Predictor Of Pregnancy Outcome Research Articles

Does the combination of four OGTT values enhance the prediction of adverse pregnancy outcomes? Insights from a retrospective cohort study.

To explore the correlation between a singular value of additive OGTT scores and adverse maternal and neonatal outcomes. We postulated that a higher additive OGTT score would predict poorer maternal and neonatal outcomes. In this retrospective cohort study, data were collected from all women with a documented complete OGTT result and subsequent diagnosis of GDM. The additive OGTT score was calculated by adding each individual hourly glucose measurement. Maternal demographics, pregnancy and labor characteristics, and neonatal outcomes were compared between the lower-sum and higher-sum OGTT groups. A multivariate regression analysis was performed to identify confounders associated with adverse outcomes. In this study, a total of 1497 patients were assessed. The group with higher-sum OGTT scores was characterized by increased rates of GDMA2 (p = 0.008), higher insulin doses (p = 0.009), and higher rates of composite maternal and neonatal adverse outcomes (p = 0.021 and p = 0.030, respectively) compared to the lower-sum OGTT group. The additive OGTT score may aid in predicting the need for insulin treatment, labor course, and neonatal outcomes in GDM patients.

102 Estradiol and follicular growth are associated with estrous behavior monitored by an accelerometer in grazing beef cows

Abstract In beef cattle, 40% of cows that display estrus do not remain pregnant after embryo transfer (ET). Estrus is a physiological behavior influenced by the concentration of sex-steroids. The use of accelerometer devices for estrus detection is a common practice in dairy operations. It remains unclear if this same artificial intelligence software can accurately measure reproductive behavior in beef females. We hypothesized that estrous variables detected by an accelerometer are associated with ovarian, hormonal, pregnancy outcome, and fertility-related variables measured in the cow. Fifty Bos indicus-influenced, cyclic, primiparous cows were fitted with an accelerometer collar (SCR Engineers, Israel) and a breeding indicator (Estrotectâ) to detect estrus after a synchronization protocol in five subsequent experimental replicates (n = 50*5 = 250). Only cows that showed estrus (d 0) remained in the study. The following variables were used from the accelerometer software: Activity Peak, Rumination Nadir, Estrus Duration, and Heat Index, calculated by proprietary algorithms. Dominant follicle (DF) diameter and plasma concentration of estradiol were measured on d -2 (day of progesterone device removal) and on d 0. On d -1 and d 4, endometrial thickness and luminal fluid accumulation were measured by ultrasonography. On d 7, two embryos were transferred/cow. Pregnancies were diagnosed on d 45 and terminated. After 30 d, a new replicate started. Cows included in at least two replicates that remained pregnant 100%, 99-50%, or less than 50% were classified as fertile, sub fertile, and infertile, respectively. Estrus display was recorded for 166 cows (66%). Estrus detection by accelerometer and Estrotect had excellent agreement rate (kappa coefficient 0.76). Cows detected in estrus only by Estrotect had 66% less pregnancy/ET than cows in estrus by both (9/21 vs. 97/145; P = 0.01). The DF diameter on d 0 was not associated with accelerometer variables. Cows with greater and moderate Activity Peak had a greater growth rate of the DF from d -2 to d 0 than lower Activity Peak cows (interaction day*Activity Peak; P = 0.06). Estradiol on d -1 was positively associated with the Activity Peak (P < 0.0001). Cows with lower Activity Peak had a thicker endometrium on both d -1 and d 4 (P=0.02), and greater uterine luminal fluid score on d -1 (P=0.03). Fertility status was not associated with any accelerometer variables. In conclusion, the Activity Peak is associated positively with estradiol concentration and DF growth, however no association was found with pregnancy outcome and fertility. Therefore, the main advantage of accelerometers in beef ranches is the ability to detect estrus at a similar accuracy as breeding indicators, using less labor. Future enhancements in hardware and software to allow prediction of pregnancy outcomes are expected to increase reproductive efficiency in cow-calf operations.

Unlocking Infertility: Enhancing Pregnancy Rates With Personalized Embryo Transfers Using Optimal Time for Endometrial Receptivity Analysis in Recurrent Implantation Failure Patients Undergoing In Vitro Fertilization.

