Predictive Value of Ultrasound Elastography in Acute Pancreatitis:A Prediction Model for Severe Acute Pancreatitis Based on Controlled Attenuation Parameter
10.3969/j.issn.1008-7125.2025.02.001
- VernacularTitle:超声弹性成像在急性胰腺炎中的预测价值:基于肝脂肪受控衰减参数的重度急性胰腺炎预测模型
- Author:
Xinyu WEI
1
;
Miaoyan FAN
;
Jiangfeng HU
;
Yingying LU
;
Qiaoli JIANG
;
Sumin CHEN
Author Information
1. 上海交通大学附属第一人民医院消化内科(201602)
- Publication Type:Journal Article
- Keywords:
Ultrasound Elastography;
Acute Pancreatitis;
Controlled Attenuation Parameter;
Prediction Models
- From:
Chinese Journal of Gastroenterology
2025;30(2):65-72
- CountryChina
- Language:Chinese
-
Abstract:
Background:Acute pancreatitis(AP)is a common disease of the digestive system,among which severe acute pancreatitis(SAP)has a high mortality rate.Finding more accurate and convenient methods for early recognition of SAP is one of the major challenges in clinical treatment.Aims:To explore the application value of the controlled attenuation parameter(CAP)of ultrasound elastography in predicting SAP.Methods:A retrospective cohort study was conducted involving 135 AP patients admitted to Jiading Branch of Shanghai General Hospital from February to October 2024.Patients were categorized into non-SAP and SAP groups according to the severity of the disease.Clinical data,local complications,laboratory indicators,and CAP were compared between the two groups.Univariate and multivariate Logistic regression analyses were used to identify independent risk factors for SAP.A SAP prediction model based on CAP was constructed according to the identified risk factors and the minimum Akaike information criterion(AIC).ROC curve and Bootstrap method were used to evaluate the efficacy of the prediction model and conduct internal validation,respectively.Results:There were statistically significant differences between the non-SAP group and SAP group in body mass index(BMI),incidence of hyperlipidemia,etiological composition,incidence of pleural and ascitic fluid,length of hospital stay,incidence of peripancreatic effusion,incidence of pancreatic necrosis,white blood cell count(WBC),D-dimer(D-D)level,blood glucose,triglyceride(TG),C-reactive protein(CRP),neutrophil count,procalcitonin(PCT),interleukin-6(IL-6),free triiodothyronine(FT3),and CAP(all P<0.05).Multivariate Logistic regression analysis showed that pancreatic necrosis(OR=13.39,95%CI:3.10-57.94,P<0.001)and CAP(OR=1.01,95%CI:1.01-1.02,P=0.038)were independent risk factors for SAP.The SAP prediction model based on CAP was formulated as:Logit(P)=-5.884+0.010×CAP+2.839×pancreatic necrosis+0.169×D-D+0.132×blood glucose+0.006×CRP.The model showed an area under the curve(AUC)of 0.834 for predicting SAP,which was superior to CAP alone(P<0.05).Internal validation indicated that the prediction model had high stability and accuracy(C-index=0.808).Conclusions:The prediction model constructed based on CAP has good clinical value for predicting SAP,providing a new perspective and tool for early identification and prognostic assessment of AP.
