Time Of Ovulation Research Articles

Luteinizing hormone stimulates ingression of mural granulosa cells within the mouse preovulatory follicle†.

Luteinizing hormone (LH) induces ovulation by acting on its receptors in the mural granulosa cells that surround a mammalian oocyte in an ovarian follicle. However, much remains unknown about how activation of the LH receptor modifies the structure of the follicle such that the oocyte is released and the follicle remnants are transformed into the corpus luteum. The present study shows that the preovulatory surge of LH stimulates LH receptor-expressing granulosa cells, initially located almost entirely in the outer layers of the mural granulosa, to rapidly extend inwards, intercalating between other cells. The cellular ingression begins within 30 min of the peak of the LH surge, and the proportion of LH receptor-expressing cell bodies in the inner half of the mural granulosa layer increases until the time of ovulation, which occurs at about 10h after the LH peak. During this time, many of the initially flask-shaped cells appear to detach from the basal lamina, acquiring a rounder shape with multiple filipodia. Starting at about 4h after the LH peak, the mural granulosa layer at the apical surface of the follicle where ovulation will occur begins to thin, and the basolateral surface develops invaginations and constrictions. Our findings raise the question of whether LH stimulation of granulosa cell ingression may contribute to these changes in the follicular structure that enable ovulation.

A cross-sectional study on assessment of birth control methods in family planning facilities among pregnant mothers in parts of Hong, Adamawa State, Nigeria

The study assessed the knowledge, accessibility and utilized birth control methods among pregnant mothers. Surveys and choice-type questionnaires were the study methodology used. A total of 222 pregnant women were drawn at random from three different health facilities in Hong. Frequency and percentage were used in the data presentation. Age group 36–50 (47.1%) years, NCE/Diploma (38.1%), civil servant (25.1%), pregnant women with parity of 3 and 4 children (24.8%) and child spacing of ≥ 2 years (53.4%) had the highest number of subjects, according to the sociodemographic characteristics of those who participated. Participant's knowledge of and access to birth control methods revealed those who were already sensitized (83.3%), knowledge source of birth control method was hospital (46.3%), who knew the precise time of ovulation (65.2%), who had access to birth control through Primary Health Care centers and acknowledge the importance of birth control techniques (80.5%) recorded high numbers of participants. According to the utilization of birth control techniques, the highest rates were seen in both participants who frequently breastfed and utilized a calendar or rhythm with equal score (40.5%) as a natural method of birth control, those who employ coitus interruptus (54.3%), menstruated while breastfeeding (56.6%), and who frequently used condoms, pills etc. (37.4%). Additionally, 57.4% cited cost serve as a barrier for condom utilization, while 58.2% cited their culture and religious beliefs have not prevented them from utilizing birth control. Therefore, Birth control technique sensitization at home and health care center, level of education alongside availability and access point to modern contraceptive at health care influence utilization of both natural and modern methods of birth control.

Influence of injecting the different dose of ovaprim against ovulation time of goldfish (Carassius auratus)

Goldfish is one of the freshwater ornamental fish that is in great demand for the Indonesian community, but its production is still not meeting the demand of the market because it has to wait for the process of ovulation. Therefore, to accelerate the occurrence of the ovulation process can be done with the injection of the hormone ovaprim. So the purpose of this research is to determine the time of ovulation of the goldfish by doing the injection of the hormone ovaprim. The research was conducted for two months at the Djuanda Bogor University Fisheries Laboratory. The research design was a Complete Random Plan (RAL) with 4 treatments and 3 repetitions. Treatment K (control) did not give hormones, treatment A (0.3 mL/kg of female mother weight), treatment B (0.5 mL /kg of feminine mother body weight), C (0.7 ml / kg of femal mother weight) and 0.5 mL per kg of male mother for each treatment. Research shows the fastest.

DINAMIKA OVARIUM PADA SAPI PERANAKAN SIMMENTAL MENGALAMI ESTRUS BERKEPANJANGAN YANG DITERAPI DENGAN HUMAN CHORIONIC GONADOTROPHIN (hCG) SECARA INTRAVENA

