Intrauterine insemination timing models-LH can only take you so far.

RESEARCH QUESTION: Can an optimal LH threshold algorithm accurately predict timing of ovulation for natural cycle-intrauterine insemination (NC-IUI)? DESIGN: A retrospective cohort study (2018-2022) including 2467 natural cycles. Ovulation timing for these cycles was determined using a previously developed AI model. Two LH thresholds, low and high, were determined in the LH algorithm. Being below the low threshold meant that ovulation is likely to occur in ≥ 4 days, suggesting another daily blood test. Between the two thresholds meant that ovulation was likely in 2-3 days, suggesting IUI the next day. Above the high threshold meant that ovulation will likely occur tomorrow, suggesting performing IUI on the same day. RESULTS: The optimal LH model with a high threshold of 40 mIU/ml and a low threshold of 11 mIU/ml succeeded in correctly predicting timing for IUI (day - 1, - 2 relative to ovulation) in 75.4% (95%CI 75.3-75.4). In 23.1% (95%CI 23.0-23.2), the algorithm predicted "error," suggesting performing insemination when in fact it would have been performed on a non-optimal day (0 or - 3). A previously described 3-hormone-based (LH, estradiol, progesterone) AI model performed significantly better in all parameters (93.6% success rate, 4.3 "error" rate). CONCLUSIONS: An LH threshold model, representing common practice, evaluating all possible high and low LH threshold combinations, was successful in accurately scheduling timing for IUI in only 75% of cases. Integrating all three hormones as performed in the AI model may have an advantage in accurately predicting the optimal time for IUI, over the use of LH only.

The effect of COVID-19 vaccination during IVF stimulation on cycle outcomes- a retrospective cohort study.

The effect of the mRNA-BNT162b2 vaccine administered prior to fertility treatments has been addressed in several studies, presenting reassuring results. Cycle outcomes of patients receiving the vaccine during the stimulation itself have not been previously described. This retrospective cohort study included patients who received mRNA-BNT162b2-vaccine during the stimulation of fresh IVF cycles, between January-September 2021, age matched to pre-stimulation vaccinated patients and to non-vaccinated patients. Demographics, cycle characteristics and cycle outcomes were compared between groups. A total of 132 in-treatment vaccinated patients (study group), 132 pre-treatment vaccinated and 132 non-vaccinated patients that underwent fresh IVF cycles were included. Mean time from vaccination to retrieval in the study group was 6.68 days (SD 3.74; range 0-12). Oocyte yield was similar between groups (9.35 versus10.22 and 10.05 respectively; p=0.491). A linear regression model demonstrated no effect of vaccination before or during the stimulation, on oocyte yield (p>0.999). Clinical pregnancy rates (30 % versus 30 % versus 28 %) and ongoing pregnancy rates (25 % for all groups) did not differ between groups. In a logistic regression model for clinical pregnancy rates, vaccine administration and timing of vaccination were not a significant factor. This is the first study reporting the outcome of the mRNA BNT162b2 vaccine administration during the IVF stimulation itself. The vaccine administration had no impact on fresh IVF treatment outcomes compared to pre-treatment vaccinated or non-vaccinated patients. This adds to the growing evidence of COVID-19 vaccine safety in relation to fertility treatments and enables more flexibility regarding timing of vaccine administration.

Follicular challenge test to predict suboptimal response to gonadotropin releasing hormone agonist trigger in elective oocyte cryopreservation cycles.

