Study on the Number of Oocytes Retrieved Based on Multinomial Logistic Regression Model

Xi Wang

doi:https://doi.org/10.14445/22315373/IJMTT-V69I4P503

International Journal of Mathematics Trends and Technology

Research Article | Open Access | Download PDF

Volume 69 | Issue 4 | Year 2023 | Article Id. IJMTT-V69I4P503 | DOI : https://doi.org/10.14445/22315373/IJMTT-V69I4P503

Study on the Number of Oocytes Retrieved Based on Multinomial Logistic Regression Model

Xi Wang

Received	Revised	Accepted	Published
26 Feb 2023	01 Apr 2022	13 Apr 2023	28 Apr 2023

Citation :

Xi Wang, "Study on the Number of Oocytes Retrieved Based on Multinomial Logistic Regression Model," International Journal of Mathematics Trends and Technology (IJMTT), vol. 69, no. 4, pp. 17-28, 2023. Crossref, https://doi.org/10.14445/22315373/IJMTT-V69I4P503

Abstract

This paper selects the clinical data of patients receiving assisted reproductive therapy from 2019 to 2021 in the department of Obstetrics and Gynecology of a hospital in Jiaozuo City. We screen 1386 patients eligible for single blastocyst transplantation. According to the method of fertilization, patients are divided into natural fertilization group consisting of 1167 patients and an artificial fertilization group consisting of 219 patients. Based on existing studies, we preliminarily identify 5 covariables to explain the number of oocytes retrieved. Then the likelihood ratio test is used to screen covariates, and the multinomial logistic regression model is used to fit the two groups of data respectively. By comparison, we find that the covariates affecting the number of retrieved oocytes in the two groups are not the same. The results show that the age, duration of infertility, Anti-Müllerian Hormone, and Gonadotropins dosage of natural fertilization patients all have a significant impact on the number of oocytes retrieved, while the number of oocytes retrieved in artificial fertilization patients is only affected by Anti-Müllerian Hormone. The doctor can predict the number of oocytes retrieved by the patient based on the regression model and can optimize the number of oocytes retrieved by adjusting the patient's covariables.

Keywords

Multinomial logistic regression, the number of oocytes retrieved, Likelihood ratio test, Assisted Reproductive Technology.

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