This study was aimed to identify ovarian dynamics using ultrasonography (USG) in simmental crossbreedcows diagnosed prolonged oestrustreatment with human chorionic gonadotrophin (hCG). A total of four Simmental crossbreed cows diagnosed with prolonged oestrouswere used in this study. The first oestrous observations in all four cows were a control group, where as the next oestrous cycle observation to the same four cows treated with 1500 IU hCG in jugular vein refer to treated group. The observation of ovarian dynamics was started from the first oestrous day until ovulation occurs in the second oestrus cycle using ultrasonography (USG) with a linear rectal probe. At the same time, follicle and corpus luteum (CL) images were recorded every day. Data were analyzed using paired data comparison test (pair sample t-test). The observation results ovarian dynamics on prolonged oestruscows showed that the long of oestrous cycle was 22.5 ± 0.5 days, and there are three follicular wave patterns in oestrous cycle. The first wave of dominant follicle was firstly identified on day 3.3 ± 0.5, reached maximum diameter 12.0 ± 0.3 cm. The second and third dominant follicle appeared on day 10.8 ± 0.5 and 15.8 ± 0.5 cm reached maximum diameter 1.2 ± 0.3 cm dan 1.5 ± 0.3 cm.Therapy with hCG does not significantly affect the dominant follicle’s diameter during oestrous (p>0.05). The conclusion of this study showed that 1500 IU of hCG therapy does not affect the development of dominant follicle, however, it can shorten the duration of oestrous and ovulation time.

Timing of ovulation in the fat-tailed Qezel ewes after synchronization with vaginal devices containing endogenous or exogenous synthetic progestogens during out of the breeding season.

Wide range of ovulation distribution is the main restricting factor in establishing the pregnancy following oestrus synchronization (ES) and fixed time insemination (FTI) in sheep. Determining the ovulation time (OVT) following ES with two different vaginal devices, its relation to progesterone and conception upon FTI with frozen/thawed semen. Oestrus was synchronized using either controlled internal drug release (CIDR) (ewe, n=6; ewe lamb, n=5) or vaginal sponge (ewe, n=6; ewe lamb, n=5) insertion for 12 days, plus Equine chorionic gonadotropin (eCG) at devices removal (Day 0). Sizes of the ovarian follicles were measured using transvaginal probe at -12, 0 and 30-33, 53h and continued every 3-4h until 75h after eCG treatment. Serum progesterone amounts were measured at -12, 0, +2 and +11. Laparoscopic FTI was done at 60.5±0.5h. The CIDR-treated group initiated and completed ovulations earlier compared to sponge-treated females (median: 64 vs. 71h; p<0.05). Ewe lambs were ovulated earlier compared to ewes in the sponge-treated group (66.71 vs. 71.5; p=0.017). Mean sizes of ovulatory follicles and corpora lutea were not affected by device types. Higher amounts of progesterone were observed in CIDR group compared to sponge-treated group at device removal (2.68±0.12 vs. 0.30±0.01ng/mL; p<0.001). The conception was confirmed in 2/10, and 5/11 females of sponge and CIDR-treated females, respectively. Types of progestogens influence the OVT, and consequently the result of FTI with frozen/thawed semen. The optimum timespan for FTI should be chosen according to the device types during non-breeding season.

Neural substrates underlying rhythmic coupling of female reproductive and thermoregulatory circuits.

Coordinated fluctuations in female reproductive physiology and thermoregulatory output have been reported for over a century. These changes occur rhythmically at the hourly (ultradian), daily (circadian), and multi-day (ovulatory) timescales, are critical for reproductive function, and have led to the use of temperature patterns as a proxy for female reproductive state. The mechanisms underlying coupling between reproductive and thermoregulatory systems are not fully established, hindering the expansion of inferences that body temperature can provide about female reproductive status. At present, numerous digital tools rely on temperature to infer the timing of ovulation and additional applications (e.g., monitoring ovulatory irregularities and progression of puberty, pregnancy, and menopause are developed based on the assumption that reproductive-thermoregulatory coupling occurs across timescales and life stages. However, without clear understanding of the mechanisms and degree of coupling among the neural substrates regulating temperature and the reproductive axis, whether such approaches will bear fruit in particular domains is uncertain. In this overview, we present evidence supporting broad coupling among the central circuits governing reproduction, thermoregulation, and broader systemic physiology, focusing on timing at ultradian frequencies. Future work characterizing the dynamics of reproductive-thermoregulatory coupling across the lifespan, and of conditions that may decouple these circuits (e.g., circadian disruption, metabolic disease) and compromise female reproductive health, will aid in the development of strategies for early detection of reproductive irregularities and monitoring the efficacy of fertility treatments.

A recently published study further advances the drive toward precision medicine in IVF

The individualized timing of ovulation triggers to such very small follicle sizes and, therefore, at times extremely early egg retrieval, significantly shortens IVF cycles and mandates very close, daily observation of patients. That MII oocytes with advancing female age lose ability to produce good-quality embryos is, of course, also a potentially almost revolutionary finding because practically every IVF cycle in the world currently strives to maximize the percentage of MII oocytes in every IVF cycle’s egg-cohort.

