Background: Changes in BUN have been proposed as a risk factor for complications in acute pancreatitis (AP). Our study aimed to compare changes in BUN versus the Bedside Index for Severity in Acute Pancreatitis (BISAP) score and the Acute Physiology and Chronic Health Evaluation-II score (APACHE-II), as well as other laboratory tests such as haematocrit and its variations over 24 h and C-reactive protein, in order to determine the most accurate test for predicting mortality and severity outcomes in AP.
Methods: Clinical data of 410 AP patients, prospectively enrolled for study at our institution, were analyzed. We define AP according to Atlanta classification (AC) 2012. The laboratory test's predictive accuracy was measured using area-under-the-curve receiver-operating characteristics (AUC) analysis and sensitivity and specificity tests.
Results: Rise in BUN was the only score related to mortality on the multivariate analysis (=0.000, OR: 12.7; CI 95%: 4.2-16.6). On the comparative analysis of AUC, the rise in BUN was an accurate test in predicting mortality (AUC: 0.842) and persisting multiorgan failure (AUC: 0.828), similar to the BISAP score (AUC: 0.836 and 0.850) and APACHE-II (AUC: 0.756 and 0.741). The BISAP score outperformed both APACHE-II and rise in BUN at 24 hours in predicting severe AP (AUC: 0.873 vs. 0.761 and 0.756, respectively).
Conclusion: Rise in BUN at 24 hours is a quick and reliable test in predicting mortality and persisting multiorgan failure in AP patients.
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http://dx.doi.org/10.1155/2021/6643595 | DOI Listing |
Recent Adv Inflamm Allergy Drug Discov
December 2024
Department of Surgery, Kuban State Medical University, Krasnodar Krai, Russia.
Introduction: Acute pancreatitis (AP) is a serious inflammatory disease of the pancreas that can lead to significant morbidity and increased mortality. The special role of inflammation and disruption of the hemostatic system in the development of severe forms of the disease is known, however, the relationship between inflammatory and anti-inflammatory cytokines and thromboelastogram parameters has not been sufficiently studied.
Aim: The aim of this study is to assess the prognostic significance of thromboelastogram parameters, interleukin-6, and interleukin-22 levels in assessing the risk for developing severe forms of acute pancreatitis.
Front Med (Lausanne)
December 2024
Department of Gastroenterology, First Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Objectives: To evaluate the clinical efficacy of probiotics and early oral feeding in patients with severe acute pancreatitis.
Methods: A prospective, randomized, controlled trial was conducted involving 66 patients, who were randomly divided into a control group ( = 32) receiving standard enteral nutrition and an observation group ( = 34) receiving additional Bifidobacterium quadruplex live bacterial tablets. Serum inflammatory markers, including white blood cells (WBC), interleukin-6 (IL-6), tumor necrosis factor- (TNF-α), and C-reactive protein (CRP), were measured on days 1, 3, and 7 post-admission.
Objective: Aim: To identify markers for predicting the severity of acute pancreatitis and the possible development of pancreatic necrosis.
Patients And Methods: Materials and Methods: Prospective analysis of 81 patients with moderate and severe acute pancreatitis while performing correlation analysis, building a logistic regression model.
Results: Results: A direct correlation of medium strength between sFGL2 and the following parameters was found D-dimer (R=0.
J Inflamm Res
November 2024
Department of Gastroenterology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, People's Republic of China.
Purpose: The objective of this study was to create a predictive model for the onset of persistent organ failure (POF) in individuals suffering from acute biliary pancreatitis (ABP) by utilizing indicators observed within 24 hours of hospital admission. Early detection of high-risk POF patients is crucial for clinical decision-making.
Patients And Methods: Clinical data and laboratory indicators within 24 hours of admission from ABP patients diagnosed at The First Affiliated Hospital of Wenzhou Medical University between January 1, 2016, and January 1, 2024 were collected and retrospectively analyzed.
Objective: To evaluate machine learning models' performance in predicting acute pancreatitis severity using early-stage variables while excluding laboratory and imaging tests.
Summary Background Data: Severe acute pancreatitis (SAP) affects approximately 20% of acute pancreatitis (AP) patients and is associated with high mortality rates. Accurate early prediction of SAP and in-hospital mortality is crucial for effective management.
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