Introduction

Acute pancreatitis (AP) is a common gastrointestinal disorder with significant morbidity and mortality in severe cases. Pre-existing comorbidities and newly developed complications, like heart failure may influence outcomes in AP patients.

Aims & Methods

This study aimed to evaluate the impact of pre-existing and newly developed cardiac conditions on in-hospital and post-discharge mortality in patients with acute pancreatitis. A single-center registry analysis of the Hungarian Pancreatic Study Group Acute Pancreatitis Registry was conducted at Semmelweis University, Budapest, Hungary, involving 1,316 patients diagnosed with acute pancreatitis between 2021-2024. Data on pre-existing chronic heart failure (CHF), atrial fibrillation (AF), stroke history, and newly developed acute heart failure (AHF) were collected. Electrocardiogram (ECG) findings, including QTc prolongation, were also analyzed. In-hospital mortality and post-discharge mortality within one year were assessed. Odds ratios (OR) with 95% confidence intervals (CI) were calculated to quantify the strength of associations.

Results

Of the 1316 patients, 45% were female, the average age was 55.8 (range: 18-95) years, 8% had severe, 25% had moderate, and 65% had mild AP. Regarding cardiovascular background, pre-existing CHF and stroke history did not show a significant association with increased in-hospital mortality in AP (OR: 1.85, 95% CI: 0.63-5.44 and OR: 1.21, 95% CI: 0.36-4.02, respectively). Although AP patients with pre-existing AF had four-fold higher odds of in-hospital mortality (OR: 4.01, 95% CI: 1.92-8.34). Assessing in-hospital cardiovascular alterations, newly discovered AF was not significantly associated with increased in-hospital mortality (OR: 4.40, 95% CI: 0.97-20.02). Moreover, QTc prolongation on ECG was not significantly associated with in-hospital mortality (OR: 2.10, 95% CI: 0.61-7.25) or post-discharge mortality within one year after AP (OR: 1.65, 95% CI: 0.20-13.74). However, AP patients with newly developed AHF had a 25-times higher odds of in-hospital mortality (OR: 25.81, 95% CI: 12.13-54.98) and a 4-times higher odds for post-discharge mortality within one year (OR: 4.93, 95% CI: 1.01-24.26).

Conclusion

Pre-existing AF and newly developed AHF are significantly associated with increased in-hospital mortality in patients AP, moreover, newly developed AHF is also associated with increased post-discharge mortality within one year. These findings highlight the importance of cardiac monitoring and management in AP patients to improve outcomes.

Introduction

Neurofilaments are cytoskeletal proteins specific to neuronal tissue. As their blood levels rise following neuronal damage, they are increasingly being studied as the biomarkers for neuroaxonal injury in various conditions, such as Alzheimer’s disease, multiple sclerosis, amyotrophic lateral sclerosis, or type 2 diabetes mellitus (T2DM) related neuropathy. Pancreatic ductal adenocarcinoma (PDAC) is a malignant disease known for its poor prognosis, rapid spread, silent progression, and lack of effective diagnostic tools in its early stages. Perineural and/or endoneural invasion and neuronal damage are hallmarks of PDAC.

Aims & Methods

The aim of our study was to measure the levels of neurofilament light chain (NfL) in patients with PDAC, T2DM, chronic pancreatitis (ChP), and healthy controls. We used a Single Molecule Array (Simoa; Quanterix) to measure NfL levels in patients with PDAC (n=50, mean age 63.16 ± 8.8 years), T2DM (n=42, mean age 61.6 ± 8.4 years), ChP (n=30, mean age 56 ± 13.6 years), and healthy controls (n=46, mean age 54 ± 9.06 years).

Results

The following concentrations of NfL were obtained from the samples: PDAC: 30.31 ± 39.79 pg/ml, T2DM: 12.59 ± 10.19 pg/ml, ChP: 16.64 ± 13.78 pg/ml, Healthy controls:
7.93 ± 4.18 pg/ml. NfL levels were significantly different between PDAC and healthy controls (p < 0.001) and between T2DM and healthy controls (p < 0.001). Differences between other
groups were not significant. Further analysis confirmed age as a significant predictor of NfL levels (p < 0.001), indicating that NfL levels increase with age by 0.48 per year. We did not find a
significant impact of glycemic control (represented by glycated haemoglobin levels) or body mass index on NfL concentrations. Because of the correlation between age and NfL levels, we examined the relationship between age, diagnosis, and NfL levels using a statistical model comparison approach. After controlling for age, we found that PDAC and ChP showed significantly higher NfL levels compared to T2DM and healthy controls (p < 0.01). No significant differences were found between T2DM and healthy controls

Conclusion

This is the first study to date that evaluates serum levels of NfL in PDAC and chronic pancreatitis. The results support the possible role of NfL as a biomarker in certain non-neurological conditions. Elevated serum levels of NfL in PDAC and ChP suggest that this biomarker reflects neuronal damage, which is present in ChP and is a key feature of PDAC, even in the early stages of the disease.

