ArticleJournal of assisted reproduction and genetics2018
A predictive model for high-quality blastocyst based on blastomere number, fragmentation, and symmetry.
Article in Journal of assisted reproduction and genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- Blastulation and ploidy prediction using morphology assessment in 33,999 day-3 embryos.Scientific reports · 2025Article
- The Istanbul consensus update: a revised ESHRE/ALPHA consensus on oocyte and embryo static and dynamic morphological assessment†,‡.Human reproduction (Oxford, England) · 2025Article
- Does the cell number of 0PN embryos on day 3 affect pregnancy and neonatal outcomes following single blastocyst transfer?BMC pregnancy and childbirth · 2022Article
- Are testicular sperms superior to ejaculated sperms in couples with previous ART failure due to high rate of fragmented embryos? A retrospective cohort study.Frontiers in surgery · 2022Article
- Comparison of Multivariable Logistic Regression and Other Machine Learning Algorithms for Prognostic Prediction Studies in Pregnancy Care: Systematic Review and Meta-Analysis.JMIR medical informatics · 2020Review
- Impact of embryo quality and endometrial thickness on implantation in natural cycle IVF.Archives of gynecology and obstetrics · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe aim of this study was to create a predictive model for high-quality blastocyst progression based on the traditional morphology parameters of embryos.
methodsA 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.
resultsAll 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.
conclusionsA 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.
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