Establishment and Validation of a Nomogram Prediction Model for the Severe Acute Pancreatitis
Bo Li,1 Weiqing Wu,1 Aijun Liu,1 Lifeng Feng,1 Bin Li,1 Yong Mei,1 Li Tan,1 Chaoyang Zhang,2 Yangtao Tian1 1Department of Pancreatic Surgery, Shangluo Center Hospital, Shangluo, Shaanxi, 726000, People’s Republic of China; 2Department of Ultrasound Medicine, Shangluo Center Hospital, Shangluo, Shaan...
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| Language: | English |
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Dove Medical Press
2023-07-01
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| Series: | Journal of Inflammation Research |
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| Online Access: | https://www.dovepress.com/establishment-and-validation-of-a-nomogram-prediction-model-for-the-se-peer-reviewed-fulltext-article-JIR |
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| author | Li B Wu W Liu A Feng L Li B Mei Y Tan L Zhang C Tian Y |
| author_facet | Li B Wu W Liu A Feng L Li B Mei Y Tan L Zhang C Tian Y |
| author_sort | Li B |
| collection | DOAJ |
| description | Bo Li,1 Weiqing Wu,1 Aijun Liu,1 Lifeng Feng,1 Bin Li,1 Yong Mei,1 Li Tan,1 Chaoyang Zhang,2 Yangtao Tian1 1Department of Pancreatic Surgery, Shangluo Center Hospital, Shangluo, Shaanxi, 726000, People’s Republic of China; 2Department of Ultrasound Medicine, Shangluo Center Hospital, Shangluo, Shaanxi, 726000, People’s Republic of ChinaCorrespondence: Yangtao Tian, Department of Pancreatic Surgery, Shangluo Center Hospital, 37 Shangyang, Shangzhou, Shangluo, Shaanxi, 726000, People’s Republic of China, Email 928763821@qq.comBackground: Severe acute pancreatitis (SAP) can progress to lung and kidney dysfunction, and blood clotting within 48 hours of its onset, and is associated with a high mortality rate. The aim of this study was to establish a reliable diagnostic prediction model for the early stage of severe pancreatitis.Methods: The clinical data of patients diagnosed with acute pancreatitis from October 2017 to June 2022 at the Shangluo Central Hospital were collected. The risk factors were screened by least absolute shrinkage and selection operator (LASSO) regression analysis. A novel nomogram model was then established by multivariable logistic regression analysis.Results: The data of 436 patients with acute pancreatitis, 45 (10.3%) patients had progressed to SAP. Through univariate and LASSO regression analyses, the neutrophils (P < 0.001), albumin (P < 0.001), blood glucose (P < 0.001), serum calcium (P < 0.001), serum creatinine (P < 0.001), blood urea nitrogen (P < 0.001) and procalcitonin (P = 0.005) were identified as independent predictive factors for SAP. The nomogram built on the basis of these factors predicted SAP with sensitivity of 0.733, specificity of 0.9, positive predictive value of 0.458 and negative predictive value of 0.967. Furthermore, the concordance index of the nomogram reached 0.889 (95% CI, 0.837– 0.941), and the area under the curve (AUC) in receiver operating characteristic curve (ROC) analysis was significantly higher than that of the APACHEII and ABISAP scoring systems. The established model was validated by plotting the clinical decision curve analysis (DCA) and clinical impact curve (CIC).Conclusion: We established a nomogram to predict the progression of early acute pancreatitis to SAP with high discrimination and accuracy.Keywords: acute pancreatitis, prediction model, risk factor, nomogram, decision curve analysis |
| first_indexed | 2024-03-13T00:37:18Z |
| format | Article |
| id | doaj.art-ee5b96a84a284ca29e32313ef7e927e7 |
| institution | Directory Open Access Journal |
| issn | 1178-7031 |
| language | English |
| last_indexed | 2024-03-13T00:37:18Z |
| publishDate | 2023-07-01 |
| publisher | Dove Medical Press |
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| series | Journal of Inflammation Research |