Introduction

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer that poses significant therapeutic challenges. In this regard, the identification of prognostic biomarkers is crucial to improve the prediction of clinical outcomes and guide therapeutic decisions. Tumour-associated autoantibodies (TAAbs) have been identified as prognostic biomarkers in several types of cancer, as they can be generated before the first clinically detectable signs of disease.

Aims & Methods

The aim of this study was to identify TAAbs that can be used as prognostic biomarkers in PDAC. 80 sera from patients with PDAC, divided into four groups according to disease stage, were included in the study: patients with premalignant lesions (n = 20), patients undergoing curative resection after diagnosis (CR) (n = 20), patients with unresectable advanced locoregional disease (LA) (n = 20) and patients with metastatic disease (MT) (n = 20). Sera from each group were analysed divided into 4 pools of 5 samples each using the HuProt Human Protreome microarray v4.0 (CDI Laboratories, Baltimore, MD). Candidate TAAbs with high specific reactivity in MT and/or LA samples were selected according to the following criteria: z-score ≥ 3 in at least 2/4 pools and fold-change > 1.2. The RNAseq data collected in the Human Protein Atlas were used to determine protein expression levels and prognostic value. The GSE15471, GSE28735 and GSE16515 databases were used to compare expression levels with those of healthy subjects without the disease.

Results

43 TAAbs demonstrated high levels of specific reactivity in samples from MT and/or LA patients. Of these highly recognised proteins, 15 were selected for showing notable levels of expression in tumour tissue from PDAC patients and prognostic capacity in some types of cancer. Of these 15, 2 proteins involved in tumour development were identified. Survival analyses showed that six of the 15 selected proteins were significantly associated with a worse prognosis in PDAC patients (p < 0.05). Finally, in the comparison with control tumour tissue, 5 proteins were identified with significantly higher expression in patients diagnosed with the disease (p < 0.05 in at least 2 of the cohorts used).

Conclusion

15 TAAbs have been identified as promising candidates for prognostic biomarkers in PDAC. Further validation studies are required to confirm their prognostic value and to develop a robust biomarker signature with potential for clinical application and market translation.

Introduction

The aetiology of acute pancreatitis remains elusive in 10-30% of patients after clinical, biological and morphological investigations. Endoscopic ultrasound has shown promise and is particularly effective in exploring the bilio-pancreatic region.

Aims & Methods

The aim of our study was to evaluate the contribution of endoscopic ultrasound to the aetiological diagnosis of unexplained acute pancreatitis.
This is a retrospective descriptive study of 89 patients who underwent endoscopic ultra sound for unexplained acute pancreatitis between January 2010 and January 2025.

Results

The mean age of our patients was 55 +/- 16.3 years, with extremes ranging from 17 to 89 years. The sex ratio (M/F) was 0.81, with a slight female predominance of 55.1%. A history of previous acute pancreatitis was found in 31.9% of cases, and 16.3% of patients had undergone cholecystectomy. The diagnostic yield in our study was 68%. Biliary origin was retained in 40.4% (n=36) of patients, 19 of whom underwent complementary ERCP at the same anaesthetic time. Neoplastic pathology was found in 32.5% of cases (n=30). Chronic pancreatitis was reported in 22.4% of patients (n=20). Two cases of pancreas divisum, one case of sphincter of Oddi dysfunction and one case of choledocele were found. In the remaining 32% of cases, the endoscopic ultrasound was normal and no cause could be found.

Conclusion

Endoscopic ultrasound is currently an indispensable tool in the etiological investigation of unexplained acute pancreatitis. In our study, the diagnostic efficiency was around 68%.

Introduction

Contrast-enhanced endoscopic ultrasound (CE-EUS) is a valuable tool for evaluating gastrointestinal lesions, providing real-time insights into vascular patterns and tissue perfusion. It is increasingly utilized to differentiate solid and cystic lesions, particularly in pancreaticobiliary diseases. However, CE-EUS interpretation remains operator-dependent, with variability influenced by observer expertise and a lack of standardized criteria. Previous studies on interobserver agreement (IOA) in CE-EUS interpretation have yielded inconsistent results, underscoring the need for further investigation into dynamic contrast features such as enhancement patterns and wash-in/wash-out phases.

