Predictor Of Pregnancy Outcome Research Articles

O-150 Identification and validation of RPL7 and RCCD1 as potential biomarkers associated with immune infiltration in patients with thin endometrium

Abstract Study question For patients with thin endometrium (TE), what potential genes could be utilized for exploring the underlying mechanisms and clinical therapy? Summary answer Ribosomal protein L7 (RPL7) and RCC1 domain containing 1 (RCCD1) were suggested as specific biomarkers for TE. What is known already TE is an important contributor to embryo implantation failure and female infertility. However, the pathogenesis and mechanism of TE are not clear, and consequently, there is a paucity of data on effective targeted treatments for patients with TE. Study design, size, duration Endometrial cells were collected from 18 women with TE and 18 normal controls for transcriptional sequencing. Experimental validation was based on other 10 endometrium samples, consisting of 6 TE samples and 4 controls. Participants/materials, setting, methods After performing transcriptional sequencing, differentially expressed genes (DEGs) were extracted between the two groups via bioinformatic analysis. Based on DEGs, we applied functional enrichment and LASSO analysis to identify potential biomarkers, whose expressions were then validated by quantitative real-time PCR and western blot. Immune infiltration as well as the correlation with immune cells was also explored in the study. Main results and the role of chance RPL7 and RCC1 were identified and validated to be potential biomarkers, which exhibited an overexpression in TE at both mRNA and protein levels. An abnormal immune environment was found in TE, and correlation analysis showed that the two candidate genes correlated with atypical regulation of immune cells. Limitations, reasons for caution It might not be adequate to evaluate TE by only considering the immunologic aspects. Moreover, prospective studies are required to determine whether RPL7 and RCC1 may be used for early clinical diagnosis and prediction of pregnancy outcomes. Wider implications of the findings Further understanding and better knowledge of the functions of RPL7 and RCCD1 can promote the development of targeted therapeutics to improve clinical outcomes of patients with TE. Trial registration number not applicable

P-204 Automated embryo assessment: a simple web application correlates scores with embryo morphology, developmental velocity, ploidy, and clinical outcomes

Abstract Study question How does the novel automated scoring system in our laboratory correlate with treatment success in different subpopulations? Summary answer The web app automates embryo assessment, linking scores to morphology, development speed, ploidy, and clinical outcomes in treatments with both patient and donor oocytes. What is known already In the realm of assisted reproductive technologies, numerous platforms employing artificial intelligence (AI) have emerged for embryo assessment. Substantial research has been dedicated to evaluating the efficacy of AI in predicting pregnancy outcomes, particularly following blastocyst transfer. However, not all available options have undergone external validation, a crucial step deemed necessary before investing in such tools. This project endeavors to validate the utility of EMBRYOAID v1.0, a straightforward web application capable of assessing embryos through photos and/or videos. Study design, size, duration This is a retrospective cohort study including 485 patients who underwent IVF treatments with embryos (n = 5,710) cultured in EmbryoScope® time-lapse systems. Senior embryologists routinely assessed blastocysts using ASEBIR morphological criteria (A-D). Then, time-lapse videos were scored by the EMBRYOAID algorithm (0-10). We investigated the relationship between automated scoring and: (I) conventional morphology, (II) morphokinetic parameters, (III) euploidy rate, and (IV) implantation in cycles with own oocytes, egg donation, and preimplantation genetic testing for aneuploidies (PGT-A). Participants/materials, setting, methods The association with morphology and morphokinetics was investigated in 5,710 embryos. Ploidy correlation involved 258 blastocysts undergoing trophectoderm biopsy and next-generation sequencing analysis. Implantation association was studied in 381 single blastocyst transfers. Finally, a multivariable analysis considered oocyte age, body mass index, type of transfer (fresh-frozen) and day of transfer (5-6) to quantify the relevance of automated scoring in different treatment subpopulations. Model performance was assessed through ROC curves and area under the curve calculations. Main results and the role of chance The results that involved grouping were quartiled based on sample size, calculated by the statistical software. This deep-learning score was related to conventional morphology (7.9±1 for A, n = 295; 6.9±1.3 for B n = 1168; 5.9±1.3 for C, n = 830; and 3.1±1.8 for D, n = 3,417)*. Embryos with faster development in early stages received higher scores, considering division times at 2, 3, 4, and 5 cells*. Euploidy rate increased as the embryo score was higher: 39.1% for ≤5.6 (n = 54), 45.5% for 5.6-6.2 (n = 61), 48.5% for 6.2-6.9 (n = 65) and 58.2% for >6.9 (n = 78). Similarly, the implantation rate was also higher in accordance with the score: 42.7% for ≤6.2 (n = 73), 50.6% for 6.2-7.4 (n = 87), 60.2% for 7.4-8.2 (n = 103) and 69.4% for >8.2 (n = 118). The stepwise multivariate analysis showed that embryo score was related to the odds of implantation in conventional treatments with patient oocytes (OR = 1.4; 95% CI [1.1-1.8]*) and in the oocyte donation program (OR = 1.2; 95% CI [1–1.4]*). The AUCs demonstrated the following performance: 0.643 (0.559-0.727) for patient oocytes and 0.677 (0,624-0,731) for the oocyte donation program. There was no significant association of embryo score with implantation in PGT-A treatments. Limitations, reasons for caution The retrospective nature of the study, despite serving as a thorough external validation, introduces inherent limitations. Notably, in PGT-A treatments, embryos underwent assisted hatching on day 3, potentially influencing the model’s performance. Wider implications of the findings The implications of our findings validate a user-friendly tool for automated embryo scoring in the laboratory. The achieved performance is comparable or superior to other tested models, particularly in egg donation programs, potentially encouraging clinics to adopt this tool routinely. Trial registration number Not applicable

