Literature DB >> 29331237

Time-lapse algorithms and morphological selection of day-5 embryos for transfer: a preclinical validation study.

Ashleigh Storr1, Christos Venetis2, Simon Cooke2, Suha Kilani2, William Ledger2.   

Abstract

OBJECTIVE: To determine the agreement between published time-lapse algorithms in selecting the best day-5 embryo for transfer, as well as the agreement between these algorithms and embryologists.
DESIGN: Prospective study.
SETTING: Private in vitro fertilization center. PATIENT(S): Four hundred and twenty-eight embryos from 100 cycles cultured in the EmbryoScope. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Interalgorithm agreement as assessed by the Fleiss kappa coefficient. RESULT(S): Of seven published algorithms analyzed in this study, only one of the 18 possible pairs showed very good agreement (κ = 0.867); one pair showed good agreement (κ = 0.725), four pairs showed fair agreement (κ = 0.226-0.334), and the remaining 12 pairs showed poor agreement (κ = 0.008-0.149). Even in the best-case scenario, the majority of algorithms showed poor to moderate kappa scores (κ = 0.337-0.722) for the assessment of agreement between the embryo(s) selected as "best" by the algorithms and the embryo that was chosen by the majority (>5) of embryologists, as well as with the embryo that was actually selected in the laboratory on the day of transfer (κ = 0.315-0.802). CONCLUSION(S): The results of this study raise concerns as to whether the tested algorithms are applicable in different clinical settings, emphasizing the need for proper external validation before clinical use.
Copyright © 2017 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Agreement; algorithm; embryologist; morphokinetics; time-lapse

Mesh:

Year:  2018        PMID: 29331237     DOI: 10.1016/j.fertnstert.2017.10.036

Source DB:  PubMed          Journal:  Fertil Steril        ISSN: 0015-0282            Impact factor:   7.329


  8 in total

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Authors:  Mara Simopoulou; Konstantinos Sfakianoudis; Evangelos Maziotis; Nikolaos Antoniou; Anna Rapani; George Anifandis; Panagiotis Bakas; Stamatis Bolaris; Agni Pantou; Konstantinos Pantos; Michael Koutsilieris
Journal:  J Assist Reprod Genet       Date:  2018-07-27       Impact factor: 3.412

Review 2.  Artificial intelligence in reproductive medicine.

Authors:  Renjie Wang; Wei Pan; Lei Jin; Yuehan Li; Yudi Geng; Chun Gao; Gang Chen; Hui Wang; Ding Ma; Shujie Liao
Journal:  Reproduction       Date:  2019-10       Impact factor: 3.906

3.  The KidscoreTM D5 algorithm as an additional tool to morphological assessment and PGT-A in embryo selection: a time-lapse study.

Authors:  Eduardo Gazzo; Fernando Peña; Federico Valdéz; Arturo Chung; Claudio Bonomini; Mario Ascenzo; Marcelo Velit; Ernesto Escudero
Journal:  JBRA Assist Reprod       Date:  2020-01-30

4.  Using Deep Learning in a Monocentric Study to Characterize Maternal Immune Environment for Predicting Pregnancy Outcomes in the Recurrent Reproductive Failure Patients.

Authors:  Chunyu Huang; Zheng Xiang; Yongnu Zhang; Dao Shen Tan; Chun Kit Yip; Zhiqiang Liu; Yuye Li; Shuyi Yu; Lianghui Diao; Lap Yan Wong; Wai Lim Ling; Yong Zeng; Wenwei Tu
Journal:  Front Immunol       Date:  2021-04-01       Impact factor: 7.561

5.  A double-blind randomized controlled trial investigating a time-lapse algorithm for selecting Day 5 blastocysts for transfer.

Authors:  Aisling Ahlström; Kersti Lundin; Anna-Karin Lind; Kristina Gunnarsson; Göran Westlander; Hannah Park; Anna Thurin-Kjellberg; Steinunn A Thorsteinsdottir; Snorri Einarsson; Mari Åström; Kristina Löfdahl; Judith Menezes; Susanne Callender; Cina Nyberg; Jens Winerdal; Camilla Stenfelt; Brit-Randi Jonassen; Nan Oldereid; Lisa Nolte; Malin Sundler; Thorir Hardarson
Journal:  Hum Reprod       Date:  2022-04-01       Impact factor: 6.353

6.  Faster Fertilization and Cleavage Kinetics Reflect Competence to Achieve a Live Birth: Data from Single-Embryo Transfer Cycles.

Authors:  Yongle Yang; Xiyuan Dong; Jian Bai; Lei Jin; Bo Huang
Journal:  Biomed Res Int       Date:  2022-07-15       Impact factor: 3.246

7.  Good practice recommendations for the use of time-lapse technology.

Authors:  Susanna Apter; Thomas Ebner; Thomas Freour; Yves Guns; Borut Kovacic; Nathalie Le Clef; Monica Marques; Marcos Meseguer; Debbie Montjean; Ioannis Sfontouris; Roger Sturmey; Giovanni Coticchio
Journal:  Hum Reprod Open       Date:  2020-03-19

8.  Can Time-Lapse Incubation and Monitoring Be Beneficial to Assisted Reproduction Technology Outcomes? A Randomized Controlled Trial Using Day 3 Double Embryo Transfer.

Authors:  Yu-Han Guo; Yan Liu; Lin Qi; Wen-Yan Song; Hai-Xia Jin
Journal:  Front Physiol       Date:  2022-01-04       Impact factor: 4.566

  8 in total

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