Background Infertility remains a significant global challenge, and recurrent implantation failure (RIF) poses a considerable concern in assisted reproductive technology. Understanding the factors contributing to implantation failure is essential for developing accurate diagnostic tools and treatment strategies. Endometrial receptivity (ER) during the window of implantation is crucial for successful embryo implantation in in vitro fertilization (IVF) procedures. Molecular-based endometrial receptivity analysis and next-generation sequencing provide insights into ER, but there is a lack of research on these in the Indian population, particularly in patients with RIF. This retrospective cohort study evaluates the effectiveness of Optimal Timing for Endometrial Receptivity Analysis (OpERA)-guided personalized embryo transfer (pET) in Indian patients with a history of RIF. Methodology The study includes 158 female patients with a history of failed embryo transfers who underwent OpERA testing before frozen embryo transfer. Patients were categorized based on the number of previous failed transfers. OpERA outcomes were assessed, and clinical outcomes were compared between groups undergoing preimplantation genetic testing for aneuploidy (PGT-A) with and without OpERA. Endometrial preparation involved hormone replacement therapy, and OpERA testing was performed at the Neuberg Centre for Genomic Medicine using RNA extraction, cDNA conversion, and sequencing. Results OpERA outcomes showed no significant differences in receptive rates among patient groups. Group 3, with three or more failed transfers, exhibited significantly higher biochemical pregnancy rates (BPRs), clinical pregnancy rates (CPRs), and abortion rates (ARs) compared to Groups 1 and 2. OpERA with PGT-A showed significantly higher BPR, implantation rate, CPR, and lower AR compared to OpERA without PGT-A. Conclusions OpERA-guided pET, especially with PGT-A, demonstrated improved pregnancy outcomes, particularly in patients with a history of RIF. The study emphasizes the importance of OpERA in determining optimal transfer timing, moving beyond the traditional reliance on embryo quality alone.OpERA presents promise in predicting pregnancy outcomes for Indian patients with previous IVF failures. The integration of OpERA and PGT-A represents a significant advancement in personalized reproductive medicine, offering new hope for individuals grappling with infertility complexities.

The role of the cerebroplacental ratio in predicting pregnancy outcomes at 40-42 gestational weeks: a prospective observational trial.

The cerebroplacental ratio is a sonographic tool used to predict poor pregnancy outcomes. Data are insufficient regarding its use in postdate pregnancy. We evaluated the cerebroplacental ratio's prediction of unfavorable pregnancy outcomes in women at 40-42 weeks gestation with normal amniotic fluid index. This prospective observational study included 101 women with low-risk singleton pregnancy and gestational age > 40 weeks who delivered in a university affiliated hospital during 2020-2021. The middle cerebral artery pulsatility index, the umbilical artery pulsatility index, and the cerebroplacental ratio, which is their quotient, were compared between women with favorable and unfavorable pregnancy outcomes. The latter included: meconium-stained amniotic fluid, cesarean or vacuum-assisted delivery due to pathological cardiotocography (category 2 or 3), 5-min Apgar score < 7, umbilical cord pH < 7.1, neonatal intensive care unit admission, and neonatal death. Fetal Doppler, performed at a median gestational age of 40.3 (40.0-41.6), did not differ between 75 (74.3%) women with favorable obstetrical outcomes and 26 (25.7%) with unfavorable outcomes. In multivariate analysis, advanced maternal age and a history of a cesarean section were correlated with unfavorable outcomes, while Doppler indices were not found to be predictive. Among women at 41-42 weeks' gestation, for those with intrapartum fetal monitor category 2-3 vs. category 1, the mean umbilical artery pulsatility index was higher: 0.92±0.34 vs. 0.71±0.11 (p = 0.044). According to the study results, fetal Doppler indices, including the cerebroplacental ratio, are not predictive of unfavorable outcome in women with pregnancies exceeding 40 weeks. Larger prospective studies are needed.

Preliminary application of real-time shear wave elastography to evaluate endometrial receptivity and predict pregnancy outcome

BACKGROUND: Endometrial receptivity is crucial for the establishment of a healthy pregnancy outcome. Previous research on endometrial receptivity primarily examined endometrial thickness, endometrial echo types, and endometrial blood supply. OBJECTIVE: To explore the differences in the elastic modulus of the endometrium in women with various pregnancy outcomes by real-time shear wave elastography (SWE) and to investigate its application value in evaluation of endometrial receptivity. METHODS: A total of 205 pregnant women who were admitted at Wenzhou People’s Hospital between January 2021 and December 2022 were selected. Three-dimensional transvaginal sonography and real-time shear wave elastography were performed in the proliferative phase and receptive phase of the endometrium, and the average elastic modulus of the endometrium in the two phases was obtained and compared. According to whether the pregnancy was successful or not, the participants were divided into the pregnancy group (n= 72) and non-pregnancy group (n= 133), and the differences in intimal thickness, 3D blood flow parameters, and average elastic modulus of intima were compared between the two groups. RESULTS: The average elastic modulus of the endometrium in the proliferative phase and receptive phase was (23.92 ± 2.31) kPa and (11.82 ± 2.24) kPa, respectively, and the difference was statistically significant P&lt; 0.05. The average elastic modulus of the endometrium in the pregnancy group and non-pregnancy group was (9.97 ± 1.08) kPa and (12.82 ± 2.06) kPa, respectively, and the difference was statistically significant P&lt; 0.05. The area under the curve of predicting pregnancy by the average elastic modulus of the endometrium in the receptive phase was 0.888 (0.841∼0.934), with corresponding P value &lt; 0.05. The critical value was 11.15, with a corresponding sensitivity of 81.7% and specificity of 78.2%. CONCLUSION: Real-time shear wave elastography can quantitatively evaluate endometrial elasticity, indirectly reflect the endometrial phase, and provide a new diagnostic concept for evaluating endometrial receptivity and predicting pregnancy outcome in infertile patients.

