Establishment of a nomogram model for predicting adverse outcomes in advanced-age pregnant women with preterm preeclampsia
Abstract Aim To establish a model for predicting adverse outcomes in advanced-age pregnant women with preterm preeclampsia in China. Methods We retrospectively collected the medical records of 896 pregnant women with preterm preeclampsia who were older than 35 years and delivered at the Affiliated H...
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| Format: | Article |
| Language: | English |
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BMC
2022-03-01
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| Series: | BMC Pregnancy and Childbirth |
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| Online Access: | https://doi.org/10.1186/s12884-022-04537-x |
| _version_ | 1818773666034352128 |
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| author | Bohan Lv Yan Zhang Guanghui Yuan Ruting Gu Jingyuan Wang Yujiao Zou Lili Wei |
| author_facet | Bohan Lv Yan Zhang Guanghui Yuan Ruting Gu Jingyuan Wang Yujiao Zou Lili Wei |
| author_sort | Bohan Lv |
| collection | DOAJ |
| description | Abstract Aim To establish a model for predicting adverse outcomes in advanced-age pregnant women with preterm preeclampsia in China. Methods We retrospectively collected the medical records of 896 pregnant women with preterm preeclampsia who were older than 35 years and delivered at the Affiliated Hospital of Qingdao University from June 2018 to December 2020. The pregnant women were divided into an adverse outcome group and a non-adverse outcome group according to the occurrence of adverse outcomes. The data were divided into a training set and a verification set at a ratio of 8:2. A nomogram model was developed according to a binary logistic regression model created to predict the adverse outcomes in advanced-age pregnant women with preterm preeclampsia. ROC curves and their AUCs were used to evaluate the predictive ability of the model. The model was internally verified by using 1000 bootstrap samples, and a calibration diagram was drawn. Results Binary logistic regression analysis showed that platelet count (PLT), uric acid (UA), blood urea nitrogen (BUN), prothrombin time (PT), and lactate dehydrogenase (LDH) were the factors that independently influenced adverse outcomes (P < 0.05). The AUCs of the internal and external verification of the model were 0.788 (95% CI: 0.737 ~ 0.764) and 0.742 (95% CI: 0.565 ~ 0.847), respectively. The calibration curve was close to the diagonal. Conclusions The model we constructed can accurately predict the risk of adverse outcomes of pregnant women of advanced age with preterm preeclampsia, providing corresponding guidance and serving as a basis for preventing adverse outcomes and improving clinical treatment and maternal and infant prognosis. |
| first_indexed | 2024-12-18T10:28:52Z |
| format | Article |
| id | doaj.art-e6f5b38f53c141ec9df83dffbf8ef294 |
| institution | Directory Open Access Journal |
| issn | 1471-2393 |
| language | English |
| last_indexed | 2024-12-18T10:28:52Z |
| publishDate | 2022-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Pregnancy and Childbirth |
| spelling | doaj.art-e6f5b38f53c141ec9df83dffbf8ef2942022-12-21T21:10:56ZengBMCBMC Pregnancy and Childbirth1471-23932022-03-012211910.1186/s12884-022-04537-xEstablishment of a nomogram model for predicting adverse outcomes in advanced-age pregnant women with preterm preeclampsiaBohan Lv0Yan Zhang1Guanghui Yuan2Ruting Gu3Jingyuan Wang4Yujiao Zou5Lili Wei6School of Nursing, Qingdao UniversityDepartment of Nursing, The Affiliated Hospital of Qingdao UniversityMedical College of Qingdao UniversityDepartment of Nursing, The Affiliated Hospital of Qingdao UniversityDepartment of Respiratory and Critical Care Medicine, The Affiliated Hospital of Qingdao UniversitySchool of Nursing, Qingdao UniversityDepartment of Nursing, The Affiliated Hospital of Qingdao UniversityAbstract Aim To establish a model for predicting adverse outcomes in advanced-age pregnant women with preterm preeclampsia in China. Methods We retrospectively collected the medical records of 896 pregnant women with preterm preeclampsia who were older than 35 years and delivered at the Affiliated Hospital of Qingdao University from June 2018 to December 2020. The pregnant women were divided into an adverse outcome group and a non-adverse outcome group according to the occurrence of adverse outcomes. The data were divided into a training set and a verification set at a ratio of 8:2. A nomogram model was developed according to a binary logistic regression model created to predict the adverse outcomes in advanced-age pregnant women with preterm preeclampsia. ROC curves and their AUCs were used to evaluate the predictive ability of the model. The model was internally verified by using 1000 bootstrap samples, and a calibration diagram was drawn. Results Binary logistic regression analysis showed that platelet count (PLT), uric acid (UA), blood urea nitrogen (BUN), prothrombin time (PT), and lactate dehydrogenase (LDH) were the factors that independently influenced adverse outcomes (P < 0.05). The AUCs of the internal and external verification of the model were 0.788 (95% CI: 0.737 ~ 0.764) and 0.742 (95% CI: 0.565 ~ 0.847), respectively. The calibration curve was close to the diagonal. Conclusions The model we constructed can accurately predict the risk of adverse outcomes of pregnant women of advanced age with preterm preeclampsia, providing corresponding guidance and serving as a basis for preventing adverse outcomes and improving clinical treatment and maternal and infant prognosis.https://doi.org/10.1186/s12884-022-04537-xPreterm preeclampsiaAdvanced age pregnant womenNomogramPrediction model |
| spellingShingle | Bohan Lv Yan Zhang Guanghui Yuan Ruting Gu Jingyuan Wang Yujiao Zou Lili Wei Establishment of a nomogram model for predicting adverse outcomes in advanced-age pregnant women with preterm preeclampsia BMC Pregnancy and Childbirth Preterm preeclampsia Advanced age pregnant women Nomogram Prediction model |
| title | Establishment of a nomogram model for predicting adverse outcomes in advanced-age pregnant women with preterm preeclampsia |
| title_full | Establishment of a nomogram model for predicting adverse outcomes in advanced-age pregnant women with preterm preeclampsia |
| title_fullStr | Establishment of a nomogram model for predicting adverse outcomes in advanced-age pregnant women with preterm preeclampsia |
| title_full_unstemmed | Establishment of a nomogram model for predicting adverse outcomes in advanced-age pregnant women with preterm preeclampsia |
| title_short | Establishment of a nomogram model for predicting adverse outcomes in advanced-age pregnant women with preterm preeclampsia |
| title_sort | establishment of a nomogram model for predicting adverse outcomes in advanced age pregnant women with preterm preeclampsia |
| topic | Preterm preeclampsia Advanced age pregnant women Nomogram Prediction model |
| url | https://doi.org/10.1186/s12884-022-04537-x |
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