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Szentesi A, Hegyi P. The 12-Year Experience of the Hungarian Pancreatic Study Group. J Clin Med 2025; 14:1362. [PMID: 40004893 PMCID: PMC11855942 DOI: 10.3390/jcm14041362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2025] [Revised: 02/11/2025] [Accepted: 02/14/2025] [Indexed: 02/27/2025] Open
Abstract
The Hungarian Pancreatic Study Group (HPSG) was established with the aim of advancing pancreatology. Our summary outlines the methodologies, key results, and future directions of the HPSG. Methodological elements included, the formation of strategic national and international collaborations, the establishment of patient registries and biobanks, and a strong focus on education and guideline development. Key results encompassed, pioneering research on pancreatic ductal function and the role of cystic fibrosis transmembrane conductance regulator (CFTR) in inflammation, significant advancements in understanding acute and chronic pancreatitis, and the execution of numerous clinical trials to explore new therapeutic approaches. Despite challenges, such as securing funding and translating research into clinical practice, the HPSG's commitment to patient care and scientific innovation has been unwavering. The group aims to deepen research into pancreatic cancer and chronic pancreatitis, conduct more randomized controlled trials (RCTs), and expand its efforts internationally by involving global staff and patients. The authors hope that this summary inspires others to undertake similar initiatives and contribute to the global advancement of medical research and patient care in pancreatology.
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Affiliation(s)
- Andrea Szentesi
- Institute for Translational Medicine, Medical School, University of Pécs, 7624 Pécs, Hungary;
| | - Péter Hegyi
- Institute for Translational Medicine, Medical School, University of Pécs, 7624 Pécs, Hungary;
- Institute of Pancreatic Diseases, Semmelweis University, 1083 Budapest, Hungary
- Centre for Translational Medicine, Semmelweis University, 1085 Budapest, Hungary
- Translational Pancreatology Research Group, Interdisciplinary Centre of Excellence for Research Development and Innovation, University of Szeged, 6720 Szeged, Hungary
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Chen X, Huang Y, Xu Q, Zhang B, Wang Y, Huang M. C-reactive protein to serum calcium ratio as a novel biomarker for predicting severity in acute pancreatitis: a retrospective cross-sectional study. Front Med (Lausanne) 2025; 12:1506543. [PMID: 39991053 PMCID: PMC11842247 DOI: 10.3389/fmed.2025.1506543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2024] [Accepted: 01/29/2025] [Indexed: 02/25/2025] Open
Abstract
Background Acute pancreatitis (AP) is a prevalent gastrointestinal emergency with a wide spectrum of clinical outcomes, varying from mild cases to severe forms. The early identification of high-risk patients is essential for improving prognosis. However, the predictive and prognostic potential of the C-reactive protein to serum calcium ratio (CCR) in AP has not been investigated. This study aims to explore the association between CCR and disease severity in patients with AP. Methods This retrospective cross-sectional study included 476 AP patients. The CCR was calculated from C-reactive protein and serum calcium levels within the first 24 h of admission. Multivariable logistic regression models were used to evaluate the relationship between CCR and AP severity, with restricted cubic spline analysis and receiver operating characteristic (ROC) analysis to assess dose-response and predictive performance, respectively. Results Of the 476 patients, 176 (37%) had mild acute pancreatitis (MAP) and 300 (63%) had moderate to severe AP. The CCR distribution had a median value of 17.5, with an interquartile range (IQR) of 3.0 to 60.2. Each unit increase in CCR was associated with a 7% increase in the risk of developing moderate to severe AP (OR: 1.07; 95% CI: 1.06-1.09). In fully adjusted models, this association remained statistically significant. The area under the curve (AUC) for CCR in predicting moderate to severe AP was 86.9%, with a sensitivity of 73.7% and specificity of 89.2%. Conclusion The CCR measured within the first 24 h of admission shows promise as a valuable biomarker for predicting the severity of AP. However, further multicenter prospective cohort studies are needed to confirm its clinical utility and investigate its role in improving treatment strategies and patient management.
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Ratiu I, Bende R, Nica C, Budii O, Burciu C, Barbulescu A, Moga T, Miutescu B, Sirli R, Danila M, Popescu A, Bende F. Prediction Models of Severity in Acute Biliary Pancreatitis. Diagnostics (Basel) 2025; 15:126. [PMID: 39857010 PMCID: PMC11763760 DOI: 10.3390/diagnostics15020126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2024] [Revised: 12/25/2024] [Accepted: 01/04/2025] [Indexed: 01/27/2025] Open
Abstract
Background: Acute pancreatitis is a common condition with a variable prognosis. While the overall mortality rate of acute pancreatitis is relatively low, ranging between 3 and 5% in most cases, severe forms can result in significantly higher morbidity and mortality. Therefore, early risk assessment is crucial for optimizing management and treatment. The aim of the present study wasto compare simple prognostic markers and identify the best predictors of severity in patients with acute pancreatitis. Material and Methods: A retrospective analysis was carried outon 108 patients admitted in our center during one year with acute biliary pancreatitis. Acute pancreatitis severity was stratified based on the revised Atlanta criteria. Results: 108 subjects (mean age of 60.1 ± 18.6, 65.7% females) diagnosed with acute biliary pancreatitis were included. Based on the Atlanta criteria, 59.3% (64/108) of the subjects were classified as having mild acute biliary pancreatitis, 35.2% (38/108) as having a moderate-severe pancreatitis, and 5.5% (6/108) were classified as having severe acute pancreatitis. In univariate analysis, the following parameterswere associatedwith at least a moderate-severe form of acute pancreatitis: Balthazar score, fasting blood glucose (mg/dL), modified CTSI score, CRP values at 48 h, BISAP score at admission, CTSI score, Ranson score, duration of hospitalization (days), and the presence of leukocytosis (×1000/µL) (all p < 0.05).BISAP score at admission (AUC-0.91), CRP levels at 48 h (AUC-0.92), mCTSI (AUC-0.94), and CTSI score (AUC-0.93) had the highest area under the curve (AUC) for predicting the severity of acute pancreatitis. In multivariate analysis, the model including the following independent parameters was predictive for the severity of acute pancreatitis: CTSI score (p < 0.0001), BISAP score (p = 0.0082), and CRP levels at 48 h (p = 0.0091), respectively. The model showed a slightly higher AUC compared to the independent predictors (AUC-0.96). Conclusions: The use of a multiparametric prediction model can increase the accuracy of predicting severity in patients with acute biliary pancreatitis.
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Affiliation(s)
- Iulia Ratiu
- Department of Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (I.R.); (C.N.); (O.B.); (T.M.); (B.M.); (R.S.); (M.D.); (A.P.); (F.B.)
- Advanced Regional Research Center in Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (C.B.); (A.B.)
| | - Renata Bende
- Department of Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (I.R.); (C.N.); (O.B.); (T.M.); (B.M.); (R.S.); (M.D.); (A.P.); (F.B.)
- Advanced Regional Research Center in Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (C.B.); (A.B.)
| | - Camelia Nica
- Department of Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (I.R.); (C.N.); (O.B.); (T.M.); (B.M.); (R.S.); (M.D.); (A.P.); (F.B.)
- Advanced Regional Research Center in Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (C.B.); (A.B.)
| | - Oana Budii
- Department of Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (I.R.); (C.N.); (O.B.); (T.M.); (B.M.); (R.S.); (M.D.); (A.P.); (F.B.)
| | - Calin Burciu
- Advanced Regional Research Center in Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (C.B.); (A.B.)
- Department of Gastroenterology, Faculty of Medicine, Pharmacy and Dental Medicine, “Vasile Goldis” West University of Arad, 310414 Arad, Romania
| | - Andreea Barbulescu
- Advanced Regional Research Center in Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (C.B.); (A.B.)
| | - Tudor Moga
- Department of Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (I.R.); (C.N.); (O.B.); (T.M.); (B.M.); (R.S.); (M.D.); (A.P.); (F.B.)
- Advanced Regional Research Center in Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (C.B.); (A.B.)
| | - Bogdan Miutescu
- Department of Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (I.R.); (C.N.); (O.B.); (T.M.); (B.M.); (R.S.); (M.D.); (A.P.); (F.B.)
- Advanced Regional Research Center in Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (C.B.); (A.B.)
| | - Roxana Sirli
- Department of Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (I.R.); (C.N.); (O.B.); (T.M.); (B.M.); (R.S.); (M.D.); (A.P.); (F.B.)
- Advanced Regional Research Center in Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (C.B.); (A.B.)
| | - Mirela Danila
- Department of Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (I.R.); (C.N.); (O.B.); (T.M.); (B.M.); (R.S.); (M.D.); (A.P.); (F.B.)
- Advanced Regional Research Center in Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (C.B.); (A.B.)
| | - Alina Popescu
- Department of Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (I.R.); (C.N.); (O.B.); (T.M.); (B.M.); (R.S.); (M.D.); (A.P.); (F.B.)
- Advanced Regional Research Center in Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (C.B.); (A.B.)
| | - Felix Bende
- Department of Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (I.R.); (C.N.); (O.B.); (T.M.); (B.M.); (R.S.); (M.D.); (A.P.); (F.B.)
- Advanced Regional Research Center in Gastroenterology and Hepatology, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania; (C.B.); (A.B.)
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Özdede M, Batur A, Aksoy AE. Improved outcome prediction in acute pancreatitis with generated data and advanced machine learning algorithms. Turk J Emerg Med 2025; 25:32-40. [PMID: 39882088 PMCID: PMC11774427 DOI: 10.4103/tjem.tjem_161_24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2024] [Revised: 10/30/2024] [Accepted: 10/31/2024] [Indexed: 01/31/2025] Open
Abstract
OBJECTIVES Traditional scoring systems have been widely used to predict acute pancreatitis (AP) severity but have limitations in predictive accuracy. This study investigates the use of machine learning (ML) algorithms to improve predictive accuracy in AP. METHODS A retrospective study was conducted using data from 101 AP patients in a tertiary hospital in Türkiye. Data were preprocessed, and synthetic data were generated with Gaussian noise addition and balanced with the ADASYN algorithm, resulting in 250 cases. Supervised ML models, including random forest (RF) and XGBoost (XGB), were trained, tested, and validated against traditional clinical scores (Ranson's, modified Glasgow, and BISAP) using area under the curve (AUC), F1 score, and recall. RESULTS RF outperformed XGB with an AUC of 0.89, F1 score of 0.82, and recall of 0.82. BISAP showed balanced performance (AUC = 0.70, F1 = 0.44, and recall = 0.85), whereas the Glasgow criteria had the highest recall but lower precision (AUC = 0.70, F1 = 0.38, and recall = 0.95). Ranson's admission criteria were the least effective (AUC = 0.53, F1 = 0.42, and recall = 0.39), probable because it lacked the 48th h features. CONCLUSION ML models, especially RF, significantly outperform traditional clinical scores in predicting adverse outcomes in AP, suggesting that integrating ML into clinical practice could improve prognostic assessments.
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Affiliation(s)
- Murat Özdede
- Department of Internal Medicine, Faculty of Medicine, Hacettepe University, Ankara, Türkiye
| | - Ali Batur
- Department of Emergency Medicine, Faculty of Medicine, Hacettepe University, Ankara, Türkiye
| | - Alp Eren Aksoy
- Department of Emergency Medicine, Faculty of Medicine, Hacettepe University, Ankara, Türkiye
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Xing J, Xu M, Xu J, Liu J, He F. Development and validation of a nomogram combining pain score with laboratory indicators for predicting persistent organ failure in acute pancreatitis: a retrospective cohort study. Front Med (Lausanne) 2024; 11:1411288. [PMID: 39165374 PMCID: PMC11333219 DOI: 10.3389/fmed.2024.1411288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Accepted: 07/26/2024] [Indexed: 08/22/2024] Open
Abstract
Background Acute pancreatitis is an inflammatory disease that can lead to persistent organ failure (POF), which is associated with increased morbidity and mortality. Early prediction of POF in AP can significantly improve patient outcomes. Objective To develop and validate a nomogram that combines pain score with laboratory indicators for predicting POF in patients with AP. Methods A retrospective cohort study was conducted, including patients diagnosed with AP. Pain score and laboratory indicators were collected within the first 24 h of admission. A nomogram was developed using logistic regression models and validated in a separate cohort. Results There were 807 patients in the training cohort and 375 patients in the internal validation cohort.Multivariate logistic regression demonstrated that pain score, serum creatinine, hematocrit, serum calcium, and serum albumin were independent risk factors for the incidence of POF in patients with AP. The area under the curve of the nomogram constructed from the above factors were 0.924, respectively. The model demonstrated good calibration and discrimination in both the development and validation cohorts. Conclusion The nomogram had a good performance in predicting POF in patients with AP and can be used to guide clinical decision-making.
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Affiliation(s)
- Jiayu Xing
- Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Musen Xu
- Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
| | - Jiale Xu
- Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
| | - Jiao Liu
- Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Fang He
- Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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McDermott J, Kao LS, Keeley JA, Nahmias J, de Virgilio C. Management of Gallstone Pancreatitis: A Review. JAMA Surg 2024; 159:818-825. [PMID: 38691369 DOI: 10.1001/jamasurg.2023.8111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2024]
Abstract
Importance Gallstone pancreatitis (GSP) is the leading cause of acute pancreatitis, accounting for approximately 50% of cases. Without appropriate and timely treatment, patients are at increased risk of disease progression and recurrence. While there is increasing consensus among guidelines for the management of mild GSP, adherence to these guidelines remains poor. In addition, there is minimal evidence to guide clinicians in the treatment of moderately severe and severe pancreatitis. Observations The management of GSP continues to evolve and is dependent on severity of acute pancreatitis and concomitant biliary diagnoses. Across the spectrum of severity, there is evidence that goal-directed, moderate fluid resuscitation decreases the risk of fluid overload and mortality compared with aggressive resuscitation. Patients with isolated, mild GSP should undergo same-admission cholecystectomy; early cholecystectomy within 48 hours of admission has been supported by several randomized clinical trials. Cholecystectomy should be delayed for patients with severe disease; for severe and moderately severe disease, the optimal timing remains unclear. Preoperative endoscopic retrograde cholangiopancreatography (ERCP) is only useful for patients with suspected cholangitis or biliary obstruction, although the concomitance of these conditions in patients with GSP is rare. Modality of evaluation of the common bile duct to rule out concomitant choledocholithiasis varies and should be tailored to level of concern based on objective measures, such as laboratory results and imaging findings. Among these modalities, intraoperative cholangiography is associated with reduced length of stay and decreased use of ERCP. However, the benefit of routine intraoperative cholangiography remains in question. Conclusions and Relevance Treatment of GSP is dependent on disease severity, which can be difficult to assess. A comprehensive review of clinically relevant evidence and recommendations on GSP severity grading, fluid resuscitation, timing of cholecystectomy, need for ERCP, and evaluation and management of persistent choledocholithiasis can help guide clinicians in diagnosis and management.
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Affiliation(s)
- James McDermott
- David Geffen School of Medicine, University of California, Los Angeles
| | - Lillian S Kao
- Department of Surgery, McGovern Medical School, The University of Texas Health Science Center at Houston
| | - Jessica A Keeley
- Department of Surgery, Harbor-UCLA Medical Center, Torrance, California
| | - Jeffry Nahmias
- Division of Trauma, Burns, and Surgical Critical Care, Department of Surgery, University of California, Irvine, Orange
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Zhang C, Peng J, Wang L, Wang Y, Chen W, Sun MW, Jiang H. A deep learning-powered diagnostic model for acute pancreatitis. BMC Med Imaging 2024; 24:154. [PMID: 38902660 PMCID: PMC11188273 DOI: 10.1186/s12880-024-01339-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Accepted: 06/17/2024] [Indexed: 06/22/2024] Open
Abstract
BACKGROUND Acute pancreatitis is one of the most common diseases requiring emergency surgery. Rapid and accurate recognition of acute pancreatitis can help improve clinical outcomes. This study aimed to develop a deep learning-powered diagnostic model for acute pancreatitis. MATERIALS AND METHODS In this investigation, we enrolled a cohort of 190 patients with acute pancreatitis who were admitted to Sichuan Provincial People's Hospital between January 2020 and December 2021. Abdominal computed tomography (CT) scans were obtained from both patients with acute pancreatitis and healthy individuals. Our model was constructed using two modules: (1) the acute pancreatitis classifier module; (2) the pancreatitis lesion segmentation module. Each model's performance was assessed based on precision, recall rate, F1-score, Area Under the Curve (AUC), loss rate, frequency-weighted accuracy (fwavacc), and Mean Intersection over Union (MIOU). RESULTS Upon admission, significant variations were observed between patients with mild and severe acute pancreatitis in inflammatory indexes, liver, and kidney function indicators, as well as coagulation parameters. The acute pancreatitis classifier module exhibited commendable diagnostic efficacy, showing an impressive AUC of 0.993 (95%CI: 0.978-0.999) in the test set (comprising healthy examination patients vs. those with acute pancreatitis, P < 0.001) and an AUC of 0.850 (95%CI: 0.790-0.898) in the external validation set (healthy examination patients vs. patients with acute pancreatitis, P < 0.001). Furthermore, the acute pancreatitis lesion segmentation module demonstrated exceptional performance in the validation set. For pancreas segmentation, peripancreatic inflammatory exudation, peripancreatic effusion, and peripancreatic abscess necrosis, the MIOU values were 86.02 (84.52, 87.20), 61.81 (56.25, 64.83), 57.73 (49.90, 68.23), and 66.36 (55.08, 72.12), respectively. These findings underscore the robustness and reliability of the developed models in accurately characterizing and assessing acute pancreatitis. CONCLUSION The diagnostic model for acute pancreatitis, driven by deep learning, exhibits excellent efficacy in accurately evaluating the severity of the condition. TRIAL REGISTRATION This is a retrospective study.
