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Updated: Jul 11, 2025

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Human Blastocyst Biopsy and Vitrification
Published on: July 26, 2019
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Correlations between clinical parameters, blastocyst morphological classification and embryo euploidy
Juliano Brum Scheffer1, Rafaela Friche de Carvalho1, Bruno Brum Scheffer1
1IBRRA - Brazilian Institute of Assisted Reproduction, Belo Horizonte, Brazil.
JBRA Assisted Reproduction
|November 14, 2023
Summary
Predicting embryo ploidy is possible using clinical and embryo factors. Lower maternal age, higher anti-Mullerian hormone (AMH) levels, and superior embryo quality are linked to euploid embryos, indicating a higher chance of successful implantation.
Area of Science:
- Reproductive Medicine
- Embryology
- Genetics
Background:
- Assisted reproductive technologies (ART) rely on accurate embryo selection.
- Ploidy status is a critical factor influencing implantation and pregnancy outcomes.
- Predictive markers for embryo ploidy can optimize ART success rates.
Purpose of the Study:
- To identify clinical and embryo-derived parameters for predicting embryo ploidy.
- To compare characteristics of euploid versus aneuploid embryos.
Main Methods:
- Retrospective analysis of 838 day-5 blastocysts from 219 patients.
- Embryos classified morphologically and grouped by genetic test results (euploid vs. aneuploid).
- Comparison of maternal age, anti-Mullerian hormone (AMH), antral follicle count (AFC), and embryo morphology.
Main Results:
- Euploid embryos associated with significantly lower maternal age (36.2 vs. 37.1 years) and higher AMH levels (3.9 vs. 3.6 IU/L).
- Antral follicle count (AFC) did not significantly differ between euploid and aneuploid groups.
- Aneuploidy was negatively correlated with top embryo quality (4AA, 4AB); all euploid embryos were top quality versus 61.49% of aneuploid embryos.
Conclusions:
- Lower maternal age, higher AMH, and superior embryo morphology are predictive of euploidy.
- These factors can aid in selecting embryos with a higher likelihood of successful implantation.
- Further research may refine predictive models for embryo selection in ART.

