Predictor Of Pregnancy Outcome Research Articles

Free Androgen Index Might Not Be a Perfect Predictor of Infertility Outcomes in Patients with Polycystic Ovary Syndrome Undergoing Frozen Embryo Transfer:A Retrospective Cohort Study.

It is well known that androgen excess impairs oocyte quality, endometrial receptivity and even embryo invasion to some extent. Free androgen index (FAI) is strongly recommended to evaluate active androgen. Previous studies have showed conflicting conclusions on the effect of hyperandrogenism on the pregnancy outcomes in patients with polycystic ovary syndrome (PCOS). This study aims to analyze the influence of hyperandrogenemia based on FAI on frozen embryo transfer (FET) outcomes in patients with PCOS. Patients diagnosed with PCOS who underwent their first FET between January 2017 and April 2022 were stratified into two cohorts using FAI, a highly recommended parameter: PCOS with hyperandrogenemia (n=73) and PCOS without hyperandrogenemia (n=255). Basic and infertility characteristics were analyzed using Student's t-test or chi-square (χ2) statistics. Logistic regression analysis was performed to verify whether FAI was helpful in predicting pregnancy outcomes in women with PCOS. Body mass index (BMI), total gonadotropin (Gn), basal serum follicle-stimulating hormone (bFSH), basal serum testosterone (bT), sex hormone binding globulin (SHBG), and FAI were significantly different between the two groups. (P=0.005, P<0.001, P<0.001, P<0.001, and P<0.001, respectively). However, clinical pregnancies, abortions, and live births did not differ significantly. Further regression analyses showed that FAI was not related to clinical pregnancy, abortion, or live birth rates (adjusted odds ratio (OR)=0.978, 95% confidence interval (CI)=0.911-1.050, P=0.539; adjusted OR=1.033, 95% CI=0.914-1.168, P=0.604; and adjusted OR=0.976, 95% CI=0.911-1.047, P=0.499, respectively). FAI was not associated with pregnancy outcomes in patients with PCOS; that is, it did not reflect any negative effects of hyperandrogenemia on pregnancy outcomes in patients with PCOS and was not an informative clinical parameter. Therefore, more attention should be paid to the factors that influence the accuracy of FAI in reflecting androgen levels in vivo, and further discussion is needed.

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

The role of ultrasound and mitofusin-2 levels to predict pregnancy outcomes in patients with severe preeclampsia: a case-control study.

The aim of this study was to evaluate mitofusin-2 levels and fetal Doppler ultrasonography effects in patients with severe preeclampsia. This single-center case-control study was conducted in the gynecology service of the university hospital in Van. A total of 90 pregnant women aged 18-40 years were included in the study. Of these, 30 are normal, 30 have mild preeclampsia, and 30 are pregnant with severe preeclampsia. In this study, especially in severe preeclampsia patients, serum mitofusin-2 levels and important fetal Doppler flows such as uterine arterial pressure, umbilical arterial pressure, and 1st and 5th minute Apgar scores, birth weight, and the relationship between postnatal outcomes such as week of birth and the number of patients in the neonatal intensive care unit were investigated. There was a significant difference between the three groups in terms of mitofusin-2 levels, which was the highest in the group (p<0.05). Maternal serum mitofusin-2 levels were positively correlated with uterine arterial pressure (r=0.543, p=0.007), umbilical arterial pressure (r=0.238, p=0.008), diastolic blood pressure, and systolic blood pressure (p<0.001). Receiver operating characteristic curve of mitofusin-2 in predicting preeclampsia is as follows: optimal cutoff 1.6 ng/mL; area under the curve: 0.861; 95%CI: 0.786-0.917; sensitivity: 83.9%; and specificity: 70.0%, (p≤0.001). A one-unit increase in mitofusin-2 resulted in a statistically significant 4.21-fold increase in preeclampsia risk. This study recommends the use of mitofusin-2 together with fetal Doppler ultrasound findings as a reliable indicator of preeclampsia severity.

