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Purpose The incidence of poor ovarian response in controlled ovarian stimulation (COH) has been reported in 9–24 % of IVF-ET cycles. Growth hormone augments the effect of gonadotropin on granulosa and theca cells, and plays an essential role in ovarian function, including follicular development, estrogen synthesis and oocyte maturation. The aim of this study was to assess IVF-ET cycle outcome after the addition of growth hormone in antagonist protocol in poor responders. Materials and methods Eighty-two poor responder patients selected for ART enrolled the study and were randomly divided into two groups. Group I (GH/HMG/GnRHant group, n  = 40) received growth hormone/gonadotropin/GnRH antagonist protocol and group II (HMG/GnRHant group, n  = 42) received gonadotropin/GnRH antagonist protocol. Results The number of retrieved oocytes was significantly higher in GH/HMG/GnRHant group than HMG/GnRHant group, 6.10 ± 2.90 vs. 4.80 ± 2.40 ( p  = 0.035) and the number of obtained embryos was also significantly higher in GH/HMG/GnRHant group than HMG/GnRHant group, 3.7 ± 2.89 as compared to 2.7 ± 1.29 ( p  = 0.018). There were no significant differences between groups regarding implantation, and chemical and clinical pregnancy rates. Conclusion Our study showed that co-treatment with growth hormone in antagonist protocol in patients with a history of poor response in previous IVF-ET cycles did not increase pregnancy rates.

Purpose Ectopic pregnancy (EP) constitutes 1–2% of all pregnancies. Methotrexate (MTX) is commonly used in treating EP, but it has some limitations and potential side effects. Clinical studies have shown that letrozole, an aromatase inhibitor, may potentially be used in conjunction with MTX therapy. In our study, we explored the efficacy of adding letrozole to MTX in managing EP. Methods Between June 2021 and September 2022, a total of 60 patients diagnosed with EP at the Faculty of Medicine, Yüzüncü Yıl University, were randomly divided into two groups. Group 1 received MTX alone, while Group 2 received a combination of MTX and letrozole. The primary outcome measure was the change in serum β-hCG levels. Secondary outcomes included the need for surgical intervention and the occurrence of side effects. Results Both groups demonstrated similar success rates in treatment, and there was no significant difference between the MTX and MTX + letrozole groups regarding the need for surgical intervention. Although β-hCG levels declined more rapidly in the MTX + letrozole group, these decreases were not statistically significant. The combination of MTX and letrozole in the treatment of ectopic pregnancy has shown similar efficacy to single-dose MTX. Conclusion Letrozole may offer a potential contribution to MTX therapy by providing a more pronounced reduction in β-hCG levels, but further research with larger sample sizes and longer follow-up periods is needed to confirm these findings.

Background The proportion of hyperglycosylated human chorionic gonadotropin (hCG-h) to total human chorionic gonadotropin (%hCG-h) during the first trimester is a promising biomarker for prediction of early-onset pre-eclampsia. We wanted to evaluate the performance of clinical risk factors, mean arterial pressure (MAP), %hCG-h, hCGβ, pregnancy-associated plasma protein A (PAPP-A), placental growth factor (PlGF) and mean pulsatility index of the uterine artery (Uta-PI) in the first trimester in predicting pre-eclampsia (PE) and its subtypes early-onset, late-onset, severe and non-severe PE in a high-risk cohort. Methods We studied a subcohort of 257 high-risk women in the prospectively collected Prediction and Prevention of Pre-eclampsia and Intrauterine Growth Restriction (PREDO) cohort. Multivariate logistic regression was used to construct the prediction models. The first model included background variables and MAP. Additionally, biomarkers were included in the second model and mean Uta-PI was included in the third model. All variables that improved the model fit were included at each step. The area under the curve (AUC) was determined for all models. Results We found that lower levels of serum PlGF concentration were associated with early-onset PE, whereas lower %hCG-h was associated with the late-onset PE. Serum PlGF was lower and hCGβ higher in severe PE, while %hCG-h and serum PAPP-A were lower in non-severe PE. By using multivariate regression analyses the best prediction for all PE was achieved with the third model: AUC was 0.66, and sensitivity 36% at 90% specificity. Third model also gave the highest prediction accuracy for late-onset, severe and non-severe PE: AUC 0.66 with 32% sensitivity, AUC 0.65, 24% sensitivity and AUC 0.60, 22% sensitivity at 90% specificity, respectively. The best prediction for early-onset PE was achieved using the second model: AUC 0.68 and 20% sensitivity at 90% specificity. Conclusions Although the multivariate models did not meet the requirements to be clinically useful screening tools, our results indicate that the biomarker profile in women with risk factors for PE is different according to the subtype of PE. The heterogeneous nature of PE results in difficulty to find new, clinically useful biomarkers for prediction of PE in early pregnancy in high-risk cohorts. Trial registration International Standard Randomised Controlled Trial number ISRCTN14030412 , Date of registration 6/09/2007, retrospectively registered.

