Bibliographic citations
San, M., (2020). Evaluación del modelo fullPIERS como predictor de complicaciones maternas en gestantes con preeclampsia del Hospital Regional de Loreto durante el periodo 2018-2020 [Universidad Nacional de la Amazonía Peruana]. http://repositorio.unapiquitos.edu.pe/handle/20.500.12737/7048
San, M., Evaluación del modelo fullPIERS como predictor de complicaciones maternas en gestantes con preeclampsia del Hospital Regional de Loreto durante el periodo 2018-2020 []. : Universidad Nacional de la Amazonía Peruana; 2020. http://repositorio.unapiquitos.edu.pe/handle/20.500.12737/7048
@misc{sunedu/3118579,
title = "Evaluación del modelo fullPIERS como predictor de complicaciones maternas en gestantes con preeclampsia del Hospital Regional de Loreto durante el periodo 2018-2020",
author = "San Román Arispe, Martha Galia",
publisher = "Universidad Nacional de la Amazonía Peruana",
year = "2020"
}
The present academic work is a longitudinal study since the measurement of the variables was carried out at various times during the study period. The pregnant women were monitored for symptoms, symptoms of preeclampsia, biochemical laboratory, and maternal complications. A risk prediction score was calculated using the full PIERS calculator. The statistical analysis of the rates and proportions was carried out by evaluating ? 2 and the odds ratio. This work was done with the objective of determining if the fullPIERS model is a useful predictor of maternal complications in pregnant women with pre-eclampsia of the Regional Hospital of Loreto during the 2018-2020 periods. Our population for the present study was made up of pregnant women with a diagnosis of hypertensive disorders of pregnancy admitted to the Obstetrics service of the Regional Hospital of Loreto during the period from January 1 to December 31, 2020. The size of the study population was determined by all pregnant women who meet the diagnostic criteria for preeclampsia admitted to the Obstetrics service of the Regional Hospital of Loreto during the period from January 1 to December 31, 2020, either by the Emergency service or Clinics, from the entire Loreto region, to say locals and references from the different towns. The statistical analysis of the rates and proportions was obtained by evaluating ? 2 and the odds ratio, for which significance was considered to be P <0.05. Using the EPI INFO version 7.2 software, the univariate logistic regression was performed. Sensitivity, specificity, and positive likelihood ratios (LR) were calculated using MedCalc software. The risk prediction score was obtained using the full PIERS calculator.
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