A novel clinical prediction model of severity based on red cell distribution width, neutrophil-lymphocyte ratio and intra-abdominal pressure in acute pancreatitis in pregnancy
Abstract Background Acute pancreatitis in pregnancy (APIP) with a high risk of death is extremely harmful to mother and fetus. There are few models specifically designed to assess the severity of APIP. Our study aimed to establish a clinical model for early prediction of severity of APIP. Methods A...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-03-01
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| Series: | BMC Pregnancy and Childbirth |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12884-023-05500-0 |
| _version_ | 1797863253039120384 |
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| author | Wenyan Liao Guangwei Tao Guodong Chen Jun He Chunfen Yang Xiaohua Lei Shuo Qi Jiafeng Hou Yi Xie Can Feng Xinmiao Jiang Xin Deng Chengming Ding |
| author_facet | Wenyan Liao Guangwei Tao Guodong Chen Jun He Chunfen Yang Xiaohua Lei Shuo Qi Jiafeng Hou Yi Xie Can Feng Xinmiao Jiang Xin Deng Chengming Ding |
| author_sort | Wenyan Liao |
| collection | DOAJ |
| description | Abstract Background Acute pancreatitis in pregnancy (APIP) with a high risk of death is extremely harmful to mother and fetus. There are few models specifically designed to assess the severity of APIP. Our study aimed to establish a clinical model for early prediction of severity of APIP. Methods A retrospective study in a total of 188 patients with APIP was enrolled. The hematological indicators, IAP (intra-abdominal pressure) and clinical data were obtained for statistical analysis and prediction model construction. Results According to univariate and multivariate logistic regression analysis, we found that red cell distribution width (RDW), neutrophil-lymphocyte ratio (NLR) and Intra-abdominal pressure (IAP) are prediction indexes of the severity in APIP (p-value < 0.05). Our novel clinical prediction model was created by based on the above three risk factors and showed superior predictive power in primary cohort (AUC = 0.895) and validation cohort (AUC = 0.863). A nomogram for severe acute pancreatitis in pregnancy (SAPIP) was created based on the three indicators. The nomogram was well-calibrated. Conclusion RDW, NLR and IAP were the independent risk factors of APIP. Our clinical prediction model of severity in APIP based on RDW, NLR and IAP with predictive evaluation is accurate and effective. |
| first_indexed | 2024-04-09T22:32:35Z |
| format | Article |
| id | doaj.art-30094acafd6641ba81371f3ccc874030 |
| institution | Directory Open Access Journal |
| issn | 1471-2393 |
| language | English |
| last_indexed | 2024-04-09T22:32:35Z |
| publishDate | 2023-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Pregnancy and Childbirth |
| spelling | doaj.art-30094acafd6641ba81371f3ccc8740302023-03-22T12:39:08ZengBMCBMC Pregnancy and Childbirth1471-23932023-03-0123111110.1186/s12884-023-05500-0A novel clinical prediction model of severity based on red cell distribution width, neutrophil-lymphocyte ratio and intra-abdominal pressure in acute pancreatitis in pregnancyWenyan Liao0Guangwei Tao1Guodong Chen2Jun He3Chunfen Yang4Xiaohua Lei5Shuo Qi6Jiafeng Hou7Yi Xie8Can Feng9Xinmiao Jiang10Xin Deng11Chengming Ding12The First Affiliated Hospital, Department of Gynaecology and Obstetrics, Hengyang Medical School, University of South ChinaThe First Affiliated Hospital, Department of Hepatopancreatobiliary Surgery, Hengyang Medical School, University of South ChinaThe First Affiliated Hospital, Department of Hepatopancreatobiliary Surgery, Hengyang Medical School, University of South ChinaThe Nanhua Affiliated Hospital, Hengyang Medical School, University of South ChinaThe First Affiliated Hospital, Department of Gynaecology and Obstetrics, Hengyang Medical School, University of South ChinaThe First Affiliated Hospital, Department of Hepatopancreatobiliary Surgery, Hengyang Medical School, University of South ChinaThe First Affiliated Hospital, Department of Hepatopancreatobiliary Surgery, Hengyang Medical School, University of South ChinaThe First Affiliated