A risk factor-based predictive model for new-onset hypertension during pregnancy in Chinese Han women

Abstract Background Hypertensive disorders of pregnancy (HDP) is one of the leading causes of maternal and neonatal mortality, increasing the long-term incidence of cardiovascular diseases. Preeclampsia and gestational hypertension are the major components of HDP. The aim of our study is to establis...

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Main Authors: Yamin Hou, Lin Yun, Lihua Zhang, Jingru Lin, Rui Xu
Format: Article
Language:English
Published: BMC 2020-04-01
Series:BMC Cardiovascular Disorders
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12872-020-01428-x
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spelling doaj-ed99f43e61464c929a162cd7545b3f282020-11-25T03:17:08ZengBMCBMC Cardiovascular Disorders1471-22612020-04-0120111010.1186/s12872-020-01428-xA risk factor-based predictive model for new-onset hypertension during pregnancy in Chinese Han womenYamin Hou0Lin Yun1Lihua Zhang2Jingru Lin3Rui Xu4Department of Cardiology, Shandong Provincial Qianfoshan Hospital, Shandong UniversityDepartment of Medicine, Jinan Maternity and Child Care HospitalDepartment of Medicine, Jinan Maternity and Child Care HospitalDepartment of Cardiology, Shandong Provincial Third HospitalDepartment of Cardiology, Shandong Provincial Qianfoshan Hospital, Shandong UniversityAbstract Background Hypertensive disorders of pregnancy (HDP) is one of the leading causes of maternal and neonatal mortality, increasing the long-term incidence of cardiovascular diseases. Preeclampsia and gestational hypertension are the major components of HDP. The aim of our study is to establish a prediction model for pregnant women with new-onset hypertension during pregnancy (increased blood pressure after gestational age > 20 weeks), thus to guide the clinical prediction and treatment of de novo hypertension. Methods A total of 117 pregnant women with de novo hypertension who were admitted to our hospital’s obstetrics department were selected as the case group and 199 healthy pregnant women were selected as the control group from January 2017 to June 2018. Maternal clinical parameters such as age, family history and the biomarkers such as homocysteine, cystatin C, uric acid, total bile acid and glomerular filtration rate were collected at a mean gestational age in 16 to 20 weeks. The prediction model was established by logistic regression. Results Eleven indicators have statistically significant difference between two groups (P < 0.05). These 11 factors were substituted into the logistic regression equation and 7 independent predictors were obtained. The equation expressed including 7 factors. The calculated area under the curve was 0.884(95% confidence interval: 0.848–0.921), the sensitivity and specificity were 88.0 and 75.0%. A scoring system was established to classify pregnant women with scores ≤15.5 as low-risk pregnancy group and those with scores > 15.5 as high-risk pregnancy group. Conclusions Our regression equation provides a feasible and reliable means of predicting de novo hypertension after pregnancy. Risk stratification of new-onset hypertension was performed to early treatment interventions in high-risk populations.http://link.springer.com/article/10.1186/s12872-020-01428-xHypertension, pregnancy inducedPrediction modelRisk factorsHomocysteine
collection DOAJ
language English
format Article
sources DOAJ
author Yamin Hou
Lin Yun
Lihua Zhang
Jingru Lin
Rui Xu
spellingShingle Yamin Hou
Lin Yun
Lihua Zhang
Jingru Lin
Rui Xu
A risk factor-based predictive model for new-onset hypertension during pregnancy in Chinese Han women
BMC Cardiovascular Disorders
Hypertension, pregnancy induced
Prediction model
Risk factors
Homocysteine
author_facet Yamin Hou
Lin Yun
Lihua Zhang
Jingru Lin
Rui Xu
author_sort Yamin Hou
title A risk factor-based predictive model for new-onset hypertension during pregnancy in Chinese Han women
title_short A risk factor-based predictive model for new-onset hypertension during pregnancy in Chinese Han women
title_full A risk factor-based predictive model for new-onset hypertension during pregnancy in Chinese Han women
title_fullStr A risk factor-based predictive model for new-onset hypertension during pregnancy in Chinese Han women
title_full_unstemmed A risk factor-based predictive model for new-onset hypertension during pregnancy in Chinese Han women
title_sort risk factor-based predictive model for new-onset hypertension during pregnancy in chinese han women
publisher BMC
series BMC Cardiovascular Disorders
issn 1471-2261
publishDate 2020-04-01
description Abstract Background Hypertensive disorders of pregnancy (HDP) is one of the leading causes of maternal and neonatal mortality, increasing the long-term incidence of cardiovascular diseases. Preeclampsia and gestational hypertension are the major components of HDP. The aim of our study is to establish a prediction model for pregnant women with new-onset hypertension during pregnancy (increased blood pressure after gestational age > 20 weeks), thus to guide the clinical prediction and treatment of de novo hypertension. Methods A total of 117 pregnant women with de novo hypertension who were admitted to our hospital’s obstetrics department were selected as the case group and 199 healthy pregnant women were selected as the control group from January 2017 to June 2018. Maternal clinical parameters such as age, family history and the biomarkers such as homocysteine, cystatin C, uric acid, total bile acid and glomerular filtration rate were collected at a mean gestational age in 16 to 20 weeks. The prediction model was established by logistic regression. Results Eleven indicators have statistically significant difference between two groups (P < 0.05). These 11 factors were substituted into the logistic regression equation and 7 independent predictors were obtained. The equation expressed including 7 factors. The calculated area under the curve was 0.884(95% confidence interval: 0.848–0.921), the sensitivity and specificity were 88.0 and 75.0%. A scoring system was established to classify pregnant women with scores ≤15.5 as low-risk pregnancy group and those with scores > 15.5 as high-risk pregnancy group. Conclusions Our regression equation provides a feasible and reliable means of predicting de novo hypertension after pregnancy. Risk stratification of new-onset hypertension was performed to early treatment interventions in high-risk populations.
topic Hypertension, pregnancy induced
Prediction model
Risk factors
Homocysteine
url http://link.springer.com/article/10.1186/s12872-020-01428-x
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