O-297 Prediction of pregnancy outcomes of single vitrified-warmed blastocyst transfer using combination of an automatic classification algorithm applied on cleavage stage embryos and blastocyst morphology

Abstract Study question Does combination of embryo assessment algorithm on cleavage-stage based on the automatic annotation of morphokinetic and blastocyst morphology in embryo selection improve implantation outcomes? Summary answer Combination of embryo assessment algorithm on cleavage-stage based on the automatic morphokinetic annotation and blastocyst morphological evaluation was showed significantly predictive for implantation outcomes. What is known already Conventional morphological assessment is still the gold standard for embryo selection. Timelapse monitoring of embryo development may represent a superior way to culture and select embryos in vitro. Nowadays, time-lapse culture systems are becoming more popular, many algorithms have been developed for embryo selection based on embryo morphokinetics, providing additional information for morphological assessment. However, manual annotations of developmental events and application of algorithms can be time-consuming and subjective processes. Automation of morphokinetic annotation can be a potential approach that reduces subjectivity in embryo selection. Study design, size, duration The observational, retrospective study was conducted in a single centre between 2020-2023 and included 511 single vitrified-warmed blastocyst transfer cycles. Blastocyst selected for transfer on Day 5,6 based on conventional morphological evaluation. Embryos were evaluated on Day 3 with a score from 1 (best) to 5 (worst) (from highest to lowest developmental potential) by the automatic embryo assessment algorithm. The correlation of the algorithms scoring and pregnancy outcomes was qualified by generalized estimating equations (GEEs). Participants/materials, setting, methods Embryos were cultured in timelapse GERI incubator and classified on day 3 by automatic embryo assessment algorithm depending on four parameters: P2 (t3-t2), P3 (t4-t3), oocyte age, and number of cells. The correlation of the algorithms scoring and pregnancy outcomes was qualified by generalized estimating equations (GEEs). Three GEE model using embryo assessment algorithm, conventional morphological assessment, and a combination of both classification system as the predictor were compared. Main results and the role of chance The implantation rate was higher with lower the scores generated by the embryo assessment algorithm. A GEE model showed the negative association between higher embryo score and lower odds of implantation. The OR of Score 3; 4; 5 vs 1 were 0.335; 0.259; 0.245 (95% CI 0.194-0.580; 0.138-0.485; 0.111-0.544, P = 0.000), respectively, for implantation. The AUC of the model using embryo assessment algorithm for implantation potential = 0.641. The AUC of the model combining both embryo assessment algorithm and conventional morphological assessment for implantation potential = 0.733. The differences were statistically significant (z-statistic = 3.896, p = 0.0001). Limitations, reasons for caution The sample size was enough to confirm the ability of the model for embryo selection. However, the retrospective nature of this study may be a limitation. Wider implications of the findings Using combination of timelapse technology with automated embryo assessment and conventional morphological assessment can predict the success rates of assisted reproduction cycles. To our knowledge, this is the first study using embryo dataset from single vitrified-warmed blastocyst transfer cycles with this embryo assessment algorithm. Trial registration number not applicable

P-032 Prospective and multi-site analysis of pregnancy outcomes in 488 patients who completed the Sperm Quality Test (SpermQT) measuring the utility of sperm epigenetics

Abstract Study question Do SpermQT results prospectively correlate with fertility outcomes of couples undergoing intrauterine insemination (IUI)? Summary answer We observe a decrease in IUI pregnancy rates in men with Abnormal compared to Normal SpermQT results irrespective of their sperm total motile count (TMC). What is known already As the mainstay of male infertility diagnosis, the standard semen analysis provides limited value for predicting pregnancy outcomes. New technologies are needed for a more comprehensive assessment of male fertility. A novel, epigenetic assessment of sperm quality, SpermQT, was implemented clinically in 2022. Retrospective studies have shown that sperm health, as identified through DNA methylation patterns, is predictive of IUI outcomes in a subset of infertile men. Additional prospective research is needed for validation of these data. Study design, size, duration Over an 18-month period (June 2022 - January 2024), 23 reproductive endocrinologists over eight clinics ordered 488 SpermQT tests on male patients. For these patients, physicians and clinical support staff were asked to provide the sperm total motile count (TMC) from the semen analysis, male and female ages, procedure information and outcomes. SpermQT results were categorized as Normal or Abnormal. Associations between SpermQT results, outcomes, age, and TMC were analyzed. Participants/materials, setting, methods The selection of patients for SpermQT assessment was based on the clinical decision of the ordering physician. SpermQT requires a semen sample which was collected by the patient either at the andrology laboratory or at home using an at-home collection kit. All sample types were shipped directly to the vendor’s laboratory for analysis and report generation. Following the completion of the epigenetic analysis, all SpermQT results were provided to the ordering physician for patient consultation. Main results and the role of chance 488 patients received a SpermQT result. 83.6% of men had a Normal SpermQT (n = 408), and 16.4% had an Abnormal SpermQT (n = 80). 180 couples had pregnancy outcomes from at least one IUI. Of the 180, 14% of men had an Abnormal SpermQT (n = 25) and 86% had a Normal SpermQT (n = 155). Analysis of pregnancy outcomes from all 180 couples who completed one, two, or three IUI cycles showed a 15% IUI cumulative pregnancy rate. The men with a Normal SpermQT had a 17.42% cumulative IUI pregnancy rate within the first three IUI cycles while men with an Abnormal SpermQT (N = 25) had no reported pregnancies and a 0% cumulative IUI pregnancy rate. Within this patient cohort, 338 patients had reported TMC where 82% had a TMC ≥20 million (n = 276). 72% of men with an Abnormal SpermQT had a TMC ≥20M, while 84% of men with a Normal SpermQT had a TMC ≥20M. Median male and female ages in the Normal SpermQT category were both 34, while median male and female ages in the Abnormal SpermQT category were 32 and 33 respectively, indicating age did not play a role in IUI pregnancy outcomes. Limitations, reasons for caution Limitations within this study include the sample size of men with an Abnormal SpermQT result. In order to identify a statistical significance between IUI pregnancy outcomes, a total sample size of 500 patients will be needed. Data and outcomes will continue to be collected to continue the validation of SpermQT. Wider implications of the findings There is strong data showing that sperm epigenetics play an important role in IUI outcomes. Here we show in a prospective and multi-site population that a new assessment of sperm epigenetics (SpermQT) identifies men less likely to achieve an IUI pregnancy, and also identifies subfertile men with normal TMC. Trial registration number Non Applicable