Ovarian function and pregnancy rates in dairy goats that received 300 IU of human chorionic gonadotropin (hCG) intravaginally at the time of artificial insemination

Two experiments were carried out to evaluate the effects of administering 300 IU hCG intravaginally (i.vag.) at the time of artificial insemination (AI) on ovulatory response, luteal function and pregnancy rates in cyclic Alpine (A) and Saanen (S) goats. All animals received two i.m. injections of 37.5 μg of d-cloprostenol (Prolise®; Tecnopec, São Paulo, SP, Brazil) at 11.5-day (Experiments 1 and 2) or 7.5-day intervals (Experiment 2). One day after the onset of estrus (day of AI=D0), the goats were randomly allocated to one of the two groups that received: 300 IU hCG (Vetecor®; Hertape-Calier, São Paulo, SP, Brazil) i.vag. (G-hCG; Experiment 1: n = 12 A; Experiment 2: n = 80 A + 63 S) or 0.3 mL or saline solution i.vag. (G-Control; Experiment 1: n = 12 A; Experiment 2: n = 82 A + 65 S). Blood samples for measurements of circulating progesterone concentrations were drawn on both days of d-cloprostenol injections and on D3, D7, D10, D13 and D21 (Experiment 1). Transrectal ovarian ultrasonography was done on D7, D10, D13, D17 and D21 (Experiment 1), and pregnancy detection was performed on D60 (Experiment 2). In Experiment 1, there were no differences (P > 0.05) in the mean diameter of ovulatory follicles, timing and number of ovulations, and incidence of early luteal regression between the two groups of goats. However, the total luteal area on D17 and D21 and luteal vascularization on D10 and D13 were higher (P < 0.05) in G-hCG compared with G-Control does. In Experiment 2, the pregnancy rate was higher (P < 0.05) in G-hCG compared with G-Control goats (80.4% compared with 67.3%, respectively). Human chorionic gonadotropin (300 IU) given i.vag. at the time of AI did not alter ovulatory response or progesterone secretory ability of resultant corpora lutea nor did it completely prevent premature luteal regression, but it increased the luteal area and luteal vascularization as well as the conception rate in dairy goats (the latter by 13.1%).

Increase of Body Temperature Immediately After Ovulation in Mares.

To successfully inseminate mares, precise detection of ovulation time is crucial, especially when using frozen-thawed semen. Monitoring body temperature, as has been described in women, could be a noninvasive way to detect ovulation. The objective of this study was to investigate the relationship between the time of ovulation and the variation of body temperature in mares based on automatic continuous measurements during estrus. The experimental group included 21mares for 70analyzed estrous cycles. When the mares showed estrous behavior, they were administered intramuscular deslorelin acetate (2.25mg) in the evening. At the same time, monitoring of body temperature using a sensor device fixed at the left lateral thorax was started and continued for over 60hours. In 2-hour intervals, transrectal ultrasonography was performed to detect ovulation. Estimated body temperature in the 6 hours following ovulation detection was on average 0.06°C +/- 0.05°C (mean+/-SD) significantly higher when compared with body temperature at the same time on the preceding day (P=.01). In addition, a significant effect of PGF2α administration for estrus induction on the body temperature was found, being significantly higher until 6hours before ovulation compared to that of uninduced cycles (P=.005). In conclusion, changes in body temperature during estrus in mares were related to ovulation. The increase in body temperature immediately after ovulation might be used in the future to establish automatized and noninvasive systems to detect ovulation. However, the identified temperature rise is relatively small on average and hardly identifiable in the individual mares.

Comparison of the efficacy of altrenogest versus transdermal progestin patches on estrus synchronization and ovulation in mares.

The adhesive progestin patch was investigated for estrus synchronization in mares because this method is convenient and safe in other species. This study aimed to compare the efficacy of a transdermal progestin patch versus oral altrenogest on estrus synchronization, preovulatory follicle development, and ovulation. Twenty-four broodmares were randomly divided into two groups. In Group 1, mares (n = 12) were fed 0.044 mg/kg altrenogest daily for 14 days. Group 2 (n = 12) mares were treated with adhesive transdermal progestin patches for 14 days. Mares were observed for estrus daily, from day 3 until day 7, after hormone withdrawal. Follicular development was determined by ultrasonography. The preovulatory follicle size and ovulation time after hormone treatments and ovulation rate were determined for both groups. Plasma progesterone levels were measured during the experimental periods and 2 days after hormone termination in both groups. The results revealed that the transdermal progestin patch efficiently controlled follicular growth and estrus synchronization in mares. The percentage of mares exhibiting estrus was similar in the altrenogest (100.00%) and transdermal patch (91.67%) groups. Ovulation rates were equivalent with either altrenogest or progestin patch protocols (91.67% [11/12] vs. 83.33% [10/12]). In addition, the preovulatory follicle size was similar in mares treated with altrenogest and progestin patches. This study revealed that the transdermal progestin patch provides effective estrus synchronization and ovulation, similar to altrenogest treatment. However, the transdermal patch was more convenient with a shorter predictable ovulation time after estrus synchronization and should be considered as an alternative method for mares.