Hospital, Department of Hepatopancreatobiliary Surgery, Hengyang Medical School, University of South ChinaThe First Affiliated Hospital, Department of Hepatopancreatobiliary Surgery, Hengyang Medical School, University of South ChinaThe First Affiliated Hospital, Department of Hepatopancreatobiliary Surgery, Hengyang Medical School, University of South ChinaThe First Affiliated Hospital, Department of Hepatopancreatobiliary Surgery, Hengyang Medical School, University of South ChinaThe First Affiliated Hospital, Department of Hepatopancreatobiliary Surgery, Hengyang Medical School, University of South ChinaThe First Affiliated Hospital, Department of Hepatopancreatobiliary Surgery, Hengyang Medical School, University of South ChinaAbstract Background Acute pancreatitis in pregnancy (APIP) with a high risk of death is extremely harmful to mother and fetus. There are few models specifically designed to assess the severity of APIP. Our study aimed to establish a clinical model for early prediction of severity of APIP. Methods A retrospective study in a total of 188 patients with APIP was enrolled. The hematological indicators, IAP (intra-abdominal pressure) and clinical data were obtained for statistical analysis and prediction model construction. Results According to univariate and multivariate logistic regression analysis, we found that red cell distribution width (RDW), neutrophil-lymphocyte ratio (NLR) and Intra-abdominal pressure (IAP) are prediction indexes of the severity in APIP (p-value < 0.05). Our novel clinical prediction model was created by based on the above three risk factors and showed superior predictive power in primary cohort (AUC = 0.895) and validation cohort (AUC = 0.863). A nomogram for severe acute pancreatitis in pregnancy (SAPIP) was created based on the three indicators. The nomogram was well-calibrated. Conclusion RDW, NLR and IAP were the independent risk factors of APIP. Our clinical prediction model of severity in APIP based on RDW, NLR and IAP with predictive evaluation is accurate and effective.https://doi.org/10.1186/s12884-023-05500-0Acute pancreatitis in pregnancyInflammationRed cell distribution widthNeutrophil-lymphocyte ratioIntra-abdominal pressurePrediction model |
| spellingShingle | Wenyan Liao Guangwei Tao Guodong Chen Jun He Chunfen Yang Xiaohua Lei Shuo Qi Jiafeng Hou Yi Xie Can Feng Xinmiao Jiang Xin Deng Chengming Ding A novel clinical prediction model of severity based on red cell distribution width, neutrophil-lymphocyte ratio and intra-abdominal pressure in acute pancreatitis in pregnancy BMC Pregnancy and Childbirth Acute pancreatitis in pregnancy Inflammation Red cell distribution width Neutrophil-lymphocyte ratio Intra-abdominal pressure Prediction model |
| title | A novel clinical prediction model of severity based on red cell distribution width, neutrophil-lymphocyte ratio and intra-abdominal pressure in acute pancreatitis in pregnancy |
| title_full | A novel clinical prediction model of severity based on red cell distribution width, neutrophil-lymphocyte ratio and intra-abdominal pressure in acute pancreatitis in pregnancy |
| title_fullStr | A novel clinical prediction model of severity based on red cell distribution width, neutrophil-lymphocyte ratio and intra-abdominal pressure in acute pancreatitis in pregnancy |
| title_full_unstemmed | A novel clinical prediction model of severity based on red cell distribution width, neutrophil-lymphocyte ratio and intra-abdominal pressure in acute pancreatitis in pregnancy |
| title_short | A novel clinical prediction model of severity based on red cell distribution width, neutrophil-lymphocyte ratio and intra-abdominal pressure in acute pancreatitis in pregnancy |
| title_sort | novel clinical prediction model of severity based on red cell distribution width neutrophil lymphocyte ratio and intra abdominal pressure in acute pancreatitis in pregnancy |
| topic | Acute pancreatitis in pregnancy Inflammation Red cell distribution width Neutrophil-lymphocyte ratio Intra-abdominal pressure Prediction model |
| url | https://doi.org/10.1186/s12884-023-05500-0 |
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