To date there is limited published data assessing whether body mass index (BMI) influences endometrial thickness (ET) and whether this impacts on pregnancy outcomes in single blastocyst FET cycles. The objective of this study, therefore, was to examine the relationship between BMI and ET on the outcome of single blastocyst FET cycles over a five-year period from 2012 until 2016. Patient age, BMI, endometrial pattern and ET prior to FET were recorded. Pregnancy outcomes included: implantation rate, clinical pregnancy rate and live birth rate. A total of 464 cycles met the inclusion criteria and the female age was 36.0 ± 3.0 years (mean ± SD). The mean ± SD BMI was 23.3 ± 3.1 kg/m and median ± SD ET was 8.1 ± 1.5 mm. BMI and ET were modestly correlated (Pearson = 0.244) and there was an association between higher BMI category and higher median ET (7.2, 8.0, 8.3, 8.9 mm; < 0.001). However, there was no association between ET and pregnancy outcome, either unadjusted, or adjusted for BMI, age, endometrial pattern or embryo quality. The data suggests that although ET increases with increasing BMI, there are no differences in cycle outcome. Importantly, this implies that an ET <8 mm may not jeopardize pregnancy outcome in women with lower BMI. The development of a norm referenced test for BMI and ET may prove to be a helpful adjunct in the clinical IVF setting.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1080/14647273.2018.1504324 | DOI Listing |
Clin Kidney J
January 2025
State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University, Jinan, Shandong, China.
Background: Hereditary nephropathy is an important cause of renal insufficiency and end-stage renal disease. Therefore, for couples with monogenic nephropathy, preventing transmission of the disease to offspring is urgent. Preimplantation genetic testing for monogenic disorders (PGT-M) is a means to prevent intergenerational inheritance by screening and transplanting normal embryos.
View Article and Find Full Text PDFHum Reprod
January 2025
Next Fertility GynePro, Bologna, Italy.
In recent years, the transfer of more than one embryo has become less frequent to diminish multiple pregnancies. Even so, there is still a risk of one embryo splitting into two or even three. This report presents the case of a triamniotic monochorionic gestation in a 35-year-old woman, obtained after the transfer of a single day 5 embryo that had been previously hatched with a laser and subsequently transferred in a fresh IVF cycle.
View Article and Find Full Text PDFOrphanet J Rare Dis
January 2025
Center for Reproductive Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Purpose: Severe combined immunodeficiency (SCID) is a set of rare monogenic inherited diseases that together represent the most severe form of the primary immunodeficiency disease phenotype. Preimplantation genetic testing for monogenic defects (PGT-M) is an effective reproductive technology strategy to prevent disease-causing gene mutations from being transmitted to offspring. The aim of this study was to report the use of PGT-M strategy based on karyomapping in four families to avoid the birth of SCID children.
View Article and Find Full Text PDFF S Rep
December 2024
Department of Obstetrics and Gynecology, University of South Florida, Morsani College of Medicine, Tampa, Florida.
Objective: To compare pregnancy outcomes after single blastocyst embryo transfer among patients whose first autologous embryo transfer was either a fresh embryo transfer or a frozen embryo transfer (FET) after a freeze-all, in the absence of preimplantation genetic testing for aneuploidy (PGT-A).
Design: A multicenter retrospective cohort analysis.
Setting: National multicenter fertility practice.
Cell Syst
December 2024
Center for Bioinformatics and Computational Medicine, Ann Arbor, MI 48109, USA; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA; Program in Chemical Biology, University of Michigan, Ann Arbor, MI, USA; Rogel Cancer Center, University of Michigan Medical School, Ann Arbor, MI 48109, USA. Electronic address:
While proliferating cells optimize their metabolism to produce biomass, the metabolic objectives of cells that perform non-proliferative tasks are unclear. The opposing requirements for optimizing each objective result in a trade-off that forces single cells to prioritize their metabolic needs and optimally allocate limited resources. Here, we present single-cell optimization objective and trade-off inference (SCOOTI), which infers metabolic objectives and trade-offs in biological systems by integrating bulk and single-cell omics data, using metabolic modeling and machine learning.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!