This prospective study aimed to test the ability of follicular GnRH agonist challenge test (FACT) to predict suboptimal response to GnRH agonist trigger, assessed by LH levels post ovulation trigger in non-medical oocyte cryopreservation program. The study included 91 women that underwent non-medical fertility preservation. On day two to menstrual cycle, blood tests were drawn (basal Estradiol, basal FSH, basal LH, Progesterone) and ultrasound (US) was performed. On that evening, the women were instructed to inject 0.2 mg GnRH agonist (FACT) and arrive for repeated blood workup 10-12 h later in the next morning, followed by a flexible antagonist protocol. LH levels on the morning after ovulation trigger were compared to FACT LH levels. The results demonstrated that LH levels following agonist ovulation trigger below 15IU/L occurred in 1.09% of cycles and were predicted by FACT, r = 0.57, p < 0.001. ROC analysis demonstrated that FACT LH > 42.70 IU/L would predict LH post trigger of more than 30 IU/L with 75% sensitivity and 70% specificity, AUC = 0.81. LH levels post trigger also displayed significant positive correlation to basal FSH (r = 0.35, p = 0.002) and basal LH (r = 0.54, p < 0.001). LH levels post ovulation trigger were not associated with total oocytes number or maturity rate. The strongest correlation to the number of frozen oocytes was progesterone levels post agonist trigger (r = 0.746, p < 0.001). We concluded that suboptimal response to agonist trigger, as assessed by post trigger LH levels was a rare event. FACT could serve as an adjunct pre-trigger, intracycle tool to predict adequate LH levels elevation after agonist ovulation trigger. Future studies should focus on optimization of agonist trigger efficacy assessment and prediction, especially in high responders.

Israeli students' perceptions regarding sperm donation: dilemmas reflections with dominant demographic effect.

BACKGROUND: Sperm donation has undergone significant medical and social transformations in recent decades. This study aimed to explore Israeli students' perceptions towards sperm donation and investigate the potential influence of demographic characteristics on these perceptions. DESIGN: The study encompassed 254 students from Tel-Aviv University, who completed an anonymous online survey in January-February 2021. This cross-sectional quantitative online survey, comprised 35 questions categorized into three sections: demographic data, assessment of prior knowledge, and perceptions of sperm donation (general perceptions related to both positive and negative stigmas associated with sperm donation, the roles and activities of sperm banks, and considerations surrounding identity disclosure versus the anonymity of sperm donors and their offspring). RESULTS: Participants exhibited a relatively low level of prior knowledge (mean 31.2 ± 19 of 100). Scores for positive and negative stigmas ranged from 1.3 to 2.2. Notably, the statement "Donors' anonymity preservation is crucial to maintain sperm donation" received a mean of 3.7. Seeking for anonymous sperm donation identity both by recipients and offspring was ranked with low means (1.5 and 1.7, respectively). However, the pursuit of half-siblings by mothers or siblings themselves received higher ratings ranging from 2.7 to 3. Women's stigma ranking were notably lower, while men emphasized the importance of donor anonymity. CONCLUSIONS: Sperm Banks hold a position of medical authority rather than being perceived as being commercial entity. The preservation of donor anonymity is widely accepted as a crucial element, prioritized over the requests for identity disclosure from recipients and offspring. Demographic parameters exhibit a strong and precise effects on participants' perceptions.

Autologous sperm usage after cryopreservation-the crucial impact of patients' characteristics.

BACKGROUND: The wide implementation of sperm freezing presents a growing burden on sperm banks. OBJECTIVES: To evaluate sperm freezing and usage patterns over 30 years, according to demographic parameters of age at first cryopreservation and number of children, and indication for cryopreservation. MATERIAL AND METHODS: This retrospective, population based, cohort study included all sperm cryopreservation cases performed at a tertiary referral center from October 1993 to December 2021, among patients aged 18 years and older. First, we determined the interval between first sperm sample and use. Then, we examined sperm usage separately for: (1) age, comparing patients grouped into 5-year age cohorts; (2) paternal status according to number of children; (3) indication, comparison among seven indications. Secondary analysis included correlations between main age groups and paternal status versus the four most common indications found. RESULTS: During the study period 1490 men who cryopreserved sperm met the inclusion criteria. Average age at cryopreservation of the first sample was 33.9 ± 8.1 years. Average age at first sperm use was 37 ± 8.5 years. Cumulative sperm usage was 38.7% after 17.8 years. Increasing age was associated with progressive increase in sperm usage rate and shorter preservation period. Use significantly decreased with increasing number of children. Examination of seven reasons for sperm cryopreservation found the highest cumulative sperm usage was related to azoospermia (67.7%), followed by functional cryopreservation (39.3%), oligoasthenoteratospermia (27.3%), other (26.5%), patient's request (24%), cancer (19%), and systemic disease (7.2%). Secondary analysis defined specific usage patterns mainly related to age and indication, with less of an effect based on the number of children. DISCUSSION AND CONCLUSION: After decades of cryopreservation, the paradigm of sperm cryopreservation is mostly related to cancer patients. This should be reevaluated and evolve to include broader patient-targeted factors and perceptions.