Associations between the artificial intelligence scoring system and live birth outcomes in preimplantation genetic testing for aneuploidy cycles

BackgroundSeveral studies have demonstrated that iDAScore is more accurate in predicting pregnancy outcomes in cycles without preimplantation genetic testing for aneuploidy (PGT-A) compared to KIDScore and the Gardner criteria. However, the effectiveness of iDAScore in cycles with PGT-A has not been thoroughly investigated. Therefore, this study aims to assess the association between artificial intelligence (AI)-based iDAScore (version 1.0) and pregnancy outcomes in single-embryo transfer (SET) cycles with PGT-A.MethodsThis retrospective study was approved by the Institutional Review Board of Chung Sun Medical University, Taichung, Taiwan. Patients undergoing SET cycles (n = 482) following PGT-A at a single reproductive center between January 2017 and June 2021. The blastocyst morphology and morphokinetics of all embryos were evaluated using a time-lapse system. The blastocysts were ranked based on the scores generated by iDAScore, which were defined as AI scores, or by KIDScore D5 (version 3.2) following the manufacturer’s protocols. A single blastocyst without aneuploidy was transferred after examining the embryonic ploidy status using a next-generation sequencing-based PGT-A platform. Logistic regression analysis with generalized estimating equations was conducted to assess whether AI scores are associated with the probability of live birth (LB) while considering confounding factors.ResultsLogistic regression analysis revealed that AI score was significantly associated with LB probability (adjusted odds ratio [OR] = 2.037, 95% confidence interval [CI]: 1.632–2.542) when pulsatility index (PI) level and types of chromosomal abnormalities were controlled. Blastocysts were divided into quartiles in accordance with their AI score (group 1: 3.0–7.8; group 2: 7.9–8.6; group 3: 8.7–8.9; and group 4: 9.0–9.5). Group 1 had a lower LB rate (34.6% vs. 59.8–72.3%) and a higher rate of pregnancy loss (26% vs. 4.7–8.9%) compared with the other groups (p < 0.05). The receiver operating characteristic curve analysis verified that the iDAScore had a significant but limited ability to predict LB (area under the curve [AUC] = 0.64); this ability was significantly weaker than that of the combination of iDAScore, type of chromosomal abnormalities, and PI level (AUC = 0.67). In the comparison of the LB groups with the non-LB groups, the AI scores were significantly lower in the non-LB groups, both for euploid (median: 8.6 vs. 8.8) and mosaic (median: 8.0 vs. 8.6) SETs.ConclusionsAlthough its predictive ability can be further enhanced, the AI score was significantly associated with LB probability in SET cycles. Euploid or mosaic blastocysts with low AI scores (≤ 7.8) were associated with a lower LB rate, indicating the potential of this annotation-free AI system as a decision-support tool for deselecting embryos with poor pregnancy outcomes following PGT-A.

Overexpression of regulatory T cells in patients with unexplained recurrent pregnancy loss: friend or foe?

This study aimed to investigate the role of regulatory T cells in patients with unexplained recurrent pregnancy loss (URPL). We retrospectively analyzed 136 women who had experienced two or more miscarriages before 24 weeks of gestation for no obvious reason from May 2018 to October 2021. The basic clinical data of the patients and expression of lymphocyte subsets such as regulatory T cells (Tregs) and natural killer cells (NKs) by flow cytometry were collected to explore the risk factors of pregnancy outcome in URPL patients. A total of 136 URPL patients were enrolled in this study. Eventually, 50 patients attained clinical pregnancy. The median age was 31.8 ± 4.6 years in patients with clinical pregnancy. The univariate and multivariate logistic regression analyses indicated that Tregs was associated with the pregnancy outcomes of patients with URPL (odds ratio 0.63, 95% confidence interval 0.50-0.80). More importantly, a U-shaped association was found between Tregs and pregnancy outcome (p < 0.001), with either higher or lower Tregs levels adversely affecting pregnancy outcome. Tregs levels that are either too high or too low can harm pregnancy outcomes. It was expected to be a very promising quantitative biomarker for predicting pregnancy outcomes in URPL patients.

