiol (pg/mL), progesterone (ng/mL), and testosterone (ng/dL).

RESULTS

We tested 29 women during their EL phases, 32 during their ML phases, and 10 during anovulatory cycles. Although we observed relatively large individual changes in sex hormone concentrations and MVIC torques across the 2 test sessions, we observed no difference in MVIC torque between test phases (F(1,68)  =  1.17, P  =  .28) or among groups by test phase (F(2,68)  =  0.31, P  =  .74).

CONCLUSIONS

Thigh MVIC torque did not change from time of menses (when estradiol and progesterone were lowest) to time in the luteal phase after an unopposed estradiol rise or combined estradiol and progesterone rise. However, these findings were limited to MVIC torque production measured at 2 different times, and further research examining these relationships at multiple times and using other measures of neuromuscular function is needed.

Efficacy of cervical mucus observations plus electronic hormonal fertility monitoring as a method of natural family planning

OBJECTIVE

To determine the effectiveness of an electronic hormonal fertility monitor plus cervical mucus monitoring to avoid pregnancy.

DESIGN

A 12-month prospective clinical efficacy trial.

SETTING AND PARTICIPANTS

One hundred ninety five (195) women (mean age 29.8 years) seeking to avoid pregnancy with a natural method at 5 clinical sites in 4 cities.

INTERVENTION

Each participant was taught to track fertility by self-observation of cervical mucus and an electronic monitor that measures urinary levels of estrone-3-glucuronide and luteinizing hormone.

MAIN OUTCOME MEASURES

Correct- and typical-use unintended pregnancy rates.

RESULTS

There were a total of 26 unintended pregnancies, 3 with correct use. With 1,795 months of use, the correct-use pregnancy rate was 2.1% per 12 months of use (i.e., 97.9% effective in avoiding pregnancy when rules of the method were always followed) and the imperfect-use pregnancy rate was 14.2% per 12 months of use (i.e., 85.8% effective in avoiding pregnancy when rules of the method were not always followed and all unintended pregnancies and months of use were included in the calculations).

CONCLUSIONS

Correct use of an electronic hormonal fertility monitor with cervical mucus observations can be as effective as other fertility awareness-based methods of natural family planning. Comparative studies are needed to confirm this conclusion.

Variability in the Phases of the Menstrual Cycle

OBJECTIVE

To determine variability in the phases of the menstrual cycle among healthy, regularly cycling women.

DESIGN

A prospective descriptive study of a new data set with biological markers to estimate parameters of the menstrual cycles.

PARTICIPANTS

One hundred forty one healthy women (mean age 29 years) who monitored 3 to 13 menstrual cycles with an electronic fertility monitor and produced 1,060 usable cycles of data. MEASURES AND OUTCOMES: Variability in the length of the menstrual cycle and of the follicular, fertile, and luteal phases, and menses. The estimated day of ovulation and end of the fertile phase was the peak fertility reading on the monitor (i.e., the urinary luteinizing hormone surge).

RESULTS

Mean total length was 28.9 days (SD = 3.4) with 95% of the cycles between 22 and 36 days. Intracycle variability of greater than 7 days was observed in 42.5% of the women. Ninety-five percent of the cycles had all 6 days of fertile phase between days 4 and 23, but only 25% of participants had all days of the fertile phase between days 10 and 17.

CONCLUSIONS

Among regularly cycling women, there is considerable normal variability in the phases of the menstrual cycle. The follicular phase contributes most to this variability.