Aims & Methods

This study aimed to evaluate IOA among endosonographers with varying levels of expertise in interpreting CE-EUS videos, focusing on lesion classification, dynamic contrast features, and video quality. This multicenter retrospective study involved 24 endosonographers (15 experts, 9 non-experts) from 16 European centers. Participants completed an initial survey capturing their experience and institutional characteristics. Subsequently, they independently reviewed 60 CE-EUS videos (~1 minute each), recorded between 2021 and 2023, comprising 40 solid, 15 cystic, and 5 mixed lesions. Videos varied in quality. Observers assessed lesion type (solid or cystic), arterial and venous enhancement patterns (hyper-, hypo-, or non-enhancing), wash-in and wash-out timing (rapid or late), contrast distribution (homogeneous or inhomogeneous), and video quality. Fleiss’ kappa (κ) was used to calculate IOA for each parameter. A multivariate analysis was conducted to identify factors influencing IOA.

Results

Moderate agreement was found for lesion classification (κ = 0.47). IOA for arterial phase enhancement was slight (κ = 0.38), as was agreement for arterial wash-in timing (κ = 0.27), venous wash-out timing (κ = 0.21), and contrast distribution homogeneity (κ = 0.24). No agreement was reached for video quality assessment (κ = 0.14). Operator experience was not significantly associated with IOA. Multivariate analysis revealed that IOA for wash-in timing was influenced by procedural volume at the observer's center and the type of endoscopic equipment used (p = 0.004 and p = 0.034, respectively). Additionally, center volume significantly affected perceived video quality assessment (p = 0.035).

Conclusion

This study demonstrates considerable variability in CE-EUS interpretation among observers, particularly for dynamic contrast features, where agreement was slight. Lesion classification showed moderate reproducibility, but standardized evaluation criteria are needed for other parameters. Procedural volume at the observer's center significantly influenced IOA, emphasizing the importance of institutional experience. These findings highlight the need for improved training programs and interpretation frameworks to enhance the diagnostic consistency and clinical utility of CE-EUS.

Introduction

Acute pancreatitis (AP) is a common gastrointestinal disorder with significant morbidity and mortality, particularly in severe cases (SAP). Early prediction of SAP is crucial for timely intervention and improved patient outcomes. Traditional scoring systems like Ranson, BISAP, and APACHE II have limitations in accuracy and timeliness. Machine learning (ML) has shown promise in enhancing SAP prediction, but the potential of advanced architectures like Transformer models remains unexplored. This study aims to develop a Transformer-based model for SAP prediction and compare its performance with traditional ML methods.

Aims & Methods

The primary aim of this study was to develop a Transformer-based prediction model for acute pancreatitis severity and evaluate its performance compared to traditional machine learning models. Retrospective data from 722 AP patients admitted to the Second Affiliated Hospital of Guilin Medical University between January 2020 and June 2024 were analyzed. Patient data included 24-hour admission laboratory indicators such as electrolytes, liver function, renal function, and inflammatory markers. To construct the prediction model, a comprehensive workflow was designed. Data preprocessing involved feature vectorization using One-Hot encoding, missing value imputation using the K-Nearest Neighbor (KNN) algorithm, normalization of feature values to a [0, 1] range, and handling class imbalance using Synthetic Minority Over-Sampling Technique (SMOTE). Feature selection was performed by dividing patients into SAP and MAP groups, identifying features with significant differences using non-parametric tests, and ranking features by their relevance through correlation analysis. Features causing a decline in AUC during incremental addition were removed to optimize the feature set. The Transformer model, leveraging self-attention mechanisms to process sequential data, was trained alongside traditional ML models (Logistic Regression, Decision Tree, Random Forest, and XGBoost). Five-fold cross-validation was used to prevent overfitting, and model performance was evaluated using metrics such as AUC, accuracy, precision, recall, F1 score, and specificity. SHAP analysis was employed to interpret the Transformer model's predictions, providing insights into the contribution of each feature to the model's output.

Results

The Transformer model outperformed traditional ML models (Table 1), achieving an AUC of 0.9662 and exceeding 0.90 in all metrics. It maintained robust performance even with minimal training data (AUC: 0.8437 at 5% training). SHAP analysis highlighted key predictors (calcium, amylase, basophil percentage, CO2 binding capacity), aligning with clinical relevance.

Table 1. Performance metrics comparison of different models.