O-028 DNA methylation testing with cervical secretion can serve as a non-invasive biomarker for predicting successful implantation in frozen-thawed embryo transfer

Abstract Study question Is cervical secretion gene methylation profile associated with embryo implantation outcome, and can be used as a non-invasive biomarker for pregnancy prediction in FET cycles? Summary answer Cervical secretion gene methylation profiles show significant associations with implantation outcomes, and can serve as a non-invasive predictor of successful pregnancy in FET cycles. What is known already Cause of implantation failure remains a black box in reproductive medicine, and the exact mechanism of how endometrial receptivity is still behind the curtain. Epigenetic modifications including DNA methylation regulate gene expression and may alter endometrium receptivity. Endometrial DNA methylation changes vigorously only during the reconstruction of a new endometrium throughout each menstrual cycle, suggesting a unique methylation landscape in each regenerated endometrium. Cervical secretions contain implantation-related cytokines and genetic material from endometrium, and the DNA methylation profiles of cervical secretions is highly correlated with endometrium. Therefore, cervical secretions can be used as non-invasive surrogates for investigating endometrial condition. Study design, size, duration This multi-centered, case-control study enrolled 72 infertile females who entered the FET cycle with at least one high-quality blastocyst available between Aug 2017 and Dec 2022. Embryos assessed by Gardner scoring system with grade 3BB or above were defined as high-quality. Cervical secretions were collected on the day right before embryo transfer, and then DNA methylation profile were assessed. Participants/materials, setting, methods These females aged between 20-45 years-old with regular menstruation cycle (24-35 days) and normal BMI (17.5–32.0 kg/m2). Uterine cavity lesions and hydrosalpinx without treatment, adenomyosis, large uterine myoma that distorted endometrium, and thin endometrium (<7mm) were excluded. The association between the cervical secretion gene methylation profile and pregnancy outcome was evaluated via quantitative methylation-specific PCR (qMSP), methylation array, and genome-wide analysis. Different machine learning algorithms were utilized for differential methylation analysis and implantation prediction. Main results and the role of chance Cervical secretion DNA methylome differed between receptive (pregnant) and non-receptive (non-pregnant) FET cycle with genome-wide methylation array. The accuracy of pregnancy outcome prediction using top 2000 differential methylation probes (DMPs) in promoter region can be as high as 86% in all tested sample and 96.4% in pregnant samples. Bioinformatic analysis of six selected candidate genes related to implantation from literature review showed significant differences in DNA methylation between receptive and non-receptive endometrium. The methylation level of the six candidate genes with eight regions were measured by the qMSP platform and showed varying degrees of differential methylation status between the pregnancy and non-pregnancy groups. The AUCs for a single gene/region ranged from 0.53–0.67 for implantation prediction. Ten different machine learning models were applied and the results showed that the combination of candidate genes’ DNA methylation profiles could differentiate pregnant from non-pregnant samples with an accuracy as high as 86.67% and an AUC of 0.81 by logistic regression model. The best model from different machine learning algorithms using selected DMPs of genes related to window of implantation (WOI) can predict ongoing pregnancy with accuracy rates as high as 86.78% and AUC values up to 0.91. Limitations, reasons for caution The results obtained from a relatively small cohort size, and the timing of sample collection is on the day right before embryo transfer. Further investigation of methylation profiles in late follicular phase along with large sample size with euploid embryo transfer are mandatory for validation and clinical applications. Wider implications of the findings We firstly demonstrated the feasibility of cervical secretion methylation profile as a non-invasive testing for pregnancy prediction. The promising result may contribute to predicting endometrial receptivity for cycles with a favorable endometrium and maximize the successful pregnancy rate of embryo transfer. Trial registration number not applicable

The Effect of Progesterone Elevation on the Day of Trigger Administration: A Review of the Literature.

Since the advent of assisted reproductive technology, different variables have been shown to affect pregnancy outcomes. One of the most prevalent studied events is the premature rise in serum progesterone concentrations on the day of trigger administration during cycles of ovarian stimulation. This phenomenon, classically known as premature luteinization, has been observed significantly for decades and has been linked to adverse pregnancy outcomes and lower live birth rates. Ultimately, a quest to find a precise serum progesterone concentration cut-off value that can be effectively used to predict pregnancy outcomes prior to trigger administration is still underway. The purpose of the current research was to study the available literature on the relationship between serum progesterone on the day of trigger administration in controlled ovarian stimulation cycles used for IVF in an attempt to identify a cut-off serum progesterone concentration that can be used to effectively predict future pregnancy outcomes in fresh transfers. This study is a review of the literature and is based on information and data gathered from 36 published articles. The majority of the literature shows that a serum progesterone concentration cut-off of 1.5 ng/ml (4.77 nmol/L) can be used prior to trigger administration to effectively predict pregnancy outcomes. Premature progesterone elevation on the day or prior to the trigger administration is associated with adverse pregnancy outcomes in IVF cycles. Other factors such as follicle number, serum concentration of other hormones, and ovarian response to ovarian stimulation should also be considered to predict the success of IVF protocols.

