Prediction Model for Pre-Eclampsia Using Gestational-Age-Specific Serum Creatinine Distribution
Pre-eclampsia (PE) is a pregnancy-related disease, causing significant threats to both mothers and babies. Numerous studies have identified the association between PE and renal dysfunction. However, in clinical practice, kidney problems in pregnant women are often overlooked due to physiologic adapt...
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MDPI AG
2023-06-01
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| Online Access: | https://www.mdpi.com/2079-7737/12/6/816 |
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| author | Jieun Kang Sangwon Hwang Taesic Lee Kwangjin Ahn Dong Min Seo Seong Jin Choi Young Uh |
| author_facet | Jieun Kang Sangwon Hwang Taesic Lee Kwangjin Ahn Dong Min Seo Seong Jin Choi Young Uh |
| author_sort | Jieun Kang |
| collection | DOAJ |
| description | Pre-eclampsia (PE) is a pregnancy-related disease, causing significant threats to both mothers and babies. Numerous studies have identified the association between PE and renal dysfunction. However, in clinical practice, kidney problems in pregnant women are often overlooked due to physiologic adaptations during pregnancy, including renal hyperfiltration. Recent studies have reported serum creatinine (SCr) level distribution based on gestational age (GA) and demonstrated that deviations from the expected patterns can predict adverse pregnancy outcomes, including PE. This study aimed to establish a PE prediction model using expert knowledge and by considering renal physiologic adaptation during pregnancy. This retrospective study included pregnant women who delivered at the Wonju Severance Christian Hospital. Input variables, such as age, gestational weeks, chronic diseases, and SCr levels, were used to establish the PE prediction model. By integrating SCr, GA, GA-specific SCr distribution, and quartile groups of GA-specific SCr (GAQ) were made. To provide generalized performance, a random sampling method was used. As a result, GAQ improved the predictive performance for any cases of PE and triple cases, including PE, preterm birth, and fetal growth restriction. We propose a prediction model for PE consolidating readily available clinical blood test information and pregnancy-related renal physiologic adaptations. |
| first_indexed | 2024-03-11T02:44:45Z |
| format | Article |
| id | doaj.art-67dc4673a72f43b1b3ec0eea6828af38 |
| institution | Directory Open Access Journal |
| issn | 2079-7737 |
| language | English |
| last_indexed | 2024-03-11T02:44:45Z |
| publishDate | 2023-06-01 |
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| spelling | doaj.art-67dc4673a72f43b1b3ec0eea6828af382023-11-18T09:22:58ZengMDPI AGBiology2079-77372023-06-0112681610.3390/biology12060816Prediction Model for Pre-Eclampsia Using Gestational-Age-Specific Serum Creatinine DistributionJieun Kang0Sangwon Hwang1Taesic Lee2Kwangjin Ahn3Dong Min Seo4Seong Jin Choi5Young Uh6Department of Obstetrics and Gynecology, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of KoreaDepartment of Precision Medicine, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of KoreaDivision of Data-Mining and Computational Biology, Institute of Global Health Care and Development, Wonju 26426, Republic of KoreaDepartment of Laboratory Medicine, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of KoreaDepartment of Medical Information, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of KoreaDepartment of Obstetrics and Gynecology, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of KoreaDepartment of Laboratory Medicine, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of KoreaPre-eclampsia (PE) is a pregnancy-related disease, causing significant threats to both mothers and babies. Numerous studies have identified the association between PE and renal dysfunction. However, in clinical practice, kidney problems in pregnant women are often overlooked due to physiologic adaptations during pregnancy, including renal hyperfiltration. Recent studies have reported serum creatinine (SCr) level distribution based on gestational age (GA) and demonstrated that deviations from the expected patterns can predict adverse pregnancy outcomes, including PE. This study aimed to establish a PE prediction model using expert knowledge and by considering renal physiologic adaptation during pregnancy. This retrospective study included pregnant women who delivered at the Wonju Severance Christian Hospital. Input variables, such as age, gestational weeks, chronic diseases, and SCr levels, were used to establish the PE prediction model. By integrating SCr, GA, GA-specific SCr distribution, and quartile groups of GA-specific SCr (GAQ) were made. To provide generalized performance, a random sampling method was used. As a result, GAQ improved the predictive performance for any cases of PE and triple cases, including PE, preterm birth, and fetal growth restriction. We propose a prediction model for PE consolidating readily available clinical blood test information and pregnancy-related renal physiologic adaptations.https://www.mdpi.com/2079-7737/12/6/816pre-eclampsiapregnancycreatininegestational agerenal hyperfiltration |
| spellingShingle | Jieun Kang Sangwon Hwang Taesic Lee Kwangjin Ahn Dong Min Seo Seong Jin Choi Young Uh Prediction Model for Pre-Eclampsia Using Gestational-Age-Specific Serum Creatinine Distribution Biology pre-eclampsia pregnancy creatinine gestational age renal hyperfiltration |
| title | Prediction Model for Pre-Eclampsia Using Gestational-Age-Specific Serum Creatinine Distribution |
| title_full | Prediction Model for Pre-Eclampsia Using Gestational-Age-Specific Serum Creatinine Distribution |
| title_fullStr | Prediction Model for Pre-Eclampsia Using Gestational-Age-Specific Serum Creatinine Distribution |
| title_full_unstemmed | Prediction Model for Pre-Eclampsia Using Gestational-Age-Specific Serum Creatinine Distribution |
| title_short | Prediction Model for Pre-Eclampsia Using Gestational-Age-Specific Serum Creatinine Distribution |
| title_sort | prediction model for pre eclampsia using gestational age specific serum creatinine distribution |
| topic | pre-eclampsia pregnancy creatinine gestational age renal hyperfiltration |
| url | https://www.mdpi.com/2079-7737/12/6/816 |
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