The purpose of the study is to identify novel blood-based biomarkers for prediction and diagnosis of infected pancreatic necrosis (IPN) in patients with necrotizing pancreatitis (NP). Acute pancreatitis (AP) is the leading cause of gastrointestinal hospital admissions, accounting for over 300,000 emergency department visits annually and imposing a significant socio-economic burden. It is an acute inflammatory condition of the pancreas characterized by damage to the acinar cells, which triggers an inflammatory response and causes widespread systemic damage. In about 20% of cases, the disease progresses to necrotizing pancreatitis (NP), a severe form characterized by tissue necrosis. NP poses serious health risks, especially when the necrotic tissue becomes infected, leading to infected (peri-)pancreatic necrosis (IPN), which is associated with secondary organ failure (OF), sepsis, and mortality rates as high as 40%. While patients with sterile (peri-)pancreatic necrosis (SPN) can often be managed conservatively, those with IPN typically require antibiotics and therapeutic interventions such as endoscopic drainage or surgery. Timely recognition and treatment of IPN are crucial for improving patient outcomes, yet current diagnostic methods based on clinical symptoms and routine lab markers lack the specificity to reliably distinguish SPN from IPN in the early stages. Furthermore, while multifactorial scoring systems like Ranson, Imrie, and APACHE II predict necrosis and overall severity in AP, they are not accurate for identifying IPN or predicting mortality in NP. The diagnostic gap delays appropriate treatment, allowing the infection to advance and limiting available therapeutic options. The growing incidence and significant impact of AP and NP in the general population underscore the urgent need to better understand IPN pathophysiology and to develop specific diagnostic biomarkers that can improve prognosis, guide therapeutic decisions, and enhance patient outcomes.
Age range
18 Years
Sex
ALL
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Understand immune-metabolic dynamics in NP
Timeframe: 3 months
Identify novel biomarkers
Timeframe: 3 months