Vaginal and vestibular electrical resistance as an alternative marker for optimum timing of artificial insemination with liquid-stored and frozen-thawed spermatozoa in sows

Development of a pen-side test to objectively determine the ideal time for artificial insemination (AI) in the sow would save producers time and money. Current processes rely on identification of oestrus via subjective behavioural and physiological markers that are indicative of high blood oestrogen concentrations. This study attempted to use measurements of electrical resistance (ER) in the cervical mucus to pinpoint timing of AI accurately enough to lead to equivalent pregnancy rates as a natural mating. Thirty-six sows were divided into 3 groups and observed for signs of oestrus. Seven sows did not show any oestrus behaviour and were excluded from the study. The remaining 29 sows were inseminated via natural mating and conventional oestrus detection (n = 14), or inseminated artificially with either liquid-stored semen (n = 8) or frozen-thawed semen (n = 7) according to timing indicated from electrical resistance measurements in the vagina and vestibule. Sows that were artificially inseminated on the basis of the electrical resistance readings had a lower pregnancy rate (P = 0.034) and less piglets born alive per litter (P < 0.05) than those that were naturally mated according to a conventional oestrus detection regime. However, the pregnancy rate and total piglets born alive did not differ between the two groups that underwent artificial insemination. Change in electrical resistance in the vagina has the potential to accurately predict ovulation timing, but more work is required to refine the timing of AI in relation to the readings before the technique can be adopted by industry.

Artificial intelligence in the service of intrauterine insemination and timed intercourse in spontaneous cycles

To develop a machine learning model designed to predict the time of ovulation and optimal fertilization window for performing intrauterine insemination or timed intercourse (TI) in natural cycles. A retrospective cohort study. A large invitro fertilization unit. Patients who underwent 2,467 natural cycle-frozen embryo transfer cycles between 2018 and2022. None. Prediction accuracy of the optimal day for performing insemination or TI. The data set was split into a training set including 1,864 cycles and 2 test sets. In the test sets, ovulation was determined according to either expert opinion, with 2 independent fertility experts determining ovulation day ("expert") (496 cycles), or according to the disappearance of the leading follicle between 2 consecutive days' ultrasound examinations ("certain ovulation") (107 cycles). Two algorithms were trained: an NGBoost machine learning model estimating the probability of ovulation occurring on each cycle day and a treatment management algorithm using the learning model to determine an optimal insemination day or whether another blood test should be performed. The estradiol progesterone and luteinizing hormone levels on the last test performed were the most influential features used by the model. The mean numbers of tests were 2.78 and 2.85 for the "certain ovulation" and "expert" test sets, respectively. In the "expert" set, the algorithm correctly predicted ovulation and suggested day 1 or 2 for performing insemination in 92.9% of the cases. In 2.9%, the algorithm predicted a "miss," meaning that the last test day was already ovulation day or beyond, suggesting avoiding performing insemination. In 4.2%, the algorithm predicted an "error," suggesting performing insemination when in fact it would have been performed on a nonoptimal day (0 or -3). The "certain ovulation" set had similar results. To our knowledge, this is the first study to implement a machine learning model, on the basis of the blood tests only, for scheduling insemination or TI with high accuracy, attributed to the capability of the algorithm to integrate multiple factors and not rely solely on the luteinizing hormone surge. Introducing the capabilities of the model may improve the accuracy and efficiency of ovulation prediction and increase the chance of conception. HMC-0008-21.

Effect of hCG administration on ovulation and estrus in Saanen goats subjected to short-term estrus synchronization protocol during the breeding season

This study aimed to compare the effect of hCG administered at 24 or 36 h following a short-term estrus synchronization treatment on the ovulation time and estrus parameters in non-lactating Saanen goats during the breeding season. The estrous cycles of does were synchronized with an intravaginal sponge containing 60 mg of medroxyprogesterone acetate (MAP) for six days, and an injection of 125 µg of d-cloprostenol at the time of sponge insertion in addition to an injection of 300 IU of eCG 24h before sponge removal. After removal of the sponges, does were injected intramuscularly either 1 ml physiological saline (0.9% NaCl) solution after 12 h (Group1/Control; n=10), 100 IU hCG after 24 h (Group2; n=9) or 100 IU hCG after 36 h (Group3; n=9). Estrus behavior after sponge removal was observed twice daily for 84 h using teaser bucks and transrectal ovarian ultrasonography was performed twice a day for seven days to determine small, medium and large follicle numbers, luteal development and the time of ovulation. Blood samples were collected on the same days to determine serum progesterone (P4) and estradiol (E2) concentrations. No significant differences were observed in terms of estrus parameters, ovarian structure and serum P4 and E2 concentrations between the hCG-treated groups and the control group. Average values observed for all groups: estrous response (53.57%), the interval from sponge removal to estrus and ovulation (35.2 h and 67.86 h, respectively), duration of estrus (18.4 h), the interval from estrus onset to ovulation (50.37 h), ovulation rate (96.43%), number of ovulations (1.36), ovulatory follicle diameter (6.86 mm), corpus luteum diameter (8.22 mm), follicle and luteal growth rate (1.17 and 0.68 mm/day, respectively). In conclusion, administration of hCG at 24 or 36 h following a short-term estrous synchronization protocol does not affect ovulation time, estrus parameters, and serum P4 and E2 concentrations in goats during the breeding season.