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Affiliation(s)
- Chi Zhang
- Department of Intensive Care Medicine, The Third People's Hospital of Chengdu, Affiliated Hospital of Southwest Jiaotong University, Chengdu, China
| | - Jin Peng
- Institute for Emergency and Disaster Medicine, School of Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Department of Histology and Neuroscience, Sichuan University, Chengdu, China
| | - Lu Wang
- Institute for Emergency and Disaster Medicine, School of Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Department of Emergency Medicine, School of Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Sichuan Provincial Clinical Research Center for Emergency and Critical Care, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Yu Wang
- Sichuan Provincial Clinical Research Center for Emergency and Critical Care, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Department of Clinical Nutrition, Peking Union Medical College Hospital, Beijing, China
| | - Wei Chen
- Department of Clinical Nutrition, Peking Union Medical College Hospital, Beijing, China
| | - Ming-Wei Sun
- Institute for Emergency and Disaster Medicine, School of Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Hua Jiang
- Institute for Emergency and Disaster Medicine, School of Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
- Department of Emergency Medicine, School of Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
- Sichuan Provincial Clinical Research Center for Emergency and Critical Care, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
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Liu Q, Yang J, Zhang J. Factors affecting the time interval of endoscopic ultrasound-guided endoscopic necrosectomy of walled-off pancreatic necrosis: A retrospective single-center study in China. Pancreatology 2024; 24:357-362. [PMID: 38369393 DOI: 10.1016/j.pan.2024.02.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 02/07/2024] [Accepted: 02/12/2024] [Indexed: 02/20/2024]
Abstract
BACKGROUND AND AIM Endoscopic ultrasound (EUS)-guided endoscopic necrosectomy is an effective and minimally invasive treatment for walled-off pancreatic necrosis (WON). This study investigated the factors affecting the time interval of EUS-guided WON necrosectomy. METHODS Patients who received EUS-guided necrosectomy in the Endoscopy Center of the First Affiliated Hospital of Chongqing Medical University in the past 5 years were retrospectively analyzed. Data including general information, etiology, blood biochemical indexes, physical signs, CT severity grade, location, size, solid necrotic ratio, type and number of stents, and immediate necrosectomy were collected to explore the relationships between these factors and the interval of endoscopic necrosectomy. RESULTS A total of 51 WON patients were included. No significant correlation has been noted between the endoscopic debridement interval and the following indexes, including the patients' general information, the etiology of pancreatitis, blood biochemical indexes (leukocyte count, neutrophil percentage, C-reactive protein), preoperative fever, and WON's location and size, type and number of stents, and whether immediate necrosectomy. However, there were significant differences between the debridement interval and the modified CT Severity Index (MCTSI) (p < 0.001), the solid necrotic ratio of WON (p < 0.001) before the intervention, postoperative fever (p = 0.038), C-reactive protein increasing (p = 0.012) and fever before reintervention (p = 0.024). CONCLUSIONS The EUS-measured solid necrotic ratio, the MCTSI, postoperative fever, C-reactive protein increase, and fever before reintervention in patients affect the time interval of EUS-guided endoscopic necrosectomy in WON patients. These five indicators may be promisingly effective in predicting and managing endoscopic necrosectomy intervals.
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Affiliation(s)
- Qing Liu
- Department of Gastroenterology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Jian Yang
- Department of Gastroenterology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Junwen Zhang
- Department of Gastroenterology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
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Qian R, Zhuang J, Xie J, Cheng H, Ou H, Lu X, Ouyang Z. Predictive value of machine learning for the severity of acute pancreatitis: A systematic review and meta-analysis. Heliyon 2024; 10:e29603. [PMID: 38655348 PMCID: PMC11035062 DOI: 10.1016/j.heliyon.2024.e29603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 04/02/2024] [Accepted: 04/10/2024] [Indexed: 04/26/2024] Open
Abstract
Background Predicting the severity of acute pancreatitis (AP) early poses a challenge in clinical practice. While there are well-established clinical scoring tools, their actual predictive performance remains uncertain. Various studies have explored the application of machine-learning methods for early AP prediction. However, a more comprehensive evidence-based assessment is needed to determine their predictive accuracy. Hence, this systematic review and meta-analysis aimed to evaluate the predictive accuracy of machine learning in assessing the severity of AP. Methods PubMed, EMBASE, Cochrane Library, and Web of Science were systematically searched until December 5, 2023. The risk of bias in eligible studies was assessed using the Prediction Model Risk of Bias Assessment Tool (PROBAST). Subgroup analyses, based on different machine learning types, were performed. Additionally, the predictive accuracy of mainstream scoring tools was summarized. Results This systematic review ultimately included 33 original studies. The pooled c-index in both the training and validation sets was 0.87 (95 % CI: 0.84-0.89) and 0.88 (95 % CI: 0.86-0.90), respectively. The sensitivity in the training set was 0.81 (95 % CI: 0.77-0.84), and in the validation set, it was 0.79 (95 % CI: 0.71-0.85). The specificity in the training set was 0.84 (95 % CI: 0.78-0.89), and in the validation set, it was 0.90 (95 % CI: 0.86-0.93). The primary model incorporated was logistic regression; however, its predictive accuracy was found to be inferior to that of neural networks, random forests, and xgboost. The pooled c-index of the APACHE II, BISAP, and Ranson were 0.74 (95 % CI: 0.68-0.80), 0.77 (95 % CI: 0.70-0.85), and 0.74 (95 % CI: 0.68-0.79), respectively. Conclusions Machine learning demonstrates excellent accuracy in predicting the severity of AP, providing a reference for updating or developing a straightforward clinical prediction tool.
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Affiliation(s)
- Rui Qian
- Department of Gastroenterology, Shenzhen Bao'an Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen 518000, China
| | - Jiamei Zhuang
- The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, 518033, China
| | - Jianjun Xie
- Department of Gastroenterology, Shenzhen Bao'an Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen 518000, China
| | - Honghui Cheng
- Department of Gastroenterology, Shenzhen Bao'an Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen 518000, China
| | - Haiya Ou
- Department of Gastroenterology, Shenzhen Bao'an Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen 518000, China
| | - Xiang Lu
- Department of Plumonary and Critical Care Medicine, Shenzhen Bao'an Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen 518000, China
| | - Zichen Ouyang
- Department of Hepatology, Shenzhen Bao'an Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen 518000, China
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Zhu J, Wu L, Wang Y, Fang M, Liu Q, Zhang X. Predictive value of the Ranson and BISAP scoring systems for the severity and prognosis of acute pancreatitis: A systematic review and meta-analysis. PLoS One 2024; 19:e0302046. [PMID: 38687745 PMCID: PMC11060534 DOI: 10.1371/journal.pone.0302046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 03/26/2024] [Indexed: 05/02/2024] Open
Abstract
BACKGROUND To systematically assess and compare the predictive value of the Ranson and Bedside Index of Severity in Acute Pancreatitis (BISAP) scoring systems for the severity and prognosis of acute pancreatitis (AP). METHODS PubMed, Embase, Cochrane Library, and Web of Science were systematically searched until February 15, 2023. Outcomes in this analysis included severity and prognosis [mortality, organ failure, pancreatic necrosis, and intensive care unit (ICU) admission]. The revised Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was used to evaluate the quality of diagnostic accuracy studies. The threshold effect was evaluated for each outcome. The sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the summary receiver operating characteristic (SROC) curve (AUC) as well as 95% confidence intervals (CI) were calculated. The DeLong test was used for AUC comparisons. For the outcome evaluated by over 9 studies, publication bias was assessed using the Deeks' funnel plot asymmetry test. RESULTS Totally 17 studies of 5476 AP patients were included. For severity, the pooled sensitivity of the Ranson and BISAP was 0.95 (95%CI: 0.87, 0.98) and 0.67 (95%CI: 0.27, 0.92); the pooled specificity of the Ranson and BISAP was 0.74 (0.52, 0.88) and 0.95 (95%CI: 0.85, 0.98); the pooled AUC of the Ranson and BISAP was 0.95 (95%CI: 0.93, 0.97) and 0.94 (95%CI: 0.92, 0.96) (P = 0.480). For mortality, the pooled sensitivity of the Ranson and BISAP was 0.89 (95%CI: 0.73, 0.96) and 0.77 (95%CI: 0.58, 0.89); the pooled specificity of the Ranson and BISAP was 0.79 (95%CI: 0.68, 0.87) and 0.90 (95%CI: 0.86, 0.93); the pooled AUC of the Ranson and BISAP was 0.91 (95%CI: 0.88, 0.93) and 0.92 (95%CI: 0.90, 0.94) (P = 0.480). For organ failure, the pooled sensitivity of the Ranson and BISAP was 0.84 (95%CI: 0.76, 0.90) and 0.78 (95%CI: 0.60, 0.90); the pooled specificity of the Ranson and BISAP was 0.84 (95%CI: 0.63, 0.94) and 0.90 (95%CI: 0.72, 0.97); the pooled AUC of the Ranson and BISAP was 0.86 (95%CI: 0.82, 0.88) and 0.90 (95%CI: 0.87, 0.93) (P = 0.110). For pancreatic necrosis, the pooled sensitivity of the Ranson and BISAP was 0.63 (95%CI: 0.35, 0.84) and 0.63 (95%CI: 0.23, 0.90); the pooled specificity of the Ranson and BISAP was 0.90 (95%CI: 0.77, 0.96) and 0.93 (95%CI: 0.89, 0.96); the pooled AUC of the Ranson and BISAP was 0.87 (95%CI: 0.84, 0.90) and 0.93 (95%CI: 0.91, 0.95) (P = 0.001). For ICU admission, the pooled sensitivity of the Ranson and BISAP was 0.86 (95%CI: 0.77, 0.92) and 0.63 (95%CI: 0.52, 0.73); the pooled specificity of the Ranson and BISAP was 0.58 (95%CI: 0.55, 0.61) and 0.84 (95%CI: 0.81, 0.86); the pooled AUC of the Ranson and BISAP was 0.92 (95%CI: 0.81, 1.00) and 0.86 (95%CI: 0.67, 1.00) (P = 0.592). CONCLUSION The Ranson score was an applicable tool for predicting severity and prognosis of AP patients with reliable diagnostic accuracy in resource and time-limited settings. Future large-scale studies are needed to verify the findings.
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Affiliation(s)
- Jianpeng Zhu
- The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Linfei Wu
- The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Yue Wang
- Zhejiang University of Medicine, Hangzhou, Zhejiang, China
| | - Mengdie Fang
- The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Qiang Liu
- Department of Gastroenterology, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xiaofeng Zhang
- Department of Gastroenterology, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
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Shu L, Yan H, Wu Y, Yan T, Yang L, Zhang S, Chen Z, Liao Q, Yang L, Xiao B, Ye M, Lv S, Wu M, Zhu X, Hu P. Explainable machine learning in outcome prediction of high-grade aneurysmal subarachnoid hemorrhage. Aging (Albany NY) 2024; 16:4654-4669. [PMID: 38431285 PMCID: PMC10968679 DOI: 10.18632/aging.205621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 01/29/2024] [Indexed: 03/05/2024]
Abstract
OBJECTIVE Accurate prognostic prediction in patients with high-grade aneruysmal subarachnoid hemorrhage (aSAH) is essential for personalized treatment. In this study, we developed an interpretable prognostic machine learning model for high-grade aSAH patients using SHapley Additive exPlanations (SHAP). METHODS A prospective registry cohort of high-grade aSAH patients was collected in one single-center hospital. The endpoint in our study is a 12-month follow-up outcome. The dataset was divided into training and validation sets in a 7:3 ratio. Machine learning algorithms, including Logistic regression model (LR), support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost), were employed to develop a prognostic prediction model for high-grade aSAH. The optimal model was selected for SHAP analysis. RESULTS Among the 421 patients, 204 (48.5%) exhibited poor prognosis. The RF model demonstrated superior performance compared to LR (AUC = 0.850, 95% CI: 0.783-0.918), SVM (AUC = 0.862, 95% CI: 0.799-0.926), and XGBoost (AUC = 0.850, 95% CI: 0.783-0.917) with an AUC of 0.867 (95% CI: 0.806-0 .929). Primary prognostic features identified through SHAP analysis included higher World Federation of Neurosurgical Societies (WFNS) grade, higher modified Fisher score (mFS) and advanced age, were found to be associated with 12-month unfavorable outcome, while the treatment of coiling embolization for aSAH drove the prediction towards favorable prognosis. Additionally, the SHAP force plot visualized individual prognosis predictions. CONCLUSIONS This study demonstrated the potential of machine learning techniques in prognostic prediction for high-grade aSAH patients. The features identified through SHAP analysis enhance model interpretability and provide guidance for clinical decision-making.
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Affiliation(s)
- Lei Shu
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Hua Yan
- Department of Emergency, Affiliated Hospital of Panzhihua University, Panzhihua 617000, Sichuan, China
| | - Yanze Wu
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Tengfeng Yan
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Li Yang
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Si Zhang
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Zhihao Chen
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Qiuye Liao
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Lu Yang
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Bing Xiao
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Minhua Ye
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Shigang Lv
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Miaojing Wu
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Xingen Zhu
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Ping Hu
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
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Kashintsev AA, Anisimov SV, Nadeeva A, Proutski V. Early selective enteral feeding in treatment of acute pancreatitis: A case report. World J Clin Cases 2024; 12:637-642. [PMID: 38322476 PMCID: PMC10841949 DOI: 10.12998/wjcc.v12.i3.637] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 12/08/2023] [Accepted: 01/05/2024] [Indexed: 01/18/2024] Open
Abstract
BACKGROUND Early initiation of enteral feeding is recognized to play a crucial role in improving the outcomes of treatment of acute pancreatitis. However, the method of administration of enteral nutrition remains debatable. We present the experience of treating a patient with moderate-severe acute pancreatitis, at high risk of progressing to a severe or fatal condition, using a novel method of selective feeding with duodenal isolation. CASE SUMMARY A 27-year-old female patient presented to the emergency unit of the hospital with a typical manifestation of acute pancreatitis. Despite a conventional treatment, the patient's condition deteriorated by day 2 of hospitalization. Using an endoscopic approach, a novel catheter PandiCath® was placed to the duodenum of the patient, isolating its segment between the duodenal bulb and the ligament of Treitz. In the isolated area created, a negative pressure was applied, followed by introduction of early selective enteral feeding. The patient's condition subsequently improved in a rapid manner, and no complications often associated with moderate-to-severe acute pancreatitis developed. CONCLUSION Within 48 h of starting treatment with the novel method, it can prevent the development of multiple organ failure and, when combined with minimally invasive drainage methods, help prevent infection.
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Yu X, Zhang N, Wu J, Zhao Y, Liu C, Liu G. Predictive value of adipokines for the severity of acute pancreatitis: a meta-analysis. BMC Gastroenterol 2024; 24:32. [PMID: 38218787 PMCID: PMC10787974 DOI: 10.1186/s12876-024-03126-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 01/04/2024] [Indexed: 01/15/2024] Open
Abstract
BACKGROUND Severe acute pancreatitis (SAP) is a dangerous condition with a high mortality rate. Many studies have found an association between adipokines and the development of SAP, but the results are controversial. Therefore, we performed a meta-analysis of the association of inflammatory adipokines with SAP. METHODS We screened PubMed, EMBASE, Web of Science and Cochrane Library for articles on adipokines and SAP published before July 20, 2023. The quality of the literature was assessed using QUADAS criteria. Standardized mean differences (SMD) with 95% confidence intervals (CI) were calculated to assess the combined effect. Subgroup analysis, sensitivity analysis and publication bias tests were also performed on the information obtained. RESULT Fifteen eligible studies included 1332 patients with acute pancreatitis (AP). Pooled analysis showed that patients with SAP had significantly higher serum levels of resistin (SMD = 0.78, 95% CI:0.37 to 1.19, z = 3.75, P = 0.000). The difference in leptin and adiponectin levels between SAP and mild acute pancreatitis (MAP) patients were not significant (SMD = 0.30, 95% CI: -0.08 to 0.68, z = 1.53, P = 0.127 and SMD = 0.11, 95% CI: -0.17 to 0.40, z = 0.80, P = 0.425, respectively). In patients with SAP, visfatin levels were not significantly different from that in patients with MAP (SMD = 1.20, 95% CI: -0.48 to 2.88, z = 1.40, P = 0.162). CONCLUSION Elevated levels of resistin are associated with the development of SAP. Resistin may serve as biomarker for SAP and has promise as therapeutic target.
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Affiliation(s)
- Xuehua Yu
- Hebei North University, Zhangjiakou, 075132, China
- Department of Gastroenterology, Hebei General Hospital, No.348, Heping West Road, Shijiazhuang, Hebei Province, 050057, China
| | - Ning Zhang
- Department of Gastroenterology, Hebei General Hospital, No.348, Heping West Road, Shijiazhuang, Hebei Province, 050057, China
- Hebei Medical University, Shijiazhuang, 050011, China
| | - Jing Wu
- Department of Gastroenterology, Hebei General Hospital, No.348, Heping West Road, Shijiazhuang, Hebei Province, 050057, China
| | - Yunhong Zhao
- Department of Gastroenterology, Hebei General Hospital, No.348, Heping West Road, Shijiazhuang, Hebei Province, 050057, China
| | - Chengjiang Liu
- Department of Gastroenterology, Anhui Medical University, He Fei, 230601, China
| | - Gaifang Liu
- Department of Gastroenterology, Hebei General Hospital, No.348, Heping West Road, Shijiazhuang, Hebei Province, 050057, China.