Alteration in maternal serum uric acid levels in pre-eclampsia and associated perinatal outcomes: a cross-sectional study in Ghana.

pre-eclampsia (PE) is a multisystemic pregnancy-specific hypertensive disorder associated with significant adverse maternal and perinatal outcomes. Maternal serum uric acid level is hypothesized as a reliable marker for predicting the severity and adverse outcomes of pre-eclampsia and facilitating clinical decisions. This study explored the association between maternal serum uric acid and adverse pregnancy outcomes in pre-eclampsia. a cross-sectional study involving women diagnosed with pre-eclampsia was conducted at Korle-Bu Teaching Hospital (KBTH), a tertiary hospital in Ghana. Descriptive analyses were performed and multivariable logistic regression model was used to explore the association between maternal serum uric acid levels and pregnancy outcomes using R software. we included 100 women with pre-eclampsia comprising 79% and 21% preterm and term pre-eclampsia respectively and with mean gestational age (GA) at diagnosis of 32.35±2.66 weeks and 35.96±1.94 weeks respectively. The mean maternal age of preterm and term pre-eclampsia groups was 29.81±5.29 years and 29.46±5.78 years respectively. Hyperuricemia (serum uric acid >375 µmol/L) occurred in 61% of the pre-eclamptic women. The mean gestational age (in weeks) at diagnosis was significantly lower in the pre-eclamptic women with hyperuricemia compared with those with normal levels of uric acid (33.51±3.03 versus 34.80±2.71). There was a significant negative association (moderate correlation) between maternal serum uric acid levels and birth weight (R= -0.34, p < 0.001) in pre-eclampsia; the statistical significance was limited to preterm only (Pearson R= -0.39, p-value <0.001) but not term pre-eclampsia. Hyperuricemia was significantly associated with low birth weight [aOR: 3.222 (95% CI: 1.098, 10.393)], caesarean section [aOR: 2.281 (95% CI: 1.084, 7.568)] and severe diastolic pressure at birth [aOR: 3.517 (95% CI: 1.123, 11.939)]. hyperuricemia in pre-eclampsia was significantly associated with both maternal (caesarean section and severe hypertension) and neonatal (low birth weight) adverse outcomes. Hyperuricemia seems clinically useful in predicting pregnancy outcomes, especially in preterm pre-eclampsia. Further longitudinal study is recommended in exploring the clinical significance of maternal uric acid levels and pregnancy outcomes in pre-eclampsia.

1138 Prediction of pregnancy outcomes by various blood pressure metrics among patients with mild chronic hypertension

1138 Prediction of pregnancy outcomes by various blood pressure metrics among patients with mild chronic hypertension

Application value of serum S100B combined with glucose metabolism indexes in predicting adverse pregnancy outcomes of patients with severe preeclampsia.

S100 calcium-binding protein B (S100B) and glucose control are reflective of maternal-fetal risks. We investigated the value of serum S100B combined with fasting blood glucose (FBG)/hemoglobin A1c (HbA1c) in evaluating the pregnancy outcomes of patients with severe preeclampsia (SPE). The clinical characteristics of SPE patients/controls were collected. FBG/HbA1c and serum S100B levels were measured, with their correlations analyzed. SPE patients were subdivided into adverse/non-adverse outcome groups based on follow-up results. The value of different indexes in predicting pregnancy outcomes was analyzed. SPE patients showed higher systolic blood pressure, diastolic blood pressure, urine protein, and body mass index and lower platelets, gestational age at delivery, and infant birth weight than healthy controls. FBG and HbA1c were positively correlated with serum S100B. SPE patients with adverse outcomes exhibited increased serum S100B and FBG/HbA1c levels. The area under the curve of serum S100B + FBG/HbA1c in evaluating adverse pregnancy outcomes of SPE patients was 0.8412 (77.05% sensitivity/84.21% specificity), higher than either alone. Serum S100B and FBG/HbA1c were independent risk factors for adverse outcomes of SPE patients. Overall, serum S100B positively-correlates with FBG/HbA1c in SPE patients. Serum S100B and FBG/HbA1c are independent risk factors, and their combination has high value on predicting adverse pregnancy outcomes of SPE patients.

