Characterization of COVID-19 infected pregnant women with ICU admission and the risk of preterm: A cluster analysis
Background: The unique physiological changes during pregnancy present challenges in understanding the full scope and effects of COVID-19 on pregnant women, adding complexity to their medical management. Given the significant changes in the immune, circulatory, respiratory, and hormonal systems durin...
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Elsevier
2024-12-01
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| Series: | Journal of Infection and Public Health |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S187603412400306X |
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| author | Antonio Sarria-Santamera Nurly Kapashova Radmir Sarsenov Kymbat Mukhtarova Aigerim Sipenova Milan Terzic Gauri Bapayeva Asselzhan Sarbalina Saule Zhumambayeva Kamalzhan Nadyrov Karina Tazhibayeva Kulyash K. Jaxalykova Aigul Myrzabekova Zaituna Khamidullina |
| author_facet | Antonio Sarria-Santamera Nurly Kapashova Radmir Sarsenov Kymbat Mukhtarova Aigerim Sipenova Milan Terzic Gauri Bapayeva Asselzhan Sarbalina Saule Zhumambayeva Kamalzhan Nadyrov Karina Tazhibayeva Kulyash K. Jaxalykova Aigul Myrzabekova Zaituna Khamidullina |
| author_sort | Antonio Sarria-Santamera |
| collection | DOAJ |
| description | Background: The unique physiological changes during pregnancy present challenges in understanding the full scope and effects of COVID-19 on pregnant women, adding complexity to their medical management. Given the significant changes in the immune, circulatory, respiratory, and hormonal systems during the progression of the pregnancy, and the specific factors with higher risk of COVID-19, like metabolic, vascular, and endothelial factors, typically also associated with maternal and neonatal unfavorable outcomes, the full understanding of how COVID-19 affects pregnant women is not clarified yet. Methods: In this study, anonymous data from medical records of pregnant women with lab-confirmed COVID‐19 in Astana, Kazakhstan from May 1, 2021, to July 14, 2021, were collected retrospectively. A multivariate regression model was built to identify factors associated with the risk of ICU admission. Cluster analysis was performed to identify distinct groups among women admitted to the ICU based on their blood parameters, coagulation profiles, and oxygenation saturation levels. Results: 10.7 % of pregnant women were admitted to ICU. Among them, 4.36 % were in the 2nd trimester and 13.58 % in the 3rd trimester. No women in the 1st trimester were admitted to ICU. A multivariate regression model demonstrates that gestational diabetes, leukocytes, CRP, and saturation were the factors significantly associated with a higher risk of ICU admission. Three clusters of pregnant women were segmented, and preterm birth was frequent in clusters 1 (serious systemic conditions affecting multiple organs) and 3 (women with hypertension and preeclampsia), whereas cluster 2 represents women who can also be characterized as suffering from infections with a possible autoimmune component. Neutrophil to lymphocyte ratio was frequent in clusters 1 and 3. Conclusion: In this study, multivariable analysis identified factors with a risk of ICU admission, and clustering analysis helped to identify groups of COVID-19-infected pregnant women admitted to ICU with similar risk profiles. Differences in clusters can help to explain discrepancies in COVID-19 outcomes and suggest biochemical and molecular mechanisms involved in COVID-19 and outline a more personalized approach to understanding, diagnosing, and treating women. |
| format | Article |
| id | doaj-art-538fde1535464053956ce69c0f9f5001 |
| institution | Kabale University |
| issn | 1876-0341 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Infection and Public Health |
| spelling | doaj-art-538fde1535464053956ce69c0f9f50012024-11-27T05:02:03ZengElsevierJournal of Infection and Public Health1876-03412024-12-011712102572Characterization of COVID-19 infected pregnant women with ICU admission and the risk of preterm: A cluster analysisAntonio Sarria-Santamera0Nurly Kapashova1Radmir Sarsenov2Kymbat Mukhtarova3Aigerim Sipenova4Milan Terzic5Gauri Bapayeva6Asselzhan Sarbalina7Saule Zhumambayeva8Kamalzhan Nadyrov9Karina Tazhibayeva10Kulyash K. Jaxalykova11Aigul Myrzabekova12Zaituna Khamidullina13Department of Biomedical Sciences, School of Medicine, Nazarbayev University, Astana, Kazakhstan; Correspondence to: Department of Biomedical Sciences, Nazarbayev University School of Medicine, Astana, Kazakhstan.School of Sciences and Humanities, Nazarbayev University, Astana, KazakhstanSchool of Sciences and Humanities, Nazarbayev