| spelling | doaj.art-ee5b96a84a284ca29e32313ef7e927e72023-07-09T19:03:31ZengDove Medical PressJournal of Inflammation Research1178-70312023-07-01Volume 162831284385008Establishment and Validation of a Nomogram Prediction Model for the Severe Acute PancreatitisLi BWu WLiu AFeng LLi BMei YTan LZhang CTian YBo Li,1 Weiqing Wu,1 Aijun Liu,1 Lifeng Feng,1 Bin Li,1 Yong Mei,1 Li Tan,1 Chaoyang Zhang,2 Yangtao Tian1 1Department of Pancreatic Surgery, Shangluo Center Hospital, Shangluo, Shaanxi, 726000, People’s Republic of China; 2Department of Ultrasound Medicine, Shangluo Center Hospital, Shangluo, Shaanxi, 726000, People’s Republic of ChinaCorrespondence: Yangtao Tian, Department of Pancreatic Surgery, Shangluo Center Hospital, 37 Shangyang, Shangzhou, Shangluo, Shaanxi, 726000, People’s Republic of China, Email 928763821@qq.comBackground: Severe acute pancreatitis (SAP) can progress to lung and kidney dysfunction, and blood clotting within 48 hours of its onset, and is associated with a high mortality rate. The aim of this study was to establish a reliable diagnostic prediction model for the early stage of severe pancreatitis.Methods: The clinical data of patients diagnosed with acute pancreatitis from October 2017 to June 2022 at the Shangluo Central Hospital were collected. The risk factors were screened by least absolute shrinkage and selection operator (LASSO) regression analysis. A novel nomogram model was then established by multivariable logistic regression analysis.Results: The data of 436 patients with acute pancreatitis, 45 (10.3%) patients had progressed to SAP. Through univariate and LASSO regression analyses, the neutrophils (P < 0.001), albumin (P < 0.001), blood glucose (P < 0.001), serum calcium (P < 0.001), serum creatinine (P < 0.001), blood urea nitrogen (P < 0.001) and procalcitonin (P = 0.005) were identified as independent predictive factors for SAP. The nomogram built on the basis of these factors predicted SAP with sensitivity of 0.733, specificity of 0.9, positive predictive value of 0.458 and negative predictive value of 0.967. Furthermore, the concordance index of the nomogram reached 0.889 (95% CI, 0.837– 0.941), and the area under the curve (AUC) in receiver operating characteristic curve (ROC) analysis was significantly higher than that of the APACHEII and ABISAP scoring systems. The established model was validated by plotting the clinical decision curve analysis (DCA) and clinical impact curve (CIC).Conclusion: We established a nomogram to predict the progression of early acute pancreatitis to SAP with high discrimination and accuracy.Keywords: acute pancreatitis, prediction model, risk factor, nomogram, decision curve analysishttps://www.dovepress.com/establishment-and-validation-of-a-nomogram-prediction-model-for-the-se-peer-reviewed-fulltext-article-JIRacute pancreatitisprediction modelrisk factornomogramdecision curve analysis |
| spellingShingle | Li B Wu W Liu A Feng L Li B Mei Y Tan L Zhang C Tian Y Establishment and Validation of a Nomogram Prediction Model for the Severe Acute Pancreatitis Journal of Inflammation Research acute pancreatitis prediction model risk factor nomogram decision curve analysis |
| title | Establishment and Validation of a Nomogram Prediction Model for the Severe Acute Pancreatitis |
| title_full | Establishment and Validation of a Nomogram Prediction Model for the Severe Acute Pancreatitis |
| title_fullStr | Establishment and Validation of a Nomogram Prediction Model for the Severe Acute Pancreatitis |
| title_full_unstemmed | Establishment and Validation of a Nomogram Prediction Model for the Severe Acute Pancreatitis |
| title_short | Establishment and Validation of a Nomogram Prediction Model for the Severe Acute Pancreatitis |
| title_sort | establishment and validation of a nomogram prediction model for the severe acute pancreatitis |
| topic | acute pancreatitis prediction model risk factor nomogram decision curve analysis |
| url | https://www.dovepress.com/establishment-and-validation-of-a-nomogram-prediction-model-for-the-se-peer-reviewed-fulltext-article-JIR |
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