Correlation between preoperative three-dimensional transvaginal ultrasound and postoperative pregnancy outcomes after hysteroscopic adhesiolysis.

Uterine adhesion is mainly caused by endometrial injury, leading to poor postoperative pregnancy outcome. Therefore, preoperative evaluation on uterine cavity, especially endometrial condition, is very necessary. This study aims to explore the correlation between preoperative three-dimensional transvaginal ultrasound (3D-TVS) imaging characteristics and postoperative pregnancy outcomes after hysteroscopic adhesiolysis (HA). A total of 401 patients, who underwent HA surgery from February 22, 2018 to October 31, 2018 at the Third Xiangya Hospital of Central South University or Changsha Jiangwan Hospital, were enrolled, and we collected data regarding the preoperative 3D-TVS imaging characteristics and followed up their postoperative pregnancy outcomes. Correlation analysis and univariate and multivariate logistic regression analysis were performed between imaging features and pregnancy outcomes (live and non-live birth outcomes) in patients with intrauterine adhesion. The results of correlation analysis showed that endometrial thickness, endometrial echo, visible tubal openings, endometrial blood flow, intercornual distance, and endometrial peristalsis were correlated with the live birth rate (all P<0.05). Logistic regression analysis revealed that in the HA patients with the live birth, the endometrial thickness was thicker (P<0.001), endometrial echo was more homogeneous (P<0.001), the number of tubal openings was more (P<0.001), the intercornual distance was wider (P<0.05), the endometrial blood flow, and irregular cases of endometrial peristaltic waves were more and cases of deficiency were fewer (both P<0.01) than those in the non-live birth group. Preoperative 3D-TVS imaging performance is closely related to pregnancy outcomes of HA patients, and preoperative 3D-TVS can be used to predict pregnancy outcomes after HA.

Species composition of vaginal lactobacilli in the first, second and third trimester as a marker of pregnancy outcomes

BACKGROUND: Lactobacilli are the main and most important component of the vaginal microbiota of reproductive-age women. During pregnancy, the composition of the vaginal microbiota changes and acquires additional significance, acting as a barrier against infection for both the mother and the fetus. Furthermore, the vaginal microbiota contributes to the normal course of pregnancy, postpartum recovery, and primary colonization of the newborn. Changes in the composition and number of vaginal lactobacilli during pregnancy can lead to serious disorders. Despite much research on the role of the vaginal microbiota, the details of how changes in lactobacilli composition and diversity may affect pregnancy outcomes are poorly understood.&#x0D; AIM: The aim of this study was to evaluate the vaginal lactoflora composition and stability in each trimester to predict pregnancy outcomes.&#x0D; MATERIALS AND METHODS: This open prospective study involved 100 women who had been registered at the dispensary in early pregnancy (up to 12 weeks). To determine the type of microbiocenosis and the species composition of lactobacilli, the vaginal discharge was examined microscopically and by real-time polymerase chain reaction.&#x0D; RESULTS: Normocenosis was identified in 86 (86%) pregnant women, the intermediate type of vaginal microbiocenosis in 4 (4%) pregnant women, and bacterial vaginosis in 10 (10%) pregnant women. The rate of negative pregnancy outcomes was 19%, of which 7% and 12% of women had premature births or miscarriages, respectively. The concentration of vaginal lactobacilli in each pregnant woman was relatively stable over the three trimesters. Among the dominant microflora, the frequency of Lactobacillus crispatus increased by the third trimester. Lactobacillus iners was associated with an increased incidence of premature birth and may be considered as a risk factor.&#x0D; CONCLUSIONS: Real-time PCR test for specific detection and quantification of vaginal lactobacilli in pregnant women has prognostic value and may be recommended as a possible screening test for women with high risk of adverse pregnancy outcomes.

Enhancing IVF Success: The Role of Endometrial Receptivity and Uterine Scoring in Predicting Pregnancy Outcomes

Enhancing IVF Success: The Role of Endometrial Receptivity and Uterine Scoring in Predicting Pregnancy Outcomes

#92 : An Artificial Intelligence Algorithm Outperforms Highly Variable Embryologist Grading for Predicting the Likelihood of Pregnancy Outcome from Embryo Images

