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Trophectoderm morphology is a better predictor of clinical pregnancy in blastocyst transfers
- Source :
- International Journal of Research in Pharmaceutical Sciences. 11:214-219
- Publication Year :
- 2020
- Publisher :
- GP Innovations Pvt. Ltd., 2020.
-
Abstract
- In assisted reproduction, a successful outcome is closely associated with the selection of potentially implantable. culture has its own merits that it can possibly eliminate the selection of non-viable embryos, can mimic physiology with better embryo-uterine and the extended culture can also assess the embryos post-embryonic activation. Scoring of characteristics can also aid in single embryo transfers (SET), reducing the risks of multiple pregnancies. The morphological assessment can serve as a non-invasive tool for better prediction of the outcome in IVF. The two important morphological parameters of grading the inner cell mass (ICM) and the (TE) other than the expansion of the cavity. Various groups reported the importance of either characteristic predicting implantation, pregnancy and live birth. In this retrospective study, we have evaluated which one of these parameters possess the predictive ability of implantation and pregnancy. The embryos frozen as following morphological scoring in the stimulated cycles were replaced in subsequent cycles. The transferred with known implantation were grouped into four different combinations of grades of ICM and TE and analyzed for the association with the clinical pregnancy and the findings were statistically validated. This study demonstrates there is a significant correlation between the grades of TE cells and the clinical pregnancy, so TE grade possibly is a better predictor of in transfers. The grades of embryo can be used as a selection tool for a better IVF outcome.
- Subjects :
- Pregnancy
business.industry
Embryo
Retrospective cohort study
medicine.disease
Andrology
medicine.anatomical_structure
embryonic structures
Biomarker (medicine)
Inner cell mass
Medicine
Blastocyst
General Pharmacology, Toxicology and Pharmaceutics
business
Live birth
Selection (genetic algorithm)
Subjects
Details
- ISSN :
- 09757538
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- International Journal of Research in Pharmaceutical Sciences
- Accession number :
- edsair.doi...........b615c22bfa46679533b511b927a93091