scholarly journals A comparative study of severity scoring systems in acute pancreatitis

2020 ◽  
Vol 4 (2) ◽  
pp. 237-241
Author(s):  
Meghana Taggarsi ◽  
Anil Kumar ◽  
HR Ravishankar
Keyword(s):  
Acute Pancreatitis ◽  
Comparative Study ◽  
Scoring Systems ◽  
Severity Scoring

scholarly journals The Best Prediction Model for Trauma Outcomes of the Current Korean Population: a Comparative Study of Three Injury Severity Scoring Systems

2016 ◽  
Vol 31 (3) ◽  
pp. 221-228 ◽  
Author(s):  
Kyoungwon Jung ◽  
John Cook-Jong Lee ◽  
Rae Woong Park ◽  
Dukyong Yoon ◽  
Sungjae Jung ◽  
...  
Keyword(s):  
Comparative Study ◽  
Prediction Model ◽  
Injury Severity ◽  
Scoring Systems ◽  
Korean Population ◽  
Trauma Outcomes ◽  
Severity Scoring

A Comparative Study between Apache II and Ran son Scoring Systems in Predicting the Severity of Acute Pancreatitis

2016 ◽  
Vol 7 (2) ◽  
pp. 165-170
Author(s):  
G. Chandrashekar Naik ◽  
◽  
Kailas C.T. ◽  
Ramesh K. ◽  
◽  
...  
Keyword(s):  
Acute Pancreatitis ◽  
Comparative Study ◽  
Scoring Systems ◽  
Apache Ii

Acute Pancreatitis

2020 ◽  
Author(s):  
Jason Ahn ◽  
Calvin K. Huang
Keyword(s):  
Computed Tomography ◽  
Acute Pancreatitis ◽  
Differential Diagnosis ◽  
Abdominal Pain ◽  
Disease Severity ◽  
Scoring Systems ◽  
Apache Ii Score ◽  
Severity Scoring ◽  
Key Words Pancreatitis ◽  
Sirs Criteria

Pancreatitis is a leading differential diagnosis in patients presenting with abdominal pain.  Although there are multiple initial inciting factors, the end result is the inappropriate activation of pancreatic enzymes leading to localized, and sometimes systemic, inflammation.  The severity of pancreatitis as a disease can range from mild pain to shock and hypotension.  This review covers the initial treatment and stabilization of patients with this disease as well as the mainstay of diagnosis including lab testing and imaging.  Disease severity scoring systems including the revised Atlanta Criteria, APACHE II score, SIRS criteria, BISAP score, and Ranson criteria, followed by treatment and disposition stratified by disease severity, are discussed.  Figures display pertinent findings of the imaging modalities including fluoroscopy, ultrasound, and computed tomography.  Tables list the major causes of pancreatitis, differential diagnosis, and non-pancreatic causes of amylase and lipase elevation. This review contains 6 figures, 5 tables, and 53 references. Key words: pancreatitis, abdominal pain, shock, gallstones, ultrasound, lipase, amylase

scholarly journals Haemoconcentration as a predictor of severity in acute pancreatitis

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

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

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.

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