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Erschienen in: Journal of Assisted Reproduction and Genetics 9/2018

20.07.2018 | Assisted Reproduction Technologies

Euploid embryos selected by an automated time-lapse system have superior SET outcomes than selected solely by conventional morphology assessment

verfasst von: E. Rocafort, M. Enciso, A. Leza, J. Sarasa, J. Aizpurua

Erschienen in: Journal of Assisted Reproduction and Genetics | Ausgabe 9/2018

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Abstract

Purpose

We investigated if automated TLI selection may be a valuable strategy to identify those euploid embryos with the best chances of success.

Methods

This is a unicentric and retrospective study involving 244 patients undergoing preimplantational genetic screening (PGS) cycles with autologous oocytes or oocyte donation (OD) with single euploid embryo transferred. We examined euploid embryos selected for transfer based on morphology evaluation alone (PGS-only; control group) or by assessment using an automated TLI system (Eeva™; PGS-TLI group).

Results

In both, autologous oocytes and OD patients, significantly better implantation and clinical and ongoing pregnancy rates were obtained in the PGS-TLI group when euploid embryos with high implantation potential as predicted by the automated TLI System (Eeva™) were transferred compared with the PGS-only group. This improvement was also observed when only transfers of good morphological quality embryos were compared. TLI categories showed significant differences on blastocyst formation and euploidy rate.

Conclusions

Automated TLI combined with PGS is a useful prognostic tool to identify euploid embryos with the highest potential for implantation and pregnancy. Further, these results provide evidence that a healthy pregnancy does not only depend upon normal chromosomal status.
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Metadaten
Titel
Euploid embryos selected by an automated time-lapse system have superior SET outcomes than selected solely by conventional morphology assessment
verfasst von
E. Rocafort
M. Enciso
A. Leza
J. Sarasa
J. Aizpurua
Publikationsdatum
20.07.2018
Verlag
Springer US
Erschienen in
Journal of Assisted Reproduction and Genetics / Ausgabe 9/2018
Print ISSN: 1058-0468
Elektronische ISSN: 1573-7330
DOI
https://doi.org/10.1007/s10815-018-1265-7

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