Abstract
PurposeThe aim of this study was to create a model to predict the implantation of transferred embryos based on information contained in the morphokinetic parameters of time-lapse monitoring.MethodsAn analysis of time-lapse recordings of 410 embryos transferred in 343 cycles of in vitro fertilization (IVF) treatment was performed. The study was conducted between June 2012 and November 2014. For each embryo, the following data were collected: the duration of time from the intracytoplasmic sperm injection (ICSI) procedure to further division for two, three, four, and five blastomeres, time intervals between successive divisions, and the level of fragmentation assessed in successive time-points. Principal component analysis (PCA) and logistic regression were used to create a predictive model.ResultsBased on the results of principal component analysis and logistic regression analysis, a predictive equation was constructed. Statistically significant differences (p < 0.001) in the size of the created parameter between the implanted group (the median value: Me = −5.18 and quartiles: Q1 = −5.61; Q3 = −4.79) and the non-implanted group (Me = −5.69, Q1 = −6.34; Q3 = −5.16) were found. A receiver operating characteristic (ROC) curve constructed for the considered model showed the good quality of this predictive equation. The area under the ROC curve was AUC = 0.70 with a 95 % confidence interval (0.64, 0.75). The presented model has been validated on an independent data set, illustrating that the model is reliable and repeatable.ConclusionsMorphokinetic parameters contain information useful in the process of creating pregnancy prediction models. However, embryo quality is not the only factor responsible for implantation, and, thus, the power of prediction of the considered model is not as high as in models for blastocyst formation. Nevertheless, as illustrated by the results of this study, the application of advanced data-mining methods in reproductive medicine allows one to create more accurate and useful models.
Highlights
Progress in reproductive medicine has resulted in a growth in the efficacy of infertility treatment
Morphokinetic predictive markers are created in such a way that endows them with the potential to improve the effectiveness of embryo selection, allowing single embryo transfers to be performed, thereby minimizing the rate of multiple pregnancies without the loss of treatment efficacy
After dividing the embryos into four groups according to quartiles and the median value of the Sc parameter (C1–C4), statistically significant differences in pregnancy rates were found between the studied groups (p = 0.009) (Table 1)
Summary
Progress in reproductive medicine has resulted in a growth in the efficacy of infertility treatment. Racowsky et al [7] pay attention to the limitations of studies reporting algorithms that may assist in selecting the most viable embryos They list variables other than embryo health (e.g., the type of ovarian stimulation or culture conditions) that influence the timing of embryo development. In their assessment, created scoring systems should not be limited to time-lapse parameters only. They claim that a lack of universally accepted nomenclature for morphokinetic features limits the ability to compare results among different studies. In addition to developing a universally accepted nomenclature, studies with the aim of constructing and validating scoring systems that depend on morphologic as well as kinetic features, in order to utilize timelapse systems to the best advantage, are greatly needed
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