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Capurso G, Ponz de Leon Pisani R, Lauri G, Archibugi L, Hegyi P, Papachristou GI, Pandanaboyana S, Maisonneuve P, Arcidiacono PG, de‐Madaria E. Clinical usefulness of scoring systems to predict severe acute pancreatitis: A systematic review and meta-analysis with pre and post-test probability assessment. United European Gastroenterol J 2023; 11:825-836. [PMID: 37755341 PMCID: PMC10637128 DOI: 10.1002/ueg2.12464] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Accepted: 08/05/2023] [Indexed: 09/28/2023] Open
Abstract
BACKGROUND Scoring systems for severe acute pancreatitis (SAP) prediction should be used in conjunction with pre-test probability to establish post-test probability of SAP, but data of this kind are lacking. OBJECTIVE To investigate the predictive value of commonly employed scoring systems and their usefulness in modifying the pre-test probability of SAP. METHODS Following PRISMA statement and MOOSE checklists after PROSPERO registration, PubMed was searched from inception until September 2022. Retrospective, prospective, cross-sectional studies or clinical trials on patients with acute pancreatitis defined as Revised Atlanta Criteria, reporting rate of SAP and using at least one score among Bedside Index for Severity in Acute Pancreatitis (BISAP), Acute Physiology and Chronic Health Examination (APACHE)-II, RANSON, and Systemic Inflammatory Response Syndrome (SIRS) with their sensitivity and specificity were included. Random effects model meta-analyses were performed. Pre-test probability and likelihood ratio (LR) were combined to estimate post-test probability on Fagan nomograms. Pooled severity rate was used as pre-test probability of SAP and pooled sensitivity and specificity to calculate LR and generate post-test probability. A priori hypotheses for heterogeneity were developed and sensitivity analyses planned. RESULTS 43 studies yielding 14,116 acute pancreatitis patients were included: 42 with BISAP, 30 with APACHE-II, 27 with Ranson, 8 with SIRS. Pooled pre-test probability of SAP ranged 16.6%-25.3%. The post-test probability of SAP with positive/negative score was 47%/6% for BISAP, 43%/5% for APACHE-II, 48%/5% for Ranson, 40%/12% for SIRS. In 18 studies comparing BISAP, APACHE-II, and Ranson in 6740 patients with pooled pre-test probability of SAP of 18.7%, post-test probability when scores were positive was 48% for BISAP, 46% for APACHE-II, 50% for Ranson. When scores were negative, post-test probability dropped to 7% for BISAP, 6% for Ranson, 5% for APACHE-II. Quality, design, and country of origin of the studies did not explain the observed high heterogeneity. CONCLUSIONS The most commonly used scoring systems to predict SAP perform poorly and do not aid in decision-making.
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Affiliation(s)
- Gabriele Capurso
- Pancreato‐Biliary Endoscopy and Endosonography DivisionPancreas Translational & Clinical Research CenterSan Raffaele Scientific Institute IRCCSVita‐Salute San Raffaele UniversityMilanItaly
| | - Ruggero Ponz de Leon Pisani
- Pancreato‐Biliary Endoscopy and Endosonography DivisionPancreas Translational & Clinical Research CenterSan Raffaele Scientific Institute IRCCSVita‐Salute San Raffaele UniversityMilanItaly
| | - Gaetano Lauri
- Pancreato‐Biliary Endoscopy and Endosonography DivisionPancreas Translational & Clinical Research CenterSan Raffaele Scientific Institute IRCCSVita‐Salute San Raffaele UniversityMilanItaly
| | - Livia Archibugi
- Pancreato‐Biliary Endoscopy and Endosonography DivisionPancreas Translational & Clinical Research CenterSan Raffaele Scientific Institute IRCCSVita‐Salute San Raffaele UniversityMilanItaly
| | - Peter Hegyi
- Centre for Translational MedicineSemmelweis UniversityBudapestHungary
- Institute of Pancreatic DiseasesSemmelweis UniversityBudapestHungary
- Translational Pancreatology Research GroupInterdisciplinary Centre of Excellence for Research Development and Innovation University of SzegedSzegedHungary
| | - Georgios I. Papachristou
- Division of Gastroenterology, Hepatology, and NutritionThe Ohio State UniversityWexner Medical CenterColumbusOhioUSA
| | - Sanjay Pandanaboyana
- Department of Hepato‐Pancreato‐Biliary and Transplant SurgeryThe Freeman HospitalNewcastle upon TyneTyne and WearUK
- Population Health Sciences InstituteNewcastle UniversityNewcastleUK
| | - Patrick Maisonneuve
- Division of Epidemiology and BiostatisticsIEO European Institute of OncologyMilanItaly
| | - Paolo Giorgio Arcidiacono
- Pancreato‐Biliary Endoscopy and Endosonography DivisionPancreas Translational & Clinical Research CenterSan Raffaele Scientific Institute IRCCSVita‐Salute San Raffaele UniversityMilanItaly
| | - Enrique de‐Madaria
- Gastroenterology DepartmentDr. Balmis General University HospitalISABIALAlicanteSpain
- Department of Clinical MedicineMiguel Hernández UniversityElcheSpain
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15
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Hu JX, Zhao CF, Wang SL, Tu XY, Huang WB, Chen JN, Xie Y, Chen CR. Acute pancreatitis: A review of diagnosis, severity prediction and prognosis assessment from imaging technology, scoring system and artificial intelligence. World J Gastroenterol 2023; 29:5268-5291. [PMID: 37899784 PMCID: PMC10600804 DOI: 10.3748/wjg.v29.i37.5268] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 07/31/2023] [Accepted: 09/14/2023] [Indexed: 09/25/2023] Open
Abstract
Acute pancreatitis (AP) is a potentially life-threatening inflammatory disease of the pancreas, with clinical management determined by the severity of the disease. Diagnosis, severity prediction, and prognosis assessment of AP typically involve the use of imaging technologies, such as computed tomography, magnetic resonance imaging, and ultrasound, and scoring systems, including Ranson, Acute Physiology and Chronic Health Evaluation II, and Bedside Index for Severity in AP scores. Computed tomography is considered the gold standard imaging modality for AP due to its high sensitivity and specificity, while magnetic resonance imaging and ultrasound can provide additional information on biliary obstruction and vascular complications. Scoring systems utilize clinical and laboratory parameters to classify AP patients into mild, moderate, or severe categories, guiding treatment decisions, such as intensive care unit admission, early enteral feeding, and antibiotic use. Despite the central role of imaging technologies and scoring systems in AP management, these methods have limitations in terms of accuracy, reproducibility, practicality and economics. Recent advancements of artificial intelligence (AI) provide new opportunities to enhance their performance by analyzing vast amounts of clinical and imaging data. AI algorithms can analyze large amounts of clinical and imaging data, identify scoring system patterns, and predict the clinical course of disease. AI-based models have shown promising results in predicting the severity and mortality of AP, but further validation and standardization are required before widespread clinical application. In addition, understanding the correlation between these three technologies will aid in developing new methods that can accurately, sensitively, and specifically be used in the diagnosis, severity prediction, and prognosis assessment of AP through complementary advantages.
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Affiliation(s)
- Jian-Xiong Hu
- Intensive Care Unit, The Affiliated Hospital of Putian University, Putian 351100, Fujian Province, China
| | - Cheng-Fei Zhao
- School of Pharmacy and Medical Technology, Putian University, Putian 351100, Fujian Province, China
- Key Laboratory of Pharmaceutical Analysis and Laboratory Medicine, Putian University, Putian 351100, Fujian Province, China
| | - Shu-Ling Wang
- Department of Critical Care Medicine, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
| | - Xiao-Yan Tu
- Department of Critical Care Medicine, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
| | - Wei-Bin Huang
- Department of Critical Care Medicine, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
| | - Jun-Nian Chen
- Department of Critical Care Medicine, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
| | - Ying Xie
- School of Mechanical, Electrical and Information Engineering, Putian University, Putian 351100, Fujian Province, China
| | - Cun-Rong Chen
- Department of Critical Care Medicine, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
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Lin XY, Lai YX, Lin Y, Lin ZH. Low-grade inflammation for predicting severe acute pancreatitis in patients with hypertriglyceridemic acute pancreatitis. J Dig Dis 2023; 24:562-569. [PMID: 37796144 DOI: 10.1111/1751-2980.13231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 08/30/2023] [Accepted: 10/04/2023] [Indexed: 10/06/2023]
Abstract
OBJECTIVES We aimed to evaluate the association between low-grade inflammation (LGI) and the severity of hypertriglyceridemic acute pancreatitis (HTG-AP). METHODS We retrospectively reviewed 311 patients with HTG-AP who were admitted to the Department of Gastroenterology, Fujian Provincial Hospital between April 2012 and March 2021. Inpatient medical and radiological records were reviewed to collect the clinical manifestations, disease severity, and comorbidities. C-reactive protein (CRP) level, white blood cell (WBC) count, platelet (PLT) count, and neutrophil-to-lymphocyte ratio (NLR) were considered LGI components and were combined to calculate a standardized LGI score. The association between the LGI score and the severity of HTG-AP was analyzed using univariate and multivariate logistic regression analyses. RESULTS Of the 311 patients with HTG-AP, 47 (15.1%) had mild acute pancreatitis (MAP), 184 (59.2%) had moderately severe acute pancreatitis (MSAP), and 80 (25.7%) had severe acute pancreatitis (SAP), respectively. Patients with MSAP and SAP had a higher LGI score than those with MAP (1.50 vs -6.00, P < 0.001). Univariate logistic regression analysis revealed that patients with LGI scores in the fourth quartile were more likely to have MSAP and SAP (odds ratio [OR] 21.925, 95% confidence interval [CI] 5.014-95.867, P < 0.001). The multivariate logistic regression analysis confirmed that low calcium (OR 0.105, 95% CI 0.011-0.969, P = 0.047) and high LGI score (OR 1.253, 95% CI 1.066-1.473, P = 0.006) were associated with MSAP and SAP. When predicting the severity of acute pancreatitis, the LGI score had the highest area under the receiver operating characteristic (ROC) curve (0.7737) compared to its individual components. CONCLUSION An elevated LGI score was associated with a higher risk of SAP in patients with HTG-AP.
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Affiliation(s)
- Xue Yan Lin
- Department of Gastroenterology, Fujian Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, China
| | - Yong Xing Lai
- Department of Gerontology, Fujian Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, China
| | - Yi Lin
- Department of Gastroenterology, Fujian Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, China
| | - Zhi Hui Lin
- Department of Gastroenterology, Fujian Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, China
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Váncsa S, Sipos Z, Váradi A, Nagy R, Ocskay K, Juhász FM, Márta K, Teutsch B, Mikó A, Hegyi PJ, Vincze Á, Izbéki F, Czakó L, Papp M, Hamvas J, Varga M, Török I, Mickevicius A, Erőss B, Párniczky A, Szentesi A, Pár G, Hegyi P. Metabolic-associated fatty liver disease is associated with acute pancreatitis with more severe course: Post hoc analysis of a prospectively collected international registry. United European Gastroenterol J 2023; 11:371-382. [PMID: 37062947 PMCID: PMC10165320 DOI: 10.1002/ueg2.12389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 03/21/2023] [Indexed: 04/18/2023] Open
Abstract
INTRODUCTION Non-alcoholic fatty liver disease (NAFLD) is a proven risk factor for acute pancreatitis (AP). However, NAFLD has recently been redefined as metabolic-associated fatty liver disease (MAFLD). In this post hoc analysis, we quantified the effect of MAFLD on the outcomes of AP. METHODS We identified our patients from the multicentric, prospective International Acute Pancreatitis Registry of the Hungarian Pancreatic Study Group. Next, we compared AP patients with and without MAFLD and the individual components of MAFLD regarding in-hospital mortality and AP severity based on the revised Atlanta classification. Lastly, we calculated odds ratios (ORs) with 95% confidence intervals (CIs) using multivariate logistic regression analysis. RESULTS MAFLD had a high prevalence in AP, 39% (801/2053). MAFLD increased the odds of moderate-to-severe AP (OR = 1.43, CI: 1.09-1.89). However, the odds of in-hospital mortality (OR = 0.89, CI: 0.42-1.89) and severe AP (OR = 1.70, CI: 0.97-3.01) were not higher in the MAFLD group. Out of the three diagnostic criteria of MAFLD, the highest odds of severe AP was in the group based on metabolic risk abnormalities (OR = 2.68, CI: 1.39-5.09). In addition, the presence of one, two, and three diagnostic criteria dose-dependently increased the odds of moderate-to-severe AP (OR = 1.23, CI: 0.88-1.70, OR = 1.38, CI: 0.93-2.04, and OR = 3.04, CI: 1.63-5.70, respectively) and severe AP (OR = 1.13, CI: 0.54-2.27, OR = 2.08, CI: 0.97-4.35, and OR = 4.76, CI: 1.50-15.4, respectively). Furthermore, in patients with alcohol abuse and aged ≥60 years, the effect of MAFLD became insignificant. CONCLUSIONS MAFLD is associated with AP severity, which varies based on the components of its diagnostic criteria. Furthermore, MAFLD shows a dose-dependent effect on the outcomes of AP.
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18
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Luo Z, Shi J, Fang Y, Pei S, Lu Y, Zhang R, Ye X, Wang W, Li M, Li X, Zhang M, Xiang G, Pan Z, Zheng X. Development and evaluation of machine learning models and nomogram for the prediction of severe acute pancreatitis. J Gastroenterol Hepatol 2023; 38:468-475. [PMID: 36653317 DOI: 10.1111/jgh.16125] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 12/27/2022] [Accepted: 01/16/2023] [Indexed: 01/20/2023]
Abstract
BACKGROUND AND AIM Severe acute pancreatitis (SAP) in patients progresses rapidly and can cause multiple organ failures associated with high mortality. We aimed to train a machine learning (ML) model and establish a nomogram that could identify SAP, early in the course of acute pancreatitis (AP). METHODS In this retrospective study, 631 patients with AP were enrolled in the training cohort. For predicting SAP early, five supervised ML models were employed, such as random forest (RF), K-nearest neighbors (KNN), and naive Bayes (NB), which were evaluated by accuracy (ACC) and the areas under the receiver operating characteristic curve (AUC). The nomogram was established, and the predictive ability was assessed by the calibration curve and AUC. They were externally validated by an independent cohort of 109 patients with AP. RESULTS In the training cohort, the AUC of RF, KNN, and NB models were 0.969, 0.954, and 0.951, respectively, while the AUC of the Bedside Index for Severity in Acute Pancreatitis (BISAP), Ranson and Glasgow scores were only 0.796, 0.847, and 0.837, respectively. In the validation cohort, the RF model also showed the highest AUC, which was 0.961. The AUC for the nomogram was 0.888 and 0.955 in the training and validation cohort, respectively. CONCLUSIONS Our findings suggested that the RF model exhibited the best predictive performance, and the nomogram provided a visual scoring model for clinical practice. Our models may serve as practical tools for facilitating personalized treatment options and improving clinical outcomes through pre-treatment stratification of patients with AP.
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Affiliation(s)
- Zhu Luo
- Department of Clinical Laboratory, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jialin Shi
- Key Laboratory of Intelligent Medical Imaging of Wenzhou, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yangyang Fang
- School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, China
| | - Shunjie Pei
- School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, China
| | - Yutian Lu
- Department of Clinical Laboratory, Affiliated Central Hospital of Taizhou University, Taizhou, China
| | - Ruxia Zhang
- Department of Clinical Laboratory, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xin Ye
- Department of Clinical Laboratory, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Wenxing Wang
- Department of Gastroenterology and Hepatology, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Mengtian Li
- Department of Clinical Laboratory, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xiangjun Li
- Department of Clinical Laboratory, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Mengyue Zhang
- Department of Clinical Laboratory, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Guangxin Xiang
- School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, China
| | - Zhifang Pan
- Key Laboratory of Intelligent Medical Imaging of Wenzhou, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xiaoqun Zheng
- Department of Clinical Laboratory, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.,School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, China.,Key Laboratory of Laboratory Medicine, Ministry of Education of China, Wenzhou, China
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19
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Liang Y, Ding H. Expression levels of RUNX3 and FGFR2 in peripheral blood of severe acute pancreatitis and their clinical significance. Ann Surg Treat Res 2023; 104:90-100. [PMID: 36816737 PMCID: PMC9929434 DOI: 10.4174/astr.2023.104.2.90] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 10/13/2022] [Accepted: 10/27/2022] [Indexed: 02/10/2023] Open
Abstract
Purpose Severe acute pancreatitis (SAP) is a life-threatening inflammatory syndrome of the pancreas. This study aimed to analyze the clinical significance of runt-associated transcription factor 3 (RUNX3) and fibroblast growth factor receptor 2 (FGFR2) expression alterations in SAP. Methods This study included 18 SAP patients in Wuzhong People's Hospital from November 2019 to December 2021 and 18 healthy controls. RUNX3 and FGFR2 expression levels were determined by RT-quantitative PCR. Correlations between RUNX3/FGFR2 and sex, age, etiology, CRP, procalcitonin, AST, LDH, BUN, Acute Physiology and Chronic Health Evaluation II (APACHE II), Ranson score, Bedside Index for Severity in Acute Pancreatitis (BISAP) score, sequential organ failure assessment (SOFA), and modified computed tomography severity index (MCTSI) score were analyzed. Diagnostic values of RUNX3 and FGFR2 in SAP were analyzed using the receiver-operating characteristic curve. The binding of RUNX3 to FGFR2 was analyzed by chromatin immunoprecipitation. Results RUNX3 and FGFR2 were downregulated in peripheral blood of SAP patients. RUNX3 and FGFR2 were negatively correlated with CRP, procalcitonin, AST, LDH, BUN, APACHE II score, Ranson score, BISAP score, SOFA score, and MCTSI score. Sensitivity and specificity of RUNX3 level of <0.9650 for SAP diagnosis were 88.89% and 72.22%, respectively. Sensitivity and specificity of FGFR2 level of <0.8950 for SAP diagnosis were 66.67% and 83.33%, respectively. RUNX3 was enriched in the FGFR2 promoter and was positively correlated with FGFR2. Conclusion RUNX3 and FGFR2 were downregulated in peripheral blood of SAP patients and served as candidate biomarkers for SAP diagnosis. RUNX3 bound to the FGFR2 promoter to promote FGFR2 transcription.
