Vol 87, No 10 (2016)
Research paper
Published online: 2016-10-31

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Morphokinetic parameters as a source of information concerning embryo developmental and implantation potential

Robert Milewski, Jan Czerniecki, Agnieszka Kuczyńska, Bożena Stankiewicz, Waldemar Kuczyński
Pubmed: 27958618
Ginekol Pol 2016;87(10):677-684.

Abstract

Objectives: The aim of the study was to present the results of time-lapse observation and to verify whether morphokinetic parameters are associated with embryo developmental and implantation potential.

Material and methods: The analysed data concern the development of 1,060 embryos, 898 of which (84.72%) achieved the blastocyst stage and 307 were transferred into the uterine cavity. As a result, 126 (41.04%) biochemical pregnancies and 109 (35.50%) clinical pregnancies were observed. Time from fertilisation to further divisions into 2–9 blastomeres, first to fourth round of cleavage, second to third synchronisation parameters and the duration of stages after the first, second and third division were analysed.

Results: Most of the parameters in the group of embryos developed to the blastocyst stage reached lower values than in the non-developed group. Moreover, parameters in the first group clearly had less dispersion. The differences between the groups with and without a biochemical pregnancy were smaller than the differences in the analysis of development to the blastocyst stage. However, in the case of clinical pregnancy analysis, there were again larger differences between both groups. A strong correlation was found between the majority of absolute morphokinetic parameters. A weaker, but still statistically significant correlation, was established between relative and other parameters.

Conclusions: Morphokinetic parameters are associated with embryo developmental and implantation potential and can be considered as predictors of their quality. However, the development of efficient pregnancy prediction models needs further research utilising information from all available parameters and using advanced biostatistical methods.