A predictive model for diagnosis of lower extremity cellulitis: A cross-sectional study

Abstract

Background: Cellulitis has many clinical mimickers (pseudocellulitis), which leads to frequent misdiagnosis.

Objective: To create a model for predicting the likelihood of lower extremity cellulitis.

Methods: A cross-sectional review was performed of all patients admitted with a diagnosis of lower extremity cellulitis through the emergency department at a large hospital between 2010 and 2012. Patients discharged with diagnosis of cellulitis were categorized as having cellulitis, while those given an alternative diagnosis were considered to have pseudocellulitis. Bivariate associations between predictor variables and final diagnosis were assessed to develop a 4-variable model.

Results: In total, 79 (30.5%) of 259 patients were misdiagnosed with lower extremity cellulitis. Of the variables associated with true cellulitis, the 4 in the final model were asymmetry (unilateral involvement), leukocytosis (white blood cell count ≥10,000/uL), tachycardia (heart rate ≥90 bpm), and age ≥70 years. We converted these variables into a points system to create the ALT-70 cellulitis score as follows: Asymmetry (3 points), Leukocytosis (1 point), Tachycardia (1 point), and age ≥70 (2 points). With this score, 0-2 points indicate ≥83.3% likelihood of pseudocellulitis, and ≥5 points indicate ≥82.2% likelihood of true cellulitis.

Limitations: Prospective validation of this model is needed before widespread clinical use.

Conclusion: Asymmetry, leukocytosis, tachycardia, and age ≥70 are predictive of lower extremity cellulitis. This model might facilitate more accurate diagnosis and improve patient care.

Keywords: cellulitis; diagnosis; diagnostic model; lower extremity cellulitis; misdiagnosis; predictive model; pseudocellulitis.