Background Cesarean scar pregnancy (CSP) remains a sporadic and special form of ectopic pregnancy in which the fertilized ovum is implanted on a previous cesarean scar within 12 weeks. This study aims to evaluate the optimal time interval between uterine artery embolization (UAE) and curettage modalities in order to provide the best clinical outcomes. Methods From January 2018 to December 2020, we recruited 61 patients with CSP. They were randomly divided into two groups depending on whether the time interval between UAE and dilatation and curettage (D&C) requires additional hospitalization: 31 patients received prophylactic UAE followed by D&C on the same day (0–12 h; group A) and 30 patients need hospitalization (12–72 h; group B). The clinical characteristics, diagnostic data, and outcomes of the two groups were compared and analyzed. Results A total of 59 (96.72%) cases had responded well to the first treatment. One patient in each arm undergone retreatment, but none of the 61 patients needed additional hysterectomy. There was no considerable relationship between the two groups with respect to the intraoperative hemorrhage during D&C, serum index (containing β-hCG, hemoglobin, CRP, and D-dimer) on the first day after D&C, side effects (containing fever and abdominal pain), renal, hepatic, and coagulation function, time of CSP residual mass disappearance, and hospitalization cost. The time of serum β-hCG resolution after surgery was 41.22 ± 14.97 days in group A and 66.67 ± 36.64 days in group B ( P  = 0.027), and group A treatment resulted in a shorten hospital stay as compared with group B (4.81 ± 2.74 days vs. 6.80 ± 2.14 days, P  <  0.001). However, the average hourly serum β-hCG decrease rate within 24 h and the leukocytes on the first day after D&C in group B were superior than in group A ( P  <  0.050). Conclusion For patients with CSP, UAE followed by D&C on the same day (0–12 h) appears to have more advantages in hospitalization and recovery time, while the long time interval (12–72 h) may have a lower risk of inflammation and a more rapid decrease in serum β-hCG level within 24 h after D&C surgery. The treatment of CSP should be individualized based on the conditions of patients.

Purpose To compare the effectiveness of expectant management versus methotrexate in selected cases of tubal ectopic pregnancy. Methods A double-blind randomized trial included 23 selected patients with a confirmed diagnosis of tubal pregnancy who met the inclusion criteria (hemodynamic stability, initial serum β-hCG concentration <2,000 mIU/mL, declining titers of β-hCG 48 h prior to treatment, visible tubal pregnancy on transvaginal ultrasound, a tubal mass <5.0 cm and fertility desire). The patients were divided into two groups: 10 patients in the methotrexate group (MTX 50 mg/m 2 administered as a single intramuscular dose) and 13 patients in the placebo group (saline solution administered in a single intramuscular dose). Quantitative variables were expressed as means ± standard deviations and compared by Student’s t test or Mann–Whitney test. Dichotomous variables (success/treatment failure) were presented as proportions and compared by the Fisher exact test. Results Successful treatment with negative titers of β-hCG occurred in 9 cases (90.0 %) of the methotrexate group and in 12 (92.3 %) of the placebo group ( p  > 0.999). The β-hCG values became undetectable at 22 ± 15.4 days in the methotrexate group and 20.6 ± 8.4 days in the placebo group ( p  = 0.80). Conclusion This study showed no statistically significant difference between the treatment with methotrexate and placebo, with similar success rates and similar time interval for β-hCG to become undetectable.