DETERMINATION OF OVULATION TIME IN GAYO MARES BASED ON IMAGE OF PREOVULATORY FOLLICLE GROWTH

This study aimed to obtain the ultrasound image of preovulatory follicle growth in gayo mares to predict the ovulation time. This study used three Gayo mares and one gayo stallion for teaser aged 5-10 years and weighed 200-250 kg. Preovulatory follicle growth was observed using transrectal ultrasonography which was performed when the dominant follicle size was ≥ 3.5 cm. Observations were made for 3 consecutive estrous periods on gayo mares at relatively the same time. The absence of previous follicular appearance and the presence of hypoechoic area in the same ovary indicate that ovulation has occurred. The result revealed that the diameter of preovulatory follicle of gayo mares was 4.02±0.32 to 5.05±0.04 cm. There was no significant follicle growth in the last 48 hours before ovulation and the preovulatory follicle shape altered from spherical to pearshape. Many small follicles (2 cm in diameter) were observed in peripheral area of the ovary indicated the recruitment of follicles which form the first follicular wave. To conclude, the alteration in the size and pearshape of preovulatory follicle and the recruitment of small follicles can be used as a marker to determine the time of ovulation on gayo mares.

O-296 Progesterone level is an alternative marker to detect ovulation time in natural cycle frozen-thawed embryo transfers

Abstract Study question Do serum progesterone or LH levels better predict the optimal timing for embryo transfer in true natural cycle frozen-thawed embryo transfers (NC-FET)? Summary answer Performing embryo transfer according to serum progesterone levels (PL) had similar ongoing pregnancy rates compared to embryo transfer according to serum LH levels. What is known already With efficient and safe embryo vitrification techniques, there is an increasing trend in frozen-thawed embryo cycles (FET) over fresh cycles. FET protocols are programmed cycle, NC-FET and modified NC-FET. NC-FET is increasing in popularity, since it is associated with favourable obstetric and perinatal outcomes. In NC-FETs, ovulation time is the critical parameter for synchronization of embryo and endometrium. In the literature, LH surge is the most commonly used test to define ovulation time. Study design, size, duration This prospective cohort study included 183 NC-FET cycles in an IVF clinic between March 2022 and November 2022. Main outcome measure is ongoing pregnancy. Participants/materials, setting, methods 183 subfertile women aged between 18-40, having regular menstruation with a cycle length between 24-38 days are included. Protocol for NC-FET included serial hormone measurements and ultrasound monitoring when the dominant follicle reached the diameter of 15-16 mm. Serum LH level ≥15 IU/l defined as ‘ovulation -1’ in Group 1 and blastocyst embryo transfer was performed after 6 days. Serum PL &amp;gt; 1 ug/ml was defined as the ‘ovulation day’ in Group 2. Main results and the role of chance: There were no significant differences in baseline characteristics including female age, female body mass index, infertility duration, infertility diagnosis and number of failed IVF cycles between two groups. Also, cycle characteristics regarding endometrial thickness, number of embryos transferred, embryo quality and PLs at transfer day were similar. The overall clinical pregnancy was 59.6% and ongoing pregnancy was 50.8%. The implantation rate was 61.7%. The clinical pregnancy and ongoing pregnancy of Group 1 and Group 2 were 49.5%, 50.5% and 47.3%, 52.7%, respectively (p &amp;gt; 0.05). PLs in order to detect ovulation time were calculated according to a mathematical modelling (PL(Ov )=a1 eb1 Ov )(Ov:ovulation day; a1,b1:regression coefficients; e:euler number≌2.718) described in our previous study. Embryo transfer timing was planned after 5,4 or 3 days based on PLs calculated by modelling. Limitations, reasons for caution Since this is the first study planning embryo transfer in NC-FET based on progesterone levels, sample size should be increased and also serial change of progesterone levels were unknown in women &amp;gt;40 years of age. Wider implications of the findings Progesterone has a particular increasing pattern that enables ovulation day prediction accurately and may be used instead of serum LH levels in timing of embryo transfer. Trial registration number NCT05690360

P-621 Machine learning software significantly increase clinical pregnancy rates in natural frozen-thawed embryo transfer cycles

