Early prediction of outcomes in acute pancreatitis evaluation of current scoring systems

Abstract Background Acute pancreatitis (AP) is an inflammatory disorder that causes a considerable economic health burden. While the overall mortality is low, around 20% of patients have a complicated course of disease resulting in increased morbidity and mortality. There is an emerging body of evidence that the microbiome exerts a crucial impact on the pathophysiology and course of AP. For several decades multiple clinical and laboratory parameters have been evaluated, and complex scoring systems were developed to predict the clinical course of AP upon admission. However, the majority of scoring systems are determined after several days and achieve a sensitivity around 70% for early prediction of severe AP. Thus, continued efforts are required to investigate reliable biomarkers for the early prediction of severity in order to guide early clinical management of AP patients. Methods We designed a multi-center, prospective clinical-translational study to test whether the orointestinal microbiome may serve as novel early predictor of the course, severity and outcome of patients with AP. We will recruit 400 AP patients and obtain buccal and rectal swabs within 72 h of admission to the hospital. Following DNA extraction, microbiome analysis will be performed using 3rd generation sequencing Oxford Nanopore Technologies (ONT) for 16S rRNA and metagenomic sequencing. Alpha- and beta-diversity will be determined and correlated to the revised Atlanta classification and additional clinical outcome parameters such as the length of hospital stay, number and type of complications, number of interventions and 30-day mortality. Discussion If AP patients show a distinct orointestinal microbiome dependent on the severity and course of the disease, microbiome sequencing could rapidly be implemented in the early clinical management of AP patients in the future. Trial registration: ClinicalTrials.gov Identifier: NCT04777812

Download Full-text

Faculty Opinions recommendation of The early prediction of mortality in acute pancreatitis: a large population-based study.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1115429.623303 ◽

2009 ◽

Author(s):

Enrique Dominguez-Munoz ◽

Julio Iglesias-Garcia

Keyword(s):

Acute Pancreatitis ◽

Large Population ◽

Population Based ◽

Early Prediction ◽

Population Based Study ◽

Prediction Of Mortality

Download Full-text

Haemoconcentration as a predictor of severity in acute pancreatitis

Journal of Kathmandu Medical College ◽

10.3126/jkmc.v4i1.15020 ◽

2016 ◽

Vol 4 (1) ◽

pp. 3-7

Author(s):

Tanka Prasad Bohara ◽

Dimindra Karki ◽

Anuj Parajuli ◽

Shail Rupakheti ◽

Mukund Raj Joshi

Keyword(s):

Acute Pancreatitis ◽

Pearson Correlation ◽

Characteristic Curve ◽

Scoring Systems ◽

Cost Effective ◽

Receiver Operator Characteristic Curve ◽

First Episode ◽

P Value ◽

Receiver Operator Characteristic ◽

Chi Square

Background: Acute pancreatitis is usually a mild and self-limiting disease. About 25 % of patients have severe episode with mortality up to 30%. Early identification of these patients has potential advantages of aggressive treatment at intensive care unit or transfer to higher centre. Several scoring systems are available to predict severity of acute pancreatitis but are cumbersome, take 24 to 48 hours and are dependent on tests that are not universally available. Haematocrit has been used as a predictor of severity of acute pancreatitis but some have doubted its role.Objectives: To study the significance of haematocrit in prediction of severity of acute pancreatitis.Methods: Patients admitted with first episode of acute pancreatitis from February 2014 to July 2014 were included. Haematocrit at admission and 24 hours of admission were compared with severity of acute pancreatitis. Mean, analysis of variance, chi square, pearson correlation and receiver operator characteristic curve were used for statistical analysis.Results: Thirty one patients were included in the study with 16 (51.61%) male and 15 (48.4%) female. Haematocrit at 24 hours of admission was higher in severe acute pancreatitis (P value 0.003). Both haematocrit at admission and at 24 hours had positive correlation with severity of acute pancreatitis (r: 0.387; P value 0.031 and r: 0.584; P value 0.001) respectively.Area under receiver operator characteristic curve for haematocrit at admission and 24 hours were 0.713 (P value 0.175, 95% CI 0.536 - 0.889) and 0.917 (P value 0.008, 95% CI 0.813 – 1.00) respectively.Conclusion: Haematocrit is a simple, cost effective and widely available test and can predict severity of acute pancreatitis.Journal of Kathmandu Medical College, Vol. 4(1) 2015, 3-7

Download Full-text

Accuracy of conventional and novel scoring systems in predicting severity and outcomes of acute pancreatitis: a retrospective study

Lipids in Health and Disease ◽

10.1186/s12944-021-01470-4 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Qing Wu ◽

Jie Wang ◽

Mengbin Qin ◽

Huiying Yang ◽

Zhihai Liang ◽

...

Keyword(s):

Acute Pancreatitis ◽

Organ Failure ◽

Scoring System ◽

Characteristic Curve ◽

Failure Prediction ◽

Scoring Systems ◽

Mortality Prediction ◽

Severity Prediction ◽

Index Of Severity ◽

Glasgow Score

Abstract Background Recently, several novel scoring systems have been developed to evaluate the severity and outcomes of acute pancreatitis. This study aimed to compare the effectiveness of novel and conventional scoring systems in predicting the severity and outcomes of acute pancreatitis. Methods Patients treated between January 2003 and August 2020 were reviewed. The Ranson score (RS), Glasgow score (GS), bedside index of severity in acute pancreatitis (BISAP), pancreatic activity scoring system (PASS), and Chinese simple scoring system (CSSS) were determined within 48 h after admission. Multivariate logistic regression was used for severity, mortality, and organ failure prediction. Optimum cutoffs were identified using receiver operating characteristic curve analysis. Results A total of 1848 patients were included. The areas under the curve (AUCs) of RS, GS, BISAP, PASS, and CSSS for severity prediction were 0.861, 0.865, 0.829, 0.778, and 0.816, respectively. The corresponding AUCs for mortality prediction were 0.693, 0.736, 0.789, 0.858, and 0.759. The corresponding AUCs for acute respiratory distress syndrome prediction were 0.745, 0.784, 0.834, 0.936, and 0.820. Finally, the corresponding AUCs for acute renal failure prediction were 0.707, 0.734, 0.781, 0.868, and 0.816. Conclusions RS and GS predicted severity better than they predicted mortality and organ failure, while PASS predicted mortality and organ failure better. BISAP and CSSS performed equally well in severity and outcome predictions.

Download Full-text