Claman P, Armant DR, Seibel MM, Wang TA, Oskowitz SP, Taymor ML. The impact of embryo quality and quantity on implantation and the establishment of viable pregnancies. J In Vitro Fert Embryo Transf. 1987;4(4):218–22.
Article CAS PubMed Google Scholar
Edwards RG, Fishel SB, Cohen J, Fehilly CB, Purdy JM, Slater JM, et al. Factors influencing the success of in vitro fertilization for alleviating human infertility. J In Vitro Fert Embryo Transf. 1984;1(1):3–23.
Article CAS PubMed Google Scholar
Nicoli A, Palomba S, Capodanno F, Fini M, Falbo A, La Sala GB. Pronuclear morphology evaluation for fresh in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI) cycles: a systematic review. J Ovarian Res. 2013;6(1):64.
Article PubMed PubMed Central Google Scholar
Tesarik J, Greco E. The probability of abnormal preimplantation development can be predicted by a single static observation on pronuclear stage morphology. Hum Reprod. 1999;14(5):1318–23.
Article CAS PubMed Google Scholar
Ahlstrom A, Westin C, Reismer E, Wikland M, Hardarson T. Trophectoderm morphology: an important parameter for predicting live birth after single blastocyst transfer. Hum Reprod. 2011;26(12):3289–96.
Article CAS PubMed Google Scholar
Gardner DK, Lane M, Stevens J, Schlenker T, Schoolcraft WB. Blastocyst score affects implantation and pregnancy outcome: towards a single blastocyst transfer. Fertil Steril. 2000;73(6):1155–8.
Article CAS PubMed Google Scholar
Alpha Scientists in Reproductive M, Embryology ESIGo. The Istanbul consensus workshop on embryo assessment: proceedings of an expert meeting. Hum Reprod. 2011;26(6):1270–83.
Armstrong S, Bhide P, Jordan V, Pacey A, Marjoribanks J, Farquhar C. Time-lapse systems for embryo incubation and assessment in assisted reproduction. Cochrane Database Syst Rev. 2019;5:CD011320.
Kaser DJ, Racowsky C. Clinical outcomes following selection of human preimplantation embryos with time-lapse monitoring: a systematic review. Hum Reprod Update. 2014;20(5):617–31.
Meseguer M, Herrero J, Tejera A, Hilligsoe KM, Ramsing NB, Remohi J. The use of morphokinetics as a predictor of embryo implantation. Hum Reprod. 2011;26(10):2658–71.
Liu Y, Chapple V, Feenan K, Roberts P, Matson P. Time-lapse deselection model for human day 3 in vitro fertilization embryos: the combination of qualitative and quantitative measures of embryo growth. Fertil Steril. 2016;105(3):656-62 e1.
Carrasco B, Arroyo G, Gil Y, Gomez MJ, Rodriguez I, Barri PN, et al. Selecting embryos with the highest implantation potential using data mining and decision tree based on classical embryo morphology and morphokinetics. J Assist Reprod Genet. 2017;34(8):983–90.
Article PubMed PubMed Central Google Scholar
Milewski R, Kuczynska A, Stankiewicz B, Kuczynski W. How much information about embryo implantation potential is included in morphokinetic data? A prediction model based on artificial neural networks and principal component analysis. Adv Med Sci. 2017;62(1):202–6.
Fishel S, Campbell A, Montgomery S, Smith R, Nice L, Duffy S, et al. Time-lapse imaging algorithms rank human preimplantation embryos according to the probability of live birth. Reprod Biomed Online. 2018;37(3):304–13.
Bodri D, Milewski R, Yao Serna J, Sugimoto T, Kato R, Matsumoto T, et al. Predicting live birth by combining cleavage and blastocyst-stage time-lapse variables using a hierarchical and a data mining-based statistical model. Reprod Biol. 2018;18(4):355–60.
Motato Y, de los Santos MJ, Escriba MJ, Ruiz BA, Remohi J, Meseguer M. Morphokinetic analysis and embryonic prediction for blastocyst formation through an integrated time-lapse system. Fertil Steril. 2016;105(2):376–849.
Basile N, Vime P, Florensa M, Aparicio Ruiz B, Garcia Velasco JA, Remohi J, et al. The use of morphokinetics as a predictor of implantation: a multicentric study to define and validate an algorithm for embryo selection. Hum Reprod. 2015;30(2):276–83.
Article CAS PubMed Google Scholar
Petersen BM, Boel M, Montag M, Gardner DK. Development of a generally applicable morphokinetic algorithm capable of predicting the implantation potential of embryos transferred on Day 3. Hum Reprod. 2016;31(10):2231–44.