Abstract Study question To study the effect of physician support software for determining ovulation time on pregnancy outcomes in natural cycle frozen embryo transfers (NC-FET) Summary answer Match between the physician and the algorithm regarding the time of ovulation in NC-FET cycles resulted in significant 14.4% increase in clinical pregnancy rates. What is known already Today the preferred method for frozen embryo transfer is natural cycle based on ovulation detection. As of today, an algorithm for predicting ovulation has not been developed and its use and its effect on success rates have not been tested. The aim of this study was to test a physician support artificial intelligence (AI) software for determining ovulation time and to study the effect of its use on pregnancy outcomes in frozen-thawed embryo transfers (NC-FET). Study design, size, duration NC-FET cycles from September 2018 to June 2021 were used to develop ovulation detection algorithm. Next, the effect of the selection of the ovulation date by the algorithm on pregnancy rates was tested by retrospective analysis on NC-FET cycles performed between July 2021 to June 2022. Cycles were divided into two groups: The Matched group in which there was a match between the ovulation date set by the physician and the algorithm and Mismatched group. Participants/materials, setting, methods Study group included 349 single embryo transfer patients after applying strict inclusion criteria. The Matched group included 198 patients and 151 patients in the Mismatched group. Patient's age, BMI, smoking, number of past retrievals and past embryo transfers, endometrium thickness, embryos age and quality, number of tests per cycle and pregnancy rates were compared. Statistical analysis included multivariable logistic regression to study the association between Match/Mismatch and clinical pregnancy rates while controlling for potential confounders Main results and the role of chance Matched group and Mismatched group had similar characteristics. Mean patients age at oocyte retrieval were 34.5 + 5.5 vs. 34.7 + 5.5 respectively (p=0.72). Clinical pregnancy rate in the Matched group were 38.9% compared to 24.4% in the Mismatched group (p =0.006). The difference was particularly noticeable when day 3 embryos were transferred (39.8% vs. 17.6% respectively p=0.009), and was also observed on day 5 embryos transfer, although non-significant (39.1% vs. 30.0% respectively, p=0.197). In the Matched group the chance of pregnancy actually almost doubled (OR = 1.97, CI 95% 1.23-3.17, p=0.005) while controlling potential confounders. Further analysis of the Mismatch group found that in 120 cycles (%) the doctor set the ovulation date one day or more before the date set by the algorithm and in 31(%) cases the date was a day or more after the ovulation date according to the algorithm. Logistic regression showed that the chance of pregnancy was significantly affected when the doctor determines the day of ovulation earlier than the algorithm (OR = 0.42, CI 95% 0.29-1.43, p=0.005) Limitations, reasons for caution Although cycles selected for comparison were controlled for key factors that affect pregnancy outcomes, The main drawback is the retrospective analysis. Further prospective randomized trials are needed to study the effectiveness of the algorithm and its effect on treatment results. Wider implications of the findings This is the first AI algorithm designed to predict ovulation. Using AI algorithms in NC-FET can help in identifying ovulation accurately and reliably and may increase pregnancy rate Trial registration number Not applicable

P-787 Ovarian morphology and length of follicular phase differ between immediate and postponed modified natural-cycle frozen embryo transfer (mNC-FET) cycles – Sub-study of an ongoing RCT

