Predicting Ectopic Pregnancy Using Human Chorionic Gonadotropin (hCG) Levels and Main Cause of Infertility in Women Undergoing Assisted Reproductive Treatment: Retrospective Observational Cohort Study.

Huiyu Xu,Yuan Wei,Hongxia Zhang,Jie Qiao,Ying Feng,Rui Yang,Rong Li,Liying Wang,Guoshuang Feng

doi:10.2196/17366

Abstract

BackgroundEctopic pregnancy (EP) is a serious complication of assisted reproductive technology (ART). However, there is no acknowledged mathematical model for predicting EP in the ART population.ObjectiveThe goal of the research was to establish a model to tailor treatment for women with a higher risk of EP.MethodsFrom December 2015 to July 2016, we retrospectively included 1703 women whose serum human chorionic gonadotropin (hCG) levels were positive on day 21 (hCG21) after fresh embryo transfer. Multivariable multinomial logistic regression was used to predict EP, intrauterine pregnancy (IUP), and biochemical pregnancy (BCP).ResultsThe variables included in the final predicting model were (hCG21, ratio of hCG21/hCG14, and main cause of infertility). During evaluation of the model, the areas under the receiver operating curve for IUP, EP, and BCP were 0.978, 0.962, and 0.999, respectively, in the training set, and 0.963, 0.942, and 0.996, respectively, in the validation set. The misclassification rates were 0.038 and 0.045, respectively, in the training and validation sets. Our model classified the whole in vitro fertilization/intracytoplasmic sperm injection–embryo transfer population into four groups: first, the low-risk EP group, with incidence of EP of 0.52% (0.23%-1.03%); second, a predicted BCP group, with incidence of EP of 5.79% (1.21%-15.95%); third, a predicted undetermined group, with incidence of EP of 28.32% (21.10%-35.53%), and fourth, a predicted high-risk EP group, with incidence of EP of 64.11% (47.22%-78.81%).ConclusionsWe have established a model to sort the women undergoing ART into four groups according to their incidence of EP in order to reduce the medical resources spent on women with low-risk EP and provide targeted tailor-made treatment for women with a higher risk of EP.

Highlights

Ectopic pregnancy (EP) is the leading cause of maternal morbidity and mortality during the first trimester, accounting for 5% to 10% of all maternal deaths [1]
As the early pregnancy outcome was an EP, intrauterine pregnancy (IUP), or biochemical pregnancy (BCP), we used univariate multinomial logistic regression to test the relationships between each independent variable and the outcome variable
Considering the strong correlation between human chorionic gonadotropin (hCG) level >5 IU/L on days 14 (hCG14) and hCG21 (R2=.74)—which is an indication of collinearity—the serum levels of hCG14 and hCG21 could not be included in the prediction model simultaneously, so we only included the hCG21 level in further analysis

Summary

Introduction

Ectopic pregnancy (EP) is the leading cause of maternal morbidity and mortality during the first trimester, accounting for 5% to 10% of all maternal deaths [1]. The incidence of EP is 2 to 3 times higher in pregnancies resulting from assisted reproductive technology (ART) than in natural pregnancies [2]. It is well acknowledged that the circulating human chorionic gonadotropin (hCG) level in early pregnancy aids in diagnosis of EP before any gestational sac can be http://medinform.jmir.org/2020/4/e17366/ XSLFO RenderX. A significant amount of time and resources are spent in reproductive centers on monitoring women with early pregnancies to identify EP in time to prevent its complications. Tests for assuring the location of gestational sacs have significant cost burdens on patients and centers. Ectopic pregnancy (EP) is a serious complication of assisted reproductive technology (ART). There is no acknowledged mathematical model for predicting EP in the ART population

Methods

Results

Conclusion