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

  • Authors:

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

  • Affiliations:

  • Escuela de Estadística, Universidad de Los Andes, Mérida, Venezuela;Instituto de Estadística Aplicada y Computación, Universidad de Los Andes, Mérida, Venezuela;Laboratorio de Sistemas Inteligentes, Universidad de Los Andes, Mérida, Venezuela;Departamento de Toxicología y Farmacología, Universidad de Los Andes, Mérida, Venezuela

  • Venue:
  • ICS'06 Proceedings of the 10th WSEAS international conference on Systems
  • Year:
  • 2006

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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 the main risk factors for PE and others HDP.