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Affiliation(s)
- Yongyong Liang
- Department of Critical Medicine, Dushu Lake Hospital Affiliated to Soochow University, Suzhou, China
| | - Huaming Ding
- Department of Critical Medicine, Wuzhong People’s Hospital, Suzhou, China
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20
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Hökenek UD, Aydıner Ö, Kart JS, Arslan G, Saracoglu KT. Evaluation of the effect of pancreatic volume on mortality in patients with acute pancreatitis. Am J Emerg Med 2023; 63:38-43. [PMID: 36327747 DOI: 10.1016/j.ajem.2022.10.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 10/10/2022] [Accepted: 10/14/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Pancreatic volume is enlarged in acute pancreatitis. OBJECTIVE This study aimed to evaluate whether there was a difference in pancreatic volume between survivors and non-survivors with acute pancreatitis using computer-generated 3D imaging. METHOD This single-center retrospective observational cohort study was conducted between January 2015 and December 2020. The hospital automation system was used to get the patients diagnosed with acute pancreatitis by using International Classification of Diseases (ICD) (ninth edition, code 577.0 or 10th version, code K 85.0) codes. The patients' pancreatic volumes, computed tomography severity index (CTSI), and modified computed tomography severity index (mCTSI) scores were calculated using the data obtained from the hospital automation system. The pancreatic volumes of the patients were measured using the computer-generated 3D imaging method. Pancreatic volume, CTSI, and mCTSI were then statistically compared in terms of mortality prediction by using the receiver operating characteristic (ROC) analysis. RESULTS Of the 143 patients, 57.34% were female and 42.66% were male. The cut-off value of pancreatic volume in determining mortality was>81.5 cm3 OR:17.43 (%95 CI: 2.2-138.1) Cohen's d:1.126, at which it had 92.3% sensitivity, 60.0% specificity, 18.8% positive predictive value, and 98.7% negative predictive value. As a result of the ROC analysis of pancreatic volume in mortality prediction, the area under curve (AUC) value was determined as 0.787 [95% confidence interval (CI): 0.711-0.851]. The ROC analysis of the CTSI and mCTSI scores in mortality prediction revealed AUC values of 0.822 (95%CI: 0.750-0.881) and 0.955 (95%CI: 0.907-0.983) respectively. CONCLUSION Although CTSI scores pancreatic enlargement and mCTSI scores pancreatic necrosis and inflammation, the pancreatic volume value is not clearly scored in both. In this study population, pancreatic volume above 81.5 cm was associated with increased mortality. Both CTSI and mCTSI scores outperformed pancreatic volume in predicting mortality.
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Affiliation(s)
- Ummahan Dalkılınç Hökenek
- Department of Anaesthesiology and Reanimation, University of Health Sciences, Kartal Dr. Lutfi Kirdar City Hospital, Istanbul, Turkey.
| | - Ömer Aydıner
- Department of Interventional Radiology, University of Health Sciences, Kartal Dr. Lutfi Kirdar City Hospital, Istanbul, Turkey
| | - Julide Sayın Kart
- Department of Anaesthesiology and Reanimation, University of Health Sciences, Kartal Dr. Lutfi Kirdar City Hospital, Istanbul, Turkey
| | - Gülten Arslan
- Department of Anaesthesiology and Reanimation, University of Health Sciences, Kartal Dr. Lutfi Kirdar City Hospital, Istanbul, Turkey
| | - Kemal Tolga Saracoglu
- Department of Anaesthesiology and Reanimation, University of Health Sciences, Kartal Dr. Lutfi Kirdar City Hospital, Istanbul, Turkey
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21
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Chen Z, Wang Y, Zhang H, Yin H, Hu C, Huang Z, Tan Q, Song B, Deng L, Xia Q. Deep Learning Models for Severity Prediction of Acute Pancreatitis in the Early Phase From Abdominal Nonenhanced Computed Tomography Images. Pancreas 2023; 52:e45-e53. [PMID: 37378899 DOI: 10.1097/mpa.0000000000002216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/29/2023]
Abstract
OBJECTIVES To develop and validate deep learning (DL) models for predicting the severity of acute pancreatitis (AP) by using abdominal nonenhanced computed tomography (CT) images. METHODS The study included 978 AP patients admitted within 72 hours after onset and performed abdominal CT on admission. The image DL model was built by the convolutional neural networks. The combined model was developed by integrating CT images and clinical markers. The performance of the models was evaluated by using the area under the receiver operating characteristic curve. RESULTS The clinical, Image DL, and the combined DL models were developed in 783 AP patients and validated in 195 AP patients. The combined models possessed the predictive accuracy of 90.0%, 32.4%, and 74.2% for mild, moderately severe, and severe AP. The combined DL model outperformed clinical and image DL models with 0.820 (95% confidence interval, 0.759-0.871), the sensitivity of 84.76% and the specificity of 66.67% for predicting mild AP and the area under the receiver operating characteristic curve of 0.920 (95% confidence interval, 0.873-0.954), the sensitivity of 90.32%, and the specificity of 82.93% for predicting severe AP. CONCLUSIONS The DL technology allows nonenhanced CT images as a novel tool for predicting the severity of AP.
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Affiliation(s)
- Zhiyao Chen
- From the Pancreatitis Center, Center of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Centre, West China Hospital, Sichuan University, Chengdu, China
| | - Yi Wang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Huiling Zhang
- Infervision Medical Technology Co., Ltd, Beijing, China
| | - Hongkun Yin
- Infervision Medical Technology Co., Ltd, Beijing, China
| | - Cheng Hu
- From the Pancreatitis Center, Center of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Centre, West China Hospital, Sichuan University, Chengdu, China
| | - Zixing Huang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Qingyuan Tan
- From the Pancreatitis Center, Center of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Centre, West China Hospital, Sichuan University, Chengdu, China
| | | | - Lihui Deng
- From the Pancreatitis Center, Center of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Centre, West China Hospital, Sichuan University, Chengdu, China
| | - Qing Xia
- From the Pancreatitis Center, Center of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Centre, West China Hospital, Sichuan University, Chengdu, China
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22
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Tarján D, Hegyi P. Acute Pancreatitis Severity Prediction: It Is Time to Use Artificial Intelligence. J Clin Med 2022; 12:jcm12010290. [PMID: 36615090 PMCID: PMC9821076 DOI: 10.3390/jcm12010290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 12/26/2022] [Indexed: 12/31/2022] Open
Abstract
The clinical course of acute pancreatitis (AP) can be variable depending on the severity of the disease, and it is crucial to predict the probability of organ failure to initiate early adequate treatment and management. Therefore, possible high-risk patients should be admitted to a high-dependence unit. For risk assessment, we have three options: (1) There are univariate biochemical markers for predicting severe AP. One of their main characteristics is that the absence or excess of these factors affects the outcome of AP in a dose-dependent manner. Unfortunately, all of these parameters have low accuracy; therefore, they cannot be used in clinical settings. (2) Score systems have been developed to prognosticate severity by using 4-25 factors. They usually require multiple parameters that are not measured on a daily basis, and they often require more than 24 h for completion, resulting in the loss of valuable time. However, these scores can foresee specific organ failure or severity, but they only use dichotomous parameters, resulting in information loss. Therefore, their use in clinical settings is limited. (3) Artificial intelligence can detect the complex nonlinear relationships between multiple biochemical parameters and disease outcomes. We have recently developed the very first easy-to-use tool, EASY-APP, which uses multiple continuous variables that are available at the time of admission. The web-based application does not require all of the parameters for prediction, allowing early and easy use on admission. In the future, prognostic scores should be developed with the help of artificial intelligence to avoid information loss and to provide a more individualized risk assessment.
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Affiliation(s)
- Dorottya Tarján
- Heart and Vascular Center, Division of Pancreatic Diseases, Semmelweis University, 1083 Budapest, Hungary
- Centre for Translational Medicine, Semmelweis University, 1085 Budapest, Hungary
- Institute for Translational Medicine, Medical School, University of Pécs, 7623 Pécs, Hungary
| | - Péter Hegyi
- Heart and Vascular Center, Division of Pancreatic Diseases, Semmelweis University, 1083 Budapest, Hungary
- Centre for Translational Medicine, Semmelweis University, 1085 Budapest, Hungary
- Institute for Translational Medicine, Medical School, University of Pécs, 7623 Pécs, Hungary
- Translational Pancreatology Research Group, Interdisciplinary Centre of Excellence for Research Development and Innovation University of Szeged, 6725 Szeged, Hungary
- Correspondence: ; Tel.: +36-703751031
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23
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Zarnescu NO, Dumitrascu I, Zarnescu EC, Costea R. Abdominal Compartment Syndrome in Acute Pancreatitis: A Narrative Review. Diagnostics (Basel) 2022; 13:1. [PMID: 36611293 PMCID: PMC9818265 DOI: 10.3390/diagnostics13010001] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 12/11/2022] [Accepted: 12/16/2022] [Indexed: 12/24/2022] Open
Abstract
Abdominal compartment syndrome (ACS) represents a severe complication of acute pancreatitis (AP), resulting from an acute and sustained increase in abdominal pressure >20 mmHg, in association with new organ dysfunction. The harmful effect of high intra-abdominal pressure on regional and global perfusion results in significant multiple organ failure and is associated with increased morbidity and mortality. There are several deleterious consequences of elevated intra-abdominal pressure on end-organ function, including respiratory, cardiovascular, gastrointestinal, neurologic, and renal effects. It is estimated that about 15% of patients with severe AP develop intra-abdominal hypertension or ACS, with a mortality rate around 50%. The treatment of abdominal compartment syndrome in acute pancreatitis begins with medical intervention and percutaneous drainage, where possible. Abdominal compartment syndrome unresponsive to conservatory treatment requires immediate surgical decompression, along with vacuum-assisted closure therapy techniques, followed by early abdominal fascia closure.
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Affiliation(s)
- Narcis Octavian Zarnescu
- Department of General Surgery, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Second Department of Surgery, University Emergency Hospital Bucharest, 050098 Bucharest, Romania
| | - Ioana Dumitrascu
- Department of General Surgery, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Second Department of Surgery, University Emergency Hospital Bucharest, 050098 Bucharest, Romania
| | - Eugenia Claudia Zarnescu
- Department of General Surgery, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Second Department of Surgery, University Emergency Hospital Bucharest, 050098 Bucharest, Romania
| | - Radu Costea
- Department of General Surgery, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Second Department of Surgery, University Emergency Hospital Bucharest, 050098 Bucharest, Romania
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24
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Chan KS, Shelat VG. Diagnosis, severity stratification and management of adult acute pancreatitis-current evidence and controversies. World J Gastrointest Surg 2022; 14:1179-1197. [PMID: 36504520 PMCID: PMC9727576 DOI: 10.4240/wjgs.v14.i11.1179] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 10/08/2022] [Accepted: 10/25/2022] [Indexed: 02/07/2023] Open
Abstract
Acute pancreatitis (AP) is a disease spectrum ranging from mild to severe with an unpredictable natural course. Majority of cases (80%) are mild and self-limiting. However, severe AP (SAP) has a mortality risk of up to 30%. Establishing aetiology and risk stratification are essential pillars of clinical care. Idiopathic AP is a diagnosis of exclusion which should only be used after extended investigations fail to identify a cause. Tenets of management of mild AP include pain control and management of aetiology to prevent recurrence. In SAP, patients should be resuscitated with goal-directed fluid therapy using crystalloids and admitted to critical care unit. Routine prophylactic antibiotics have limited clinical benefit and should not be given in SAP. Patients able to tolerate oral intake should be given early enteral nutrition rather than nil by mouth or parenteral nutrition. If unable to tolerate per-orally, nasogastric feeding may be attempted and routine post-pyloric feeding has limited evidence of clinical benefit. Endoscopic retrograde cholangiopancreatogram should be selectively performed in patients with biliary obstruction or suspicion of acute cholangitis. Delayed step-up strategy including percutaneous retroperitoneal drainage, endoscopic debridement, or minimal-access necrosectomy are sufficient in most SAP patients. Patients should be monitored for diabetes mellitus and pseudocyst.
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Affiliation(s)
- Kai Siang Chan
- Department of General Surgery, Tan Tock Seng Hospital, Singapore 308433, Singapore
| | - Vishal G Shelat
- Department of General Surgery, Tan Tock Seng Hospital, Singapore 308433, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
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25
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Sagar AJ, Khan M, Tapuria N. Evidence-Based Approach to the Surgical Management of Acute Pancreatitis. Surg J (N Y) 2022; 8:e322-e335. [PMID: 36425407 PMCID: PMC9681540 DOI: 10.1055/s-0042-1758229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Accepted: 09/13/2022] [Indexed: 11/24/2022] Open
Abstract
Background
Acute pancreatitis is a significant challenge to health services. Remarkable progress has been made in the last decade in optimizing its management.
Methods
This review is a comprehensive assessment of 7 guidelines employed in current clinical practice with an appraisal of the underlying evidence, including 15 meta-analyses/systematic reviews, 16 randomized controlled trials, and 31 cohort studies.
Results
Key tenets of early management of acute pancreatitis include severity stratification based on the degree of organ failure and early goal-directed fluid resuscitation. Rigorous determination of etiology reduces the risk of recurrence. Early enteral nutrition and consideration of epidural analgesia have been pioneered in recent years with promising results. Indications for invasive intervention are becoming increasingly refined. The definitive indications for endoscopic retrograde cholangiopancreatography in acute pancreatitis are associated with cholangitis and common bile duct obstruction. The role of open surgical necrosectomy has diminished with the development of a minimally invasive step-up necrosectomy protocol. Increasing use of endoscopic ultrasound–guided intervention in the management of pancreatic necrosis has helped reduce pancreatic fistula rates and hospital stay.
Conclusion
The optimal approach to surgical management of complicated pancreatitis depends on patient physiology and disease anatomy, in addition to the available resources and expertise. This is best achieved with a multidisciplinary approach. This review provides a distillation of the recommendations of clinical guidelines and critical discussion of the evidence that informs them and presents an algorithmic approach to key areas of patient management.
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Affiliation(s)
- Alex James Sagar
- Nuffield Department of Surgical Sciences, Oxford University, Oxford, United Kingdom,Address for correspondence Alex James Sagar, MRCS Nuffield Department of Surgical Sciences, Oxford UniversityOxfordUnited Kingdom
| | - Majid Khan
- Acute Care Common Stem, Whipps Cross Hospital, London, United Kingdom
| | - Niteen Tapuria
- Department of General Surgery, Milton Keynes University Hospital, Milton Keynes, United Kingdom
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26
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Jaber S, Garnier M, Asehnoune K, Bounes F, Buscail L, Chevaux JB, Dahyot-Fizelier C, Darrivere L, Jabaudon M, Joannes-Boyau O, Launey Y, Levesque E, Levy P, Montravers P, Muller L, Rimmelé T, Roger C, Savoye-Collet C, Seguin P, Tasu JP, Thibault R, Vanbiervliet G, Weiss E, Jong AD. Pancréatite aiguë grave du patient adulte en soins critiques 2021. ANESTHÉSIE & RÉANIMATION 2022. [DOI: 10.1016/j.anrea.2022.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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27
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Szatmary P, Grammatikopoulos T, Cai W, Huang W, Mukherjee R, Halloran C, Beyer G, Sutton R. Acute Pancreatitis: Diagnosis and Treatment. Drugs 2022; 82:1251-1276. [PMID: 36074322 PMCID: PMC9454414 DOI: 10.1007/s40265-022-01766-4] [Citation(s) in RCA: 200] [Impact Index Per Article: 66.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/04/2022] [Indexed: 11/11/2022]
Abstract
Acute pancreatitis is a common indication for hospital admission, increasing in incidence, including in children, pregnancy and the elderly. Moderately severe acute pancreatitis with fluid and/or necrotic collections causes substantial morbidity, and severe disease with persistent organ failure causes significant mortality. The diagnosis requires two of upper abdominal pain, amylase/lipase ≥ 3 ×upper limit of normal, and/or cross-sectional imaging findings. Gallstones and ethanol predominate while hypertriglyceridaemia and drugs are notable among many causes. Serum triglycerides, full blood count, renal and liver function tests, glucose, calcium, transabdominal ultrasound, and chest imaging are indicated, with abdominal cross-sectional imaging if there is diagnostic uncertainty. Subsequent imaging is undertaken to detect complications, for example, if C-reactive protein exceeds 150 mg/L, or rarer aetiologies. Pancreatic intracellular calcium overload, mitochondrial impairment, and inflammatory responses are critical in pathogenesis, targeted in current treatment trials, which are crucially important as there is no internationally licenced drug to treat acute pancreatitis and prevent complications. Initial priorities are intravenous fluid resuscitation, analgesia, and enteral nutrition, and when necessary, critical care and organ support, parenteral nutrition, antibiotics, pancreatic exocrine and endocrine replacement therapy; all may have adverse effects. Patients with local complications should be referred to specialist tertiary centres to guide further management, which may include drainage and/or necrosectomy. The impact of acute pancreatitis can be devastating, so prevention or reduction of the risk of recurrence and progression to chronic pancreatitis with an increased risk of pancreas cancer requires proactive management that should be long term for some patients.
