International Journal of Mathematical Sciences and Computing(IJMSC)
ISSN: 2310-9025 (Print), ISSN: 2310-9033 (Online)
Published By: MECS Press
IJMSC Vol.9, No.2, May. 2023
An Empirical Predictive Model for Formation Rate of the Day 5 Blastocyst
Full Text (PDF, 724KB), PP.22-30
Day 5 (D5) blastocyst transfers present higher clinical pregnancy and live birth rates than day 6 in both fresh and frozen transfers . To investigate the D5 blastocyst formation rate, in this study, we first collected clinical data from a hospital in Jiaozuo and partitioned the data into training set and validation set. We conducted univariate logistic regression analyses, which were possible predictors of the D5 blastocyst formation rate, on 12 patient covariates. According to the univariate analysis, we determined 10 covariates were suitable for multivariate analysis. Finally, we identified five covariates to construct a logistic regression model to predict the D5 blastocyst formation rate. We also used the receiver operating characteristic curve, the Hosmer–Lemeshow test, and the calibration curve to verify the accuracy of this model. The results showed that logistic regression model of D5 blastocyst formation rate directly reflected the relationship between transplantation results and covariates. According to the model, doctors can provide guidance to patients before treatment and improve the rate of blastocyst formation by changing patients' physical fitness. The model has certain clinical application value.
Cite This Paper
Xi Wang, Zhongqiang Liu, "An Empirical Predictive Model for Formation Rate of the Day 5 Blastocyst", International Journal of Mathematical Sciences and Computing(IJMSC), Vol.9, No.2, pp. 22-30, 2023. DOI: 10.5815/ijmsc.2023.02.03
M. Bourdon and K. Pocate-Cheriet, “Day 5 versus Day 6 blastocyst transfers: a systematic review and meta-analysis of clinical outcomes”, Human Reproduction. (2019), 34(10), 1948-1964.
A. D. Kulkarni, D. J. Jamieson and H. W. Jones, “Fertility Treatments and Multiple Births in the United State.”, New England Journal of Medicine. (2013), 369(23), 2218-2225.
I. Scholten，G. M. Chambers and L Van Loendersloot, “Impact of assisted reproductive technology on the incidence ofmultiple-gestation infants: apopulation perspective.”, Fertility and Sterility. (2015), 103(1), 179-183.
J. Qin and H. Wang Van, “Pregnancy-related complications and adverse pregnancy outcomes in multiple pregnancies resulting from assisted reproductive technology: a meta-analysis of cohort studies.”, Fertility and Sterility. (2015), 103(6), 1492-1508.
T. Coetsier and M. Dhont, “Avoiding multiple pregnancies in in-vitro fertilization: who's afraid of single embryo transfer?”, Human Reproduction. (1998), 13, 2663-2664.
R. Z. Karaki, S. S. Samarraie and N. A. Younis, “Blastocyst culture and transfer: a step toward improved in vitro fertilization outcome.”, Fertility and Sterility. (2002), 77(1), 114-118.
C. Serdar, H. Johannes, “Day 5 versus day 3 embryo transfer: a controlled randomized trial.”, Human Reproduction. (2000), 9, 1947-1952.
M. Henman and J. W. Catt, “Elective transfer of single fresh blastocysts and later transfer of cryostored blastocysts reduces the twin pregnancy rate and can improve the in vitro fertilization live birth rate in younger women.”, Digest of the World Core Medical Journals. (2006), 84(6), 1620-1627.
D. Wei, Y. Sun, “single blastocyst transfer (Frefro-blastocyst): study protocol for a randomized controlled trial.”, Trials. (2017), 18(1), 1-7.
D. Wei, J. Y. Liu and Y. Sun, “Frozen versus fresh single blastocyst transfer in ovulatory women: a multicentre, randomised controlled trial.”, The Lancet. (2019), 393, 1310-1318.
A. Trounson, L. Mohr, “Human pregnancy following cryopreservation, thawing and transfer of an eight-cell embryo.”, Nature. (1983), 305(5936), 707.
X. J. Wang and W. Ledger, “The contribution of embryo cryopreservation to in-vitro fertilization/gamete intra-fallopian transfer: 8 years’ experience.”, Human reproduction. (1994), 9, 103-109.
D. Gardner, “Culture and transfer of human blastocysts increases implantation rates and reduces the need for multiple embryo transfers.”, Fertility and sterility. (1998), 69.
L. L. Loendersloot ang M. Wely, “Individualized decision-making in IVF: calculating the chances of pregnancy.”, Human reproduction. (2013), 11, 2972-2980.
R. K. Dhillon and D. J. McLernon, “Predicting the chance of live birth for women undergoing IVF: a novel pretreatment counselling tool.”, Human reproduction. (2015), 1, 84.
S. Veronica and R. Marco, “Predicting the success of IVF: external validation of the van Loendersloot's model.”, Human reproduction. (2016), 6, 1245.
P. Hafiz and M. Nematollahi, “Predicting Implantation Outcome of In Vitro Fertilization and Intracytoplasmic Sperm Injection Using Data Mining Techniques.”, International journal of fertility & sterility. (2017), 11(3), 184-190.
C. Blank and R. R. Wildeboer, “Prediction of implantation after blastocyst transfer in in vitro fertilization: a machine-learning perspective.”, Fertility and Sterility. (2019), 111(2), 318-326.
L. L. Loendersloot ang M. Wely, “Predictive factors in in vitro fertilization (IVF): a systematic review and meta-analysis.”, Human reproduction update. (2010), 16(6), 577-589.
X. H. Deng ang Y. Z. Xu, “Fertility evaluation and assisted reproduction in elder women.”, Journal of Shandong University: Medical Edition. (2017), 55(1), 5-10.
Z. J. Chen, “Clinical concern of the second pregnancy under the two-child policy.”, Journal of Shandong University: Medical Edition. (2017), 55(1), 1-4.
J. X. Xiao, “Study on the correlation between anti-Müllerian hormone and pregnancy outcome of controlled ovarian hyperstimulation.”, China Maternal and Child Health. (2016), 31(19), 4010-4013.
S. L. Broer, “Added value of ovarian reserve testing on patient characteristics in the prediction of ovarian response and ongoing pregnancy: an individual patient data approach.”, Human Reproduction Update. (2013), 19(1), 26-36.
S. E. Alson, “Anti-müllerian hormone levels are associated with live birth rates in ART, but the predictive ability of anti-müllerian hormone is modest.”, Eur J Obstet Gynecol Reprod Biol. (2018), 19(1), 26-36.
M. D. Reshef Tal, “Antimüllerian hormone as a predictor of live birth following assisted reproduction: an analysis of 85,062 fresh and thawed cycles from the Society for Assisted Reproductive Technology Clinic Outcome Reporting System database for 2012-2013.”, Fertility and sterility. (2018), 109(2), 258-265.