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• W2316800570 abstract "Abnormal cleavage (AC) occurs when 1 cell divides to >2 daughter cells. It is reported that zygote AC is correlated with very low implantation (1%) (Rubio et al. 2012). The objectives of this study were to (1) further address the clinical relevance of zygote AC (AC1) and daughter cell AC (AC2), and (2) examine the potential of using automated time-lapse cleavage analysis to deselect AC. Retrospective cohort study. Patients undergoing D3 embryo transfer from 3 sites (Jun2011-Oct2012) consented to have their embryos monitored using the Eeva™ Test (Auxogyn), a time-lapse enabled system which provides a high or low score of developmental potential based on key P2 (2-to-3 cell) and P3 (3-to-4 cell) time intervals (Wong et al. 2010, Conaghan et al. 2013). AC1 and AC2 were manually evaluated, and clinical relevance was based on implantation and clinical pregnancy (ultrasound at 6 wks). Imaging data of AC embryos were processed using Eeva software. Statistical significance was calculated using Fisher's Exact or χ2 test. A total of 363 embryos from 43 patients were included. The overall prevalence of AC was 20% (AC1:10%, AC2:10%, Both:0.6%). The prevalence of AC among 107 embryos transferred was 29% (AC1:9%, AC2: 19%, Both:1%), because all AC embryos selected for transfer exhibited relatively good morphology (6-10 cell, <25% frag, perfect/moderate symmetry). The implantation rate of AC was 3% (1/30). In patient cohorts, the incidence of AC (0% vs. 1-25% vs. ≥25%) was inversely correlated with clinical pregnancy (50% vs. 29% vs. 16%). Eeva software categorized 87% (53/61) of AC embryos as low, suggesting that automated P2 and P3 timings may inherently capture AC. AC1 and AC2 embryos are often selected for Day 3 transfer due to their overall good morphology, but these embryos rarely implant. Automated time-lapse analysis using predictive cleavage timings may aid in the deselection of AC events to improve pregnancy rates – a prospective trial is currently underway." @default.
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• W2316800570 date "2013-09-01" @default.
• W2316800570 modified "2023-09-29" @default.
• W2316800570 title "Using a novel time-lapse platform with automated image analysis can detect diverse abnormal cleavage patterns that are not recognized by traditional morphology and correlate with poor implantation" @default.
• W2316800570 doi "https://doi.org/10.1016/j.fertnstert.2013.07.418" @default.
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