An artificial intelligence-based approach for selecting the optimal day for triggering in antagonist protocol cycles.

RESEARCH QUESTION: Can a machine-learning model suggest an optimal trigger day (or days), analysing three consecutive days, to maximize the number of total and mature (metaphase II [MII]) oocytes retrieved during an antagonist protocol cycle? DESIGN: This retrospective cohort study included 9622 antagonist cycles between 2018 and 2022. The dataset was divided into training, validation and test sets. An XGBoost machine-learning algorithm, based on the cycles' data, suggested optimal trigger days for maximizing the number of MII oocytes retrieved by considering the MII predictions, prediction errors and outlier detection results. Evaluation of the algorithm was conducted using a test dataset including three quality groups: 'Freeze-all oocytes', 'Fertilize-all' and 'ICSI-only' cycles. The model suggested 1, 2 or 3 days as trigger options, depending on the difference in potential outcomes. The suggested days were compared with the actual trigger day chosen by the physician and were labelled 'concordant' or 'discordant' in terms of agreement. RESULTS: In the 'freeze-all' test-set, the concordant group showed an average increase of 4.8 oocytes and 3.4 MII oocytes. In the 'ICSI-only' test set there was an average increase of 3.8 MII oocytes and 1.1 embryos, and in the 'fertilize-all' test set an average increase of 3.6 oocytes and 0.9 embryos was observed (P < 0.001 for all parameters in all groups). CONCLUSIONS: Utilizing a machine-learning model for determining the optimal trigger days may improve antagonist protocol cycle outcomes across all age groups in freeze-all or fresh transfer cycles. Implementation of these models may more accurately predict the number of oocytes retrieved, thus optimizing physicians' decisions, balancing workloads and creating more standardized, yet patient-specific, protocols.

Sperm Donors' Identity Disclosure: Is It REALLY Crucial? For Whom?

OBJECTIVE: To study the preference of sperm donors with identity disclosure (ID) versus anonymous donors (AD) and to understand if this selection affects clinical outcomes in an Israeli population. METHODS: This retrospective study included patients who chose imported sperm donation during 2017-2021. Of these, 526 used their own (autologous) oocytes and 43 patients used donated oocytes (DO). The primary endpoint was the type of chosen donor with ID versus AD. We examined the tendency toward ID according to demographic parameters and the theoretical impact of donor-type selection on reproductive outcome and compared patients who performed cycles with autologous oocytes with those using DO. RESULTS: Single women had a significantly higher probability of choosing sperm donors with ID than heterosexual couples (55.6% vs. 33.3%, OR 2.5, CI 95% 1.52-4.11, P < 0.001). Although not significant, same-sex couples were more likely to choose sperm donors with ID than heterosexual couples (49.1% vs. 33.3%, OR 1.93, CI 95% 0.97-3.85, P = 0.06). Sperm donor samples, 2501 vials, were imported. It was performed 698 intra-uterine insemination and 812 in vitro fertilization cycles were performed, respectively, resulting in 283 pregnancies without differences between patients who chose sperm donors with ID versus AD sperm. No significant differences were observed regarding the option for sperm donors with ID between patients using DO (44.2%) and those using autologous oocytes (51.3%). CONCLUSION: While ID is important for a certain section (mainly single) of recipients, it is far from the only dominant factor during donor selection. Sperm donation type does not impact clinical outcomes.

Critical Demographic Changes among Sperm Donation Recipients Over Three Decades.