The combination of mifepristone and misoprostol is an established method for induction of early first trimester abortion, but there is no consensus about the best evaluation of treatment outcome. We evaluate serum Angiopoietin-2 (Ang-2) and β human chorionic gonadotropin (β-hCG) in women who had undergone a medical abortion as markers of prolonged uterine bleeding (PUB). Prospective trial involving 2843 women attending an gynecology outpatient clinic who following a medical abortion with mifepristone and misoprostol, the study cohort was divided into women with duration of uterine bleeding >14 days (PUB) and women with duration of uterine bleeding ≤14 days (normal uterine bleeding, NUB). Serum determinations of Ang-2 levels by ELISA and β-hCG levels by electrochemiluminiscence immunoassay. Receiver Operating Characteristics (ROC) analyses were calculated and plotted for the diagnostic accuracy of serum β-hCG and Ang-2 concentration to discriminate PUB and NUB. Baseline characteristics for both groups were similar, Only duration of bleeding showed a significant difference between the PUB group and NUB group. Ang-2 serum levels moderately correlated with serum β-hCG levels with statistically significant correlation coefficients of 0.536. Serum β-hCG and Ang-2 levels on day 7 and on day 14 after medical abortion were signifcantly higher in PUB group than in NUB group. Plotted as ROC curves, β-hCG area under curve (AUC) was 0.65 (95% CI, 0.53-0.76) on day 7, rising to AUC = 0.83 (95% CI, 0.75-0.92) on day 14. Using Ang-2 on day 7 and day 14 as predictive parameter resulted in an analogous AUC (AUC = 0.61 on day 7, AUC = 0.78 on day 14). Both parameters are clinically useful as a diagnostic test in predicting PUB after medical abortion, and can be helpful in uncertain clinical situations, but should be considered as supplementary to a general clinical evaluation.

Human chorionic gonadotropin (hCG) is a glycoprotein hormone that is essential for the maintenance of pregnancy. Glycosylation of hCG is known to be essential for its biological activity. \"Hyperglycosylated\" variants secreted during early pregnancy have been proposed to be involved in initial implantation of the embryo and as a potential diagnostic marker for gestational diseases. However, what constitutes \"hyperglycosylation\" is not yet fully understood. In this study, we perform comparative N-glycomic analysis of hCG expressed in the same individuals during early and late pregnancy to help provide new insights into hCG function, reveal new targets for diagnostics and clarify the identity of hyperglycosylated hCG. hCG was isolated in urine collected from women at 7 weeks and 20 weeks' gestation. hCG was also isolated in urine from women diagnosed with gestational trophoblastic disease (GTD). We used glycomics methodologies including matrix assisted laser desorption/ionisation-time of flight (MALDI-TOF) mass spectrometry (MS) and MS/MS methods to characterise the N-glycans associated with hCG purified from the individual samples. The structures identified on the early pregnancy (EP-hCG) and late pregnancy (LP-hCG) samples corresponded to mono-, bi-, tri-, and tetra-antennary N-glycans. A novel finding was the presence of substantial amounts of bisected type N-glycans in pregnancy hCG samples, which were present at much lower levels in GTD samples. A second novel observation was the presence of abundant LewisX antigens on the bisected N-glycans. GTD-hCG had fewer glycoforms which constituted a subset of those found in normal pregnancy. When compared to EP-hCG, GTD-hCG samples had decreased signals for tri- and tetra-antennary N-glycans. In terms of terminal epitopes, GTD-hCG had increased signals for sialylated structures, while LewisX antigens were of very minor abundance. hCG carries the same N-glycans throughout pregnancy but in different proportions. The N-glycan repertoire is more diverse than previously reported. Bisected and LewisX structures are potential targets for diagnostics. hCG isolated from pregnancy urine inhibits NK cell cytotoxicity in vitro at nanomolar levels and bisected type glycans have previously been implicated in the suppression of NK cell cytotoxicity, suggesting that hCG-related bisected type N-glycans may directly suppress NK cell cytotoxicity.

This study aims to develop a machine learning model for predicting early pregnancy outcomes by combining baseline levels and dynamic changes of β-human chorionic gonadotropin (β-hCG), progesterone (P), and estradiol (E2). This retrospective study screened out 421 patients treated at the Lanzhou University Second Hospital between March 2023 and August 2024. Feature selection was performed using Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest Recursive Feature Elimination (RF-RFE). Subsequently, we constructed a traditional logistic regression model and five machine learning models: Random Forest (RF), eXtreme Gradient Boosting (XGBoost), k-Nearest Neighbors (KNN), Multilayer Perceptron (MLP) neural network, and Support Vector Machine (SVM). Internal validity was assessed through 5-fold cross-validation. Model performance was measured by the area under the Receiver Operating Characteristic curve (AUC), accuracy, precision, sensitivity, and specificity. Among the 421 enrolled patients, 263 had ongoing pregnancies while 158 experienced early pregnancy loss (EPL). LR, RF, XGBoost, KNN, MLP, and SVM achieved AUCs of 0.750, 0.784, 0.750, 0.706, 0.755, and 0.749, respectively, with all accuracy and precision metrics exceeding 0.60. Notably, the RF model yielded optimal performance for EPL prediction, attaining the highest AUC (0.784), accuracy (0.729), and precision (0.724). Integrating dynamic changes in β-hCG, P, and E2 enables effective prediction of early pregnancy outcomes. The RF model exhibited optimal performance, highlighting its potential for clinical implementation as a risk stratification tool based on serial hormone monitoring.