Background and Aims: Embryologist evaluation of embryos is critical for ensuring successful pregnancy outcomes. Standard, manual evaluation is variable, subjective, and time-consuming. The aim of this study was to evaluate whether an artificial intelligence (AI) algorithm can standardize and improve embryo evaluation during IVF. Method: 20 images of blastocyst-stage embryos on day 5 of in vitro development were selected to represent a range of morphological qualities. All embryos had been transferred and the clinical pregnancy outcome was known for each embryo based on detection of fetal heartbeat at first ultrasound scan (∼7-9 weeks gestation). 50% of embryos in the dataset resulted in pregnancy. 158 embryologists made a total of 236 attempts at providing their evaluation of the morphological quality of the 20 embryo images using the Gardner system. The embryologist-assigned grades were then used to generate their prediction of whether that embryo would lead to pregnancy or not (≥ 3BB indicated a pregnancy prediction, and &lt;3BB indicated a non-pregnancy prediction). The same 20 embryo images were also assessed by a previously developed viability AI algorithm for evaluating the likelihood of clinical pregnancy based on embryo images. An AI score of ≥5.0/10 indicated a pregnancy prediction, and &lt;5.0/10 indicated a non-pregnancy prediction. The AI algorithm provided the same score for each embryo image regardless of how many times the analysis was performed. Results: The AI algorithm correctly predicted pregnancy outcome for 14/20 embryo images (70%). Embryologists also correctly predicted 14/20 images in 14/236 attempts (6%), and in 1 attempt correctly predicted 15/20 images. In the remaining 221 attempts (94%) embryologists correctly predicted between 6-13 images, representing a range of accuracies from 30-75%. Conclusion: This study demonstrates the inherent variability and lack of objectivity associated with an embryologist’s evaluation of embryos. It highlights the benefits of accurate AI algorithms for standardizing embryo assessment

The predictive value of uterine artery Doppler in the success rate of pregnancy from the first frozen embryo transfer during the implantation window

BackgroundWorldwide, frozen embryo transfer (FET) has become a new strategy for the treatment of infertility. The success of FET is closely related to endometrial receptivity. Does uterine artery Doppler during the implantation window predict pregnancy outcome from the first FET?MethodsA total of 115 retrospectively collected cycles were included in the study, with 64 cycles of clinical pregnancy and 51 cycles of nonclinical pregnancy; There were 99 nonabsent end-diastolic flow (NAEDF) cycles and 16 absent end-diastolic flow (AEDF) cycles. The differences in uterine artery Doppler findings between different pregnancy outcomes were investigated. The clinical pregnancy rate and spontaneous abortion rate in the NAEDF and AEDF groups were compared. The predictive value of uterine artery Doppler during the implantation window in the success rate of pregnancy from the first FET was also investigated.ResultsBetween the clinical pregnancy group and the nonclinical pregnancy group, there were no significant differences in the mean resistance index (mRI) (Z = -1.065, p = 0.287), mean pulsatility index (mPI) (Z = -0.340, p = 0.734), and mean peak systolic/end-diastolic velocity(mS/D) (Z = -0.953, p = 0.341); there were significant differences in the mean peak systolic velocity (mPSV) (Z = -1.982, p = 0.048) and mean end-diastolic velocity (mEDV) (Z = -2.767, p = 0.006). Between the NAEDF and AEDF groups, there was no significant difference in the clinical pregnancy rate (χ2 = 0.003, p = 0.959), and there was a significant difference in the spontaneous abortion rate (χ2 = 3.465, p = 0.019). Compared with uterine artery Doppler alone, its combination with artificial abortion history, waist-to-hip ratio, LH (Luteinizing hormone) of P (Progesterone) administration day, mPSV and mEDV had a higher predictive value regarding clinical pregnancy from the first FET [ROC-AUC 0.782, 95% CI (0.680–0.883) vs. 0.692, 95% CI (0.587–0.797)].ConclusionsUterine artery Doppler, particularly mPSV and mEDV during the implantation window, was useful for predicting clinical pregnancy, and AEDF was related to spontaneous abortion in the first trimester. Uterine artery Doppler combined with artificial abortion history, waist-to-hip ratio, LH of P administration day, mPSV and mEDV have a higher predictive value than uterine artery Doppler alone regarding the pregnancy from the first FET.

Using feature optimization and LightGBM algorithm to predict the clinical pregnancy outcomes after in vitro fertilization.

