Infection Clinical Trial
Official title:
Risk Factors and Outcomes of Infected Pancreatic Necrosis: Retrospective Cohort of 148 Patients Admitted to the ICU for Acute Pancreatitis
Severe acute pancreatitis is a common reason for intensive care unit (ICU) admission and is associated with prolonged hospital stays and high morbidity and mortality rates. The Atlanta classification differentiates mild, moderate, and severe acute pancreatitis, and each of these categories correlates with morbidity and mortality. Mortality remains high, between 10% and 39%, in severe and moderately severe acute pancreatitis. After the first week, about 30% of patients with necrotizing pancreatitis develop infected pancreatic necrosis (IPN). IPN is a risk factor for mortality.The treatment of IPN combines antibiotics with interventions to remove the infected intra-abdominal material, preferably using minimally invasive techniques such as percutaneous and endoscopic drainage, which have been proven beneficial. In several studies biological markers such as procalcitonin and interleukin 8 were effective in predicting IPN. However, few clinical risk factors for IPN have been reported. Identifying risk factors may help to improve standardized strategies for early diagnosis and treatment, and then patients outcome. Our primary objective was to identify risk factors for IPN in patients admitted to the ICU for acute pancreatitis. Our secondary objective was to describe the management and outcomes of IPN
Using electronic patient data monitoring systems, the investigators reviewed all patients with a diagnosis of acute necrotizing pancreatitis admitted to digestive liver disease unity or ICUs at the Nantes University Hospital, from January 1, 2012, to december 31, 2015. For enrolled patients, general clinical characteristics were collected. Patients were categorized into two groups according to the development of an infected pancreatic necrosis (highly suspected or proven), and the differences of these characteristics between two groups were evaluated. Potential risk factors were collected and studied by using multiple logistic regression analysis. ;
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