BACKGROUND: Sperm banks initially focused on providing sperm donation (SD) to heterosexual couples grappling with severe male infertility. Notable advancements in fertility treatments and sociological trends have broadened the scope of SD toward single women and same sex female couples. OBJECTIVES: To evaluate SD recipient characteristics over the last three decades in Israel according to demographic parameters. METHODS: This retrospective cohort study included 5489 women who received SD between January 1992 and December 2021 from a tertiary referral center. We divided the overall period into six groups of five years each. A comparison of demographic characteristics of women who received SD in different periods was performed according to age at the beginning of the treatment, marital status (single women and same sex female couples, heterosexual couples), and ethnic origin. RESULTS: The average age of women who received SD was 37.02 ± 5.36 years. The average patient age rose from 35.08 years in 1992-1997 to 37.43 years in 2017-2021 (P-value < 0.01). The use of SD was more common among single women and same sex female couples compared to heterosexual couples in later years. Regarding single and same sex female couple, the percentage of SD recipients increased radically from 33% to 88.1% (P-value < 0.01). CONCLUSIONS: Modern sperm banks treat older patients in non-heterosexual relationships. These trends encompass not only medical implications (e.g., in vitro fertilization vs. intrauterine insemination) but also delve into the personal and sociological impact experienced by both patients and offspring.

Prediction of ovulation: new insight into an old challenge.

Ultrasound monitoring and hormonal blood testing are considered by many as an accurate method to predict ovulation time. However, uniform and validated algorithms for predicting ovulation have yet to be defined. Daily hormonal tests and transvaginal ultrasounds were recorded to develop an algorithm for ovulation prediction. The rupture of the leading ovarian follicle was a marker for ovulation day. The model was validated retrospectively on natural cycles frozen embryo transfer cycles with documented ovulation. Circulating levels of LH or its relative variation failed, by themselves, to reliably predict ovulation. Any decrease in estrogen was 100% associated with ovulation emergence the same day or the next day. Progesterone levels > 2 nmol/L had low specificity to predict ovulation the next day (62.7%), yet its sensitivity was high (91.5%). A model for ovulation prediction, combining the three hormone levels and ultrasound was created with an accuracy of 95% to 100% depending on the combination of the hormone levels. Model validation showed correct ovulation prediction in 97% of these cycles. We present an accurate ovulation prediction algorithm. The algorithm is simple and user-friendly so both reproductive endocrinologists and general practitioners can use it to benefit their patients.

Motivational stimuli to donate sperm among non-donor students.

BACKGROUND: Sperm banks face a continuously evolving gap between the increasing demand for sperm donation (SD) vs. limited available reserve. To improve donors' recruitment and increase supply, motivations towards SD should be investigated specifically among young men who have the potential to become donors. Our aim was to evaluate factors which increase and decrease predisposition to donate sperm among non-donor students, who represent a "potential pool" for possible donors' recruitment. RESULTS: Ninety-three men fulfilled the questionnaire with mean age of 28.2 ± 4.5 years. The most powerful incentive to donate sperm was financial reward followed by a willingness to help others to build a family (3.8 and 3.4, respectively). The most dominant consideration to decline donation was the fear of anonymity loss and future regret (4 and 3.8). While participants' willingness for anonymous SD was fair (2.8), the open-identity donation was rated significantly lower (1.75, p < 0.01). Familiarity with recipients and offspring had lower scores (1.9-2.2) as well. CONCLUSIONS: Young single men represent a suitable cohort for anonymous donation. Financial reward and willingness to help others are important positive incentives while anonymity preservation is crucial to maintain their willingness towards SD. Regulatory shifting towards open-identity SD necessitates the establishment of an alternative "potential pool" population as a reliable source to recruit donors.