Neutrophil to Lymphocyte Ratio Values in Late Preterm and Term Patients with Evidence of Chorioamnionitis on Placental Histopathology: A Retrospective Cohort Study

Introduction: Neutrophil to lymphocyte ratio (NLR) is an inexpensive biomarker that may aid in the prediction of adverse pregnancy outcomes, though data remains sparse at this time. Previously published research regarding chorioamnionitis almost exclusively focuses on preterm labor and preterm prelabor rupture of membranes before 34 weeks of gestation and suggests an increase in NLR in those patients with chorioamnionitis identified on placental histopathologic examination. However, chorioamnionitis in the late preterm and term timeframe also represents a significant source of maternal and neonatal morbidity. Therefore, the primary aims of the study were to: 1) compare obstetric admission NLR values among those with and without evidence of histopathologic chorioamnionitis 2) evaluate the efficacy of NLR in identifying histopathologic chorioamnionitis and 3) compare NLR values pre- and postdelivery in the setting of a placental histopathologic chorioamnionitis diagnosis in patients beyond 34 weeks of gestation. Methods: A retrospective electronic chart review was performed at an American urban safety net hospital. Institutional review board approval was obtained (UMKC #2093657), and patient consent was waived due to the retrospective nature of the review. Obstetric encounters were included if a complete blood count (CBC) with differential was performed on admission and postpartum, the subject underwent a trial of labor, a placental histopathologic examination was performed, and delivery occurred beyond 34 0/7 weeks of gestation. Subjects were excluded if an extrauterine infection was present during the hospitalization or the subject received corticosteroids within two weeks of delivery. Postdelivery placentas were examined by the University’s pathology department. Statistical analyses were performed with receiver operator curves, Mann-Whitney U test, and Wilcoxon Signed-Rank Test where applicable, with a significance level p < 0.05. Results: Three hundred seventy-nine patient encounters were reviewed, with only 30.1% of all encounters with placental histopathology available. A total of 58 subjects met the inclusion criteria and 14 additional subjects were excluded due to extrauterine infection (n=1), SARS-CoV-2 diagnosis (n=5), and late preterm steroids administration (n=8). There was no difference between those subjects with and without histopathologic chorioamnionitis in median gestational age at the time of delivery (39 0/7 versus 39 1/7 weeks of gestational, p=0.960), median time of admission CBC collection to delivery (0.98 versus 0.98 days, p=0.340), and timing of collection of postpartum CBC (1.0 versus 1.0 days postpartum, p=0.631). Predelivery neutrophil to lymphocyte ratio values were compared in subjects with and without histopathologic chorioamnionitis and there was no significant difference in median values (4.11 versus 4.52, p=0.683). The predelivery NLR predicted the presence of chorioamnionitis poorly (AUC 0.518, 95% CI [0.326, 0.711], p=0.843). The postdelivery NLR was a slightly better predictor of chorioamnionitis (AUC 0.634, 95% CI [0.454, 0.815], p=0.147), but did not reach statistical significance. Although there was no significant difference in postpartum NLR values in those with and without chorioamnionitis on final histopathology (6.73 versus 4.63, p=0.147), the value was notably higher in the former. When the antepartum and postpartum NLR were compared across individual subjects in a paired fashion, there was a significantly higher postpartum NLR in those subjects both with and without chorioamnionitis on final histopathology (with chorioamnionitis: antepartum median 4.52 versus postpartum 6.73, p=0.012, n=15; without chorioamnionitis: antepartum median 4.11 versus postpartum 4.63, p=0.043, n=29). Conclusion: Though predelivery NLR is a poor predictor of chorioamnionitis, significantly higher postpartum NLR values in the sample population suggest an increase in NLR for all laboring patients, but a more pronounced increase occurs in those with inflammatory placental findings. While the study is limited by a heterogeneous sample population, nonparametric evaluation, and small sample sizes, the data does add to the paucity of preexisting literature that seeks to utilize NLR in the prediction of chorioamnionitis during the labor course. Larger longitudinal studies may help better characterize the rising NLR values over the course of labor and delivery as seen in our study. Neutrophil to lymphocyte ratio values across the spectrum of disease states and gestational ages in pregnancy may help isolate other inflammatory processes that impact perinatal outcomes.

Comparison of maternal neonatal outcomes of normotensive and hypertensive placental abruptions: A novel approach.

To analyze maternal and neonatal effects of placental abruption (PA) through a novel classification in the presence of hypertension. Initial hemoglobin parameters were also compared to predict pregnancy outcomes in addition to hypertension. This retrospective cohort designed study was conducted on 115 pregnant women with PA. The main parameters scanned and recorded from the hospital database and patient medical files. Two groups were classified regarding of presence or absence of hypertension (53 hypertensive, 62 normotensive). Maternal demographical and clinical characteristics (abdominal pain, vaginal bleeding) were recorded. APGAR scores below 5 at 1st and 5th minute, fetal or neonatal death, admission and length of stay in Neonatal Intensive Care Unit were also investigated and compared between the groups. Stillborn to live-born ratio and lower APGAR scores < 5 at 5th minute were significantly higher in hypertensive group than normotensive group (P = .006 and 0.047, respectively). Poor maternal outcomes were detected in the hypertensive group than normotensive group regarding rate of blood transfusion (27/53, 50.9%; 18/62, 29%, respectively, P = .017). More abdominal pain and less vaginal bleeding were seen in PA with HT. Higher lymphocyte count, mean platelet volume, and platelet distribution width were reported in hypertensive group. Poorer maternal and neonatal outcomes of hypertensive patients with PA were detected. These patients should deserve greater attention to assess not only the possible risks associated with abruption but also the accompanying complications.

