An Empirical Predictive Model for Formation Rate of the Day 5 Blastocyst
Автор: Xi Wang, Zhongqiang Liu
Журнал: International Journal of Mathematical Sciences and Computing @ijmsc
Статья в выпуске: 2 vol.9, 2023 года.
Бесплатный доступ
Day 5 (D5) blastocyst transfers present higher clinical pregnancy and live birth rates than day 6 in both fresh and frozen transfers [1]. 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.
Day 5 blastocyst, Nomogram, Logistic regression, Hosmer-Lemeshow test
Короткий адрес: https://sciup.org/15019050
IDR: 15019050 | DOI: 10.5815/ijmsc.2023.02.03
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