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Erschienen in:
03.03.2018 | Embryo Biology
A predictive model for high-quality blastocyst based on blastomere number, fragmentation, and symmetry
Erschienen in: Journal of Assisted Reproduction and Genetics | Ausgabe 5/2018
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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.