IVF Australia, Sydney; and School of Women's and Children's Health, Faculty of Medicine, University of New South Wales, Randwick, New South Wales, Australia.
IVF Australia, Sydney; and School of Women's and Children's Health, Faculty of Medicine, University of New South Wales, Randwick, New South Wales, Australia.
Fertil Steril. 2018 Feb;109(2):276-283.e3. doi: 10.1016/j.fertnstert.2017.10.036. Epub 2018 Jan 11.
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.
Prospective study.
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.
确定发表的时间延迟算法在选择最佳第 5 天胚胎进行移植方面的一致性，以及这些算法与胚胎学家之间的一致性。
前瞻性研究。
私人体外受精中心。
100 个周期中在胚胎镜下培养的 428 个胚胎。
无。
采用 Fleiss kappa 系数评估算法间的一致性。
在本研究分析的 7 种已发表的算法中，只有 18 对中 1 对显示出非常好的一致性（κ=0.867）；1 对显示出良好的一致性（κ=0.725），4 对显示出适度的一致性（κ=0.226-0.334），其余 12 对显示出较差的一致性（κ=0.008-0.149）。即使在最佳情况下，大多数算法（κ=0.337-0.722）对于评估算法所选“最佳”胚胎与大多数（>5）胚胎学家选择的胚胎之间的一致性，以及与实验室在移植当天实际选择的胚胎之间的一致性（κ=0.315-0.802），评分都较差或中等。
本研究结果对所测试的算法是否适用于不同的临床环境提出了关注，强调在临床应用前需要进行适当的外部验证。
