The proposed model involving both qualitative and quantitative deselection effectively predicts day 3 embryo implantation potential and is applicable to all IVF embryos regardless of insemination method by using PNF as the reference starting time point.

Conventional practice in in vitro fertilization or intracytoplasmic sperm injection is to select the best quality embryos based on their morphology and cleavage status from a cohort of fertilized oocytes in which two pronuclei were observed at the time they were checked for fertilization. However, in a small proportion of cycles, the selection is limited to embryos that appeared to be either unfertilized (displaying zero pronuclei) or abnormally fertilized (displaying one or three pronuclei) at the time they were checked for fertilization. There is a lack of consensus on whether such embryos should be transferred to the uterus. Cytogenetic analysis of embryos from oocytes with one pronucleus has shown a proportion is diploid. Transfer of such embryos has resulted in healthy births. Limited cytogenetic analysis of oocytes that divide despite the absence of pronuclei at fertilization check indicates that a proportion also have a normal cytogenetic constitution. Cytogenetic analysis of embryos from oocytes with three pronuclei has shown high rates of triploidy and chaotic cell divisions. Subsequent foetuses have extremely unfavourable outcomes. Here, we review the published literature on the cytogenetic analysis of 'unfertilized' and 'abnormally fertilized' embryos and discuss possible pathways which lead to their formation. The limited evidence indicates that oocytes with one pronucleus and oocytes that show normal onward division despite the absence of pronuclei may be considered for replacement in certain circumstances.

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This study investigated the efficacy of four published day 3 embryo time-lapse algorithms based on different types of datasets (known implantation data [KID] and single embryo transfer [SET]), and the confounding effect of female age and conventional embryo morphology. Four algorithms were retrospectively applied to three types of datasets generated at Fertility North between February 2013 and December 2014: (a) KID dataset (n = 270), (b) a subset of SET (n = 144, end-point = implantation), and (c) SET (n = 144, end-point = live birth), respectively. All four algorithms showed progressively reduced predictive power (expressed as area under the receiver operating characteristics curve and 95% confidence interval [CI]) after application to the three datasets (a-c): Liu (0.762 [0.701-0.824] vs. 0.724 [0.641-0.807] vs. 0.707 [0.620-0.793]), KIDScore (0.614 [0.539-0.688] vs. 0.548 [0.451-0.645] vs. 0.536 [0.434-0.637]), Meseguer (0.585 [0.508-0.663] vs. 0.56 [0.462-0.658] vs. 0.549 [0.445-0.652]), and Basile (0.582 [0.505-0.659] vs. 0.519 [0.421-0.618] vs. 0.509 [0.406-0.612]). Furthermore, using KID dataset, the association (expressed as odds ratio and 95% CI) between time-lapse algorithms and implantation outcomes lost statistical significance after adjusting for conventional embryo morphology and female age in 3 of the 4 algorithms (KIDScore 1.832 [1.118-3.004] vs. 1.063 [0.659-1.715], Meseguer 1.150 [1.021-1.295] vs. 1.122 [0.981-1.284] and Basile 1.122 [1.008-1.249] vs. 1.038 [0.919-1.172]). In conclusion, SET is a preferred dataset to KID when developing or validating time-lapse algorithms, and day 3 conventional embryo morphology and female age should be considered as confounding factors.

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