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

BACKGROUND: Ectopic 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. OBJECTIVE: The goal of the research was to establish a model to tailor treatment for women with a high...

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Autores principales: Xu, Huiyu, Feng, Guoshuang, Wei, Yuan, Feng, Ying, Yang, Rui, Wang, Liying, Zhang, Hongxia, Li, Rong, Qiao, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7193436/
https://www.ncbi.nlm.nih.gov/pubmed/32297865
http://dx.doi.org/10.2196/17366
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author Xu, Huiyu
Feng, Guoshuang
Wei, Yuan
Feng, Ying
Yang, Rui
Wang, Liying
Zhang, Hongxia
Li, Rong
Qiao, Jie
author_facet Xu, Huiyu
Feng, Guoshuang
Wei, Yuan
Feng, Ying
Yang, Rui
Wang, Liying
Zhang, Hongxia
Li, Rong
Qiao, Jie
author_sort Xu, Huiyu
collection PubMed
description BACKGROUND: Ectopic 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. OBJECTIVE: The goal of the research was to establish a model to tailor treatment for women with a higher risk of EP. METHODS: From 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). RESULTS: The 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%). CONCLUSIONS: We 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.
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spelling pubmed-71934362020-05-05 Predicting Ectopic Pregnancy Using Human Chorionic Gonadotropin (hCG) Levels and Main Cause of Infertility in Women Undergoing Assisted Reproductive Treatment: Retrospective Observational Cohort Study Xu, Huiyu Feng, Guoshuang Wei, Yuan Feng, Ying Yang, Rui Wang, Liying Zhang, Hongxia Li, Rong Qiao, Jie JMIR Med Inform Original Paper BACKGROUND: Ectopic 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. OBJECTIVE: The goal of the research was to establish a model to tailor treatment for women with a higher risk of EP. METHODS: From 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). RESULTS: The 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%). CONCLUSIONS: We 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. JMIR Publications 2020-04-16 /pmc/articles/PMC7193436/ /pubmed/32297865 http://dx.doi.org/10.2196/17366 Text en ©Huiyu Xu, Guoshuang Feng, Yuan Wei, Ying Feng, Rui Yang, Liying Wang, Hongxia Zhang, Rong Li, Jie Qiao. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 16.04.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on http://medinform.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Xu, Huiyu
Feng, Guoshuang
Wei, Yuan
Feng, Ying
Yang, Rui
Wang, Liying
Zhang, Hongxia
Li, Rong
Qiao, Jie
Predicting Ectopic Pregnancy Using Human Chorionic Gonadotropin (hCG) Levels and Main Cause of Infertility in Women Undergoing Assisted Reproductive Treatment: Retrospective Observational Cohort Study
title Predicting Ectopic Pregnancy Using Human Chorionic Gonadotropin (hCG) Levels and Main Cause of Infertility in Women Undergoing Assisted Reproductive Treatment: Retrospective Observational Cohort Study
title_full Predicting Ectopic Pregnancy Using Human Chorionic Gonadotropin (hCG) Levels and Main Cause of Infertility in Women Undergoing Assisted Reproductive Treatment: Retrospective Observational Cohort Study
title_fullStr Predicting Ectopic Pregnancy Using Human Chorionic Gonadotropin (hCG) Levels and Main Cause of Infertility in Women Undergoing Assisted Reproductive Treatment: Retrospective Observational Cohort Study
title_full_unstemmed Predicting Ectopic Pregnancy Using Human Chorionic Gonadotropin (hCG) Levels and Main Cause of Infertility in Women Undergoing Assisted Reproductive Treatment: Retrospective Observational Cohort Study
title_short Predicting Ectopic Pregnancy Using Human Chorionic Gonadotropin (hCG) Levels and Main Cause of Infertility in Women Undergoing Assisted Reproductive Treatment: Retrospective Observational Cohort Study
title_sort predicting ectopic pregnancy using human chorionic gonadotropin (hcg) levels and main cause of infertility in women undergoing assisted reproductive treatment: retrospective observational cohort study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7193436/
https://www.ncbi.nlm.nih.gov/pubmed/32297865
http://dx.doi.org/10.2196/17366
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