Article PubMed PubMed Central Google Scholar
Storr A, Venetis C, Cooke S, Kilani S, Ledger W. Time-lapse algorithms and morphological selection of day-5 embryos for transfer: a preclinical validation study. Fertil Steril. 2018;109(2):276-83 e3.
Barrie A, Homburg R, McDowell G, Brown J, Kingsland C, Troup S. Examining the efficacy of six published time-lapse imaging embryo selection algorithms to predict implantation to demonstrate the need for the development of specific, in-house morphokinetic selection algorithms. Fertil Steril. 2017;107(3):613–21.
Liu Y, Feenan K, Chapple V, Matson P. Assessing efficacy of day 3 embryo time-lapse algorithms retrospectively: impacts of dataset type and confounding factors. Hum Fertil (Camb). 2019;22(3):182–90.
Freour T, Le Fleuter N, Lammers J, Splingart C, Reignier A, Barriere P. External validation of a time-lapse prediction model. Fertil Steril. 2015;103(4):917–22.
Barrie A, McDowell G, Troup S. An investigation into the effect of potentialconfounding patient and treatment parameters on human embryo morphokinetics. Fertil Steril. 2021;115(4):1014–22.
Kirkegaard K, Sundvall L, Erlandsen M, Hindkjaer JJ, Knudsen UB, Ingerslev HJ. Timing of human preimplantation embryonic development is confounded by embryo origin. Hum Reprod. 2016;31(2):324–31.
Speirs AL, Lopata A, Gronow MJ, Kellow GN, Johnston WI. Analysis of the benefits and risks of multiple embryo transfer. Fertil Steril. 1983;39(4):468–71.
Article CAS PubMed Google Scholar
Roberts SA, Fitzgerald CT, Brison DR. Modelling the impact of single embryo transfer in a national health service IVF programme. Hum Reprod. 2009;24(1):122–31.
Dukic V, Hogan JW. A hierarchical Bayesian approach to modeling embryo implantation following in vitro fertilization. Biostatistics. 2002;3(3):361–77.
Zhou H, Weinberg CR. Evaluating effects of exposures on embryo viability and uterine receptivity in in vitro fertilization. Stat Med. 1998;17(14):1601–12.
Article CAS PubMed Google Scholar
Roberts SA. Models for assisted conception data with embryo-specific covariates. Stat Med. 2007;26(1):156–70.
Stylianou C, Pickles A, Roberts SA. Using Bonferroni, BIC and AIC to assess evidence for alternative biological pathways: covariate selection for the multilevel Embryo-Uterus model. BMC Med Res Methodol. 2013;13:73.
Article PubMed PubMed Central Google Scholar
Eijkemans MJ, Heijnen EM, de Klerk C, Habbema JD, Fauser BC. Comparison of different treatment strategies in IVF with cumulative live birth over a given period of time as the primary end-point: methodological considerations on a randomized controlled non-inferiority trial. Hum Reprod. 2006;21(2):344–51.
Article CAS PubMed Google Scholar
Giorgetti C, Hans E, Terriou P, Salzmann J, Barry B, Chabert-Orsini V, et al. Early cleavage: an additional predictor of high implantation rate following elective single embryo transfer. Reprod Biomed Online. 2007;14(1):85–91.
Article CAS PubMed Google Scholar
Lundin K, Bergh C, Hardarson T. Early embryo cleavage is a strong indicator of embryo quality in human IVF. Hum Reprod. 2001;16(12):2652–7.
Article CAS PubMed Google Scholar
Terriou P, Giorgetti C, Hans E, Salzmann J, Charles O, Cignetti L, et al. Relationship between even early cleavage and day 2 embryo score and assessment of their predictive value for pregnancy. Reprod Biomed Online. 2007;14(3):294–9.
Article CAS PubMed Google Scholar
Ciray HN, Campbell A, Agerholm IE, Aguilar J, Chamayou S, Esbert M, et al. Proposed guidelines on the nomenclature and annotation of dynamic human embryo monitoring by a time-lapse user group. Hum Reprod. 2014;29(12):2650–60.
Rubio I, Kuhlmann R, Agerholm I, Kirk J, Herrero J, Escriba MJ, et al. Limited implantation success of direct-cleaved human zygotes: a time-lapse study. Fertil Steril. 2012;98(6):1458–63.
Sakkas D, Percival G, D’Arcy Y, Sharif K, Afnan M. Assessment of early cleaving in vitro fertilized human embryos at the 2-cell stage before transfer improves embryo selection. Fertil Steril. 2001;76(6):1150–6.
Article CAS PubMed Google Scholar
Moons KG, Kengne AP, Woodward M, Royston P, Vergouwe Y, Altman DG, et al. Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker. Heart. 2012;98(9):683–90.
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