Serum parameters of inflammatory markers as prognostic biomarkers with maternal-neonatal outcome in patients with GDM.

Gestational diabetes mellitus (GDM) is one of the most common complications of pregnancy, which is increasing annually. GDM can cause serious harm to both the mother and the offspring. However, the clinical indicators that predict pregnancy outcomes with GDM remain limited. This study included 3,229 pregnancies. Inflammatory markers were defective in the mother's peripheral blood. Also, the Chi-square test, logistic regression analyses and Spearman rank correlation coefficient were performed to evaluate inflammatory markers with pregnancy outcomes. The association between inflammatory markers and pregnancy outcomes was analyzed. The optimal cut-off values of inflammatory markers were calculated. Finally, 3,229 women were included. 1852 (57.36%) participants suffered good pregnancy outcomes. This study revealed that the maternal age, the baseline BMI (kg/m2), the times of parity, and the level of lymphocyte, SII and SIRI significantly increased in poor pregnancy outcomes groups. Additionally, inflammatory markers, such as white blood cells (WBC), neutrophils, monocytes, platelet counts, lymphocytes, systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI) were related to pregnancy outcomes. Furthermore, the results revealed that the SII level had the highest odd rates (OR) [OR = 6.957; 95% CI (5.715-8.468)], followed by SIRI level [OR = 2.948; 95% CI (2.382-3.649)], the WBC counts [OR = 1.930; 95% CI (0.901-2.960)], the lymphocyte counts [OR = 1.668; 95% CI (1.412-1.970)], and baseline BMI [OR = 1.050; 95% (1.021-1.080)]. This study presented that the baseline SII and SIRI levels can be valuable biochemical markers to predict the pregnancy outcome with GDM with non-invasive procedures. They can help identify high-risk pregnant women with GDM early, provide a personalized intervention in time, and enhance perinatal surveillance.

Decreased complexity of glucose time series index associated with adverse pregnancy outcomes in gestational diabetes mellitus.

We investigated the relationship between the complexity of the glucose time series index (CGI) during pregnancy and adverse pregnancy outcomes in women with gestational diabetes mellitus (GDM). In this retrospective cohort study, 388 singleton pregnant women with GDM underwent continuous glucose monitoring (CGM) at a median of 26.86 gestational weeks. CGI was calculated using refined composite multiscale entropy based on CGM data. The participants were categorized into tertiles according to their baseline CGI (CGI <2.32, 2.32-3.10, ≥3.10). Logistic regression was used to assess the association between CGI and composite adverse outcomes or large for gestational age (LGA). The discrimination performance of CGI was estimated using receiver operating characteristic analysis. Of the 388 participants, 71 (18.3%) had LGA infants and 63 (16.2%) had composite adverse outcomes. After adjustments were made for confounders, compared with those with a high CGI (CGI ≥3.10), participants with a low CGI (CGI <2.32) had a higher risk of composite adverse outcomes (odds ratio: 12.10, 95% confidence interval: 4.41-33.18) and LGA (odds ratio: 12.68, 95% confidence interval: 4.04-39.75). According to the receiver operating characteristic analysis, CGI was significantly better than glycated haemoglobin and conventional CGM indicators for the prediction of adverse pregnancy outcomes (all p < .05). A lower CGI during pregnancy was associated with composite adverse outcomes and LGA. CGI, a novel glucose homeostasis predictor, seems to be superior to conventional glucose indicators for the prediction of adverse pregnancy outcomes in women with GDM.

Combined analysis of estradiol and β-hCG to predict the early pregnancy outcome of FET: a retrospective study

BackgroundThe accurate prediction of pregnancy outcomes in in vitro fertilization (IVF) cycles is crucial. While several studies have been conducted on the predictive power of serum estradiol (E2) and β-hCG concentrations post-embryo transfer (ET) for pregnancy outcomes, there is debate on the predictive value of E2. The objective of this study was to investigate the predictive efficacy of combining serum E2 and β-hCG levels on early reproductive outcomes 12 days after embryo transfer.MethodsA total of 1521 patients with β-hCG positive values on day 12 following frozen-thawed embryo transfer (FET) with natural endometrial preparation cycles (NCs) were gathered in affiliated Women’s Hospital of Jiangnan University. Using logistic regression, the relationship between pregnancy outcome and early serum E2 and β-hCG concentrations was examined. The receiver-operating characteristic (ROC) analysis was used to assess the predictive accuracy of the serum E2 and β-hCG concentrations.ResultsNotable distinctions were observed in the serum E2 and β-hCG levels on the twelfth day following FET with NCs between the groups classified as clinical pregnancy group (CP Group) and biochemical pregnancy group (BP Group). In addition, the cutoff values for E2 and β-hCG on day 12 following FET with NCs in cleavage embryo group (CE Group) were 129.25 pg/mL and 156.60 mIU/mL, respectively. The threshold values for E2 and β-hCG for the blastocyst group (B Group) were 174.45 pg/mL and 217.70 mIU/mL. Serum E2 day12 and β-hCG day12 were found to be substantially linked with clinical pregnancy by logistic regression analysis.ConclusionsSerum E2 and β-hCG concentrations were found to be significantly different between the CP Group and BP Group in infertility women underwent FET with NCs. Our retrospective cohort study’s findings suggest that the combination of early E2 and β-hCG levels on day 12 post-FET could be used as a predictive tool to evaluate the likelihood of both positive and negative pregnancy outcomes in FET with NCs.