RéSUMé: CONTEXTE: Les banques de sperme font face à un écart en constante évolution entre la demande croissante de dons de sperme et les réserves disponibles limitées. Pour améliorer le recrutement des donneurs et augmenter l'offre, les motivations à l'égard du don de sperme devraient être étudiées spécifiquement chez les jeunes hommes qui ont le potentiel de devenir donneurs. Notre objectif était d'évaluer les facteurs qui augmentent et diminuent la prédisposition au don de sperme chez les étudiants non-donneurs, qui représentent un « bassin potentiel ¼ pour le recrutement possible de donneurs. RéSULTATS: Ninety-three hommes ont rempli le questionnaire avec un âge moyen de 28,2±4,5 ans. L'incitation la plus puissante à donner du sperme était la récompense financière, suivie de la volonté d'aider les autres à fonder une famille (3,8 et 3,4, respectivement). La considération la plus dominante pour refuser le don était la peur de perdre l'anonymat et les regrets futurs (4 et 3.8). Alors que la volonté des participants de faire un don anonyme de sperme était passable (2,8), le don d'identité ouverte a été jugé significativement plus faible (1,75, p<0,01). La familiarité avec les receveurs et la progéniture avait également des scores plus faibles (1,9-2,2). CONCLUSIONS: Les jeunes hommes célibataires représentent une cohorte appropriée pour le don anonyme. La récompense financière et la volonté d'aider les autres sont des incitations positives importantes, tandis que la préservation de l'anonymat est cruciale pour maintenir leur volonté de donner du sperme. L'évolution réglementaire vers le don de sperme à identité ouverte nécessite l'établissement d'une population alternative de « bassin potentiel ¼ comme source fiable pour recruter des donneurs.

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

OBJECTIVE: 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. DESIGN: A retrospective cohort study. SETTING: A large in vitro fertilization unit. PATIENT(S): Patients who underwent 2,467 natural cycle-frozen embryo transfer cycles between 2018 and 2022. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Prediction accuracy of the optimal day for performing insemination or TI. RESULT(S): 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. CONCLUSION(S): 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. CLINICAL TRIAL REGISTRATION NUMBER: HMC-0008-21.

ABCC4 is a PGE2 efflux transporter in the ovarian follicle: A mediator of ovulation and a potential non-hormonal contraceptive target.

The role of prostaglandins (PGs) in the ovulatory process is known. However, the role of the ATP binding cassette subfamily C member 4 (ABCC4), transmembrane PG carrier protein, in ovulation remains unknown. We report herein that ABCC4 expression is significantly upregulated in preovulatory human granulosa cells (GCs). We found that PGE2 efflux in cultured human GCs is mediated by ABCC4 thus regulating its extracellular concentration. The ABCC4 inhibitor probenecid demonstrated effective blocking of ovulation and affects key ovulatory genes in female mice in vivo. We postulate that the reduction in PGE2 efflux caused by the inhibition of ABCC4 activity in GCs decreases the extracellular concentration of PGE2 and its ovulatory effect. Treatment of female mice with low dose of probenecid as well as with the PTGS inhibitor indomethacin or Meloxicam synergistically blocks ovulation. These results support the hypothesis that ABCC4 has an important role in ovulation and might be a potential target for non-hormonal contraception, especially in combination with PGE2 synthesis inhibitors. These findings may fill the gap in understanding the role of ABCC4 in PGE2 signaling, enhance the understanding of ovulatory disorders, and facilitate the treatment and control of fertility.

Treatment safety of ART cycles with extremely high oestradiol concentrations using GnRH agonist trigger.

