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Utility of Magnetic Resonance Imaging for Differentiating Necrotizing Fasciitis from Severe Cellulitis: A Magnetic Resonance Indicator for Necrotizing Fasciitis (MRINEC) Algorithm.
Kim, Min-Chul; Kim, Sujin; Cho, Eun Been; Lee, Guen Young; Choi, Seong-Ho; Kim, Seon Ok; Chung, Jin-Won.
Afiliação
  • Kim MC; Division of Infectious Diseases, Department of Internal Medicine, Chung-Ang University Hospital, Seoul 06973, Korea.
  • Kim S; Department of Radiology, Chung-Ang University Hospital, Seoul 06973, Korea.
  • Cho EB; Division of Infectious Diseases, Department of Internal Medicine, Chung-Ang University Hospital, Seoul 06973, Korea.
  • Lee GY; Department of Radiology, Chung-Ang University Hospital, Seoul 06973, Korea.
  • Choi SH; Division of Infectious Diseases, Department of Internal Medicine, Chung-Ang University Hospital, Seoul 06973, Korea.
  • Kim SO; Departments of Clinical Epidemiology and Biostatistics, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, Korea.
  • Chung JW; Division of Infectious Diseases, Department of Internal Medicine, Chung-Ang University Hospital, Seoul 06973, Korea.
J Clin Med ; 9(9)2020 Sep 21.
Article em En | MEDLINE | ID: mdl-32967282
ABSTRACT
We developed a new magnetic resonance indicator for necrotizing fasciitis (MRINEC) algorithm for differentiating necrotizing fasciitis (NF) from severe cellulitis (SC). All adults with suspected NF between 2010 and 2018 in a tertiary hospital in South Korea were enrolled. Sixty-one patients were diagnosed with NF and 28 with SC. Among them, 34 with NF and 15 with SC underwent magnetic resonance imaging (MRI). The MRINEC algorithm, a two-step decision tree including T2 hyperintensity of intermuscular deep fascia and diffuse T2 hyperintensity of deep peripheral fascia, diagnosed NF with 94% sensitivity (95% confidence interval (CI), 80-99%) and 60% specificity (95% CI, 32-84%). The algorithm accurately diagnosed all 15 NF patients with a high (≥8) laboratory risk indicator for necrotizing fasciitis (LRINEC) score. Among the five patients with an intermediate (6-7) LRINEC score, sensitivity and specificity were 100% (95% CI, 78-100%) and 0% (95% CI, 0-84%), respectively. Finally, among the 29 patients with a low (≤5) LRINEC score, the algorithm had a sensitivity and specificity of 88% (95% CI, 62-98%) and 69% (95% CI, 39-91%), respectively. The MRINEC algorithm may be a useful adjuvant method for diagnosing NF, especially when NF is suspected in patients with a low LRINEC score.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article