The Relationship Between Anti-Mullerian Hormone Levels and Pregnancy Outcomes in Patients with Recurrent Unexplained Miscarriage

Background: This study aimed to assess the correlation between serum levels of anti-Mullerian hormone (AMH), basal follicle-stimulating hormone (FSH), basal luteinizing hormone (LH), and basal estradiol with pregnancy outcomes. Methods: Conducted at Shariati Hospital in Tehran from 2020 to 2021, this prospective cohort study included women under 38 years old with idiopathic recurrent miscarriage (IRM). Individuals with AMH levels below 1 ng/mL were classified as the poor responder group. All participants with IRM received a daily combination of 20 mg prednisolone and 200 mg progesterone vaginal suppositories from the beginning of pregnancy until 12 weeks, along with aspirin and folic acid. Pregnancy was monitored until 36 weeks, and outcomes were evaluated over two years using univariate and multiple logistic regression, with P-values &lt; 0.05 considered significant. Results: The study comprised 128 individuals with a mean age of 36.4 ± 3.9 years. Of these, 80 became pregnant, while 48 did not. Among the pregnant individuals, 34 had terminations before 26 weeks (13 ongoing and 21 clinical), while 46 had pregnancies lasting 26 weeks or longer. Maternal age (RR = 1.23, 95% CI: 1.10 - 1.90, P = 0.001), history of abortion (RR = 1.262, 95% CI: 1.052 - 1.327, P = 0.008), and low serum AMH level (RR = 0.752, 95% CI: 0.227 - 0.934, P = 0.035) were significantly associated with the probability of subsequent pregnancies. Maternal age (RR = 1.108, 95% CI: 1.05 - 1.350, P = 0.025) and history of abortion (RR = 1.097, 95% CI: 1.02 - 1.161, P = 0.042) were the only factors associated with the risk of non-pregnancy. Conclusions: The study findings suggest that AMH levels in women with IRM significantly influence pregnancy outcomes, including abortion and live births at 26 weeks or more. The univariate analysis revealed significant correlations between age, serum AMH levels, previous history of abortion, and the risk of abortion. Additionally, AMH levels were found to relate to follicle storage rather than egg quality, indicating that AMH does not predict live birth after IVF. Overall, this prospective study underscores the importance of maternal age, AMH level, and previous abortion history in predicting pregnancy outcomes.

Endometrial compaction to predict pregnancy outcomes in patients undergoing assisted reproductive technologies: a systematic review and meta-analysis.

Does endometrial compaction (EC) help predict pregnancy outcomes in those undergoing ART? EC is associated with a significantly higher clinical pregnancy rate (CPR) and ongoing pregnancy rate (OPR), but this does not translate to live birth rate (LBR). EC describes the progesterone-induced decrease in endometrial thickness, which may be observed following the end of the proliferative phase, prior to embryo transfer. EC is proposed as a non-invasive tool to help predict pregnancy outcome in those undergoing ART, however, published data is conflicting. A literature search was carried out by two independent authors using PubMed, Cochrane Library, MEDLINE, Embase, Science Direct, Scopus, and Web of Science from inception of databases to May 2023. All peer-reviewed studies reporting EC and pregnancy outcomes in patients undergoing IVF/ICSI treatment were included. The primary outcome is LBR. Secondary outcomes included other pregnancy metrics (positive pregnancy test (PPT), CPR, OPR, miscarriage rate (MR)) and rate of EC. Comparative meta-analyses comparing EC and no EC were conducted for each outcome using a random-effects model if I 2 > 50%. The Mantel-Haenszel method was applied for pooling dichotomous data. Results are presented as odds ratios (OR) with 95% CI. Out of 4030 screened articles, 21 cohort studies were included in the final analysis (n = 27 857). No significant difference was found between LBR in the EC versus the no EC group (OR 0.95; 95% CI 0.87-1.04). OPR was significantly higher within the EC group (OR 1.61; 95% CI 1.09-2.38), particularly when EC ≥ 15% compared to no EC (OR 3.52; 95% CI 2.36-5.23). CPR was inconsistently defined across the studies, affecting the findings. When defined as a viable intrauterine pregnancy <12 weeks, the EC group had significantly higher CPR than no EC (OR 1.83; 95% CI 1.15-2.92). No significant differences were found between EC and no EC for PPT (OR 1.54; 95% CI 0.97-2.45) or MR (OR 1.06; 95% CI 0.92-1.56). The pooled weighted incidence of EC across all studies was 32% (95% CI 26-38%). Heterogeneity due to differences between reported pregnancy outcomes, definition of EC, method of ultrasound, and cycle protocol may account for the lack of translation between CPR/OPR and LBR findings; thus, all pooled data should be viewed with an element of caution. In this dataset, the significantly higher CPR/OPR with EC does not translate to LBR. Although stratification of women according to EC cannot currently be recommended in clinical practice, a large and well-designed clinical trial to rigorously assess EC as a non-invasive predictor of a successful pregnancy is warranted. We urge for consistent outcome reporting to be mandated for ART trials so that data can be pooled, compared, and concluded on. H.A. was supported by the Hewitt Fertility Centre. S.G.P. and J.W. were supported by the Liverpool University Hospital NHS Foundation Trust. D.K.H. was supported by a Wellbeing of Women project grant (RG2137) and MRC clinical research training fellowship (MR/V007238/1). N.T. was supported by the National Institute for Health and Care Research. D.K.H. had received honoraria for consultancy for Theramex and has received payment for presentations from Theramex and Gideon Richter. The remaining authors have no conflicts of interest to report. PROSPERO CRD42022378464.

