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Erschienen in: Journal of Assisted Reproduction and Genetics 8/2017

01.06.2017 | Embryo Biology

Selecting embryos with the highest implantation potential using data mining and decision tree based on classical embryo morphology and morphokinetics

verfasst von: Beatriz Carrasco, Gemma Arroyo, Yolanda Gil, Mª José Gómez, Ignacio Rodríguez, Pedro N. Barri, Anna Veiga, Montserrat Boada

Erschienen in: Journal of Assisted Reproduction and Genetics | Ausgabe 8/2017

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Abstract

Purpose

The objective of this work was to determine which embryonic morphokinetic parameters up to D3 of in vitro development have predictive value for implantation for the selection of embryos for transfer in clinical practice based upon information generated from embryo transfers with known implantation data (KID).

Methods

A total of 800 KID embryos (100% implantation rate (IR) per transfer and 0% IR per transfer) cultured in an incubator with Time-Lapse system were retrospectively analysed. Of them, 140 embryos implanted, whereas 660 did not.

Results

The analysis of morphokinetic parameters, together with the embryo morphology assessment on D3, enabled us to develop a hierarchical model that places the classical morphological score, the t4 and t8 morphokinetic values, as the variables with the best prognosis of implantation.

Conclusion

In our decision tree, the classical morphological score is the most predictive parameter. Among embryos with better morphological scores, morphokinetics permits deselection of embryos with the lowest implantation potential.
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Metadaten
Titel
Selecting embryos with the highest implantation potential using data mining and decision tree based on classical embryo morphology and morphokinetics
verfasst von
Beatriz Carrasco
Gemma Arroyo
Yolanda Gil
Mª José Gómez
Ignacio Rodríguez
Pedro N. Barri
Anna Veiga
Montserrat Boada
Publikationsdatum
01.06.2017
Verlag
Springer US
Erschienen in
Journal of Assisted Reproduction and Genetics / Ausgabe 8/2017
Print ISSN: 1058-0468
Elektronische ISSN: 1573-7330
DOI
https://doi.org/10.1007/s10815-017-0955-x

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