Prediction Model for Pregnancy Success in IVF Program in the Poor Prognosis Group

Sirait, Batara I. and Udjung, Gorga I. V. W. and Sandriasasti, Dzakiya Dwika (2024) Prediction Model for Pregnancy Success in IVF Program in the Poor Prognosis Group. Galore International Journal of Health Sciences and Research, 9 (1). pp. 164-173. ISSN 2456-9321

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Abstract

Introduction: Infertility has become a severe problem for married couples who have hoped to have children after having sexual intercourse 1-3 times a week for 12 months without using contraception. WHO has reported that 1 in 7 couples have problems with pregnancy, whereas around 50-80 million married couples from all over the world have infertility problems. Both husband and wife factors are related to the potential for infertility that can occur, and various examinations in the IVF program are known to predict the outcome of the IVF program. Methodology: This study aimed to predict the success of the IVF program, namely the achievement of clinical pregnancy based on IVF predictor factors in the poor prognosis group. This descriptive-analytic study uses total sampling and secondary data from medical records. Results: Based on the logistic regression test results using the IBM SPSS (Statistical Package for the Social Science) 25 program it was obtained from various variables predicting clinical pregnancy factors, a significant research variable in predicting the success of the IVF program in the poor prognosis group was endometrial thickness p value = 0.001 (p = < 0.05) which stated that there was a relationship between endometrial thickness and the incidence of clinical pregnancy. Conclusion: From the results of the bivariate test of factors predicting the incidence of pregnancy in the IVF program in the poor prognosis group, three variables are significant for the dependent variable, namely Endometrial Thickness, Number of Fertilized Oocytes, and Number of Top Quality Embryo Transfers; Results in the final model where one significant independent variable was obtained to predict the success of clinical pregnancy in the IVF program, namely Endometrial Thickness. Keywords: Infertility, prediction model, In Vitro Fertilization, Logistic Regression, Endometrial Thickness, Poor Prognosis, Clinical Pregnancy

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