Cheng-He Yu1,2, Ruo-Peng Zhang2, Juan Li3, Zhou-Cun A4,5. 1. College of Basic Medicine, Dali University, Dali, 671000, China. 2. Department of Reproductive Medicine, First Affiliated Hospital of Dali University, Dali, 671000, China. 3. Department of Ophthalmology, First Affiliated Hospital of Dali University, Dali, 671000, China. 4. College of Basic Medicine, Dali University, Dali, 671000, China. azhoucun@163.com. 5. Department of Genetics, College of Agriculture and Biology, Dali University, Dali, 671003, China. azhoucun@163.com.
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 retrospective analysis of day-3 embryo parameters, focused on blastomere number, fragmentation, the presence of a vacuole, symmetry, 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 individual 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 s_bn, s_f, and s_s parameters and their corresponding odds ratios. The value of Hc in group HQ was significantly higher than that in group NHQ. A receiver operating characteristic curve was used to test the effectiveness of the model. An area under the curve of 0.790, with a 95% confidence interval of 0.766-0.813, was calculated. A dataset was used to validate the predictive utility of the model. Moreover, another dataset was used to ensure that the model can be applied to predict the implantation of day-3 embryos. CONCLUSIONS: A predictive model for high-quality blastocysts was created based on blastomere number, fragmentation, and symmetry. This model provides novel information on the selection of potential embryos.
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 retrospective analysis of day-3 embryo parameters, focused on blastomere number, fragmentation, the presence of a vacuole, symmetry, 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 individual 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 s_bn, s_f, and s_s parameters and their corresponding odds ratios. The value of Hc in group HQ was significantly higher than that in group NHQ. A receiver operating characteristic curve was used to test the effectiveness of the model. An area under the curve of 0.790, with a 95% confidence interval of 0.766-0.813, was calculated. A dataset was used to validate the predictive utility of the model. Moreover, another dataset was used to ensure that the model can be applied to predict the implantation of day-3 embryos. CONCLUSIONS: A predictive model for high-quality blastocysts was created based on blastomere number, fragmentation, and symmetry. This model provides novel information on the selection of potential embryos.
Entities:
Keywords:
Blastocyst; Embryo development; Embryo evaluation; In vitro fertilization
Authors: Catherine Racowsky; Michael Vernon; Jacob Mayer; G David Ball; Barry Behr; Kimball O Pomeroy; David Wininger; William Gibbons; Joseph Conaghan; Judy E Stern Journal: J Assist Reprod Genet Date: 2010-06-09 Impact factor: 3.412
Authors: Sang Min Kang; Sang Won Lee; Hak Jun Jeong; San Hyun Yoon; Min Whan Koh; Jin Ho Lim; Seong Goo Lee Journal: J Assist Reprod Genet Date: 2012-03-01 Impact factor: 3.412