Background: Identification of patients at risk for severe disease early in the course of acute pancreatitis (AP) is essential to optimize management and to improve outcomes.
Aim: To assess BISAP score as a predictor of severity of AP.
Patients And Methods: Retrospective review of AP patients between January 2009 and December 2010. BISAP, APACHE II and Balthazar scores were calculated. Length of stay, local complications, organ failure and mortality were registered. Accuracy of the scoring system for predicting severity was measured by the area under the receiver operating curve (AUC).
Results: The medical records of 128 patients, median age 46.5 years (55.5% men), were reviewed. Mean hospital stay was 15 days, 18 patients (14%) had local complications, 7 patients (5.4%) developed organ failure and 2 patients died (1.6%). The AUC for BISAP score to detect organ failure was 0.977 (95% IC 0.947-1.000). A BISAP score > 3 had a sensitivity, specificity, positive and negative predictive value of 71.4, 99.1, 83.3 and 98.3% respectively. An APACHE II score > 8 had a sensitivity and specificity of 71.5 and 86.8% respectively. The figures for a Balthazar score > 6 were 42.8 and 98.3% respectively. There was a significant correlation between BISAP score and length of hospital stay.
Conclusions: BISAP score was a useful method for predicting the severity of PA, with the advantage of being simple and based on parameters obtained on the first day of hospitalization. Its sensitivity and specificity were superior to APACHE II and Balthazar score in this cohort.
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http://dx.doi.org/10.4067/S0034-98872012000800002 | 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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