Construction of a Nomogram Model for Predicting Pleural Effusion Secondary to Severe Acute Pancreatitis
Author(s) -
Bing-Mei Zhou,
Zhao-Lei Qiu,
Kai-Xuan Niu,
Yin-E. Wang,
Fu-Chen Jie
Publication year - 2022
Publication title -
emergency medicine international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.484
H-Index - 4
eISSN - 2090-2859
pISSN - 2090-2840
DOI - 10.1155/2022/4199209
Subject(s) - medicine , nomogram , acute pancreatitis , logistic regression , receiver operating characteristic , pleural effusion , gastroenterology , surgery
Background. This study aims to investigate the risk factors of pleural effusion (PE) secondary to severe acute pancreatitis (SAP) and to build a nomogram model. Methods. The clinical parameters of SAP patients admitted to the emergency department of the First Affiliated Hospital of Bengbu Medical College from January 2019 to August 2021 were retrospectively collected. The independence risk factors of PE secondary to SAP were analyzed by univariate analysis and multivariate logistic regression analysis. A nomogram risk prediction model was established and validated through the area under the ROC curve. Result. Two hundred twenty-two SAP patients were included for analysis, of which 65 patients experienced secondary PE. The incidence of PE secondary to SAP was 29.28% (65/222). Logistic regression analysis showed that serum albumin (ALB) (OR = 0.830, 95% CI: 0.736∼0.936), fibrinogen (FIB) (OR = 4.573, 95% CI: 1.795∼11.648), C-reactive protein (CRP) (OR = 1.046, 95% CI: 1.009∼1.083), acute physiology, chronic health score system (APACHE-II) score (OR = 1.484, 95% CI: 1.106∼1.990), and sequential organ failure score (SOFA) (OR = 43.038, 95% CI: 2.030∼4.548) were independent risk factors for PE secondary to SAP ( P < 0.05 ) and entered into the nomogram. The nomogram showed robust discrimination with an index of concordance of 0.755 and an area under the receiver operating characteristic curve of 0.837 (95% CI: 0.779∼0.894). Conclusion. We developed a nomogram model for PE secondary to SAP with ALB, FIB, CRP, APACHE-II scores, and SOFA scores. The nomogram model showed good discrimination and consistency, and it can better predict the risk of PE secondary to SAP.
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