Analysis of Reproductive Tract Microecological Changes During the Frozen-Thawed Embryo Transfer Cycle and Clinical Pregnancy Outcomes

This study aims to analyze the relationship between reproductive tract microecological changes, metabolic differences, and pregnancy outcomes at different time points in the frozen-thawed embryo transfer cycle while patients are undergoing hormone replacement therapy, which will be a breakthrough point for improving outcomes. A total of 20 women undergoing frozen-thawed single blastocyst transfer for the first time at the Reproductive Medicine Center of Fujian Maternal and Child Health Hospital between July 2022 and January 2023 were recruited for this study. Their vaginal and cervical secretions were collected for 16S rRNA sequencing and non-targeted metabolomics analysis on days 2-5 of menstruation, day 7 after estrogen replacement therapy started, the day when progesterone was added, and the day of transplantation. The subjects were divided into different groups according to their clinical pregnancy status and the sequencing results were analyzed using bioinformatics methods. 1) The alpha-diversity index of the vaginal and cervical microbiota was higher on days 2-5 of menstruation (P<0.01), but did not differ significantly on day 7 after oral estrogen replacement therapy started, the day of progesterone administration, and the day of transplantation (P≥0.1). 2) Both the pregnant group and the non-pregnant group showed a variety of microorganisms and metabolites with significant differences in the lower reproductive tract at different time points. 3) Microbial analysis at different time points showed that there were significant differences in vaginal flora, including Peptoniphilus, Enterocloster, Finegoldia, Klebsiella, Anaerobutyricum, Agathobaculum, Sporanaerobacter, Bilophila, Prevotella, and Anaerococcus in the pregnant group (P<0.05). 4) Metabolite analysis at different time points showed that there were significant differences in 3-hydroxybenzoic acid, linatine, (R)-amphetamine, hydroxychloroquine, and L-altarate in the vaginal secretions of the pregnant group (P<0.05), and that there were significant differences in isocitric acid, quassin, citrinin, and 12(R)-HETE in the cervical secretions (P<0.05). 5) Metabolite analysis at different time points showed that, in the non-pregnant group, there were significant differences in linatine, decanoyl-L-carnitine, aspartame, sphingosine, and hydroxychloroquine in the vaginal secretions (P<0.05), and the isocitric acid, quassin, ctrinin, and 12(R)-HETE in the cervical secretions (P<0.05). 6) Combined microbiome and metabolomics analysis showed that certain metabolites were significantly associated with microbial communities, especially Klebsiella. Significant differences in the microbiota genera and metabolites at different time points were found during the frozen-embryo transfer cycle of hormone replacement therapy, which may be used as potential biomarkers to predict pregnancy outcomes of embryo transfer.

The Inflammatory State of Follicular Fluid Combined with Negative Emotion Indicators can Predict Pregnancy Outcomes in Patients with PCOS.

Polycystic ovary syndrome (PCOS) is a complex endocrine disorder syndrome with an incidence of 6% to 10% in women of reproductive age. Women with PCOS not only exhibit abnormal follicular development and fertility disorders, but also have a greater tendency to develop anxiety and depression. Our aim was to evaluate the ability of inflammatory factors in follicular fluid to predict embryonic developmental potential and pregnancy outcome and to construct a machine learning model that can predict IVF pregnancy outcomes based on indicators such as basic sex hormones, embryonic morphology, the follicular microenvironment, and negative emotion. In this study, inflammatory factors (CRP, IL-6, and TNF-α) in follicular fluid samples obtained from 225 PCOS and 225 non-PCOS women were detected via ELISA. For patients with PCOS, the levels of CRP and IL-6 in the follicular fluid in the pregnant group were significantly lower than those in the nonpregnant group. For non-patients with PCOS, only the level of IL-6 in the follicular fluid was significantly lower in the pregnant group than in the nonpregnant group. In addition, for both PCOS and non-patients with PCOS, compared with those in the pregnant group, patients in the nonpregnant group showed more pronounced signs of anxiety and depression. Finally, the factors that were significantly different between the two subgroups (pregnancy and nonpregnancy) of patients with or without PCOS were identified by an independent sample t test first and further analysed by multilayer perceptron (MLP) and random forest (RF) models to distinguish the two clinical pregnancy outcomes according to the classification function. The accuracy of the RF model in predicting pregnancy outcomes in patients with or without PCOS was 95.6% and 91.1%, respectively. The RF model is more suitable than the MLP model for predicting pregnancy outcomes in IVF patients. This study not only identified inflammatory factors that can affect embryonic development and assessed the anxiety and depression tendencies of PCOS patients, but also constructed an AI model that predict pregnancy outcomes through machine learning methods, which is a beneficial clinical tool.

MUC16 can Predict the Pregnancy Outcomes in Human and Intraperitoneal Administration of MUC16 can Rescue Pregnancy Losses in Mouse Models.

Mucin 16 (MUC16) participates in the process of embryo implantation, but few studies have examined the association between MUC16 and pregnancy loss. To investigate this association, the expression of MUC16 in serum and decidua was compared between women with pregnancy loss and ongoing pregnancies. In vitro experiments and animal models were used to explore the role and underlying mechanisms of MUC16 in pregnancy loss. In human study, the expression of MUC16 in serum and decidua was both consistently lower in the women with pregnancy loss compared with those in women with ongoing pregnancies. In vitro experiments revealed the interaction of MUC16 with peripheral blood natural killer (pNK) cells. MUC16 changed the phenotype and reduced the pro-inflammation ability of pNK cells. MUC16 also inhibited the cytotoxicity of pNK cells through the Src homology region 2 domain-containing phosphatase-1/extracellular signal-regulated kinase (SHP-ERK) pathway. Furthermore, MUC16 promoted the migration, invasion and tube formation of trophoblast cells by co-culturing together with pNK cells. In vivo experiments, the mouse model of abortion was used to further confirm that intraperitoneal administration of MUC16 could rescue the pregnancy loss. This study reveals the still-unknown connection between MUC16 and pNK cells and indicates that MUC16 provides a novel method for future prediction and treatment of unfavorable pregnancy outcomes.