Endometrial pattern predicts pregnancy outcome in single-blastocyst frozen-embryo transfer: An analysis of 1383 cycles.

Several studies investigated endometrial patterns, with respect to pregnancy rates following the transfer of embryos but did not distinguish between single- and multiple-blastocyst procedures. We clarified how the endometrial pattern imaged to transfer a frozen embryo is associated with pregnancy outcomes in single-blastocyst frozen-embryo transfer (sbFET). Patients ≤35 years who underwent sbFET on the hormone replacement protocol. We analyzed endometrial patterns' associations with pregnancy outcomes in relation to blastocyst grade and pregnancy-related factors. Of the 1383 cycles, 483 were Lf, 840 were partial-Lf, and 60 were non-Lf. Leaf pattern (Lf): central echogenic line present and continuous. Overall, decreasing distinctness of the central echogenic line was associated with significantly lower rates of clinical pregnancy (Lf: 70.4%; partial-Lf: 58.1%; non-Lf: 28.3%) and live birth (56.3%, 45.5%, and 15.0%) and a higher miscarriage rate (20.0%, 21.7%, and 47.1%). Logistic regressions showed pregnancy and live birth to be significantly more likely and miscarriage less likely in Lf than non-Lf: OR (95% CI): 6.07 (3.24-11.37), 7.43 (3.47-15.39), and 0.20 (0.07-0.57). Non-Lf presentation was associated with lower rates of pregnancy and live birth, suggesting it signals unsuitable conditions for embryo transfer. We provide information on the pregnancy outcomes of sbFET for endometrial patterns.

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.

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.

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.

Decrease in peripheral natural killer cell level during early pregnancy predicts live birth among women with unexplained recurrent pregnancy loss: a prospective cohort study

BACKGROUNDPrevious studies have suggested that the trophoblast cells inhibit the proliferation of peripheral natural killer (pNK) cells and the level of pNK cells decrease in middle and late pregnancy stage among healthy women. The change of pNK cells level during early pregnancy and the relationship between the change of pNK level and pregnancy outcomes in women with unexplained recurrent pregnancy loss (URPL) has not been sufficiently explored. OBJECTIVEThis study aims to characterize the level of pre-pregnancy pNK to early pregnancy among women with URPL and whether the change in the level of pNK cells in early pregnancy from pre-pregnancy can predict pregnancy outcomes. STUDY DESIGNIn this prospective cohort study, 1758 women with recurrent pregnancy loss were recruited between January 2017 and December 2021, of which 252 URPL women had pre-pregnancy and early pregnancy (4-6 weeks gestation) pNK measurements. These 252 women were divided into two groups: those with a lower gestational pNK levels (Group 1) compared to pre pregnancy, and those without (Group 2). Their respective outcomes on live birth and pregnancy loss were comparatively analyzed using Chi-square and Student’s t test. Candidate influence factors for live birth were selected using the Akaike information criterion (AIC). Then the participates were randomly divided into training and testing groups. Multivariable logistic regression model was performed, and nomogram was calculated to assess the possibility of live birth. Predictive accuracy was discriminated by area under the receiver operating characteristic curve (ROC), validated by plotting the predicted probabilities and the observed probabilities. Hosmer-Lemeshow test was used to assess the goodsess of fit. RESULTSWhen early gestational pNK cells levels were compared with pre pregnancy pNK cells levels, 61.5% (154) women had a comparatively lower early gestational pNK cells levels versus 38.9% (98) women with increase or no change of their pNK cells levels. The live birth rate in Group 1 was 89.0% (137/154), which was significantly higher than 49.0% (48/98) of Group 2 (p<0.001). Decrease of pNK cells level (odds ratio [OR]=1.36, 95% CI 1.22-1.55, p<0.001) and anti-Muellerian hormone (AMH) (OR=1.41, 95% CI 1.14-1.81, p=0.003) were important predicting factors for higher live birth. Female BMI (OR=0.97, 95% CI 0.82-1.15, p=0.763) and parity (OR=1.61, 95% CI 0.71-4.12, p=0.287) were also predicting factors. Furthermore, the area under the ROC curve of the model to diagnose of live birth was 0.853 with a sensitivity of 81.6% and specificity of 78.0% using the training dataset. And the Hosmer−Lemeshow test showed that the model was a good fit (p = 6.068). CONCLUSIONWe report a comparative decrease in pNK cells levels in over 60% URPL women at 4-6 weeks of gestation, when compared to their pre-pregnancy pNK cells level. Compared to pre pregnancy pNK cells levels, a decrease pNK cells level during early pregnancy might be a useful predictor for LBR in women with URPL.

