Classifying patients suspected of appendicitis with regard to likelihood

Background: We sought to develop a clinical predictive model for acute appendicitis and contrast it with current clinical practice. Methods: A prospective observational study of patients presenting with signs or symptoms consistent with acute appendicitis. Random-partition modeling was used to develop an appendicitis likelihood model (ALM). Results: Four hundred thirty-nine patients were enrolled, 101 with appendicitis, and 338 with other diagnoses. The ALM classified patients as "low likelihood" if they had a white blood cell count < 9,500 and either no right lower-quadrant tenderness or a neutrophil count < 54%. Patients were classified as "high likelihood" if they had a white blood cell count > 13,000 with rebound tenderness or both voluntary guarding and neutrophil count > 82%. The ALM outperformed actual clinical practice with regard to "missed" appendicitis, negative laparotomies, and total number of imaging Studies. Conclusion: The ALM may permit more judicious use of advanced radiographic imaging with lower nontherapuetic laparotomy rates. (c) 2006 Excerpta Medica Inc. All rights reserved.