According to a recent report by the WHO, approximately 17.5\% (about one-sixth) of the global adult population is affected by infertility. Consequently, researchers worldwide have proposed various machine learning models to improve the prediction of clinical pregnancy outcomes during IVF cycles. The objective of this study is to develop a machine learning(ML) model that predicts the outcomes of pregnancies following in vitro fertilization (IVF) and assists in clinical treatment. This study conducted a retrospective analysis on provincial reproductive centers in China from March 2020 to March 2021, utilizing 13 selected features. The algorithms used included XGBoost, LightGBM, KNN, Naïve Bayes, Random Forest, and Decision Tree. The results were evaluated using performance metrics such as precision, recall, F1-score, accuracy and AUC, employing five-fold cross-validation repeated five times. Among the models, LightGBM achieved the best performance, with an accuracy of 92.31%, recall of 87.80%, F1-score of 90.00\%, and an AUC of 90.41%. The model identified the estrogen concentration at the HCG injection(etwo), endometrium thickness (mm) on HCG day(EM TNK), years of infertility(Years), and body mass index(BMI) as the most important features. This study successfully demonstrates the LightGBM model has the best predictive effect on pregnancy outcomes during IVF cycles. Additionally, etwo was found to be the most significant predictor for successful IVF compared to other variables. This machine learning approach has the potential to assist fertility specialists in providing counseling and adjusting treatment strategies for patients.

Evaluation of novel biomarkers for early pregnancy outcome prediction†.

To assess performance and discriminatory capacity of commercially available enzyme-linked immunosorbent assays of biomarkers for predicting first trimester pregnancy outcome in a multi-center cohort. In a case-control study at three academic centers of women with pain and bleeding in early pregnancy, enzyme-linked immunosorbent assays of biomarkers were screened for assay performance. Performance was assessed via functional sensitivity, assay reportable range, recovery/linearity, and intra-assay precision (%Coefficient of Variation). Top candidates were analyzed for discriminatory capacity for viability and location among 210 women with tubal ectopic pregnancy, viable intrauterine pregnancy, or miscarriage. Assay discrimination was assessed by visual plots, area under the curve with 95% confidence intervals, and measures of central tendency with two-sample t-tests. Of 25 biomarkers evaluated, 22 demonstrated good or acceptable assay performance. Transgelin-2, oviductal glycoprotein, and integrin-linked kinase were rejected due to poor performance. The best biomarkers for discrimination of pregnancy location were pregnancy-specific beta-1-glycoprotein 9, pregnancy-specific beta-1-glycoprotein 1, insulin-like growth factor binding protein 1, kisspeptin (KISS1), pregnancy-specific beta-1-glycoprotein 3, and beta parvin (PARVB). The best biomarkers for discrimination of pregnancy viability were pregnancy-specific beta-1-glycoprotein 9, pregnancy-specific beta-1-glycoprotein 3, EH domain-containing protein 3, KISS1, WAP four-disulfide core domain protein 2 (HE4), quiescin sulfhydryl oxidase 2, and pregnancy-specific beta-1-glycoprotein 1. Performance of commercially available enzyme-linked immunosorbent assays was acceptable for a panel of novel biomarkers to predict early pregnancy outcome. Of these, six and seven candidates demonstrated good discriminatory capacity of pregnancy location and viability, respectively, when validated in a distinct external population. Four markers demonstrated good discrimination for both location and viability.

Prediction of spontaneous preterm birth using supervised machine learning on metabolomic data: A case-cohort study.

To identify and internally validate metabolites predictive of spontaneous preterm birth (sPTB) using multiple machine learning methods and sequential maternal serum samples, and to predict spontaneous early term birth (sETB) using these metabolites. Case-cohort design within a prospective cohort study. Cambridge, UK. A total of 399 Pregnancy Outcome Prediction study participants, including 98 cases of sPTB. An untargeted metabolomic analysis of maternal serum samples at 12, 20, 28 and 36 weeks of gestation was performed. We applied six supervised machine learning methods and a weighted Cox model to measurements at 28 weeks of gestation and sPTB, followed by feature selection. We used logistic regression with elastic net penalty, followed by best subset selection, to reduce the number of predictive metabolites further. We applied coefficients from the chosen models to measurements from different gestational ages to predict sPTB and sETB. sPTB and sETB. We identified 47 metabolites, mostly lipids, as important predictors of sPTB by two or more methods and 22 were identified by three or more methods. The best 4-predictor model had an optimism-corrected area under the receiver operating characteristics curve (AUC) of 0.703 at 28 weeks of gestation. The model also predicted sPTB in 12-week samples (0.606, 95% CI 0.544-0.667) and 20-week samples (0.657, 95% CI 0.597-0.717) and it predicted sETB in 36-week samples (0.727, 95% CI 0.606-0.849). A lysolipid, 1-palmitoleoyl-GPE (16:1)*, was the strongest predictor of sPTB at 12 weeks of gestation (0.609, 95% CI 0.548-0.670), 20 weeks (0.630, 95% CI 0.569-0.690) and 28 weeks (0.660, 95% CI 0.599-0.722), and of sETB at 36 weeks (0.739, 95% CI 0.618-0.860). We identified and internally validated maternal serum metabolites predictive of sPTB. A lysolipid, 1-palmitoleoyl-GPE (16:1)*, is a novel predictor of sPTB and sETB. Further validation in external populations is required.

