Literature DB >> 28215446

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

Adam B Raff1, Qing Yu Weng1, Jeffrey M Cohen2, Nicole Gunasekera2, Jean-Phillip Okhovat2, Priyanka Vedak1, Cara Joyce3, Daniela Kroshinsky1, Arash Mostaghimi4.   

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.
Copyright © 2017 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

Entities:  

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

Mesh:

Year:  2017        PMID: 28215446     DOI: 10.1016/j.jaad.2016.12.044

Source DB:  PubMed          Journal:  J Am Acad Dermatol        ISSN: 0190-9622            Impact factor:   11.527


  7 in total

1.  Diagnosis and management of cellulitis.

Authors:  Tadhg Sullivan; Eoghan de Barra
Journal:  Clin Med (Lond)       Date:  2018-03       Impact factor: 2.659

2.  [Soft tissue infections].

Authors:  Robert Rongisch; Mario Fabri
Journal:  Hautarzt       Date:  2022-01-27       Impact factor: 0.751

Review 3.  Cellulitis: A Review of Current Practice Guidelines and Differentiation from Pseudocellulitis.

Authors:  Michelle A Boettler; Benjamin H Kaffenberger; Catherine G Chung
Journal:  Am J Clin Dermatol       Date:  2021-12-13       Impact factor: 7.403

4.  Evaluation of Dundee and ALT-70 predictive models for cellulitis in 56 patients who underwent tissue culture.

Authors:  Trent D Walker; Ty W Gilkey; John Christopher Trinidad; Catherine G Chung; Henry Wang; Arash Mostaghimi; Benjamin H Kaffenberger
Journal:  Arch Dermatol Res       Date:  2022-10-23       Impact factor: 3.033

5.  Outcomes of Early Dermatology Consultation for Inpatients Diagnosed With Cellulitis.

Authors:  David G Li; Fan Di Xia; Hasan Khosravi; Anna K Dewan; Daniel J Pallin; Christopher W Baugh; Karl Laskowski; Cara Joyce; Arash Mostaghimi
Journal:  JAMA Dermatol       Date:  2018-05-01       Impact factor: 10.282

Review 6.  A systematic review showing the lack of diagnostic criteria and tools developed for lower-limb cellulitis.

Authors:  M Patel; S I Lee; R K Akyea; D Grindlay; N Francis; N J Levell; P Smart; J Kai; K S Thomas
Journal:  Br J Dermatol       Date:  2019-06-28       Impact factor: 9.302

7.  Mass Compression from Recurrent Lymphoma Mimicking Lower Extremity Cellulitis.

Authors:  David G Li; Katherine M Krajewski; Arash Mostaghimi
Journal:  Cureus       Date:  2018-04-12
  7 in total

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