Establishment and validation of prediction model for severity of acute pancreatitis
10.3760/cma.j.cn311367-20201222-00725
- VernacularTitle:急性胰腺炎严重程度预测模型的建立与验证
- Author:
Rui LI
1
;
Yuyuan ZHANG
;
Ruochang LI
;
Jie ZHU
;
Wendi DONG
;
Hairong ZHANG
Author Information
1. 昆明医科大学第一附属医院消化内科 云南省消化系统疾病临床医学研究中心 650032
- Keywords:
Acute pancreatitis;
Severity;
Nomograms;
Internal verification
- From:
Chinese Journal of Digestion
2021;41(8):554-560
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To establish and internally validate a visualized model for predicting the severity of acute pancreatitis (AP).Methods:From September 1st 2017 to August 31st 2020, 600 patients with AP diagnosed in the First Affiliated Hospital of Kunming Medical University were enrolled. According to the Atlanta classification of AP, the 600 patients were divided into severe acute pancreatitis (SAP) group (128 cases) and non-severe acute pancreatitis (NSAP) group (472 cases). The general clinical data (age, gender, body mass index, etc), laboratory indicators (fasting blood glucose, urea nitrogen, creatinine, etc.), complicated with ascites or pleural effusion, acute physiology and chronic health evaluation Ⅱ (APACHE Ⅱ) scores and bedside index of severity in acute pancreatitis (BISAP) score between the two groups were compared. The potential predictors of SAP were screened with least absolute shrinkage and selection operator (LASSO). The screened predictors were included in the multivariate logistic regression analysis to establish the logistic regression model. The operation characteristic curves of the model, APACHE Ⅱ scores and BISAP were drawn, the discriminative capability of the model was evaluated by comparing the area under the curve (AUC). Calibration, Hosmer-Lemesshow test and decision curve analysis (DCA) were used to evaluate the accuracy and clinical practicability of the prediction model. Bootstrap was used for internally validation of the model. Independent sample t test, Wilcoxon test and chi-square test were used for statistical analysis. Results:The difference of gender composition ratio between SAP and NSAP group was statistically significant ( χ2=4.092, P<0.05). The fatality rate of SAP group was higher than that of NSAP group(21.1%, 27/128 vs. 0, 0/472); the length of hospital stay of SAP group was longer than that of NSAP group((20.33±16.21) d vs. (8.42±4.26) d); the hospitalization cost, fasting blood glucose level, urea nitrogen level, creatinine level, C-reactive protein(CRP) level, D-dimer level, fibrinogen level, white blood cell count, percentage of neutrophils, neutrophil-lymphocyte ratio, APACHEⅡ and BISAP scores, the incidence of complicated with pleural effusion or ascites and the constituent ratio of alcoholic etiology of SAP group were all higher than those of NASP group (44 837.58 yuan (23 017.73 yuan, 102 579.77 yuan) vs. 12 301.46 yuan (8 649.26 yuan, 18 823.88 yuan); (10.48±4.84) mmol/L vs. (8.45±4.80) mmol/L; (8.80±6.50) mmol/L vs. (4.90±2.33) mmol/L; (139.56±127.75) mmol/L vs. (80.05±38.54) mmol/L; (187.33±87.25) mg/L vs. (90.81±82.53) mg/L; 5.19 mg/L (2.96 mg/L, 8.52 mg/L) vs.1.29 mg/L (0.53 mg/L, 2.87 mg/L); 6.13 mg/L (4.64 mg/L, 7.31 mg/L) vs. 4.58 mg/L (3.50 mg/L, 5.98 mg/L); (14.87±5.82)×10 9/L vs. (11.79±4.86)×10 9/L; 0.84±0.12 vs.0.78±0.12; 13.16±7.57 vs. 8.77±7.28; 9.80±6.09 vs. 3.79±2.59; 2.12±0.89 vs. 1.04±0.78; 65.6%, 84/128 vs. 12.9%, 61/472; 70.3%, 90/128 vs. 20.3%, 96/472; 18.8%, 24/128 vs. 11.4%, 54/472); serum albumin level, blood calcium level, and hematocrit level of SAP group were all lower than those of NSAP group ((30.86±4.95) g/L vs. (37.14±5.44) g/L; (1.98±0.31) mmol/L vs. (2.16±0.20) mmol/L; (42.40±8.67)% vs.(44.30±6.45)%), and the differences were all statistically significant ( χ2=99.403, t=8.235, Z=-13.330, t=4.239, 10.759, 5.207 and 11.227, Z=-11.406 and -6.234, t=6.097, 4.829, 6.011, 10.899 and 12.395, χ2=152.604, 117.563 and 4.757, t=-11.788, -6.180 and -2.310, all P<0.05). LASSO regression analysis screened out four predictors of CRP, urea nitrogen, D-dimer and ascites. The results of multivariate logistic regression analysis showed that CRP (odds ratio ( OR)=1.009, 95% (confidence interval) CI 1.006 to 1.012), urea nitrogen( OR=1.185, 95% CI 1.097 to 1.280), D-dimer( OR=1.166 95% CI 1.082 to 1.256), ascites ( OR= 4.848, 95% CI 2.829 to 8.307) were the independent predictors of SAP (all P<0.01). The AUC of the model (0.895 , 95% CI 0.865 to 0.926) was higher than those of the APACHE Ⅱ(AUC=0.835, 95% CI 0.791 to 0.878)and BISAP score (AUC=0.803, 95% CI 0.760 to 0.846), and the differences were statistically significant ( Z=2.578 and 4.466, both P<0.05). The results predicted by the model in the calibration chart and the Hosmer-Lemesshow test were highly consistent with the results of actual clinical observation. When the probability of SAP in the model was 10% to 95%, the DCA curve of the model was higher than the two extreme lines, which had certain clinical practical value. After bootstrap internal validation, the model had a high discrimination ability (AUC=0.892), and its predicted AP severity curve was still in good agreement with the actual clinical AP severity curve. Conclusion:The prediction model established based on CRP, urea nitrogen, D-dimer and ascites can predict the severity of AP, and help doctors to make more scientific clinical decision.