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Affiliation(s)
- Peter Szatmary
- Liverpool Pancreatitis Research Group, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK
| | - Tassos Grammatikopoulos
- Paediatric Liver, GI and Nutrition Centre, King's College Hospital NHS Foundation Trust, London, UK
| | - Wenhao Cai
- Liverpool Pancreatitis Research Group, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,West China Centre of Excellence for Pancreatitis and West China-Liverpool Biomedical Research Centre, West China Hospital, Sichuan University, Chengdu, China
| | - Wei Huang
- West China Centre of Excellence for Pancreatitis and West China-Liverpool Biomedical Research Centre, West China Hospital, Sichuan University, Chengdu, China
| | - Rajarshi Mukherjee
- Liverpool Pancreatitis Research Group, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK.,Department of Molecular Physiology and Cell Signalling, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool , UK
| | - Chris Halloran
- Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK
| | - Georg Beyer
- Department of Medicine II, University Hospital, LMU Munich, Munich, Germany
| | - Robert Sutton
- Liverpool Pancreatitis Research Group, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK. .,Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK. .,Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK.
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Wu B, Yang J, Dai Y, Xiong L. Combination of the BISAP Score and miR-155 is Applied in Predicting the Severity of Acute Pancreatitis. Int J Gen Med 2022; 15:7467-7474. [PMID: 36187163 PMCID: PMC9519123 DOI: 10.2147/ijgm.s384068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 09/14/2022] [Indexed: 11/24/2022] Open
Abstract
Purpose To evaluate the predictive value of combination of Bedside Index for Severity in AP (BISAP) score and miR-155 for the severity of acute pancreatitis (AP). Patients and Methods A total of 1046 AP patients were divided into control group and case group according to the severity of AP [mild and moderately severe AP vs severe AP (SAP)]. Demographic data, comorbidities, clinical characteristics and laboratory data were collected. Multivariate analysis was conducted for the variables with two-sided P<0.10 in univariate analysis to identify independent associated factors for progression to SAP in AP patients. The predictive values were evaluated using receiver operating characteristic (ROC) curve, and the area under curve (AUC) was compared using Z test. Results A total of 117 (11.2%) patients were evaluated as SAP. Univariate analysis showed that there were significant differences in age, hypertension, ICU admission, hospital stay, Leukocytes, CRP, BUN, BISAP score and miR-155 between case group and control group (P<0.05), and the P value of Fibrinogen was <0.10. Multivariate analysis showed that the BISAP score, BUN, Leukocytes, age and CRP were independent risk factors for progression to SAP among AP patients after adjusting for hypertension, ICU admission, hospital stay and Fibrinogen, while miR-155 was a protective factor. The ROC curves demonstrated the AUCs of BISAP score, miR-155 and their combination were 0.842 (SE: 0.017, 95% CI: 0.809–0.874), 0.751 (SE: 0.022, 95% CI: 0.708–0.793) and 0.945 (SE: 0.007, 95% CI: 0.931–0.959), respectively. Z test showed that the AUC of combination prediction was significantly higher than that of individual predictions (0.945 vs 0.842, Z=5.602, P<0.001; 0.945 vs 0.751, Z=8.403, P<0.001). The sensitivity, specificity and negative predictive value (NPV) of combination prediction were 95.7%, 93.6% and 99.4%, respectively. Conclusion The combination of the BISAP score and miR-155 should be utilized to elevate the predictive value for the severity of AP in clinic.
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Affiliation(s)
- Bing Wu
- Department of Critical Care Medicine, Jiangjin Central Hospital, Chongqing, People’s Republic of China
| | - Jun Yang
- Department of Critical Care Medicine, Jiangjin Central Hospital, Chongqing, People’s Republic of China
| | - Yonghong Dai
- Department of Critical Care Medicine, Jiangjin Central Hospital, Chongqing, People’s Republic of China
| | - Le Xiong
- Department of Critical Care Medicine, Jiangjin Central Hospital, Chongqing, People’s Republic of China
- Correspondence: Le Xiong, Department of Critical Care Medicine, Jiangjin Central Hospital, No. 725, Jiangzhou Road, Dingshan Street, Jiangjin District, Chongqing, 402260, People’s Republic of China, Tel +86-2347521342, Email
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Liu W, Li Z, Zhang X, Du J, Liang R, Ji Y, Tang W, Zhang X. CT Characteristics of Acute Pancreatitis with Preexisting Fatty Liver and Its Impact on Pancreatitis Severity and Persistent Systemic Inflammatory Response Syndrome. Int J Gen Med 2022; 15:7017-7028. [PMID: 36090708 PMCID: PMC9462438 DOI: 10.2147/ijgm.s382287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 08/29/2022] [Indexed: 11/23/2022] Open
Abstract
Purpose To study the CT characteristics of acute pancreatitis (AP) associated with preexisting fatty liver (FL) and the impact of preexisting FL on the severity of AP and persistent systemic inflammatory response syndrome (SIRS). Patients and Methods A total of 189 patients with AP were divided into AP with and without preexisting FL. The CT features, clinical characteristics, severity of AP, and presence of persistent SIRS between the two groups were compared. Univariate and multivariate analyses were performed to determine the risk factors for predicting SIRS. The diagnostic performances of the risk factors were evaluated by receiver operating characteristic (ROC) curve analysis. Results Among the 189 patients, 49.7% (94/189) had preexisting FL. On CT, AP patients with preexisting FL were more likely to develop necrosis (23.4% vs 10.5%, p=0.021), local complications (45.7% vs 29.5%, p=0.025) and persistent SIRS (59.6% vs 27.4%, p<0.001). Multivariate analysis showed that preexisting FL (OR=2.863, 95% CI: 1.264–6.486, p=0.012), APACHE II≥6 (OR=1.334, 95% CI: 1.117–1.594, p=0.002), and MCTSI ≥4 (OR=1.489, 95% CI: 1.046–2.119, p=0.027) could be independent risk factors for persistent SIRS. The areas under the ROC curve of preexisting FL, APACHE II, and MCISI in diagnosing AP patients with persistent SIRS were 0.664, 0.703, and 0.783, respectively. Conclusion Patients with preexisting FL were more likely to develop necrosis and local complications on CT and present more severe AP and persistent SIRS. Preexisting FL can be an independent risk factor in predicting the presence of persistent SIRS in patients with AP.
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Affiliation(s)
- Wei Liu
- Medical Imaging Key Laboratory of Sichuan Province and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, People’s Republic of China
| | - Zenghui Li
- Medical Imaging Key Laboratory of Sichuan Province and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, People’s Republic of China
| | - Xinyu Zhang
- Medical Imaging Key Laboratory of Sichuan Province and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, People’s Republic of China
| | - Juanjuan Du
- Medical Imaging Key Laboratory of Sichuan Province and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, People’s Republic of China
| | - Rui Liang
- Medical Imaging Key Laboratory of Sichuan Province and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, People’s Republic of China
| | - Yifan Ji
- Medical Imaging Key Laboratory of Sichuan Province and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, People’s Republic of China
| | - Wei Tang
- Medical Imaging Key Laboratory of Sichuan Province and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, People’s Republic of China
| | - Xiaoming Zhang
- Medical Imaging Key Laboratory of Sichuan Province and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, People’s Republic of China
- Correspondence: Xiaoming Zhang; Wei Tang, Medical Imaging Key Laboratory of Sichuan Province and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, No. 1 South Maoyuan Road, Nanchong, Sichuan, 637000, People’s Republic of China, Tel +86 13808271001; +86 1369600 2904, Email ;
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Rodríguez Rojas C, García de Guadiana-Romualdo L, Morán Sánchez S, Prazak J, Algara Soriano V, Que YA, Benninga R, Albaladejo-Otón MD. Role of Pancreatic Stone Protein as an Early Biomarker for Risk Stratification of Acute Pancreatitis. Dig Dis Sci 2022; 67:3275-3283. [PMID: 34268662 DOI: 10.1007/s10620-021-07152-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Accepted: 07/02/2021] [Indexed: 12/18/2022]
Abstract
BACKGROUND Early risk stratification of acute pancreatitis is crucial to improve clinical outcomes. The objective of this study was to evaluate the ability of pancreatic stone protein (PSP) to predict acute pancreatitis severity and to compare it with the biomarkers and severity scores currently used for that purpose. PATIENTS AND METHODS Prospective single-center observational study enrolling 268 adult patients with acute pancreatitis. Biomarkers including PSP were measured upon admission to the Emergency Department and severity scores as SOFA, PANC-3, and BISAP were computed. Patients were classified into mild-moderate (non-severe) and severe acute pancreatitis according to the Determinant-Based Classification Criteria. Area under the curve (AUC) and regression analysis were used to analyze the discrimination abilities and the association of biomarkers and scores with severity. RESULTS Two hundred and thirty-five patients (87.7%) were classified as non-severe and 33 (12.3%) as severe acute pancreatitis. Median [IQR] PSP was increased in patients with severe acute pancreatitis (890 μg/L [559-1142] vs. 279 μg/L [141-496]; p < 0.001) and it was the best predictor (ROC AUC: 0.827). In multivariate analysis, PSP and urea were the only independent predictors for severe acute pancreatitis and a model combining them both ("biomarker model") showed an AUC of 0.841 for prediction of severe acute pancreatitis, higher than the other severity scores. CONCLUSIONS PSP is a promising biomarker for predicting the severity of acute pancreatitis upon admission. A model combining PSP and urea might further constitute a potential tool for early risk stratification of this disease.
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Affiliation(s)
- Carlos Rodríguez Rojas
- Laboratory Medicine Department, Hospital Universitario Santa Lucía, C/ Mezquita, s/n, Paraje Los Arcos, 30202, Cartagena, Murcia, Spain
| | - Luis García de Guadiana-Romualdo
- Laboratory Medicine Department, Hospital Universitario Santa Lucía, C/ Mezquita, s/n, Paraje Los Arcos, 30202, Cartagena, Murcia, Spain.
| | - Senador Morán Sánchez
- Gastroenterology Department, Hospital Universitario Santa Lucía, C/ Mezquita, s/n, Paraje Los Arcos, 30202, Cartagena, Murcia, Spain
| | - Josef Prazak
- Department of Intensive Care Medicine, Inselspital; Bern University Hospital, University of Bern, 3010, Bern, Switzerland
| | - Virginia Algara Soriano
- Gastroenterology Department, Hospital Universitario Santa Lucía, C/ Mezquita, s/n, Paraje Los Arcos, 30202, Cartagena, Murcia, Spain
| | - Yok-Ai Que
- Department of Intensive Care Medicine, Inselspital; Bern University Hospital, University of Bern, 3010, Bern, Switzerland
| | | | - María Dolores Albaladejo-Otón
- Laboratory Medicine Department, Hospital Universitario Santa Lucía, C/ Mezquita, s/n, Paraje Los Arcos, 30202, Cartagena, Murcia, Spain
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Kui B, Pintér J, Molontay R, Nagy M, Farkas N, Gede N, Vincze Á, Bajor J, Gódi S, Czimmer J, Szabó I, Illés A, Sarlós P, Hágendorn R, Pár G, Papp M, Vitális Z, Kovács G, Fehér E, Földi I, Izbéki F, Gajdán L, Fejes R, Németh BC, Török I, Farkas H, Mickevicius A, Sallinen V, Galeev S, Ramírez-Maldonado E, Párniczky A, Erőss B, Hegyi PJ, Márta K, Váncsa S, Sutton R, Szatmary P, Latawiec D, Halloran C, de-Madaria E, Pando E, Alberti P, Gómez-Jurado MJ, Tantau A, Szentesi A, Hegyi P. EASY-APP: An artificial intelligence model and application for early and easy prediction of severity in acute pancreatitis. Clin Transl Med 2022; 12:e842. [PMID: 35653504 PMCID: PMC9162438 DOI: 10.1002/ctm2.842] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 04/06/2022] [Accepted: 04/11/2022] [Indexed: 12/17/2022] Open
Abstract
Background Acute pancreatitis (AP) is a potentially severe or even fatal inflammation of the pancreas. Early identification of patients at high risk for developing a severe course of the disease is crucial for preventing organ failure and death. Most of the former predictive scores require many parameters or at least 24 h to predict the severity; therefore, the early therapeutic window is often missed. Methods The early achievable severity index (EASY) is a multicentre, multinational, prospective and observational study (ISRCTN10525246). The predictions were made using machine learning models. We used the scikit‐learn, xgboost and catboost Python packages for modelling. We evaluated our models using fourfold cross‐validation, and the receiver operating characteristic (ROC) curve, the area under the ROC curve (AUC), and accuracy metrics were calculated on the union of the test sets of the cross‐validation. The most critical factors and their contribution to the prediction were identified using a modern tool of explainable artificial intelligence called SHapley Additive exPlanations (SHAP). Results The prediction model was based on an international cohort of 1184 patients and a validation cohort of 3543 patients. The best performing model was an XGBoost classifier with an average AUC score of 0.81 ± 0.033 and an accuracy of 89.1%, and the model improved with experience. The six most influential features were the respiratory rate, body temperature, abdominal muscular reflex, gender, age and glucose level. Using the XGBoost machine learning algorithm for prediction, the SHAP values for the explanation and the bootstrapping method to estimate confidence, we developed a free and easy‐to‐use web application in the Streamlit Python‐based framework (http://easy‐app.org/). Conclusions The EASY prediction score is a practical tool for identifying patients at high risk for severe AP within hours of hospital admission. The web application is available for clinicians and contributes to the improvement of the model.
