Logistic regression model for determining risks factor for hypertensive disorders in pregnancy

Anna Gabriela Pérez; Elizabeth Torres Rivas; Francklin Rivas Echeverría; Carlos Rivas Echeverría

Logistic regression model for determining risks factor for hypertensive disorders in pregnancy

Anna Gabriela Pérez^*, Elizabeth Torres Rivas, Francklin Rivas Echeverría, Carlos Rivas Echeverría

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Resumen

Preeclampsia (PE), one of the hypertensive disorders of pregnancy (HDP), is the onset of hypertension accompanied with proteinuria that occurs after 20th week of gestation. It is a syndrome of worldwide distribution, that complicates up to 10% of pregnancies and remain as the major cause of maternal and neonatal mortality and morbidity [1, 13]. Multiple conditions have been associated with an increased risk for PE like maternal age, nulliparity, previous preeclampsia, obesity, hypertension, among others. In this study, a logistic regression model was performed in order to estimate main risk factors for PE and others HDP.

Idioma original	Inglés
Páginas (desde-hasta)	2135-2139
Número de páginas	5
Publicación	WSEAS Transactions on Systems
Volumen	5
N.º	9
Estado	Publicada - sep. 2006
Publicado de forma externa	Sí

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title = "Logistic regression model for determining risks factor for hypertensive disorders in pregnancy",

abstract = "Preeclampsia (PE), one of the hypertensive disorders of pregnancy (HDP), is the onset of hypertension accompanied with proteinuria that occurs after 20th week of gestation. It is a syndrome of worldwide distribution, that complicates up to 10% of pregnancies and remain as the major cause of maternal and neonatal mortality and morbidity [1, 13]. Multiple conditions have been associated with an increased risk for PE like maternal age, nulliparity, previous preeclampsia, obesity, hypertension, among others. In this study, a logistic regression model was performed in order to estimate main risk factors for PE and others HDP.",

keywords = "Logistic regression model, Multiple correspondence analysis, Preeclampsia",

author = "P{\'e}rez, {Anna Gabriela} and Rivas, {Elizabeth Torres} and Echeverr{\'i}a, {Francklin Rivas} and Echeverr{\'i}a, {Carlos Rivas}",

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AU - Pérez, Anna Gabriela

AU - Rivas, Elizabeth Torres

AU - Echeverría, Francklin Rivas

AU - Echeverría, Carlos Rivas

PY - 2006/9

Y1 - 2006/9

N2 - Preeclampsia (PE), one of the hypertensive disorders of pregnancy (HDP), is the onset of hypertension accompanied with proteinuria that occurs after 20th week of gestation. It is a syndrome of worldwide distribution, that complicates up to 10% of pregnancies and remain as the major cause of maternal and neonatal mortality and morbidity [1, 13]. Multiple conditions have been associated with an increased risk for PE like maternal age, nulliparity, previous preeclampsia, obesity, hypertension, among others. In this study, a logistic regression model was performed in order to estimate main risk factors for PE and others HDP.

AB - Preeclampsia (PE), one of the hypertensive disorders of pregnancy (HDP), is the onset of hypertension accompanied with proteinuria that occurs after 20th week of gestation. It is a syndrome of worldwide distribution, that complicates up to 10% of pregnancies and remain as the major cause of maternal and neonatal mortality and morbidity [1, 13]. Multiple conditions have been associated with an increased risk for PE like maternal age, nulliparity, previous preeclampsia, obesity, hypertension, among others. In this study, a logistic regression model was performed in order to estimate main risk factors for PE and others HDP.

KW - Logistic regression model

KW - Multiple correspondence analysis

KW - Preeclampsia

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JO - WSEAS Transactions on Systems

JF - WSEAS Transactions on Systems

IS - 9

ER -

Logistic regression model for determining risks factor for hypertensive disorders in pregnancy

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