University, Astana, KazakhstanDepartment of Biomedical Sciences, School of Medicine, Nazarbayev University, Astana, KazakhstanDepartment of Biomedical Sciences, School of Medicine, Nazarbayev University, Astana, KazakhstanDepartment of Biomedical Sciences, School of Medicine, Nazarbayev University, Astana, KazakhstanClinical Academic Department of Women’s Health, Corporate Fund “University Medical Center”, Astana, KazakhstanNuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, England, UKAstana Medical University, Astana, KazakhstanAstana Medical University, Astana, KazakhstanAstana Medical University, Astana, KazakhstanAstana Medical University, Astana, KazakhstanAstana Medical University, Astana, KazakhstanAstana Medical University, Astana, KazakhstanBackground: The unique physiological changes during pregnancy present challenges in understanding the full scope and effects of COVID-19 on pregnant women, adding complexity to their medical management. Given the significant changes in the immune, circulatory, respiratory, and hormonal systems during the progression of the pregnancy, and the specific factors with higher risk of COVID-19, like metabolic, vascular, and endothelial factors, typically also associated with maternal and neonatal unfavorable outcomes, the full understanding of how COVID-19 affects pregnant women is not clarified yet. Methods: In this study, anonymous data from medical records of pregnant women with lab-confirmed COVID‐19 in Astana, Kazakhstan from May 1, 2021, to July 14, 2021, were collected retrospectively. A multivariate regression model was built to identify factors associated with the risk of ICU admission. Cluster analysis was performed to identify distinct groups among women admitted to the ICU based on their blood parameters, coagulation profiles, and oxygenation saturation levels. Results: 10.7 % of pregnant women were admitted to ICU. Among them, 4.36 % were in the 2nd trimester and 13.58 % in the 3rd trimester. No women in the 1st trimester were admitted to ICU. A multivariate regression model demonstrates that gestational diabetes, leukocytes, CRP, and saturation were the factors significantly associated with a higher risk of ICU admission. Three clusters of pregnant women were segmented, and preterm birth was frequent in clusters 1 (serious systemic conditions affecting multiple organs) and 3 (women with hypertension and preeclampsia), whereas cluster 2 represents women who can also be characterized as suffering from infections with a possible autoimmune component. Neutrophil to lymphocyte ratio was frequent in clusters 1 and 3. Conclusion: In this study, multivariable analysis identified factors with a risk of ICU admission, and clustering analysis helped to identify groups of COVID-19-infected pregnant women admitted to ICU with similar risk profiles. Differences in clusters can help to explain discrepancies in COVID-19 outcomes and suggest biochemical and molecular mechanisms involved in COVID-19 and outline a more personalized approach to understanding, diagnosing, and treating women.http://www.sciencedirect.com/science/article/pii/S187603412400306XCOVID-19Pregnant womenCluster analysisICU admissionPreterm birth |
| spellingShingle | Antonio Sarria-Santamera Nurly Kapashova Radmir Sarsenov Kymbat Mukhtarova Aigerim Sipenova Milan Terzic Gauri Bapayeva Asselzhan Sarbalina Saule Zhumambayeva Kamalzhan Nadyrov Karina Tazhibayeva Kulyash K. Jaxalykova Aigul Myrzabekova Zaituna Khamidullina Characterization of COVID-19 infected pregnant women with ICU admission and the risk of preterm: A cluster analysis Journal of Infection and Public Health COVID-19 Pregnant women Cluster analysis ICU admission Preterm birth |
| title | Characterization of COVID-19 infected pregnant women with ICU admission and the risk of preterm: A cluster analysis |
| title_full | Characterization of COVID-19 infected pregnant women with ICU admission and the risk of preterm: A cluster analysis |
| title_fullStr | Characterization of COVID-19 infected pregnant women with ICU admission and the risk of preterm: A cluster analysis |
| title_full_unstemmed | Characterization of COVID-19 infected pregnant women with ICU admission and the risk of preterm: A cluster analysis |
| title_short | Characterization of COVID-19 infected pregnant women with ICU admission and the risk of preterm: A cluster analysis |
| title_sort | characterization of covid 19 infected pregnant women with icu admission and the risk of preterm a cluster analysis |
| topic | COVID-19 Pregnant women Cluster analysis ICU admission Preterm birth |
| url | http://www.sciencedirect.com/science/article/pii/S187603412400306X |
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