RESEARCH QUESTION: Are IVF treatments with extremely high peak oestradiol levels and gonadotrophin releasing hormone (GnRH) agonist trigger associated with higher complication rates? DESIGN: A retrospective cohort study including patients from two large medical centres treated between 2019 and 2021. A study group with extremely high peak oestradiol levels (≥20,000 pmol/l on the day of ovarian stimulation, or ≥15,000 pmol/l on the previous day) and a control group with normal range oestradiol levels (3000-12000 pmol/l) that received GnRH agonist triggering. Patients were surveyed about complaints and medical care related to ovum retrieval and medical files were reviewed. Major complication rates and the need for medical assistance were compared. RESULTS: Several differences between the study and control group were observed because of the study design: mean age was 33.01 ± 5.14 versus 34.57 ± 4.52 (P < 0.001), mean peak oestradiol levels was 26645.34 ± 8592.57 pmol/l versus 7229.75 ± 2329.20 pmol/l (P < 0.001), and mean number of oocytes were 27.55 ± 13.46 versus 11.67 ± 5.76 (P < 0.001) for the study and control group, respectively. Major complications and hospitalization rates were similar between the study and control groups (three [1.25%] versus one [0.48%]; P = 0.62 and three [1.25%] versus two [0.96%]; P = 1.0, respectively). Thirty-six patients (15.1%) in the study group and 11 (5.3%) in the control group sought medical care after retrieval, mostly due to abdominal pain, without the need for further workup or hospitalization (P < 0.001). CONCLUSIONS: Extremely high oestradiol levels were not associated with thromboembolic events, higher major complication or hospitalization rates, and therefore may be considered safe. Nevertheless, patients may be informed of possible higher rates of discomfort, mostly abdominal pain. Larger studies are warranted to confirm our results.

Covid-19 vaccination BNT162b2 temporarily impairs semen concentration and total motile count among semen donors.

BACKGROUND: The development of covid-19 vaccinations represents a notable scientific achievement. Nevertheless, concerns have been raised regarding their possible detrimental impact on male fertility OBJECTIVE: To investigate the effect of covid-19 BNT162b2 (Pfizer) vaccine on semen parameters among semen donors (SD). METHODS: Thirty-seven SD from three sperm banks that provided 216 samples were included in that retrospective longitudinal multicenter cohort study. BNT162b2 vaccination included two doses, and vaccination completion was scheduled 7 days after the second dose. The study included four phases: T0 - pre-vaccination baseline control, which encompassed 1-2 initial samples per SD; T1, T2 and T3 - short, intermediate, and long terms evaluations, respectively. Each included 1-3 semen samples per donor provided 15-45, 75-125 and over 145 days after vaccination completion, respectively. The primary endpoints were semen parameters. Three statistical analyses were conducted: (1) generalized estimated equation model; (2) first sample and (3) samples' mean of each donor per period were compared to T0. RESULTS: Repetitive measurements revealed -15.4% sperm concentration decrease on T2 (CI -25.5%-3.9%, p = 0.01) leading to total motile count 22.1% reduction (CI -35% - -6.6%, p = 0.007) compared to T0. Similarly, analysis of first semen sample only and samples' mean per donor resulted in concentration and total motile count (TMC) reductions on T2 compared to T0 - median decline of 12 million/ml and 31.2 million motile spermatozoa, respectively (p = 0.02 and 0.002 respectively) on first sample evaluation and median decline of 9.5 × 106 and 27.3 million motile spermatozoa (p = 0.004 and 0.003, respectively) on samples' mean examination. T3 evaluation demonstrated overall recovery without. Semen volume and sperm motility were not impaired. DISCUSSION: This longitudinal study focused on SD demonstrates selective temporary sperm concentration and TMC deterioration 3 months after vaccination followed by later recovery verified by diverse statistical analyses. CONCLUSIONS: Systemic immune response after BNT162b2 vaccine is a reasonable cause for transient semen concentration and TMC decline. Long-term prognosis remains good.

What can we learn about posthumous sperm retrieval after extra long-term follow-up?