Maternal high body mass index, but not gestational diabetes, is associated with poorer educational attainment in mid-childhood

Previous studies suggest that gestational diabetes mellitus is associated with poorer cognitive outcomes in children. However, confounding factors, especially maternal body mass index, have been poorly accounted for. This study aimed to examine the independent associations between maternal body mass index, gestational diabetes mellitus status, and educational outcomes. Antenatal data from a prospective birth cohort (Pregnancy Outcome Prediction Study, 2008-2012, Cambridge, United Kingdom) were linked to mid-childhood educational outcomes (Department for Education, United Kingdom). A total of 3249 children born at term were stratified by maternal gestational diabetes mellitus status and body mass index at booking (<25 vs ≥25 kg/m2). Regression models adjusted for relevant maternal, child, and socioeconomic factors were used to determine associations with academic outcomes at ages of 5 to 7 years. No differences in educational attainment were found between children exposed to gestational diabetes mellitus and nonexposed children. Neither maternal glucose levels measured at 11 to 14 or 24 to 28 weeks, nor acceleration of the fetal abdominal circumference growth velocity were related to educational attainment at ages of 5 to 7 years. Children of mothers with booking body mass index ≥25 kg/m2 (vs <25 kg/m2) were ∼50% more likely to not meet expected educational standards regardless of gestational diabetes mellitus status (age 5: adjusted odds ratio, 1.44; 95% confidence interval, 1.19-1.74; P<.001; age 6: adjusted odds ratio, 1.61; 95% confidence interval, 1.28-2.02; P<.001). The association between maternal body mass index and offspring educational attainment is dose-dependent and robust to stratification by gestational diabetes mellitus status and adjustment for socioeconomic factors. Mid-childhood educational attainment is not associated with maternal glucose status. This may provide important reassurance for pregnant women and clinicians. However, maternal body mass index is associated with lower childhood educational attainment and may be modifiable with intervention before or during pregnancy.

Initial β-hCG levels and 2-day-later increase rates effectively predict pregnancy outcomes in single blastocyst transfer in frozen-thawed or fresh cycles: A retrospective cohort study.

To investigate whether the initial beta-human chorionic gonadotropin (β-hCG) levels and their rate of increase differ after single fresh and frozen blastocyst transfers, and whether these values effectively predict pregnancy outcomes. This retrospective cohort study was conducted at the Sisli Memorial Hospital, assisted reproductive technology, and Reproductive Genetics Center in Istanbul, Turkey, between January 2016 and January 2022. Three thousand two hundred thirty-eight single blastocyst transfers with positive pregnancy test results were evaluated. Of these, 738 were fresh transfer cycles and 2500 were frozen-thawed embryo transfer (FET) cycles. β-hCG test results from 9 days after fresh and FET cycles were compared between the groups with biochemical pregnancy, early pregnancy loss, and live birth outcomes. The threshold values were determined for each pregnancy outcome. The rate of increase between the first and second β-hCG tests performed 2 days apart was determined for each pregnancy outcome. Finally, the listed values were compared between the FET and fresh cycle. Mean baseline β-hCG levels were significantly higher in FET cycles than in fresh cycles, regardless of pregnancy outcomes (P < .005). Baseline β-hCG levels were higher in fresh cycles with live births (171.76 ± 109.64 IU/L) compared to biochemical and clinical pregnancy losses (50.37 ± 24.31 and 114.86 ± 72.42, respectively) (P < .001). Live births in FET cycles resulted in higher baseline β-hCG levels (193.57 ± 100.38 IU/L) compared to biochemical and clinical pregnancy loss groups (68.41 ± 51.85 and 149.29 ± 96.99 IU/L, respectively) (P < .001). The β-hCG threshold for live birth for fresh cycles was 116.5 IU/L (sensitivity 80%, specificity 70%, positive predictive value 90%, negative predictive value 54%) and 131.5 IU/L for FET cycles (sensitivity 71%, specificity 68%, positive predictive value 87%, negative predictive value 50%). The percentage of the area under the curve for single fresh blastocyst transfers was 0.81 and 0.76 for frozen transfers. The rate of increase in β-hCG was similar in fresh and FET cycles. Initial β-hCG levels and 2-day increases are effective parameters for diagnosing pregnancy in fresh and FET cycles. The initial β-hCG level was significantly higher in the FET cycles than in the fresh cycles. Predicting outcomes earlier helps clinicians to manage and follow high-risk pregnancies.