Objective: To compare outcomes transferring one or two embryos in autologous frozen oocyte cycles.
Material And Methods: A retrospective cohort study conducted at an academic fertility center between January 2012 and December 2018. One-hundred and fourteen patients underwent frozen oocyte transfers; 67 single embryo transfer (SET) and 47 double embryo transfer (DET). No subjects had more than two embryos transferred. Data were analyzed using t-test and chi-squared testing. Multivariate logistic regression was used to control for confounding effects. Power analysis suggested an 82% power with alpha of 5% and effect size of 27%.
Results: Regarding the embryo stage, 72% were cleavage embryos and 28% were blastocyst embryos. Among those who had cleavage stage embryos, 48.8% underwent SET and 51.2% underwent DET. In the blastocyst embryos group these proportions were 84.4% and 15.6%, respectively. There were no difference in pregnancy rate for SET (40.3%) vs DET (36.2%) (p=0.78). Additionally, the live birth rate did not differ between SET and DET (28.4 vs 19.1%, respectively, p=0.26). The multivariate multilevel analysis provided adjusted odds ratios (95% confidence interval) of: 1.85 (0.46-7.44) for pregnancy; 0.497 (0.05-4.86) for clinical pregnancy; and 0.82 (0.11-6.29) for live birth when comparing SET and DET. Multiple pregnancy rates were significantly lower in the SET (0%), compared with DET group (44.4%) (p<0.002).
Conclusion: SET results in excellent live birth outcomes in autologous frozen oocyte cycles. However DET results in significantly increased rates of multiple pregnancies. This suggests that SET is a viable option in autologous frozen oocyte cycles.
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http://dx.doi.org/10.4274/jtgga.galenos.2021.2020.0207 | DOI Listing |
J Clin Med
December 2024
Collegium Medicum, WSB University, 41-300 Dąbrowa Górnicza, Poland.
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January 2025
Department of Obstetrics and Gynecology, IVF-Unit, Acibadem Kayseri Hospital, 38140 Kayseri, Türkiye.
The downregulation of anti-adhesive regulatory proteins and upregulation of adhesive genes are critical for the receptive endometrium. This study was designed to determine whether switching between the anti-adhesive podocalyxin (PDX) and adhesive HOXA10 receptivity modulator occurs in the endometrium of women with recurrent implantation failure (RIF). Twenty-four patients with RIF who could not conceive for three or more cycles despite good-quality embryo transfer constituted the study group.
View Article and Find Full Text PDFDiagnostics (Basel)
December 2024
Department of Obstetrics & Gynecology, Faculty of Medicine, "Carol Davila" University of Medicine and Pharmacy, 020021 Bucharest, Romania.
This prospective study aims to identify the effect of the dienogest 2 mg/day and aspirin 150 mg/day combined treatment for two months before frozen ET on the assisted reproduction outcome in women with adenomyosis and recurrent implantation failure (RIF). Patients were selected based on specific criteria and divided into two groups (with and without treatment). Preimplantation biochemical parameters and ultrasonographic features (endometrial thickness, uterine peristalsis, and junctional zone thickness) were compared with pregnancy rate in a non-natural cycle frozen embryo transfer technique.
View Article and Find Full Text PDFSci Rep
January 2025
Laboratory of Veterinary Embryology and Biotechnology (VETEMBIO), Veterinary Medical Center and College of Veterinary Medicine, Chungbuk National University, Cheongju, Republic of Korea.
Taiwan J Obstet Gynecol
January 2025
Division of Reproductive Medicine, Department of Obstetrics and Gynecology, Taipei Medical University Hospital, Taipei, Taiwan; Department of Obstetrics and Gynecology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan. Electronic address:
The objective of this review is to evaluate the contributions of Artificial Intelligence (AI) to Assisted Reproductive Technologies (ART), focusing on its role in enhancing the processes and outcomes of fertility treatments. This study analyzed 48 relevant articles to assess the impact of AI on various aspects of ART, including treatment efficacy, process optimization, and outcome prediction. The effectiveness of different machine learning paradigms-supervised, unsupervised, and reinforcement learning-in improving ART-related procedures was particularly examined.
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