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Affiliation(s)
- Balázs Kui
- Department of Medicine, University of Szeged, Szeged, Hungary.,Centre for Translational Medicine, Department of Medicine, University of Szeged, Szeged, Hungary
| | - József Pintér
- Department of Stochastics, Institute of Mathematics, Budapest University of Technology and Economics, Budapest, Hungary
| | - Roland Molontay
- Department of Stochastics, Institute of Mathematics, Budapest University of Technology and Economics, Budapest, Hungary.,MTA-BME Stochastics Research Group, Budapest, Hungary
| | - Marcell Nagy
- Department of Stochastics, Institute of Mathematics, Budapest University of Technology and Economics, Budapest, Hungary
| | - Nelli Farkas
- Institute for Translational Medicine, Szentágothai Research Centre, Medical School, University of Pécs, Pécs, Hungary.,Institute of Bioanalysis, Medical School, University of Pécs, Pécs, Hungary
| | - Noémi Gede
- Institute for Translational Medicine, Szentágothai Research Centre, Medical School, University of Pécs, Pécs, Hungary
| | - Áron Vincze
- Division of Gastroenterology, First Department of Medicine, University of Pécs, Medical School, Pécs, Hungary
| | - Judit Bajor
- Division of Gastroenterology, First Department of Medicine, University of Pécs, Medical School, Pécs, Hungary
| | - Szilárd Gódi
- Division of Gastroenterology, First Department of Medicine, University of Pécs, Medical School, Pécs, Hungary
| | - József Czimmer
- Division of Gastroenterology, First Department of Medicine, University of Pécs, Medical School, Pécs, Hungary
| | - Imre Szabó
- Division of Gastroenterology, First Department of Medicine, University of Pécs, Medical School, Pécs, Hungary
| | - Anita Illés
- Division of Gastroenterology, First Department of Medicine, University of Pécs, Medical School, Pécs, Hungary
| | - Patrícia Sarlós
- Division of Gastroenterology, First Department of Medicine, University of Pécs, Medical School, Pécs, Hungary
| | - Roland Hágendorn
- Division of Gastroenterology, First Department of Medicine, University of Pécs, Medical School, Pécs, Hungary
| | - Gabriella Pár
- Division of Gastroenterology, First Department of Medicine, University of Pécs, Medical School, Pécs, Hungary
| | - Mária Papp
- Department of Gastroenterology, Institute of Internal Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - Zsuzsanna Vitális
- Department of Gastroenterology, Institute of Internal Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - György Kovács
- Department of Gastroenterology, Institute of Internal Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - Eszter Fehér
- Department of Gastroenterology, Institute of Internal Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - Ildikó Földi
- Department of Gastroenterology, Institute of Internal Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - Ferenc Izbéki
- Szent György Teaching Hospital of County Fejér, Székesfehérvár, Hungary
| | - László Gajdán
- Szent György Teaching Hospital of County Fejér, Székesfehérvár, Hungary
| | - Roland Fejes
- Szent György Teaching Hospital of County Fejér, Székesfehérvár, Hungary
| | - Balázs Csaba Németh
- Department of Medicine, University of Szeged, Szeged, Hungary.,Centre for Translational Medicine, Department of Medicine, University of Szeged, Szeged, Hungary
| | - Imola Török
- County Emergency Clinical Hospital of Târgu Mures-Gastroenterology Clinic and University of Medicine, Pharmacy, Sciences and Technology 'George Emil Palade', Targu Mures, Romania
| | - Hunor Farkas
- County Emergency Clinical Hospital of Târgu Mures-Gastroenterology Clinic and University of Medicine, Pharmacy, Sciences and Technology 'George Emil Palade', Targu Mures, Romania
| | | | - Ville Sallinen
- Department of Transplantation and Liver Surgery, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Shamil Galeev
- Saint Luke Clinical Hospital, St. Petersburg, Russia
| | | | - Andrea Párniczky
- Institute for Translational Medicine, Szentágothai Research Centre, Medical School, University of Pécs, Pécs, Hungary.,Heim Pál National Pediatric Institute, Budapest, Hungary
| | - Bálint Erőss
- Institute for Translational Medicine, Szentágothai Research Centre, Medical School, University of Pécs, Pécs, Hungary.,Division of Pancreatic Diseases, Heart and Vascular Centre, Semmelweis University, Budapest, Hungary.,Centre for Translational Medicine, Semmelweis University, Budapest, Hungary
| | - Péter Jenő Hegyi
- Institute for Translational Medicine, Szentágothai Research Centre, Medical School, University of Pécs, Pécs, Hungary.,Division of Pancreatic Diseases, Heart and Vascular Centre, Semmelweis University, Budapest, Hungary
| | - Katalin Márta
- Division of Pancreatic Diseases, Heart and Vascular Centre, Semmelweis University, Budapest, Hungary.,Centre for Translational Medicine, Semmelweis University, Budapest, Hungary
| | - Szilárd Váncsa
- Institute for Translational Medicine, Szentágothai Research Centre, Medical School, University of Pécs, Pécs, Hungary.,Division of Pancreatic Diseases, Heart and Vascular Centre, Semmelweis University, Budapest, Hungary.,Centre for Translational Medicine, Semmelweis University, Budapest, Hungary
| | - Robert Sutton
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool and Liverpool University Hospitals NHS Foundation Trust, Liverpool, England, UK
| | - Peter Szatmary
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool and Liverpool University Hospitals NHS Foundation Trust, Liverpool, England, UK
| | - Diane Latawiec
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool and Liverpool University Hospitals NHS Foundation Trust, Liverpool, England, UK
| | - Chris Halloran
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool and Liverpool University Hospitals NHS Foundation Trust, Liverpool, England, UK
| | - Enrique de-Madaria
- Gastroenterology Department, Alicante University General Hospital, ISABIAL, Alicante, Spain
| | - Elizabeth Pando
- Department of Hepato-Pancreato-Biliary and Transplant Surgery, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Piero Alberti
- Department of Hepato-Pancreato-Biliary and Transplant Surgery, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Maria José Gómez-Jurado
- Department of Hepato-Pancreato-Biliary and Transplant Surgery, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Alina Tantau
- The 4th Medical Clinic, Iuliu Hatieganu' University of Medicine and Pharmacy, Cluj-Napoca, Romania.,Gastroenterology and Hepatology Medical Center, Cluj-Napoca, Romania
| | - Andrea Szentesi
- Centre for Translational Medicine, Department of Medicine, University of Szeged, Szeged, Hungary.,Institute for Translational Medicine, Szentágothai Research Centre, Medical School, University of Pécs, Pécs, Hungary
| | - Péter Hegyi
- Institute for Translational Medicine, Szentágothai Research Centre, Medical School, University of Pécs, Pécs, Hungary.,Division of Pancreatic Diseases, Heart and Vascular Centre, Semmelweis University, Budapest, Hungary.,Centre for Translational Medicine, Semmelweis University, Budapest, Hungary
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Jaber S, Garnier M, Asehnoune K, Bounes F, Buscail L, Chevaux JB, Dahyot-Fizelier C, Darrivere L, Jabaudon M, Joannes-Boyau O, Launey Y, Levesque E, Levy P, Montravers P, Muller L, Rimmelé T, Roger C, Savoye-Collet C, Seguin P, Tasu JP, Thibault R, Vanbiervliet G, Weiss E, De Jong A. Guidelines for the management of patients with severe acute pancreatitis, 2021. Anaesth Crit Care Pain Med 2022; 41:101060. [PMID: 35636304 DOI: 10.1016/j.accpm.2022.101060] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
OBJECTIVE To provide guidelines for the management of the intensive care patient with severe acute pancreatitis. DESIGN A consensus committee of 22 experts was convened. A formal conflict-of-interest (COI) policy was developed at the beginning of the process and enforced throughout. The entire guideline construction process was conducted independently of any industrial funding (i.e. pharmaceutical, medical devices). The authors were required to follow the rules of the Grading of Recommendations Assessment, Development and Evaluation (GRADE®) system to guide assessment of quality of evidence. The potential drawbacks of making strong recommendations in the presence of low-quality evidence were emphasised. METHODS The most recent SFAR and SNFGE guidelines on the management of the patient with severe pancreatitis were published in 2001. The literature now is sufficient for an update. The committee studied 14 questions within 3 fields. Each question was formulated in a PICO (Patients Intervention Comparison Outcome) format and the relevant evidence profiles were produced. The literature review and recommendations were made according to the GRADE® methodology. RESULTS The experts' synthesis work and their application of the GRADE® method resulted in 24 recommendations. Among the formalised recommendations, 8 have high levels of evidence (GRADE 1+/-) and 12 have moderate levels of evidence (GRADE 2+/-). For 4 recommendations, the GRADE method could not be applied, resulting in expert opinions. Four questions did not find any response in the literature. After one round of scoring, strong agreement was reached for all the recommendations. CONCLUSIONS There was strong agreement among experts for 24 recommendations to improve practices for the management of intensive care patients with severe acute pancreatitis.
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Affiliation(s)
- Samir Jaber
- Department of Anaesthesiology and Intensive Care (DAR B), University Hospital Center Saint Eloi Hospital, Montpellier, France; PhyMedExp, Montpellier University, INSERM, CNRS, CHU de Montpellier, Montpellier, France.
| | - Marc Garnier
- Sorbonne Université, GRC 29, DMU DREAM, Service d'Anesthésie-Réanimation et Médecine Périopératoire Rive Droite, Paris, France
| | - Karim Asehnoune
- Service d'Anesthésie, Réanimation chirurgicale, Hôtel Dieu/HME, CHU Nantes, Nantes cedex 1, France; Inserm, UMR 1064 CR2TI, team 6, France
| | - Fanny Bounes
- Toulouse University Hospital, Anaesthesia Critical Care and Perioperative Medicine Department, Toulouse, France; Équipe INSERM Pr Payrastre, I2MC, Université Paul Sabatier Toulouse III, Toulouse, France
| | - Louis Buscail
- Department of Gastroenterology & Pancreatology, University of Toulouse, Rangueil Hospital, Toulouse, France
| | | | - Claire Dahyot-Fizelier
- Anaesthesiology and Intensive Care Department, University hospital of Poitiers, Poitiers, France; INSERM U1070, University of Poitiers, Poitiers, France
| | - Lucie Darrivere
- Department of Anaesthesia and Critical Care Medicine, AP-HP, Hôpital Lariboisière, F-75010, Paris, France
| | - Matthieu Jabaudon
- Department of Perioperative Medicine, CHU Clermont-Ferrand, Clermont-Ferrand, France; iGReD, Université Clermont Auvergne, CNRS, INSERM, Clermont-Ferrand, France
| | - Olivier Joannes-Boyau
- Service d'Anesthésie-Réanimation SUD, CHU de Bordeaux, Hôpital Magellan, Bordeaux, France
| | - Yoann Launey
- Critical Care Unit, Department of Anaesthesia, Critical Care and Perioperative Medicine, University Hospital of Rennes, Rennes, France
| | - Eric Levesque
- Department of Anaesthesia and Surgical Intensive Care, AP-HP, Henri Mondor Hospital, Créteil, France; Université Paris-Est Creteil, EnvA, DYNAMiC, Faculté de Santé de Créteil, Creteil, France
| | - Philippe Levy
- Service de Pancréatologie et d'Oncologie Digestive, DMU DIGEST, Université de Paris, Hôpital Beaujon, APHP, Clichy, France
| | - Philippe Montravers
- Université de Paris Cité, INSERM UMR 1152 - PHERE, Paris, France; Département d'Anesthésie-Réanimation, APHP, CHU Bichat-Claude Bernard, DMU PARABOL, APHP, Paris, France
| | - Laurent Muller
- Réanimations et surveillance continue, Pôle Anesthésie Réanimation Douleur Urgences, CHU Nîmes Caremeau, Montpellier, France
| | - Thomas Rimmelé
- Département d'anesthésie-réanimation, Hôpital Édouard Herriot, Hospices Civils de Lyon, Lyon, France; EA 7426: Pathophysiology of Injury-induced Immunosuppression, Pi3, Hospices Civils de Lyon-Biomérieux-Université Claude Bernard Lyon 1, Lyon, France
| | - Claire Roger
- Réanimations et surveillance continue, Pôle Anesthésie Réanimation Douleur Urgences, CHU Nîmes Caremeau, Montpellier, France; Department of Intensive care medicine, Division of Anaesthesiology, Intensive Care, Pain and Emergency Medicine, Nîmes University Hospital, Nîmes, France
| | - Céline Savoye-Collet
- Department of Radiology, Normandie University, UNIROUEN, Quantif-LITIS EA 4108, Rouen University Hospital-Charles Nicolle, Rouen, France
| | - Philippe Seguin
- Service d'Anesthésie Réanimation 1, Réanimation chirurgicale, CHU de Rennes, Rennes, France
| | - Jean-Pierre Tasu
- Service de radiologie diagnostique et interventionnelle, CHU de Poitiers, Poitiers, France; LaTim, UBO and INSERM 1101, University of Brest, Brest, France
| | - Ronan Thibault
- Service Endocrinologie-Diabétologie-Nutrition, CHU Rennes, INRAE, INSERM, Univ Rennes, NuMeCan, Nutrition Metabolisms Cancer, Rennes, France
| | - Geoffroy Vanbiervliet
- Department of Digestive Endoscopy, Centre Hospitalier Universitaire de Nice, Nice, France
| | - Emmanuel Weiss
- Department of Anaesthesiology and Critical Care, Beaujon Hospital, DMU Parabol, AP-HP.Nord, Clichy, France; University of Paris, Paris, France; Inserm UMR_S1149, Centre for Research on Inflammation, Paris, France
| | - Audrey De Jong
- Department of Anaesthesiology and Intensive Care (DAR B), University Hospital Center Saint Eloi Hospital, Montpellier, France; PhyMedExp, Montpellier University, INSERM, CNRS, CHU de Montpellier, Montpellier, France
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Ha TN, Kamarova S, Youens D, Wright C, McRobbie D, Doust J, Slavotinek J, Bulsara MK, Moorin R. Trend in CT utilisation and its impact on length of stay, readmission and hospital mortality in Western Australia tertiary hospitals: an analysis of linked administrative data 2003-2015. BMJ Open 2022; 12:e059242. [PMID: 35649618 PMCID: PMC9161060 DOI: 10.1136/bmjopen-2021-059242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
OBJECTIVE High use of CT scanning has raised concern due to the potential ionising radiation exposure. This study examined trends of CT during admission to tertiary hospitals and its associations with length of stay (LOS), readmission and mortality. DESIGN Retrospective observational study from 2003 to 2015. SETTING West Australian linked administrative records at individual level. PARTICIPANTS 2 375 787 episodes of tertiary hospital admission in adults aged 18+ years. MAIN OUTCOME MEASURES LOS, 30-day readmissions and mortality stratified by CT use status (any, multiple (CTs to multiple areas during episode), and repeat (repeated CT to the same area)). METHODS Multivariable regression models were used to calculate adjusted rate of CT use status. The significance of changes since 2003 in the outcomes (LOS, 30-day readmission and mortality) was compared among patients with specific CT imaging status relative to those without. RESULTS Between 2003 and 2015, while the rate of CT increased 3.4% annually, the rate of repeat CTs significantly decreased -1.8% annually and multiple CT showed no change. Compared with 2003 while LOS had a greater decrease in those with any CT, 30-day readmissions had a greater increase among those with any CT, while the probability of mortality remained unchanged between the any CT/no CT groups. A similar result was observed in patients with multiple and repeat CT scanning, except for a significant increase in mortality in the recent years in the repeat CT group. CONCLUSION The observed pattern of increase in CT utilisation is likely to be activity-based funding policy-driven based on the discordance between LOS and readmissions. Meanwhile, the repeat CT reduction aligns with a more selective strategy of use based on clinical severity. Future research should incorporate in-hospital and out-of-hospital CT to better understand overall CT trends and potential shifts between settings over time.
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Affiliation(s)
- Thi Ninh Ha
- Health Economics and Data Analytics, School of Population Health, Curtin University, Perth, Western Australia, Australia
| | - Sviatlana Kamarova
- Health Economics and Data Analytics, School of Population Health, Curtin University, Perth, Western Australia, Australia
| | - David Youens
- Health Economics and Data Analytics, School of Population Health, Curtin University, Perth, Western Australia, Australia
| | - Cameron Wright
- Health Systems and Health Economics, Curtin University School of Public Health, Perth, Western Australia, Australia
- Fiona Stanley Hospital, Murdoch, Western Australia, Australia
- Division of Internal Medicine, Medical School, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, Western Australia, Australia
- School of Medicine, College of Health and Medicine, University of Tasmania, Hobart, Tasmania, Australia
| | - Donald McRobbie
- The University of Adelaide School of Physical Sciences, Adelaide, South Australia, Australia
| | - Jenny Doust
- Centre for Longitudinal and Life Course Research, The University of Queensland, Herston, Queensland, Australia
| | - John Slavotinek
- SA Medical Imaging, SA Health and College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - Max K Bulsara
- Institute of Health and Rehabilitation Research, University of Notre Dame, Fremantle, Western Australia, Australia
- Centre for Health Services Research, School of Population and Global Health, The University of Western Australia, Perth, Western Australia, Australia
| | - Rachael Moorin
- Health Economics and Data Analytics, School of Population Health, Curtin University, Perth, Western Australia, Australia
- Centre for Health Services Research, School of Population and Global Health, The University of Western Australia, Perth, Western Australia, Australia
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Chen X, Jin M, Li Y, Lai Y, Bai X, Yang H, Lv H, Qian J. Calcium and pH value might predict persistent renal failure in acute pancreatitis in the early phase. Curr Med Res Opin 2022; 38:535-540. [PMID: 35176958 DOI: 10.1080/03007995.2022.2038486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
OBJECTIVES Persistent renal failure (PRF) increases morbidity and mortality in acute pancreatitis (AP). Traditional scoring systems achieve good diagnostic value of AP but not PRF alone. Our study aimed to determine PRF predictors in AP patients for early intervention in the disease development. METHODS In the prospective observational study, we consecutively recruited AP patients from October 2013 to October 2016. Complete clinical characteristics on admission were collected. The 2012 revision of the Atlanta classification diagnosed AP, and the Modified Marshall scoring system defined organ failures. We used univariate and multivariate analyses to select risk factors, and plotted survival curves of different groups and ROC curves of parameters to analyze PRF predictors in AP. RESULTS A total of 29 AP patients with PRF and 280 AP patients without PRF were included. Severity scoring and ICU admission rate were higher in the former group. The PRF group's mortality was 10-fold higher than without PRF (20.7% versus 2.1%, p < .001). Most relevant kidney metabolism indicators and excretion have significant differences (p < .05) between the two groups. Serum calcium (Ca) and pH value (pH) were independent risk factors of PRF (p < .05). ROC curve analysis indicated Ca and pH might predict PRF in AP with areas under the curves (AUCs) of 0.758 and 0.809. CONCLUSIONS AP patients with PRF had higher morbidity and mortality rate. Our study showed that Ca < 1.94 mmol/L and pH < 7.37 when patients on admission could be used to predict PRF in AP.
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Affiliation(s)
- Xuanfu Chen
- Department of Gastroenterology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Meng Jin
- Department of Gastroenterology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Yi Li
- Department of Emergency, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Yamin Lai
- Department of Gastroenterology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Xiaoyin Bai
- Department of Gastroenterology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Hong Yang
- Department of Gastroenterology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Hong Lv
- Department of Gastroenterology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Jiaming Qian
- Department of Gastroenterology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
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Thapa R, Iqbal Z, Garikipati A, Siefkas A, Hoffman J, Mao Q, Das R. Early prediction of severe acute pancreatitis using machine learning. Pancreatology 2022; 22:43-50. [PMID: 34690046 DOI: 10.1016/j.pan.2021.10.003] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 09/27/2021] [Accepted: 10/12/2021] [Indexed: 12/11/2022]
Abstract
BACKGROUND Acute pancreatitis (AP) is one of the most common causes of gastrointestinal-related hospitalizations in the United States. Severe AP (SAP) is associated with a mortality rate of nearly 30% and is distinguished from milder forms of AP. Risk stratification to identify SAP cases needing inpatient treatment is an important aspect of AP diagnosis. METHODS We developed machine learning algorithms to predict which patients presenting with AP would require treatment for SAP. Three models were developed using logistic regression, neural networks, and XGBoost. Models were assessed in terms of area under the receiver operating characteristic (AUROC) and compared to the Harmless Acute Pancreatitis Score (HAPS) and Bedside Index for Severity in Acute Pancreatitis (BISAP) scores for AP risk stratification. RESULTS 61,894 patients were used to train and test the machine learning models. With an AUROC value of 0.921, the model developed using XGBoost outperformed the logistic regression and neural network-based models. The XGBoost model also achieved a higher AUROC than both HAPS and BISAP for identifying patients who would be diagnosed with SAP. CONCLUSIONS Machine learning may be able to improve the accuracy of AP risk stratification methods and allow for more timely treatment and initiation of interventions.