In this investigation, we explored the correlation between first-trimester biochemical markers and the incidence of preterm birth (PTB), irrespective of the cause, spontaneous preterm birth (sPTB), and preterm premature rupture of membranes (pPROM) within a cohort comprising 1164 patients. It was discovered that diminished levels of Pregnancy-Associated Plasma Protein-A (PAPP-A) between 11 and 13 + 6 weeks of gestation significantly contributed to the risk of preterm deliveries both before 35 and 37 weeks, as well as to pPROM instances. Furthermore, women experiencing sPTB before the 37th week of gestation also exhibited lower concentrations of PAPP-A. Moreover, reduced first-trimester concentrations of free beta-human chorionic gonadotropin (fb-HCG) were identified as a risk factor for deliveries preceding 37 weeks, pPROM, and sPTB before 35 weeks of gestation. Despite these correlations, the area under the curve for these biochemical markers did not surpass 0.7, indicating their limited diagnostic potential. The most significant discriminatory capability was noted for PAPP-A levels, with a threshold of < 0.71 multiples of the median (MoM) predicting PTB before 37 weeks, yielding an odds ratio of 3.11 (95% Confidence Interval [CI] 1.97–4.92). For sPTB, the greatest discriminatory potential was observed for PAPP-A < 0.688, providing an OR of 2.66 (95% CI 1.51–4.66). The cut-off points corresponded to accuracies of 76.05% and 79.1%, respectively. In regression analyses, the combined predictive models exhibited low explanatory power with R 2 values of 9.2% for PTB and 7.7% for sPTB below 35 weeks of gestation. In conclusion, while certain biochemical markers demonstrated associations with outcomes of preterm birth, their individual and collective predictive efficacies for foreseeing such events were found to be suboptimal.

A significant number of pregnancies are lost in the first trimester and 1–2% are ectopic pregnancies (EPs). Early pregnancy loss in general can cause significant morbidity with bleeding or infection, while EPs are the leading cause of maternal mortality in the first trimester. Symptoms of pregnancy loss and EP are very similar (including pain and bleeding); however, these symptoms are also common in live normally sited pregnancies (LNSP). To date, no biomarkers have been identified to differentiate LNSP from pregnancies that will not progress beyond early gestation (non-viable or EPs), defined together as combined adverse outcomes (CAO). In this study, we present a novel machine learning pipeline to create prediction models that identify a composite biomarker to differentiate LNSP from CAO in symptomatic women. This prospective cohort study included 370 participants. A single blood sample was prospectively collected from participants on first emergency presentation prior to final clinical diagnosis of pregnancy outcome: LNSP, miscarriage, pregnancy of unknown location (PUL) or tubal EP (tEP). Miscarriage, PUL and tEP were grouped together into a CAO group. Human chorionic gonadotrophin β (β-hCG) and progesterone concentrations were measured in plasma. Serum samples were subjected to untargeted metabolomic profiling. The cohort was randomly split into train and validation data sets, with the train data set subjected to variable selection. Nine metabolite signals were identified as key discriminators of LNSP versus CAO. Random forest models were constructed using stable metabolite signals alone, or in combination with plasma hormone concentrations and demographic data. When comparing LNSP with CAO, a model with stable metabolite signals only demonstrated a modest predictive accuracy (0.68), which was comparable to a model of β-hCG and progesterone (0.71). The best model for LNSP prediction comprised stable metabolite signals and hormone concentrations (accuracy = 0.79). In conclusion, serum metabolite levels and biochemical markers from a single blood sample possess modest predictive utility in differentiating LNSP from CAO pregnancies upon first presentation, which is improved by variable selection and combination using machine learning. A diagnostic test to confirm LNSP and thus exclude pregnancies affecting maternal morbidity and potentially life-threatening outcomes would be invaluable in emergency situations.