An evaluation method for determining preeclampsia risk levels during pregnancy

Author:

Şahin Rıdvan1ORCID,Şahin Meltem2

Affiliation:

1. Gümüşhane Üniversitesi: Gumushane Universitesi

2. Gumushane University Faculty of Health Sciences: Gumushane Universitesi Saglik Bilimleri Fakultesi

Abstract

Abstract Preeclampsia (PE), which is one of the most common complications in pregnancy and affects approximately 2% to 8% of all pregnancies, is a hypertensive disorder of gestation diagnosed with hypertension and proteinuria that usually occurs in the second trimester of pregnancy. PE is characterized by new onset of hypertension (≥140/90 mmHg) and proteinuria that develops after 20 weeks of gestation and usually resolves within 48h of fetal delivery. It can cause pain for mother and fetus as well as increase their risk of death. According to Royal College of Obstetricians and Gynaecologists, PE can be identified under three criteria: systolic blood pressure diastolic blood pressure and proteinuria. The main objective of this research is to develop an evaluation method to identify the risk degree of preeclampsia in pregnancy. When considering clinical measures as an interval rather than a single value, it is important not only to evaluate this interval but also to test the reliability of the evaluation. In order to express the uncertainty and reliability of interval data, we propose a neutrosophic interval set (NIS) model in this paper. A NIS presents the evaluation interval with regard to objects and its reliability simultaneously. In addition, in order to determine the PE risk degree, a new risk evaluation method is developed which is based on the similarity measure of NISs and considered decision maker's risk attitude. Finally, the practicability of developed method in this work are illustrated by an example of determining the PE risk degrees of 12 pregnant. The comparative analysis demonstrates that proposed evaluation approach is superior performance to that of the existing PE risk evaluation method.

Publisher

Research Square Platform LLC

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