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Machine learning predictive models for acute pancreatitis: A systematic review. Int J Med Inform 2021; 157:104641. [PMID: 34785488 DOI: 10.1016/j.ijmedinf.2021.104641] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 11/03/2021] [Accepted: 11/05/2021] [Indexed: 12/14/2022]
Abstract
INTRODUCTION Acute pancreatitis (AP) is a common clinical pancreatic disease. Patients with different severity levels have different clinical outcomes. With the advantages of algorithms, machine learning (ML) has gradually emerged in the field of disease prediction, assisting doctors in decision-making. METHODS A systematic review was conducted using the PubMed, Web of Science, Scopus, and Embase databases, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Publication time was limited from inception to 29 May 2021. Studies that have used ML to establish predictive tools for AP were eligible for inclusion. Quality assessment of the included studies was conducted in accordance with the IJMEDI checklist. RESULTS In this systematic review, 24 of 2,913 articles, with a total of 8,327 patients and 47 models, were included. The studies could be divided into five categories: 10 studies (42%) reported severity prediction; 10 studies (42%), complication prediction; 3 studies (13%), mortality prediction; 2 studies (8%), recurrence prediction; and 2 studies (8%), surgery timing prediction. ML showed great accuracy in several prediction tasks. However, most of the included studies were retrospective in nature, conducted at a single centre, based on database data, and lacked external validation. According to the IJMEDI checklist and our scoring criteria, two studies were considered to be of high quality. Most studies had an obvious bias in the quality of data preparation, validation, and deployment dimensions. CONCLUSION In the prediction tasks for AP, ML has shown great potential in assisting decision-making. However, the existing studies still have some deficiencies in the process of model construction. Future studies need to optimize the deficiencies and further evaluate the comparability of the ML systems and model performance, so as to consequently develop high-quality ML-based models that can be used in clinical practice.
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Teng TZJ, Tan JKT, Baey S, Gunasekaran SK, Junnarkar SP, Low JK, Huey CWT, Shelat VG. Sequential organ failure assessment score is superior to other prognostic indices in acute pancreatitis. World J Crit Care Med 2021; 10:355-368. [PMID: 34888161 PMCID: PMC8613719 DOI: 10.5492/wjccm.v10.i6.355] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 08/10/2021] [Accepted: 10/11/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Acute pancreatitis (AP) is a common surgical condition, with severe AP (SAP) potentially lethal. Many prognostic indices, including; acute physiology and chronic health evaluation II score (APACHE II), bedside index of severity in acute pancreatitis (BISAP), Glasgow score, harmless acute pancreatitis score (HAPS), Ranson's score, and sequential organ failure assessment (SOFA) evaluate AP severity and predict mortality. AIM To evaluate these indices' utility in predicting severity, intensive care unit (ICU) admission, and mortality. METHODS A retrospective analysis of 653 patients with AP from July 2009 to September 2016 was performed. The demographic, clinical profile, and patient outcomes were collected. SAP was defined as per the revised Atlanta classification. Values for APACHE II score, BISAP, HAPS, and SOFA within 24 h of admission were retrospectively obtained based on laboratory results and patient evaluation recorded on a secure hospital-based online electronic platform. Data with < 10% missing data was imputed via mean substitution. Other patient information such as demographics, disease etiology, and patient outcomes were also derived from electronic medical records. RESULTS The mean age was 58.7 ± 17.5 years, with 58.7% males. Gallstones (n = 404, 61.9%), alcohol (n = 38, 5.8%), and hypertriglyceridemia (n = 19, 2.9%) were more common aetiologies. 81 (12.4%) patients developed SAP, 20 (3.1%) required ICU admission, and 12 (1.8%) deaths were attributed to SAP. Ranson's score and APACHE-II demonstrated the highest sensitivity in predicting SAP (92.6%, 80.2% respectively), ICU admission (100%), and mortality (100%). While SOFA and BISAP demonstrated lowest sensitivity in predicting SAP (13.6%, 24.7% respectively), ICU admission (40.0%, 25.0% respectively) and mortality (50.0%, 25.5% respectively). However, SOFA demonstrated the highest specificity in predicting SAP (99.7%), ICU admission (99.2%), and mortality (98.9%). SOFA demonstrated the highest positive predictive value, positive likelihood ratio, diagnostic odds ratio, and overall accuracy in predicting SAP, ICU admission, and mortality. SOFA and Ranson's score demonstrated the highest area under receiver-operator curves at 48 h in predicting SAP (0.966, 0.857 respectively), ICU admission (0.943, 0.946 respectively), and mortality (0.968, 0.917 respectively). CONCLUSION The SOFA and 48-h Ranson's scores accurately predict severity, ICU admission, and mortality in AP, with more favorable statistics for the SOFA score.
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Affiliation(s)
- Thomas Zheng Jie Teng
- Department of General Surgery, Tan Tock Seng Hospital, Singapore 308433, Singapore
- Undergraduate Medicine, Lee Kong Chian School of Medicine, Singapore 308232, Singapore
| | | | - Samantha Baey
- Undergraduate Medicine, Yong Loo Lin School of Medicine, Singapore 119077, Singapore
| | | | - Sameer P Junnarkar
- Department of General Surgery, Tan Tock Seng Hospital, Singapore 308433, Singapore
| | - Jee Keem Low
- Department of General Surgery, Tan Tock Seng Hospital, Singapore 308433, Singapore
| | | | - Vishal G Shelat
- Department of General Surgery, Tan Tock Seng Hospital, Singapore 308433, Singapore
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Shi N, Sun GD, Ji YY, Wang Y, Zhu YC, Xie WQ, Li NN, Han QY, Qi ZD, Huang R, Li M, Yang ZY, Zheng JB, Zhang X, Dai QQ, Hou GY, Liu YS, Wang HL, Gao Y. Effects of acute kidney injury on acute pancreatitis patients’ survival rate in intensive care unit: A retrospective study. World J Gastroenterol 2021; 27:6453-6464. [PMID: 34720534 PMCID: PMC8517775 DOI: 10.3748/wjg.v27.i38.6453] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 04/15/2021] [Accepted: 08/23/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Acute kidney injury (AKI) is one of the most common acute pancreatitis (AP)-associated complications that has a significant effect on AP, but the factors affecting the AP patients’ survival rate remains unclear.
AIM To assess the influences of AKI on the survival rate in AP patients.
METHODS A total of 139 AP patients were included in this retrospective study. Patients were divided into AKI group (n = 72) and non-AKI group (n = 67) according to the occurrence of AKI. Data were collected from medical records of hospitalized patients. Then, these data were compared between the two groups and further analysis was performed.
RESULTS AKI is more likely to occur in male AP patients (P = 0.009). AP patients in AKI group exhibited a significantly higher acute physiologic assessment and chronic health evaluation II score, higher Sequential Organ Failure Assessment score, lower Glasgow Coma Scale score, and higher demand for mechanical ventilation, infusion of vasopressors, and renal replacement therapy than AP patients in non-AKI group (P < 0.01, P < 0.01, P = 0.01, P = 0.001, P < 0.01, P < 0.01, respectively). Significant differences were noted in dose of norepinephrine and adrenaline, duration of mechanical ventilation, maximum and mean values of intra-peritoneal pressure (IPP), maximum and mean values of procalcitonin, maximum and mean serum levels of creatinine, minimum platelet count, and length of hospitalization. Among AP patients with AKI, the survival rate of surgical intensive care unit and in-hospital were only 23% and 21% of the corresponding rates in AP patients without AKI, respectively. The factors that influenced the AP patients’ survival rate included body mass index (BMI), mean values of IPP, minimum platelet count, and hospital day, of which mean values of IPP showed the greatest impact.
CONCLUSION AP patients with AKI had a lower survival rate and worse relevant clinical outcomes than AP patients without AKI, which necessitates further attention to AP patients with AKI in surgical intensive care unit.
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Affiliation(s)
- Ni Shi
- Department of Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, Heilongjiang Province, China
| | - Guo-Dong Sun
- Department of Critical Care Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, Heilongjiang Province, China
| | - Yuan-Yuan Ji
- Department of Critical Care Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, Heilongjiang Province, China
| | - Ying Wang
- Department of Critical Care Medicine, The First People Hospital of Mudanjiang city, Mudanjiang 157000, Heilongjiang Province, China
| | - Yu-Cheng Zhu
- Department of Critical Care Medicine, The Hongxinglong Hospital of Beidahuang Group, Shuangyashan 155811, Heilongjiang Province, China
| | - Wan-Qiu Xie
- Department of Critical Care Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, Heilongjiang Province, China
| | - Na-Na Li
- Department of Critical Care Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, Heilongjiang Province, China
| | - Qiu-Yuan Han
- Department of Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, Heilongjiang Province, China
| | - Zhi-Dong Qi
- Department of Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, Heilongjiang Province, China
| | - Rui Huang
- Department of Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, Heilongjiang Province, China
| | - Ming Li
- Department of Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, Heilongjiang Province, China
| | - Zhen-Yu Yang
- Department of Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, Heilongjiang Province, China
| | - Jun-Bo Zheng
- Department of Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, Heilongjiang Province, China
| | - Xing Zhang
- Department of Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, Heilongjiang Province, China
| | - Qing-Qing Dai
- Department of Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, Heilongjiang Province, China
| | - Gui-Ying Hou
- Department of Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, Heilongjiang Province, China
| | - Yan-Song Liu
- Department of Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, Heilongjiang Province, China
| | - Hong-Liang Wang
- Department of Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, Heilongjiang Province, China
| | - Yang Gao
- Department of Critical Care Medicine, The Sixth Affiliated Hospital of Harbin Medical University, Harbin 150028, Heilongjiang Province, China
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Patel BK, Patel KH, Bhatia M, Iyer SG, Madhavan K, Moochhala SM. Gut microbiome in acute pancreatitis: A review based on current literature. World J Gastroenterol 2021; 27:5019-5036. [PMID: 34497432 PMCID: PMC8384740 DOI: 10.3748/wjg.v27.i30.5019] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 06/04/2021] [Accepted: 06/23/2021] [Indexed: 02/06/2023] Open
Abstract
The gut microbiome is a complex microbial community, recognized for its potential role in physiology, health, and disease. The available evidence supports the role of gut dysbiosis in pancreatic disorders, including acute pancreatitis (AP). In AP, the presence of gut barrier damage resulting in increased mucosal permeability may lead to translocation of intestinal bacteria, necrosis of pancreatic and peripancreatic tissue, and infection, often accompanied by multiple organ dysfunction syndrome. Preserving gut microbial homeostasis may reduce the systemic effects of AP. A growing body of evidence suggests the possible involvement of the gut microbiome in various pancreatic diseases, including AP. This review discusses the possible role of the gut microbiome in AP. It highlights AP treatment and supplementation with prebiotics, synbiotics, and probiotics to maintain gastrointestinal microbial balance and effectively reduce hospitalization, morbidity and mortality in an early phase. It also addresses novel therapeutic areas in the gut microbiome, personalized treatment, and provides a roadmap of human microbial contributions to AP that have potential clinical benefit.
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Affiliation(s)
- Bharati Kadamb Patel
- Department of Surgery, National University of Singapore, Singapore 119228, Singapore
| | - Kadamb H Patel
- School of Applied Sciences, Temasek Polytechnic, Singapore 529757, Singapore
| | - Madhav Bhatia
- Department of Pathology, University of Otago, Christchurch 8140, New Zealand
| | - Shridhar Ganpati Iyer
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
- National University Hospital, National University of Singapore, Singapore 119228, Singapore
| | - Krishnakumar Madhavan
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
- National University Hospital, National University of Singapore, Singapore 119228, Singapore
| | - Shabbir M Moochhala
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
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Abstract
Introduction: Acute pancreatitis (AP) is a common gastrointestinal disease with a wide spectrum of severity and morbidity. Developed in 1974, the Ranson score was the first scoring system to prognosticate AP. Over the past decades, while the Ranson score remains widely used, it was identified to have certain limitations, such as having low predictive power. It has also been criticized for its 48-hour requirement for computation of the final score, which has been argued to potentially delay management. With advancements in our understanding of AP, is the Ranson score still relevant as an effective prognostication system for AP?Areas covered: This review summarizes the available evidence comparing Ranson score with other conventional and novel scoring systems, in terms of prognostic accuracy, benefits, limitations and clinical applicability. It also evaluates the effectiveness of Ranson score with regard to the Revised Atlanta Classification.Expert opinion: The Ranson score consistently exhibits comparable prognostic accuracy to other newer scoring systems, and the 48-hour timeframe for computing the full Ranson score is an inherent strength, not a weakness. These aspects, coupled with relative ease of use, practicality and universality of the score, advocate for the continued relevance of the Ranson score in modern clinical practice.
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Affiliation(s)
- Yuki Ong
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Vishal G Shelat
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- FRCS (General Surgery), FEBS (HPB Surgery), Hepato-Pancreatico-BiliarySurgery, Department of Surgery, Tan Tock Seng Hospital, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
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Wang Y, Xu Z, Zhou Y, Xie M, Qi X, Xu Z, Cai Q, Sheng H, Chen E, Zhao B, Mao E. Leukocyte cell population data from the blood cell analyzer as a predictive marker for severity of acute pancreatitis. J Clin Lab Anal 2021; 35:e23863. [PMID: 34062621 PMCID: PMC8274994 DOI: 10.1002/jcla.23863] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 05/11/2021] [Accepted: 05/16/2021] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND The prediction for severe acute pancreatitis (SAP) is the key to give timely targeted treatment. Leukocyte cell population data (CPD) have been widely applied in early prediction and diagnosis of many diseases, but their predictive ability for SAP remains unexplored. We aim to testify whether CPD could be an indicator of AP severity in the early stage of the disease. METHODS The prospective observational study was conducted in the emergency department ward of a territory hospital in Shanghai. The enrolled AP patients should meet 2012 Atlanta guideline. RESULTS Totally, 103 AP patients and 62 healthy controls were enrolled and patients were classified into mild AP (n = 30), moderate SAP (n = 42), and SAP (n = 31). Forty-two CPD parameters were examined in first 3 days of admission. Four CPD parameters were highest in SAP on admission and were constantly different among 3 groups during first 3 days of hospital stay. Eighteen CPD parameters were found correlated with the occurrence of SAP. Stepwise multivariate logistic regression analysis identified a scoring system of 4 parameters (SD_LALS_NE, MN_LALS_LY, SD_LMALS_MO, and SD_AL2_MO) with a sensitivity of 96.8%, specificity of 65.3%, and AUC of 0.87 for diagnostic accuracy on early identification of SAP. AUC of this scoring system was comparable with MCTSI, SOFA, APACHE II, MMS, BISAP, or biomarkers as CRP, PCT, and WBC in prediction of SAP and ICU transfer or death. CONCLUSIONS Several leukocyte CPD parameters have been identified different among MAP, MSAP, and SAP. They might be ultimately incorporated into a predictive system marker for severity of AP.
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Affiliation(s)
- Yihui Wang
- Department of EmergencyRuijin HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Zhihong Xu
- Department of EmergencyRuijin HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Yuhua Zhou
- Department of EmergencyRuijin HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Mengqi Xie
- Department of EmergencyRuijin HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Xing Qi
- Department of EmergencyRuijin HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Zhiwei Xu
- Department of General SurgeryPancreatic Disease CenterRuijin HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Qi Cai
- Department of Laboratory MedicineRuijin HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Huiqiu Sheng
- Department of EmergencyRuijin HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Erzhen Chen
- Department of EmergencyRuijin HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Bing Zhao
- Department of EmergencyRuijin HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Enqiang Mao
- Department of EmergencyRuijin HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
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Abstract
BACKGROUND Both, acute and chronic pancreatitis represent complex disease patterns, whose effective treatment is based on structured diagnostics and therapy by a multi-professional team. There are different systems for an improved objectivity in the classification of the severity of the disease OBJECTIVES: Overview of the common classifications of acute and chronic pancreatitis. MATERIALS AND METHODS Literature research of currently used classifications of acute and chronic pancreatitis. Evaluation of the current chronic pancreatitis guideline. RESULTS For acute pancreatitis, the modified Atlanta Classification and the "determinant-based" classification are most widely used. These classifications are complemented by clinical risk scores such as the Marshall Score and the SOFA Score. In chronic pancreatitis, the image-based Cambridge classification was established. For clinical assessment further classifications such as the ABC classification and the M‑ANNHEIM classification are applied evaluating leading symptoms such as pain, exocrine and endocrine pancreatic insufficiency.
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Affiliation(s)
- K F Hoß
- Klinik für diagnostische und interventionelle Radiologie, Universitätsklinikum Bonn, Venusberg-Campus 1, 53127, Bonn, Deutschland.
| | - U I Attenberger
- Klinik für diagnostische und interventionelle Radiologie, Universitätsklinikum Bonn, Venusberg-Campus 1, 53127, Bonn, Deutschland
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Zheng Z, Ding YX, Qu YX, Cao F, Li F. A narrative review of the mechanism of acute pancreatitis and recent advances in its clinical management. Am J Transl Res 2021; 13:833-852. [PMID: 33841625 PMCID: PMC8014344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Accepted: 12/15/2020] [Indexed: 06/12/2023]
Abstract
Acute pancreatitis (AP) is a common gastrointestinal disease with a high risk of mortality. Recently, the exosome and its potential regulatory role in the progression of AP has garnered the interest of researchers. However, effective drug interventions and therapeutic targets for AP remain to be established. Treatment approaches for AP have undergone considerable changes in the recent years: there is a greater preference for minimally invasive therapy (as primary treatment), multidisciplinary participation and the step-up approach. We aimed to discuss AP mechanism and the recent advancement in its treatment strategies to manage AP better in clinical practice.