Abstract Study question Does ovarian morphology and length of the follicular phase differ between immediate and postponed mNC-FET cycles? Summary answer More cystic follicular residue after oocyte pick-up was observed at cycle day 2-5 in immediate vs postponed mNC-FET. The immediate follicular phase was longer. What is known already Whether the optimal timing for treatment with mNC-FET is in the cycle immediately following ovarian stimulation (OS) and oocyte pick-up, or in a subsequent cycle, has been much debated. Recent evidence suggests that reproductive outcomes after immediate vs postponed FET are comparable or even better in programmed-cycle FET. Due to concerns about suboptimal ovarian and endocrinological conditions in the natural cycle immediately following an OS/IVF cycle, postponed FET has become the standard treatment in most settings. However, studies describing attributes of the immediate NC-FET are lacking and little is known about cycle characteristics and ovarian morphology shortly after oocyte pick-up. Study design, size, duration The present descriptive sub-study is based on data from an ongoing Danish, multicentre, randomised controlled trial (RCT), investigating if mNC-FET can be performed in the cycle immediately following OS and oocyte pick-up, without compromising pregnancy and live birth rates. Participants were randomized 1:1 to mNC-FET in the immediate vs a subsequent cycle. The first 102 participants were included in the present sub-study. Data was collected between April 2021 and December 2022. Participants/materials, setting, methods Women with a regular menstrual cycle, aged 18-40 years, undergoing single blastocyst mNC-FET were eligible for inclusion. Ovarian morphology and cycle length were compared between immediate and postponed mNC-FET using Chi-squared test for categorical variables, and independent sample T-test or Mann Whitney U-test for continuous variables. Categorical variables were reported as numbers and percentages, continuous variables as mean and standard deviation or median and range. Main results and the role of chance Background characteristics including age, BMI, AMH and normal cycle length were similar for women in the immediate and postponed group, apart from a lower rate of elective freeze all-transfers (30.2% vs 55.1%, p = 0.011) in the OS cycle preceding FET, in the immediate vs the postponed group. The total number of cystic follicular structures (hypo- and non-hypodense) &amp;gt;10 mm (2 (range 0-11) vs 0 (range0-3), p = &amp;lt;0.001) were higher in the immediate vs the postponed group on cycle day (CD) 2-5 of the treatment cycle. On the day of hCG-trigger, there was no significant difference in the total number of cystic follicular structures between the groups, but a higher number of non-hypodense structures was found in the immediate group (p = 0.021). Endometrial thickness was greater in the immediate vs postponed group (8.6 vs 7.8 mm, p = 0.031) while the mean size of the dominant follicle was similar 17.1 vs 17.3 mm between groups (p = 0.410). The average day of hCG-trigger was CD15 (range 9-24) in the immediate group compared to CD12 (range 5-28) in the postponed group (p = 0.001). More ultrasound scans of follicular development were needed in the immediate vs postponed group (3 vs 2, p = 0.012). Limitations, reasons for caution The proportion of elective freeze-all in the OS cycle preceding FET differed between the immediate and postponed group which may bias the results. The sample size limits stratified analyses. Wider implications of the findings The findings of this study indicate that cystic follicular ovarian structures shortly after oocyte pick-up are commonly occurring. However, most of these structures seems to regress before the time of ovulation. The follicular phase was longer in immediate cycles, and whether this effects pregnancy outcomes is yet unknown. Trial registration number NCT04748874

P-599 The use of serum test to detect the LH surge in ultrasound-monitored intrauterine insemination (IUI) significantly increases pregnancy rates.

Abstract Study question Could a serum test to detect LH surge in ultrasound-monitored IUI cycle improve pregnancy rates? Summary answer Serum test to detect LH surges with ultrasound monitoring during IUI cycle significantly increased pregnancy rates. What is known already IUI is known as the first line of treatment for infertile couples and is usually administered with human chorionic gonadotropin (hCG) before ovulation with clomiphene citrate (CC) or/and human menopausal gonadotropin (hMG) to ovarian known to stimulate. One of the key factor for IUI is that insemination should be performed close to ovulation time, as there are many reports that sperm injection at the ovulation time has a high pregnancy rates. However, there are still few reports on the optimal timing of ovulation for performing IUI. Study design, size, duration The IUI performed from January 2016 through November 2022 (n = 3187) was included in this study. A total of 875 patients underwent the IUI by inferring LH surge with procedure with serum test, while 2312 patients underwent the procedure IUI without the serum test (control). Participants/materials, setting, methods In this study included 3187 IUI cycle were analyzed. Controlled ovarian hyperstimulation was conducted with CC (100 mg/day) and hMG. Patients were divided into two groups with serum test or not test (control). The serum test group was monitored LH surge by inferring LH peak during IUI cycle. When the sufficient follicular size and endometrial thickness had been reached, hCG was administrated and insemination was performed. Pregnancy rates were compared by Chi-squared test. Main results and the role of chance In each group, there were no significantly difference in age (34.4±3.7 vs. 34.7±3.7 years old) and endometrial thickness (8.8±2.2 vs. 8.9±2.2 mm) for IUI cycle condition. The serum test group was significantly higher clinical pregnancy rates compared to control group (19.0 vs. 15.7 % respectively) during IUI cycle (P &amp;lt; 0.05). In addition, patients were classified according to the history of at least one or more failed IUI cycle. The clinical pregnancy rates was significantly higher in the serum test group than control group (21.6 vs. 10.8 % respectively) who history of at least one or more failed IUI cycle (P &amp;lt; 0.001). Limitations, reasons for caution A limitation of this study has a too small size of the intervention group compared with the control group. Wider implications of the findings In our results, the serum test group had a significantly higher clinical pregnancy rates than the control group. Therefore, detecting a surge in LH with a serum test during the IUI cycle could predict the optimal timing of ovulation and thus increase the pregnancy rates. Trial registration number not applicable

O-292 Does ovulation trigger enhance live birth in a natural cycle for frozen embryo transfer: A randomized controlled trial