Prediction of embryo euploidy and pregnancy outcome by blastocyst morphology and development speed for women receiving single embryo transfer

Background Selection of high-quality blastocysts is the most important factor determining the success of assisted reproductive technology. The objective of this study is to assess the values of blastocyst morphological quality and development speed for predicting euploidy and clinical pregnancy outcome. Methods A total of 155 preimplantation genetic testing cycles including 959 blastocysts and 154 euploid blastocyst transfer cycles conducted between January 2018 and December 2019 were retrospectively analysed. The associations of blastocyst morphological quality and development speed (D) with chromosomal status, clinical pregnancy rate, early miscarriage rate, and ongoing pregnancy rate were evaluated by univariate and multivariate regression. Results The euploidy rate of development speed D5 blastocysts was significantly greater than that of D6 blastocysts (61.4% vs. 38.1%, P < 0.001), and the euploid rate of morphologically high-grade blastocysts was significantly greater than that of non-high-grade blastocysts. Development speed D5 (OR = 1.6, 95% CI 1.2–2.2, P = 0.02) and high-grade morphology (OR = 2.1, 95% CI 1.5–2.9, P = 0.01) were independent predictors of euploidy. The ongoing pregnancy rate of D5 blastocysts was significantly higher than that of D6 blastocysts (62.3% vs. 43.8%, P = 0.04). Transfer of euploid blastocysts with high-grade morphology resulted in a greater ongoing pregnancy rate than transfer of non-high-grade euploid blastocysts (60.7% vs. 43.2%, P = 0.049). Alternatively, D6 development speed was an independent risk factor for early pregnancy loss after euploid blastocyst transfer. Multivariate regression analysis adjusting for confounding factors identified maternal age, blastocyst development speed, and blastocyst morphological grade as independent predictors of euploidy but not of clinical pregnancy. Conclusion The recommended sequence of embryo transfer based on the present study is D5 high-grade > D6 high-grade > D5 non-high-grade > D6 non-high-grade.

Machine learning to identify endometrial biomarkers predictive of pregnancy success following artificial insemination in dairy cows†.

The objective was to identify a set of genes whose transcript abundance is predictive of a cow's ability to become pregnant following artificial insemination. Endometrial epithelial cells from the uterine body were collected for RNA sequencing using the cytobrush method from 193 first-service Holstein cows at estrus prior to artificial insemination (day 0). A group of 253 first-service cows not used for cytobrush collection were controls. There was no effect of cytobrush collection on pregnancy outcomes at day 30 or 70 or on pregnancy loss between days 30 and 70. There were 2 upregulated and 214 downregulated genes (false discovery rate < 0.05, absolute fold change >2-fold) for cows pregnant at day 30 versus those that were not pregnant. Functional terms overrepresented in the downregulated genes included those related to immune and inflammatory responses. Machine learning for fertility biomarkers with the R package BORUTA resulted in identification of 57 biomarkers that predicted pregnancy outcome at day 30 with an average accuracy of 77%. Thus, machine learning can identify predictive biomarkers of pregnancy in endometrium with high accuracy. Moreover, sampling of endometrial epithelium using the cytobrush can help understand functional characteristics of the endometrium at artificial insemination without compromising cow fertility. Functional characteristics of the genes comprising the set of biomarkers is indicative that a major determinant of cow fertility, at least for first insemination after calving, is immune status of the uterus, which, in turn, is likely to reflect the previous history of uterine disease.

Gestational weight gain and pregnancy outcomes in Chinese women with type 2 diabetes mellitus: evidence from a tertiary hospital in Beijing.

To examine the effects of gestational weight gain on pregnancy outcomes and determine the optimal range of weight gain during pregnancy for Chinese women with type 2 diabetes mellitus. This retrospective cohort study included 691 Chinese women with type 2 diabetes mellitus from 2012 to 2020. The study utilized a statistical-based approach to determine the optimal range of gestational weight gain. Additionally, multivariate logistic regression analysis was conducted to assess the impact of gestational weight gain on pregnancy outcomes. (1) In the obese subgroup, gestational weight gain below the recommendations was associated with decreased risks of large for gestational age (adjusted odds ratio [aOR] 0.19; 95% confidence interval [CI] 0.06-0.60) and macrosomia (aOR 0.18; 95% CI 0.05-0.69). In the normal weight subgroup, gestational weight gain below the recommendations of the Institute of Medicine was associated with decreased risks of preeclampsia (aOR 0.18; 95% CI 0.04-0.82) and neonatal hypoglycemia (aOR 0.38; 95% CI 0.15-0.97). (2) In the normal weight subgroup, gestational weight gain above the recommendations of the Institute of Medicine was associated with an increased risk of large for gestational age (aOR 4.56; 95% CI 1.54-13.46). In the obese subgroup, gestational weight gain above the recommendations was associated with an increased risk of preeclampsia (aOR 2.74; 95% CI 1.02, 7.38). (3) The optimal ranges of gestational weight gain, based on our study, were 9-16kg for underweight women, 9.5-14kg for normal weight women, 6.5-12kg for overweight women, and 3-10kg for obese women. (4) Using the optimal range of gestational weight gain identified in our study seemed to provide better prediction of adverse pregnancy outcomes. For Chinese women with type 2 diabetes, inappropriate gestational weight gain is associated with adverse pregnancy outcomes, and the optimal range of gestational weight gain may differ from the Institute of Medicine recommendations.

Role of admission cardiotocography in predicting pregnancy outcome in postdated pregnancies

Role of admission cardiotocography in predicting pregnancy outcome in postdated pregnancies