A Multicentric Study on Adverse COVID-19 Outcomes Among Pregnant and Nonpregnant Women in Multidisciplinary Hospitals of Kazakhstan.

Abstract

The study aimed at identification and analysis of adverse COVID-19 outcomes (admission to intensive care units due to COVID-19, acute respiratory distress syndrome, mechanical ventilation, and death) among hospitalized pregnant and nonpregnant women, which are critical for informed decision-making in obstetric diagnostics and healthcare. This was a retrospective observational study conducted on a series of inpatient pregnant women comparatively followed up with nonpregnant women hospitalized between 15 July 2020 to 20 January 2022 across multidisciplinary hospitals in three cities of Kazakhstan. Following group matching with propensity score for COVID-19 disease severity, residence status, and age, the study ultimately included 156 participants, of whom 50% were pregnant, from an initial sample of 314 female inpatients diagnosed with COVID-19. All findings were considered statistically significant at a -value < 0.05. Laboratory investigations revealed significantly elevated levels of erythrocyte sedimentation rate, creatinine, neutrophils, platelet count, alanine aminotransferase, aspartate aminotransferase, lymphocyte count, and C-reactive protein in pregnant inpatients compared to nonpregnant inpatients. Furthermore, pregnant women exhibited significantly higher levels of D-dimer (2402.97 ng/mL vs. 793.91 ng/mL) and procalcitonin (0.398 ng/mL vs. 0.134 ng/mL) compared to their nonpregnant counterparts. Overall, 16.88% of the pregnant women were admitted to the intensive care unit, whereas among the nonpregnant women, only 2.6% were hospitalized. The most lethal outcomes (8.3%) occurred among pregnant women, while for nonpregnant women, there were two cases (1.3%). Pregnant women diagnosed with COVID-19 may exhibit more severe clinical symptoms and encounter more adverse outcomes compared to their nonpregnant counterparts. Future research should incorporate larger matched samples to comprehensively explore the association between additional factors and clinical conditions.