Conclusion

The Transformer model demonstrated superior accuracy, generalizability, and interpretability for SAP prediction, particularly in small datasets. Its clinical utility is enhanced by SHAP-driven insights into key predictors. Retrospective design limits prospective validity; future work should validate the model in larger cohorts and integrate additional biomarkers. This study supports the potential of transformer in medical prediction to improve patient outcomes through timely interventions.

References

[1]. Sinonquel P, Laleman W, Wilmer A. Advances in acute pancreatitis. Curr Opin Crit Care. 2021;27(2):193–200.
[2]. Thapa R, Iqbal Z, Garikipati A, et al. Early prediction of severe acute pancreatitis using machine learning. Pancreatology. 2022;22(1):43–50.
[3]. Luo Z, Shi J, Fang Y, et al. Development and evaluation of machine learning models and nomogram for the prediction of severe acute pancreatitis[J]. Journal of Gastroenterology and Hepatology, 2023, 38(3): 468-475.
[4]. Zhang C, Peng J, Wang L, et al. A deep learning-powered diagnostic model for acute pancreatitis[J]. BMC Medical Imaging, 2024, 24(1): 154.
[5]. Liao H, Huang C, Liu C, et al. Deep learning-based MVIT-MLKA model for accurate classification of pancreatic lesions: a multicenter retrospective cohort study[J]. La radiologia medica, 2025: 1-16.

Introduction

Acute pancreatitis (AP) is a common acute inflammatory disease of the abdomen. ATP citrate lyase (ACLY) has been shown to play a critical role in mitigating acute pancreatitis-associated injury. Lentinan, a multifunctional polysaccharide derived from shiitake mushrooms, exhibits biological activities such as anti-inflammatory, antioxidant, and immunomodulatory effects, and is widely used in clinical settings. However, the role of Lentinan in acute pancreatitis remains unclear.

Aims & Methods

This study aimed to investigate the protective effects of Lentinan against acute pancreatitis and whether this protection depends on ATP citrate lyase. Adult healthy male C57BL/6 mice were randomly divided into control group, acute pancreatitis group, and Lentinan + acute pancreatitis group. The cerulein-LPS induced AP model was established by intraperitoneal injection of cerulein solution (100 μg/kg body weight) 10 times at hourly intervals, followed by a single injection of lipopolysaccharide (5 mg/kg) immediately after the last cerulein injection. In the lentinan + acute pancreatitis group, mice were pretreated with intraperitoneal injections of of Lentinan solution (50 mg/kg, 100 mg/kg, or 200 mg/kg) for three consecutive days before AP induction. The severity of pancreatitis was assessed by comparing plasma activities of amylase, lipase, alanine aminotransferase, aspartate aminotransferase, and plasma levels of urea, and creatinine, as well as pancreatic histopathological scores. Systemic inflammatory response was evaluated by measuring plasma IL-1β and TNF-α levels through enzyme-linked immunosorbent assay. Pancreatic infiltration of macrophages and neutrophils was detected by immunofluorescence, and protein levels of ACLY, NLRP3, and IL-1β in pancreatic tissues were measured by Western blot. To further validate the critical role of ACLY, AP was induced in mice with pancreas-specific ACLY knockout, with Lentinan pretreatment.

Results

Lentinan significantly alleviated pancreatic histopathological damage caused by AP, including edema, necrosis, and inflammatory cell infiltration. It also reduced plasma aminotransferase activity, creatinine, and urea levels, but did not significantly decrease plasma amylase or lipase activity. A higher dose of Lentinan (200 mg/kg) was less effective than lower doses in reducing plasma aminotransferase, creatinine, and urea in AP mice, possibly due to greater hepatorenal toxicity. Therefore, a moderate dose of Lentinan (100 mg/kg) provided effective protection against acute pancreatitis and was therefore selected for subsequent experiments. Additionally, Lentinan reduced pancreatic infiltration of macrophages and neutrophils, decreased plasma pro-inflammatory cytokine levels, upregulated pancreatic ACLY protein expression, and downregulated the levels of NLRP3 inflammasome and IL-1β proteins in pancreatic tissues. In mice with pancreas-specific ACLY knockout, both local pancreatic injury and systemic inflammation caused by AP were significantly exacerbated, and the protective effect of Lentinan against acute pancreatitis was diminished.

Conclusion

Lentinan exerts protective effects against acute pancreatitis by improving local and systemic inflammatory responses. The expression of pancreatic ACLY is indispensable for mediating this protective effect, which was partially achieved through the inhibition of the NLRP3 inflammasome pathway. The present study establishes a novel mechanism for this clinically available immunomodulator, which could have potential therapeutic implications in acute pancreatitis.