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.

Association between adverse pregnancy outcome and placental biomarkers in the first trimester: A prospective cohort study.

To determine the inter-relationships between five first-trimester biomarkers (pregnancy associated plasma protein A [PAPP-A], alpha-fetoprotein [AFP], beta human chorionic gonadotrophin [beta-hCG], placenta growth factor [PlGF] and soluble fms-like tyrosine kinase receptor-1 [sFlt-1]) and a range of adverse pregnancy outcomes (APOs). Prospective cohort study of nulliparous singleton pregnancy. Cambridge, UK. 4056 pregnancy outcome prediction study participants. The biomarker concentrations were measured in maternal serum at ~12 weeks of gestation. Univariable analysis of APOs was performed using logistic regression. Multivariable analysis used best subsets logistic regression with cross-validation. Pre-eclampsia (PE), small for gestational age (SGA), including severe SGA (birthweight <3rd), fetal growth restriction (FGR), preterm birth (PTB, both induced and spontaneous [iPTB and sPTB, respectively]), pre-viable loss and stillbirth, plus combinations of outcomes. Lower values of PAPP-A, PlGF and sFlt-1 and higher values of AFP were associated with FGR (OR for 1 SD higher value 0.59 [95% CI 0.48-0.74], OR 0.56 [95% CI 0.44-0.70], OR 0.68 [95% CI 0.54-0.87] and OR 1.53 [95% CI 1.25-1.88]), severe SGA (OR0.59 [95% CI 0.49-0.72], OR 0.71 [95% CI 0.57-0.87], OR 0.74 [95% CI 0.60-0.91] and OR 1.41 [95% CI 1.17-1.71]), sPTB (OR 0.61 [95% CI 0.50-0.73], OR 0.79 [95% CI 0.66-0.96], OR 0.57 [95% CI 0.47-0.70] and OR 1.41 [95% CI 1.18-1.67]) and iPTB (OR 0.72 [95% CI 0.57-0.91], OR 0.62 [95% CI 0.49-0.78], OR 0.71 [95% CI 0.56-0.90] and OR 1.44 [95% CI 1.16-1.78]), respectively. When combinations of biomarkers were assessed, PAPP-A and AFP were independently associated with severe SGA; PAPP-A alone with PE + PTB; PlGF alone with severe PE; PlGF, beta-hCG, AFP and PAPP-A with the combination of PE and SGA; AFP and sFlt-1 with sPTB; and AFP and PlGF with iPTB. Combinations of first-trimester placental biomarkers are associated with APOs. However, the patterns vary for different types of APO, indicating heterogeneity in the underlying pathophysiological pathways.

EP25.12: Role of ductus venosus Doppler for the prediction of perinatal outcome in term pregnancies with gestational diabetes mellitus

EP25.12: Role of ductus venosus Doppler for the prediction of perinatal outcome in term pregnancies with gestational diabetes mellitus

EP13.33: Prediction of adverse pregnancy outcomes using fetal abdominal circumference at 11 and 13+6 weeks of gestation

EP13.33: Prediction of adverse pregnancy outcomes using fetal abdominal circumference at 11 and 13+6 weeks of gestation