4.5 Article

Prediction of infected pancreatic necrosis in acute necrotizing pancreatitis by the modified pancreatitis activity scoring system

Journal

UNITED EUROPEAN GASTROENTEROLOGY JOURNAL
Volume 11, Issue 1, Pages 69-78

Publisher

JOHN WILEY & SONS LTD
DOI: 10.1002/ueg2.12353

Keywords

acute necrotizing pancreatitis; infected pancreatic necrosis; modified pancreatitis activity scoring system; opioid; pancreatitis activity scoring system

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This study aimed to assess the performance of the Pancreatitis Activity Scoring System (PASS) and its modifications in predicting infected pancreatic necrosis (IPN) in patients with acute necrotizing pancreatitis. The mPASS-4 model had the best predictive performance and simplified the original PASS, increasing the likelihood of clinical implementation.
ObjectivesInfected pancreatic necrosis (IPN) is a significant complication of acute necrotizing pancreatitis (ANP). Early identification of patients at high risk of IPN would enable appropriate treatment, but there is a lack of valid tools. This study aimed to assess the performance of the Pancreatitis Activity Scoring System (PASS) and its modifications (by removing or reducing the weight of opioid usage) in predicting IPN in a cohort of predicted severe ANP patients. MethodsData was prospectively collected in the TRACE trial (2017-2020) involving 16 sites across China. The predictive performance of PASS, modified PASS (mPASS), and conventional indices were assessed by the area under the receiver operating characteristic curve (AUC), Hosmer-Lemeshow c-test, Brier score, and Fagan's nomogram. Multivariate logistic regression analysis (MLRA) was used to define the relationship between the best-performing PASS/mPASS model and IPN. ResultsA total of 508 subjects were enrolled (median age, 43 years; 62.8% males) in the original trial, and 122 developed IPN (24%) within 90 days after randomization. Compared with non-IPN patients, the scores of PASS and its modified models were significantly higher in the IPN patients (all p < 0.001). Among the PASS and its modifications, mPASS-4 had the largest AUC, the lowest Brier score, and good calibration. The mPASS-4 model demonstrated an AUC of 0.752 in predicting IPN (the optimal cut-off for the mPASS-4 was 292.5) and outperformed the conventional indices. The MLRA results showed that mPASS-4 >292.5 was an independent risk factor of IPN (OR: 3.6, 95% CI: 2.1-6.3). ConclusionThe PASS and its modifications during the first week of ANP onset predict the development of IPN, with mPASS-4 performing best. The mPASS-4 model simplifies the original PASS, increasing the likelihood of clinical implementation.

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