Kristóf Bereczki

Vanishing twin syndrome (VTS) denotes the spontaneous loss of one conceptus from an initially recognized multiple pregnancy, most often during the first trimester. Its clinical relevance has increased with in vitro fertilization and embryo transfer (IVF-ET), as multiple embryo transfer creates the substrate for dizygotic VTS, while blastocyst transfer may be followed by monozygotic splitting and serial early ultrasonography increases detection. However, the literature remains heterogeneous, with empty gestational sacs, losses after fetal cardiac activity, and later single fetal demise often grouped together despite different biological and prognostic implications. New evidence published in recent years on frozen embryo transfer outcomes, cell-free DNA screening, and early childhood development warrants an updated synthesis of vanishing twin syndrome to inform individualized risk assessment, counselling, and standardized research reporting. Overall, the surviving singleton appears to have a lower risk than an ongoing twin pregnancy but a higher risk than a primary singleton, particularly for preterm birth, low birthweight, and small-for-gestational-age birth, with risk increasing when loss occurs after fetal cardiac activity or later in gestation. Nevertheless, evidence is not unanimous, as several well-characterized cohorts and earlier meta-analyses reported no measurable perinatal disadvantage. Two reports from a single tertiary center, based on substantially overlapping recruitment periods, further suggest that VTS may be proportionally less frequent among established twin pregnancies after IVF/ICSI than after spontaneous conception, while IVF-associated VTS has been linked to placental abnormalities, diabetes, and fetal growth restriction; this observation requires independent confirmation. Contemporary frozen embryo transfer cohorts indicate that VTS remains relevant in modern practice, whereas limited long-term data have not demonstrated impaired early childhood growth or development. Management should document the initial number of gestational sacs, embryonic structures, cardiac activity, chorionicity, and timing of loss, while adapting aneuploidy screening to residual trophoblastic DNA and individualizing fetal-growth surveillance. Elective single-embryo transfer remains the most effective preventive strategy, although it cannot eliminate monozygotic twinning. Standardized definitions and long-term offspring follow-up are needed.

Objectives: We aimed to develop and validate a per-cycle prediction model for in vitro fertilization (IVF) success using only preprocedural clinical variables available at the first consultation. Methods: We retrospectively analysed 1243 IVF/ICSI cycles (University of Szeged, 21 January 2022–12 December 2023). An Extreme Gradient Boosting (XGBoost version 1.7.7.1) classifier was trained on 14 baseline predictors (e.g., female age, AMH, BMI, FSH, LH, sperm concentration/motility, and infertility duration). A parsimonious 9-variable model was derived by feature importance. Model performance was assessed on the untouched test set and, as a final step, on an independent same-centre external validation cohort (n = 92) without re-fitting or recalibration. Results: The 9-variable model achieved an AUC of 0.876 on the internal test set, with an accuracy of 81.70% (95% CI 76.30–86.30%), sensitivity of 75.60%, specificity of 84.40%, PPV of 68.60%, and NPV of 88.50%. In external validation, the model maintained strong performance with an accuracy of 78.30%, confirming consistent discrimination on an independent same-centre cohort. Female age was the dominant high-impact feature, while AMH and BMI acted as “workhorse” predictors, and male factors added incremental value. Conclusions: IVF outcome can be predicted at the first visit using routinely collected preprocedural data. The model showed consistent discrimination internally and in external validation, supporting its potential utility for early, individualized counselling and treatment planning.

Background: Thyroid disorders, particularly thyroid autoimmunity, are increasingly prevalent among women of reproductive age and have been linked to fertility outcomes. While current endocrinology guidelines define distinct thyroid-stimulating hormone (TSH) target values for women undergoing assisted reproductive technology (ART), the optimal preconception TSH range for in vitro fertilization (IVF) success remains a topic of debate. Objectives: This study aimed to assess the impact of baseline TSH levels within the recommended normal range on IVF outcomes, specifically clinical pregnancy and live birth rates. Additionally, we assessed the predictive value of procedural and preprocedural factors, including maternal body mass index (BMI) and TSH, using machine learning models. Methods: We conducted a retrospective, single-center cohort study at the Institute of Reproductive Medicine, University of Szeged, involving 996 women who underwent IVF, with or without intracytoplasmic sperm injection. Biometric, medical history, laboratory, and procedural factors were analyzed. Pregnancy and live birth predictions were modeled using support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost) algorithms. The significance of features in the RF and XGBoost models was assessed. Results: SVM models achieved a mean accuracy of 72.26% in predicting pregnancy but were less effective for live birth classification. RF and XGBoost models demonstrated an area under the receiver operating characteristic curve of 0.76 and 0.74 for pregnancy and 0.67 and 0.61, respectively, for live birth. Key predictors included embryo score, maternal age, BMI, and specific hormone levels. Notably, male factors also contributed to outcome prediction. Analysis suggested that variations in maternal TSH within the normal range (0.3–4.0 mIU/L) had no significant impact on IVF success. Conclusions: Our study suggests that preconception TSH levels within the reference range do not significantly influence IVF success, which indirectly supports the validity of the current recommendations on this matter. While machine learning models demonstrated promising predictive performance, larger prospective studies are needed to refine thyroid function targets in ART, with a separate analysis of women with thyroid autoimmunity.

Introduction: While tubal occlusion is a prevalent cause of infertility, accounting for 11–35% of infertility cases among women, there remains a limited understanding of the factors influencing clinical pregnancy following in vitro fertilization (IVF). Methods: In our retrospective, cross-sectional cohort study conducted at a single tertiary center, medical records of women aged 19 to 43 years were analyzed. Logistic regression models were employed to identify the prognostic factors associated with clinical pregnancy after IVF in patients with tubal factor infertility, excluding cases with hydrosalpinx. Results: Data from 219 women diagnosed with tubal occlusion were compared to 1140 cases with non-tubal indication, covering a total of 1359 IVF cycles. A lower maternal age (adjusted odds ratio [AOR]: 0.89, p = 0.001) and a higher embryo quality (AOR: 1.26, p = 0.01) emerged as important factors in clinical pregnancy in the tubal infertility group. Moreover, a lower maternal (AOR:0.91, p < 0.01) and paternal age (p = 0.001), and favorable semen quality (AOR: 1.32, p = 0.03) were critical determinants in the non-tubal infertility group. BMI was generally higher in tubal infertility patients (p = 0.01). Furthermore, FSH level (AOR: 0.93, p = 0.004), AMH level (p < 0.04), number of embryos transferred (AOR: 2.04, p < 0.001), and embryo quality (AOR: 1.26, p < 0.001) came into prominence only in the non-tubal infertility group. The clinical pregnancy rate (34.2%) of women with tubal occlusion did not differ significantly from those in other forms of infertility undergoing IVF (35.4%). Conclusions: Although tubal infertility is typically anticipated to yield the highest clinical pregnancy rates following IVF, it is crucial to acknowledge that both maternal and paternal characteristics can also significantly impact the outcomes.