OSA (Obstructive Sleep Apnea) Risk Factor-Based Predictive Model for New-onset Preeclampsia during Pregnancy in Indonesian Women

Sulis Diana, STIKES Majapahit Mojokerto and Chatarina Umbul Wahyuni, Universitas Airlangga and Budi Prasetyo, STIKES Majapahit Mojokerto and Hari Basuki, Universitas Airlangga and Fitria Edni Wari, STIKES Majapahit Mojokerto (2022) OSA (Obstructive Sleep Apnea) Risk Factor-Based Predictive Model for New-onset Preeclampsia during Pregnancy in Indonesian Women. AGE, 205 (75). 29.74-6.20. ISSN -

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Abstract

Preeclampsia is a potentially dangerous pregnancy complication characterized by high blood pressure and its prevalence is around 5-8% of all diseases that occur during pregnancy. However, OSA (Obstruction Sleep Apnea) causes inflammation and oxidative stress, endothelial damage, and metabolic disorders. This study aims to produce a risk factor model for OSA as a predictor of preeclampsia in pregnancy.TThis is anobservational analytic study with a Case-Control design using a retrospective approach, carried out at Wahidin Sudiro Husoda Mojokerto Hospital and Sakinah Mojokerto Hospital from October 2020-February 2021. The samples were obtained by cluster random sampling of 272 people with the inclusion criteria for preeclampsia pregnant and normal pregnant> 32 weeks. The samples in the case and control groups were 136 and 136 people, respectively. The data analysis was carried out using binary logistic regression, which was a differentiating category scale. Results:: The results of the classification data in the models of the individual and familial risk factors of OSA have a suitable value of 95.2% and 80.5%(> 75%), respectively. Meanwhile, the results of data classification in the OSA incidence model have a good suitability value of 62.5%(> 50%). The predictive probability data was used to predict the incidence of preeclampsia. The results of the data classification in the Preeclampsia incidence model have a good suitability value of 74.3%(> 50%).The OSA model is an appropriate, cheap, and easy screening in predicting the incidence of preeclampsia.

Item Type:	Article
Subjects:	R Medicine > RT Nursing
Divisions:	Faculty of Medicine, Health and Life Sciences > School of Medicine
Depositing User:	Unnamed user with email libstikesmajapahit@gmail.com
Date Deposited:	11 May 2023 03:02
Last Modified:	12 May 2023 04:27
URI:	http://repo.stikesmajapahit.ac.id/id/eprint/298

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