The modified pancreatitis activity scoring system (mPASS) was proposed to assess the activity of acute pancreatitis (AP) while it doesn't include indicators that directly reflect pathophysiology processes and imaging characteristics.

To determine the threshold of admission mPASS and investigate radiomics and laboratory parameters to construct a model to predict the activity of AP.

AP inpatients at institution 1 were randomly divided into training and validation groups based on a 5:5 ratio. AP inpatients at Institution 2 were served as test group. The cutoff value of admission mPASS scores in predicting severe AP was selected to divide patients into high and low level of disease activity group. LASSO was used in screening features. Multivariable logistic regression was used to develop radiomics model. Meaningful laboratory parameters were used to construct combined model.

There were 234 (48 years ± 10, 155 men) and 101 (48 years ± 11, 69 men) patients in two institutions. The threshold of admission mPASS score was 112.5 in severe AP prediction. The AUC of the radiomics model was 0.79, 0.72, and 0.76 and that of the combined model incorporating rad-score and white blood cell were 0.84, 0.77, and 0.80 in three groups for activity prediction. The AUC of the combined model in predicting disease without remission was 0.74.

The threshold of admission mPASS was 112.5 in predicting severe AP. The model based on CECT radiomics has the ability to predict AP activity. Its ability to predict disease without remission is comparable to mPASS.

This work is the first attempt to assess the activity of acute pancreatitis using contrast-enhanced CT radiomics and laboratory parameters. The model provides a new method to predict the activity and prognosis of AP, which could contribute to further management.

Radiomics features and laboratory parameters are associated with the activity of acute pancreatitis. The combined model provides a new method to predict the activity and prognosis of AP. The ability of the combined model is comparable to the modified Pancreatitis Activity Scoring System.

Approximately 20%-30% of patients with acute necrotizing pancreatitis develop infected pancreatic necrosis (IPN), a highly morbid and potentially lethal complication. Early identification of patients at high risk of IPN may facilitate appropriate preventive measures to improve clinical outcomes. In the past two decades, several markers and predictive tools have been proposed and evaluated for this purpose. Conventional biomarkers like C-reactive protein, procalcitonin, lymphocyte count, interleukin-6, and interleukin-8, and newly developed biomarkers like angiopoietin-2 all showed significant association with IPN. On the other hand, scoring systems like the Acute Physiology and Chronic Health Evaluation II and Pancreatitis Activity Scoring System have also been tested, and the results showed that they may provide better accuracy. For early prevention of IPN, several new therapies were tested, including early enteral nutrition, antibiotics, probiotics, immune enhancement, etc., but the results varied. Taken together, several evidence-supported predictive markers and scoring systems are readily available for predicting IPN. However, effective treatments to reduce the incidence of IPN are still lacking apart from early enteral nutrition. In this editorial, we summarize evidence concerning early prediction and prevention of IPN, providing insights into future practice and study design. A more homogeneous patient population with reliable risk-stratification tools may help find effective treatments to reduce the risk of IPN, thereby achieving individualized treatment.

Acute pancreatitis (AP) is one of the most widespread clinical emergencies. Macrophages are the most common immune cells in AP pancreatic tissue and are closely associated with pancreatic necrosis and recovery. The level of heparin-binding protein (HBP) is closely linked to inflammation. In this study, we assessed the effect of HBP on AP tissue necrosis severity and whether HBP is associated with M1 macrophages in pancreatic necrosis. We observed the dynamic changes of HBP levels in the pancreas during acute inflammation in the caerulein-induced AP mice model. We used hematoxylin-eosin staining to evaluate pancreatic edema and necrosis, and to detect infiltration of macrophages by immunohistochemistry. Moreover, expressions of the maker and cytokines of macrophages, including inducible nitric oxide synthase (iNOS), and arginase 1 (Arg-1), interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6) mRNA, were detected by real-time polymerase-chain reaction (RT-PCR). High levels of HBP in the pancreas were detected at 48 h, and heparin inhibited HBP expression in AP pancreatic tissue. Inhibiting HBP expression by injecting heparin before AP can alleviate pancreatic necrosis and inhibit F4/80 labeled M1 macrophage infiltration and IL-6, TNF-α, and iNOS mRNA expression. Clodronate liposome (CLDL) intraperitoneally treated mice showed no change in pancreatic HBP levels, but pancreatic macrophage-specific antigen F4/80 and TNF-α, IL-1β, and IL-6 mRNA levels decreased after CLDL treatment. HBP is critical for pancreatic necrosis response in acute pancreatitis by increasing the infiltration of M1 macrophages and promoting the secretion of inflammatory factors, such as TNF-α, IL-6, IL-1β, which can be reduced by heparin.

To evaluate the efficacy of harmless acute pancreatitis score (HAPS) on admission for predicting mild acute pancreatitis (MAP).

We prospectively collected the data from consecutive AP patients admitted to West China Hospital between January, 2016 and August, 2017, and HAPS scores were calculated on admission. The clinical outcomes of the patients with harmless AP (HAPS>2) and those with non-harmless AP (HAPS≤2) were compared. MAP was defined based on the severity classification of 2012 Revised Atlanta guidelines. The area under the curve (AUC) of the receiver- operator characteristic curve (ROC), specificity, sensitivity, positive predictive value (PPV) and negative predictive value (NPV) of HAPS on admission for predicting MAP were analyzed.

Of the 703 patients with AP analyzed, 182 were predicted to have harmless AP and 521 to have non- harmless AP, and the patients in the latter group had significantly worse clinical outcomes (P < 0.001). The total number of patients with MAP was 359 in the study. The specificity, the sensitivity, the PPV and NPV of HAPS on admission for predicting MAP was 97.7% (95% CI: 95.4-99.0), 48.2% (95% CI: 42.9-53.3), 95.6% (95% CI: 91.5- 98.1) and 64.1% (95% CI: 59.8- 68.2), respectively, and the AUC was 0.749 (95% CI: 0.72- 0.78).

HAPS score on admission can accurately predict MAP.

Acute pancreatitis (AP) is a severe inflammation of the pancreas presented with sudden onset and severe abdominal pain with a high morbidity and mortality rate, if accompanied by severe local and systemic complications. Numerous studies have been published about the pathogenesis of AP; however, the precise mechanism behind this pathology remains unclear. Extensive research conducted over the last decades has demonstrated that the first 24 h after symptom onset are critical for the identification of patients who are at risk of developing complications or death. The identification of these subgroups of patients is crucial in order to start an aggressive approach to prevent mortality. In this sense and to avoid unnecessary overtreatment, thereby reducing the financial implications, the proper identification of mild disease is also important and necessary. A large number of multifactorial scoring systems and biochemical markers are described to predict the severity. Despite recent progress in understanding the pathophysiology of AP, more research is needed to enable a faster and more accurate prediction of severe AP. This review provides an overview of the available multifactorial scoring systems and biochemical markers for predicting severe AP with a special focus on their advantages and limitations.