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Affiliation(s)
- Zhi Zheng
- Department of General Surgery, Xuan Wu Hospital, Capital Medical UniversityBeijing 100053, China
- Clinical Center for Acute Pancreatitis, Capital Medical UniversityBeijing, China
| | - Yi-Xuan Ding
- Department of General Surgery, Xuan Wu Hospital, Capital Medical UniversityBeijing 100053, China
- Clinical Center for Acute Pancreatitis, Capital Medical UniversityBeijing, China
| | - Yuan-Xu Qu
- Department of General Surgery, Xuan Wu Hospital, Capital Medical UniversityBeijing 100053, China
- Clinical Center for Acute Pancreatitis, Capital Medical UniversityBeijing, China
| | - Feng Cao
- Department of General Surgery, Xuan Wu Hospital, Capital Medical UniversityBeijing 100053, China
- Clinical Center for Acute Pancreatitis, Capital Medical UniversityBeijing, China
| | - Fei Li
- Department of General Surgery, Xuan Wu Hospital, Capital Medical UniversityBeijing 100053, China
- Clinical Center for Acute Pancreatitis, Capital Medical UniversityBeijing, China
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Metabolomic-based clinical studies and murine models for acute pancreatitis disease: A review. Biochim Biophys Acta Mol Basis Dis 2021; 1867:166123. [PMID: 33713791 DOI: 10.1016/j.bbadis.2021.166123] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 01/21/2021] [Accepted: 03/03/2021] [Indexed: 02/07/2023]
Abstract
Acute pancreatitis (AP) is one of the most common gastroenterological disorders requiring hospitalization and is associated with substantial morbidity and mortality. Metabolomics nowadays not only help us to understand cellular metabolism to a degree that was not previously obtainable, but also to reveal the importance of the metabolites in physiological control, disease onset and development. An in-depth understanding of metabolic phenotyping would be therefore crucial for accurate diagnosis, prognosis and precise treatment of AP. In this review, we summarized and addressed the metabolomics design and workflow in AP studies, as well as the results and analysis of the in-depth of research. Based on the metabolic profiling work in both clinical populations and experimental AP models, we described the metabolites with potential utility as biomarkers and the correlation between the altered metabolites and AP status. Moreover, the disturbed metabolic pathways correlated with biological function were discussed in the end. A practical understanding of current and emerging metabolomic approaches applicable to AP and use of the metabolite information presented will aid in designing robust metabolomics and biological experiments that result in identification of unique biomarkers and mechanisms, and ultimately enhanced clinical decision-making.
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Prajapati R, Manay P, Sugumar K, Rahandale V, Satoskar R. Acute pancreatitis: predictors of mortality, pancreatic necrosis and intervention. Turk J Surg 2021; 37:13-21. [PMID: 34585089 PMCID: PMC8448565 DOI: 10.47717/turkjsurg.2021.5072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Accepted: 01/31/2021] [Indexed: 11/23/2022]
Abstract
OBJECTIVES Several predictive scoring systems are used in the prognostication of acute pancreatitis (AP). However, the quantity of evidence of these prognostic systems in the Indian population remains sparse. The aim of our study was to evaluate the usefulness of such prognostic scores to predict mortality, incidence of pancreatic necrosis and intervention in AP. MATERIAL AND METHODS This was an observational study of patients diagnosed with AP between June 2012 and November 2013 in a tertiary referral center in India. Vital signs, biochemical tests and CT-findings were recorded to identify SIRS, Ranson's score and CT-severity index at diagnosis. Chi square test was used to compare incidence of mortality, pancreatic necrosis, and intervention between mild versus severe acute pancreatitis groups. RESULTS A total of 100 patients with AP were treated during out study period. Ranson's score more than 7 and presence of pancreatic necrosis were significantly associated with increased mortality (p <0.05). SIRS, CTSI score more than 7, inotropic support, and complications were more frequently associated with patients with necrosis. Prophylactic antibiotics did not decrease mortality, but decreased intervention rate (p <0.05). Presence of systemic inflammatory response syndrome (SIRS), Ranson's score > 7, necrosis, inotropic support and presence of complications were associated with a greater rate of interventions including surgery and percutaneous procedures (p <0.05). CONCLUSION We validate SIRS, Ranson's, and CTSI score as prognostic markers for AP in the Indian population. These predictors, when used in combination, can direct early monitoring and aggressive management in order to decrease mortality associated with severe AP.
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Affiliation(s)
- Ramlal Prajapati
- Department of Surgery, University Hospitals, Seidman Cancer Center, Cleveland, United States
| | - Priyadarshini Manay
- Department of Transplant Surgery, University of Iowa Hospitals & Clinics, Iowa City, United States
| | - Kavin Sugumar
- Department of Surgery, University Hospitals, Seidman Cancer Center, Cleveland, United States
| | - Vinay Rahandale
- Department of Surgery, Seth G.S Medical College and King Edward Memorial Hospital, Mumbai, India
| | - Rajeev Satoskar
- Department of Surgery, Seth G.S Medical College and King Edward Memorial Hospital, Mumbai, India
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Wang Y, Liu K, Xie X, Song B. Potential role of imaging for assessing acute pancreatitis-induced acute kidney injury. Br J Radiol 2021; 94:20200802. [PMID: 33237803 DOI: 10.1259/bjr.20200802] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Acute kidney injury (AKI) is a common complication of acute pancreatitis (AP) that is associated with increased mortality. Conventional assessment of AKI is based on changes in serum creatinine concentration and urinary output. However, these examinations have limited accuracy and sensitivity for the diagnosis of early-stage AKI. This review summarizes current evidence on the use of advanced imaging approaches and artificial intelligence (AI) for the early prediction and diagnosis of AKI in patients with AP. CT scores, CT post-processing technology, Doppler ultrasound, and AI technology provide increasingly valuable information for the diagnosis of AP-induced AKI. Magnetic resonance imaging (MRI) also has potential for the evaluation of AP-induced AKI. For the accurate diagnosis of early-stage AP-induced AKI, more studies are needed that use these new techniques and that use AI in combination with advanced imaging technologies.
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Affiliation(s)
- Yi Wang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Kaixiang Liu
- Department of Nephrology, Sichuan Academy of Medical Sciences and Sichuan Provincial People' s Hospital, University of Electronic Science and Technology of China, Chengdu, China.,Department of Nephrology, Nanchong Central Hospital, The Second Affiliated Medical College of North Sichuan Medical College, Nanchong, China
| | - Xisheng Xie
- Department of Nephrology, Nanchong Central Hospital, The Second Affiliated Medical College of North Sichuan Medical College, Nanchong, China
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
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Zheng Z, Ding YX, Qu YX, Cao F, Li F. A narrative review of acute pancreatitis and its diagnosis, pathogenetic mechanism, and management. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:69. [PMID: 33553362 PMCID: PMC7859757 DOI: 10.21037/atm-20-4802] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Acute pancreatitis (AP) is an inflammatory disease that can progress to severe acute pancreatitis (SAP), which increases the risk of death. AP is characterized by inappropriate activation of trypsinogen, infiltration of inflammatory cells, and destruction of secretory cells. Other contributing factors may include calcium (Ca2+) overload, mitochondrial dysfunction, impaired autophagy, and endoplasmic reticulum (ER) stress. In addition, exosomes are also associated with pathophysiological processes of many human diseases and may play a biological role in AP. However, the pathogenic mechanism has not been fully elucidated and needs to be further explored to inform treatment. Recently, the treatment guidelines have changed; minimally invasive therapy is advocated more as the core multidisciplinary participation and "step-up" approach. The surgical procedures have gradually changed from open surgery to minimally invasive surgery that primarily includes percutaneous catheter drainage (PCD), endoscopy, small incision surgery, and video-assisted surgery. The current guidelines for the management of AP have been updated and revised in many aspects. The type of fluid to be used, the timing, volume, and speed of administration for fluid resuscitation has been controversial. In addition, the timing and role of nutritional support and prophylactic antibiotic therapy, as well as the timing of the surgical or endoscopic intervention, and the management of complications still have many uncertainties that could negatively impact the prognosis and patients' quality of life. Consequently, to inform clinicians about optimal treatment, we aimed to review recent advances in the understanding of the pathogenesis of AP and its diagnosis and management.
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Affiliation(s)
- Zhi Zheng
- Department of General Surgery, Xuan Wu Hospital, Capital Medical University, Beijing, China
- Clinical Center for Acute Pancreatitis, Capital Medical University, Beijing, China
| | - Yi-Xuan Ding
- Department of General Surgery, Xuan Wu Hospital, Capital Medical University, Beijing, China
- Clinical Center for Acute Pancreatitis, Capital Medical University, Beijing, China
| | - Yuan-Xu Qu
- Department of General Surgery, Xuan Wu Hospital, Capital Medical University, Beijing, China
- Clinical Center for Acute Pancreatitis, Capital Medical University, Beijing, China
| | - Feng Cao
- Department of General Surgery, Xuan Wu Hospital, Capital Medical University, Beijing, China
- Clinical Center for Acute Pancreatitis, Capital Medical University, Beijing, China
| | - Fei Li
- Department of General Surgery, Xuan Wu Hospital, Capital Medical University, Beijing, China
- Clinical Center for Acute Pancreatitis, Capital Medical University, Beijing, China
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Early laboratory biomarkers for severity in acute pancreatitis; A systematic review and meta-analysis. Pancreatology 2020; 20:1302-1311. [PMID: 32938552 DOI: 10.1016/j.pan.2020.09.007] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2020] [Revised: 08/25/2020] [Accepted: 09/05/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND/OBJECTIVES Acute pancreatitis is complicated by local and systemic complications in 20-30% of the patients. Accurate prediction of severity may be important for clinical decision making. Our aim is to identify and compare the accuracy of laboratory biomarkers that predict severity and complications in adult patients. METHODS Medline, EMBASE, Web of Science and Cochrane Library (1993 to August 2020) were searched for studies with an unselected population of patients with acute pancreatitis, that contains accuracy data for ≥1 laboratory biomarker(s) and/or APACHE-II score for the prediction of a patient outcomes of interest during the first 48 h of admission. The primary outcome is moderate severe or severe acute pancreatitis (MSAP/SAP). Secondary outcomes are severe acute pancreatitis, pancreatic necrosis and organ failure. Risk of bias was assed using QUADAS-2. Biomarkers extracted from ≥3 unique sources, were analyzed using hierarchical summary receiver operating characteristic (HSROC) and bivariate model analysis. RESULTS In total, 181 studies were included in the qualitative analysis reporting on 29 biomarkers. For the primary outcome at admission, summary sensitivities and specificities were, respectively, 87% (95% CI 69-95%) and 88% (95% CI 80-93%) for IL-6 at a threshold of >50 pg/ml, 72% (95% CI 64-79%) and 76% (95% CI 67-84%) for an APACHE-II score of ≥8, and 53% (95% CI 35-71%) and 82% (95% CI 74-88%) for CRP >150 mg/l. HSROC curve analysis confirmed these results. CONCLUSION This study indicates superiority of IL-6 for the early prediction of MSAP/SAP and may be used for to guide clinical decision making.
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Abstract
OBJECTIVES Increasing data suggest that acute pancreatitis (AP) occurs more frequently among patients with inflammatory bowel diseases (IBDs) than in the non-IBD population; however, currently no comprehensive meta-analysis is available. METHODS Systematic literature search was conducted in 4 major databases. We included observational studies sampling from the general population. Basic study characteristics and crude incidences of AP were extracted. Pooled odds ratios (ORs) with 95% confidence interval (CIs) were calculated using the random-effects model. Subgroups were set up by Crohn disease and ulcerative colitis. Heterogeneity was tested with I statistics. RESULTS Eight studies were eligible for the analysis. The odds of AP were 3 times higher in IBD (OR, 3.11; 95% CI, 2.93-3.30; I, 0.0%), significantly higher in Crohn disease than in ulcerative colitis (P < 0.001; OR, 4.12 vs OR, 2.61; I, 0.0%). The pooled annual incidence of AP in IBD was 210/100,000 person-years (95% CI, 84-392/100,000 person-years; I, 98.66%). CONCLUSIONS We confirmed that IBD elevates the risk of AP and of 100,000 IBD patients 210 AP cases are to be expected annually. Therefore, it is important to include pancreatic enzyme level measurements and radiological investigations in the workup of IBD patients with acute abdominal pain.
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Váncsa S, Németh D, Hegyi P, Szakács Z, Hegyi PJ, Pécsi D, Mikó A, Erőss B, Erős A, Pár G. Fatty Liver Disease and Non-Alcoholic Fatty Liver Disease Worsen the Outcome in Acute Pancreatitis: A Systematic Review and Meta-Analysis. J Clin Med 2020; 9:E2698. [PMID: 32825458 PMCID: PMC7564684 DOI: 10.3390/jcm9092698] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 08/10/2020] [Accepted: 08/18/2020] [Indexed: 12/12/2022] Open
Abstract
The prevalence of fatty liver disease (FLD) and that of non-alcoholic fatty liver disease (NAFLD) share some risk factors known to exacerbate the course of acute pancreatitis (AP). This meta-analysis aimed to investigate whether FLD or NAFLD carry a higher risk of untoward outcomes in AP. In accordance with PRISMA guidelines, we performed a systematic search in seven medical databases for cohort studies that compared the outcomes of AP for the presence of FLD or NAFLD, and we calculated pooled odds ratio (OR) or weighted mean difference (WMD) with 95% confidence interval (CI). We included 13 articles in our meta-analysis. AP patients with FLD were more likely to die (5.09% vs 1.89%, OR = 3.56, CI = 1.75-7.22), develop severe AP (16.33% vs 7.87%, OR = 2.67, CI = 2.01-3.56), necrotizing pancreatitis (34.83% vs 15.75%, OR = 3.08, CI = 2.44-3.90) and had longer in-hospital stay (10.8 vs 9.2 days, WMD = 1.46, OR = 0.54-2.39). Patients with NAFLD were more likely to have severe AP and longer hospital stay. Both FLD and NAFLD proved to be independent risk factors of a more severe disease course (OR = 3.68, CI = 2.16-6.29 and OR = 3.39, CI = 1.52-7.56 for moderate/ severe vs. mild AP, respectively). FLD and NAFLD worsen the outcomes of AP, which suggests that incorporating FLD or NAFLD into prognostic scoring systems of AP outcomes might improve the prediction of severity and contribute to a more individualized patient care.
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Affiliation(s)
- Szilárd Váncsa
- Institute for Translational Medicine, Medical School, University of Pécs, 7624 Pécs, Hungary; (S.V.); (D.N.); (P.H.); (Z.S.); (P.J.H.); (D.P.); (A.M.); (B.E.)
- János Szentágothai Research Centre, University of Pécs, 7624 Pécs, Hungary;
| | - Dávid Németh
- Institute for Translational Medicine, Medical School, University of Pécs, 7624 Pécs, Hungary; (S.V.); (D.N.); (P.H.); (Z.S.); (P.J.H.); (D.P.); (A.M.); (B.E.)
| | - Péter Hegyi
- Institute for Translational Medicine, Medical School, University of Pécs, 7624 Pécs, Hungary; (S.V.); (D.N.); (P.H.); (Z.S.); (P.J.H.); (D.P.); (A.M.); (B.E.)
- Centre for Translational Medicine, Department of Medicine, University of Szeged, 6725 Szeged, Hungary
| | - Zsolt Szakács
- Institute for Translational Medicine, Medical School, University of Pécs, 7624 Pécs, Hungary; (S.V.); (D.N.); (P.H.); (Z.S.); (P.J.H.); (D.P.); (A.M.); (B.E.)
- János Szentágothai Research Centre, University of Pécs, 7624 Pécs, Hungary;
| | - Péter Jeno Hegyi
- Institute for Translational Medicine, Medical School, University of Pécs, 7624 Pécs, Hungary; (S.V.); (D.N.); (P.H.); (Z.S.); (P.J.H.); (D.P.); (A.M.); (B.E.)
| | - Dániel Pécsi
- Institute for Translational Medicine, Medical School, University of Pécs, 7624 Pécs, Hungary; (S.V.); (D.N.); (P.H.); (Z.S.); (P.J.H.); (D.P.); (A.M.); (B.E.)
- Division of Gastroenterology, First Department of Medicine, Medical School, University of Pécs, 7624 Pécs, Hungary
| | - Alexandra Mikó
- Institute for Translational Medicine, Medical School, University of Pécs, 7624 Pécs, Hungary; (S.V.); (D.N.); (P.H.); (Z.S.); (P.J.H.); (D.P.); (A.M.); (B.E.)
- Division of Gastroenterology, First Department of Medicine, Medical School, University of Pécs, 7624 Pécs, Hungary
| | - Bálint Erőss
- Institute for Translational Medicine, Medical School, University of Pécs, 7624 Pécs, Hungary; (S.V.); (D.N.); (P.H.); (Z.S.); (P.J.H.); (D.P.); (A.M.); (B.E.)
| | - Adrienn Erős
- János Szentágothai Research Centre, University of Pécs, 7624 Pécs, Hungary;
- Heim Pál Children’s Hospital, 1089 Budapest, Hungary
| | - Gabriella Pár
- Division of Gastroenterology, First Department of Medicine, Medical School, University of Pécs, 7624 Pécs, Hungary
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