A predictive model for high-quality blastocyst based on blastomere number, fragmentation, and symmetry

A predictive model for high-quality blastocyst based on blastomere number, fragmentation, and... Purpose The aim of this study was to create a predictive model for high-quality blastocyst progression based on the traditional morphology parameters of embryos. Methods A total of 1564 embryos from 234 women underwent conventional in vitro fertilization and were involved in the present study. High-quality blastocysts were defined as having a grade of at least 3BB, and all embryos were divided based on the development of high-quality blastocysts (group HQ) or the failure to develop high-quality blastocysts (group NHQ). A retro- spective analysis of day-3 embryo parameters, focused on blastomere number, fragmentation, the presence of a vacuole, sym- metry, and the presence of multinucleated blastomeres was conducted. Results All parameters were related to high-quality blastocysts (p <0001) in t tests, chi-square tests, or Fisher tests. The indi- vidual scores for all parameters were determined according to their distributions and corresponding rates of forming high-quality blastocysts. Parameters are indicated by s_bn (blastomere number), s_f (fragmentation), s_pv (presence of a vacuole), s_s (symmetry), and s_MNB (multinucleated blastomeres). Subsequently, univariate and multivariate logistic regression analyses were conducted to explore their relationship. In the multivariate logistic regression analysis, a predictive model was constructed, and a parameter Hc was created based on the http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Assisted Reproduction and Genetics Springer Journals

A predictive model for high-quality blastocyst based on blastomere number, fragmentation, and symmetry

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Medicine & Public Health; Gynecology; Reproductive Medicine; Human Genetics
ISSN
1058-0468
eISSN
1573-7330
D.O.I.
10.1007/s10815-018-1132-6
Publisher site
See Article on Publisher Site

Abstract

Purpose The aim of this study was to create a predictive model for high-quality blastocyst progression based on the traditional morphology parameters of embryos. Methods A total of 1564 embryos from 234 women underwent conventional in vitro fertilization and were involved in the present study. High-quality blastocysts were defined as having a grade of at least 3BB, and all embryos were divided based on the development of high-quality blastocysts (group HQ) or the failure to develop high-quality blastocysts (group NHQ). A retro- spective analysis of day-3 embryo parameters, focused on blastomere number, fragmentation, the presence of a vacuole, sym- metry, and the presence of multinucleated blastomeres was conducted. Results All parameters were related to high-quality blastocysts (p <0001) in t tests, chi-square tests, or Fisher tests. The indi- vidual scores for all parameters were determined according to their distributions and corresponding rates of forming high-quality blastocysts. Parameters are indicated by s_bn (blastomere number), s_f (fragmentation), s_pv (presence of a vacuole), s_s (symmetry), and s_MNB (multinucleated blastomeres). Subsequently, univariate and multivariate logistic regression analyses were conducted to explore their relationship. In the multivariate logistic regression analysis, a predictive model was constructed, and a parameter Hc was created based on the

Journal

Journal of Assisted Reproduction and GeneticsSpringer Journals

Published: Mar 3, 2018

References

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