A novel scoring system for predicting disease severity without CT imaging in acute diverticulitis

Area of Science:

• Gastroenterology
• Medical Imaging
• Clinical Decision Support

Background:

• Acute diverticulitis is a common condition requiring accurate diagnosis.
• Computed tomography (CT) is often used for evaluation but may not be necessary for all patients.
• Identifying patients at risk for complicated disease is crucial for appropriate management.

Purpose of the Study:

• To identify risk factors for complicated acute diverticulitis.
• To develop a predictive risk score for disease severity.
• To aid in selecting patients who would benefit from CT imaging.

Main Methods:

• Retrospective analysis of 513 patients with CT-verified acute diverticulitis (2015-2017).
• Univariate and multivariate analyses to identify risk factors for complicated disease.
• Development of the Acute Diverticulitis Severity Score using logistic regression.

Main Results:

• Older age, comorbidities, elevated C-reactive protein, leucocyte count, vomiting, and fever were associated with complicated acute diverticulitis.
• The Acute Diverticulitis Severity Score demonstrated high accuracy (AUC=0.856) in predicting disease severity.
• Low scores indicated minimal risk for complications, potentially avoiding redundant imaging.

Conclusions:

• The Acute Diverticulitis Severity Score effectively differentiates uncomplicated from complicated acute diverticulitis.
• This score can guide clinical decisions, optimizing patient selection for further investigation.
• Implementation may reduce healthcare costs and workload by minimizing unnecessary CT scans.