Abstract Study question Does ovulation trigger enhance pregnancy rate in a natural cycle (NC) for frozen embryo transfer (FET)? Summary answer Pregnancy rates after a FET are similar in a natural cycle with detection of a spontaneous LH surge or with a triggered ovulation. What is known already Several studies have explored whether one approach might appear to be more beneficial in terms of pregnancy or live birth rates, but with inconsistent results. Thus, the best protocol to identify the time of ovulation in NC and to plan the FET is still undefined. Study design, size, duration This was a bicentric, two-arm, randomized, controlled and open-label trial, including 108 patients for 18 months. In the spontaneous-NC group, the LH surge was defined as a rise of the serum LH level at least three times above the basal LH serum value with a serum progesterone level three days after the LH surge above 3 ng/mL. Participants/materials, setting, methods Patients included were aged 18- to 39-year-old, had regular cycles and were planned for an autologous frozen day-5 blastocyst transfer in a NC. They did not have endometriosis stage AFSr 3 nor 4 nor adenomyosis. Fifty-four patients per group were included. In the modified-NC group, a spontaneous LH surge was observed in 16 women before the hCG-trigger could be administrated: they were re-allocated to the spontaneous-NC for the per-protocol (PP) analysis. Main results and the role of chance Patients characteristics were comparable in both groups. Pregnancy rates were similar in the spontaneous-NC and the modified-NC group in the intention-to-treat (ITT) (41.3 versus 37.8% respectively, p = 0.85) and in the PP analysis (39.3% versus 40% respectively, p = 0.9). Ongoing pregnancy, miscarriage and live birth rates were also similar. Significantly more visits were needed in the spontaneous-NC (3.4 ± 0.81 versus 2.59 ± 1.0, p &amp;lt; 0.0001 in the ITT analysis and 3.18 ± 0.93 versus 2.63 ± 1.03, p = 0.0064 in the PP analysis). Limitations, reasons for caution Due to group redistribution (spontaneous LH surge before hCG trigger), the number of subjects in the modified-NC group is low for the PP analysis. This may reduce the power of the trial which may fail to detect a small difference. Wider implications of the findings The results reinforce previous data that showed similar efficacy of the s-NC and the m-NC. This allows the patient to choose from several options depending on her preference. Trial registration number NCT03428165

P-656 Machine learning algorithm automatically manages and accurately predicts ovulation in natural frozen-thawed embryo transfer cycles.

Abstract Study question Can an Artificial Intelligence (AI) algorithm automatically manage frozen-thawed embryo transfer (NC-FET) treatment cycles and give an accurate prediction of ovulation day. Summary answer An AI algorithm automatically managed and predicted the ovulation of NC-FET treatment cycles with 94.8% accuracy using an average of 3.01 test days. What is known already Today the preferred method for frozen embryo transfer is natural cycle based on ovulation detection. Currently, there is no software capable of managing the treatment cycle automatically and identifying the time of ovulation to support doctor decisions. The aim of this study is to develop a physician support AI software for determining ovulation time reliably with high accuracy. Study design, size, duration 2083 NC-FET cycles from September 2018 to June 2021 were used to develop the ovulation detection and treatment management algorithms. Each cycle had data from at least 2 visits including: hormonal levels (Estrogen/Progesterone/LH) and follicle sizes. The dataset was divided into a train set and two test sets. In the 1st test set ovulation was determined by experts’ opinions and the 2nd test set included cycles in which follicle rupture was documented in consecutive ultrasounds. Participants/materials, setting, methods Two algorithms were developed, an ovulation prediction algorithm based on an NGBoost model and a treatment management algorithm that used the model to determine if and when to call for a new test or declare the ovulation day. Both algorithms were jointly tuned to reach the highest success rate, defined as providing the correct day of ovulation using the available cycle data, with as few test days as possible. Main results and the role of chance On the first test set, which consisted of 176 cycles in which ovulation was determined through the majority decision of 2 independent experts and the attending physician, the treatment management algorithm required on average 3.01 tests to reach a prediction and successfully predicted the ovulation day in 94.8% of cycles. In the second test set, which consisted of 29 cycles in which ovulation was determined through the follicular rupture in two consecutive ultrasounds, only the ovulation prediction model was tested. To ensure that the model provides a reliable answer and does not rely solely on the follicular disappearances, examined cycles were tested twice: Once using the ovulation day without the day prior to it, and again using only the day prior to ovulation without the ovulation day itself. The algorithm accurately predicted ovulation in 28 out of 29 instances (96.6%) using the day of ovulation and in 28 out of 29 instances (96.6%) using the day before ovulation. Limitations, reasons for caution The main drawback is this being a retrospective study: while the algorithm was trained to maximize accuracy when it selects the test days, the dataset test days were selected by the attending physicians. Statistical methods were used to overcome this, however further prospective trials are needed to validate the results. Wider implications of the findings This is the first AI algorithm designed to automatically manage NC-FET IVF treatment cycles and predict ovulation. The high accuracy and low average tests count might improve treatment outcomes, reduce the patients’ life disruption, and allow physicians to spend less time monitoring their patients’ treatments. Trial registration number not applicable