PURPOSE: To describe spermatozoa extraction rate by testicular sperm extraction (TESE) for posthumous sperm retrieval (PMSR) and examine harvest time impact on sperm motility; to compare long-term sperm usage between married vs. single deceased men. METHODS: This retrospective study included all PMSR cases in Shamir Medical Center during 2003-2021. We evaluated sperm cryopreservation according to latency time after death. Then, we assessed sperm usage according to Israeli PMSR regulations. RESULTS: The study included 69 (35 married and 34 singles) deceased men with average age of 30.3 ± 7.8 years. Sperm was cryopreserved in 65 cases (94.2%) after maximum and average harvest time of 40 and 16.5 ± 8.1 h, respectively. Motile sperm extraction was associated with significantly shorter harvest time compared with non-motile sperm (13.8 ± 7.3 vs. 18.7 ± 8.1 h, p = 0.046). Sperm usage among married deceased was significantly higher than single (15.6% vs. 0%, p = 0.05). Disposal requests were lower among single compared to married men relatives without reaching statistical difference. Eventually, single men had significantly higher rate of non-used cryopreserved samples (93.8% vs 69.6%, p = 0.01). CONCLUSION: This large long-term cohort study demonstrates high efficacy of PMSR. We found significant harvest latency time difference between motile and non-motile preserved sperm. Clinical sperm usage rate justifies the efforts for PMSR among married deceased. However, contradicting policy on the topic of single men (which implies liberal sperm preservation but rigid prevention of usage) results with high non-used sperm rate and relatives' extremely sophisticated emotional burden.

Endometrial compaction is associated with increased clinical and ongoing pregnancy rates in unstimulated natural cycle frozen embryo transfers: a prospective cohort study.

PURPOSE: To investigate the association between endometrial compaction and pregnancy rates in unstimulated natural cycle frozen embryo transfers. DESIGN: A single-center prospective cohort study. Endometrial thickness by transvaginal ultrasound and blood progesterone levels on the day of ovulation and the day of embryo transfer were evaluated in patients undergoing natural cycle frozen embryo transfer. Compaction was defined as > 5% decrease in endometrial thickness between ovulation day and day of transfer. Clinical and ongoing pregnancy rates in cycles with and without compaction were compared. RESULTS: Seventy-one women were included, of which 44% had endometrial compaction, with similar rates when subdividing the patients by day of transfer (day 3 or day 5). Clinical and ongoing pregnancy rates were higher in the compaction group compared to the non-compaction group (0.58 vs. 0.16, P < 0.001; 0.52 vs. 0.13, P < 0.001 respectively). Subdividing by degree of compaction > 10% and > 15% revealed similar pregnancy rates as > 5%, with no added benefit to higher degrees of compaction. CONCLUSIONS: About half the patients in our study undergoing unstimulated natural cycle frozen embryo transfer experienced compaction of the endometrium, occurring as early as day 3 post-ovulation. This was significantly correlated with increased clinical and ongoing pregnancy rates.

The impact of past COVID-19 infection on pregnancy rates in frozen embryo transfer cycles.

PURPOSE: To study the effect of SARS-CoV-2 infection on pregnancy rates in frozen embryo transfer (FET) cycles. METHODS: A retrospective cohort study including women under the age of 42 with documented SARS-CoV-2 infection up to 1 year prior to treatment, undergoing FET cycles in the first half of 2021, with transfer of embryos generated prior to the infection. Controls were SARS-CoV-2 non-diagnosed, non-vaccinated women matched by age, number, and day of embryo transfer. Demographic and cycle characteristics and outcomes were compared. RESULTS: Forty-one recovered women and 41 controls were included. Pregnancy rates were 29% and 49% respectively (p = 0.070). Stratification by time from SARS-CoV-2 infection to transfer into ≤ 60 and > 60 days revealed a difference in pregnancy rates, with women in the COVID group having lower pregnancy rates if infected in proximity to the transfer (21% vs. 55%; p = 0.006). In a logistic regression model, infection was a significant variable (p = 0.05, OR 0.325, 95% CI 0.106-0.998). Logistic regression applied on the subgroup of women infected in proximity to the transfer further strengthened the univariate results, with COVID-19 remaining a significant parameter (p = 0.005, OR 0.072, 95% CI 0.012-0.450). CONCLUSIONS: In FET cycles of patients with past SARS-CoV-2 infection, in which oocytes were retrieved prior to infection, decreased pregnancy rates were observed, specifically in patients who recovered less than 60 days prior to embryo transfer. Pending further studies, in cases of FET cycles with limited number of embryos, postponing embryo transfer for at least 60 days following recovery from COVID-19 might be considered when feasible.