Abstract

Introduction: 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. Methods: 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%). Conclusion: The OSA model is an appropriate, cheap, and easy screening in predicting the incidence of preeclampsia.

Original languageEnglish
Pages (from-to)36-41
Number of pages6
JournalMalaysian Journal of Medicine and Health Sciences
Volume18
Publication statusPublished - Oct 2022

Keywords

  • OSA
  • Peeclampsia
  • Predictor
  • Pregnancy
  • Risk Factor

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