Electrical impedance spectroscopy detects skin barrier dysfunction in childhood atopic dermatitis

• Published in: Allergy (Copenhagen) 2024-01, Vol.79 (1), p.142-152
• Main Authors: Sasaki, Mari, Sundberg, Mathilda, Frei, Remo, Ferstl, Ruth, Heye, Kristina N., Willems, Erik P., Akdis, Cezmi A., Lauener, Roger, Bieber, Thomas, Schmid‐Grendelmeier, Peter, Traidl‐Hoffmann, Claudia, Brüggen, Marie‐Charlotte, Rhyner, Claudio, Roduit, Caroline
• Format: Article
• Language: English
• Subjects: Algorithms; Allergens; Atopic dermatitis; Child, Preschool; Children; Dermatitis; Dermatitis, Atopic - diagnosis; Dielectric Spectroscopy; Eczema; Electrical impedance; electrical impedance spectroscopy; epithelial barrier; Humans; Hypersensitivity; paediatric; Pediatrics; Skin; skin barrier assessment; Spectroscopy; Spectrum analysis
• ISSN: 0105-4538; 1398-9995; 1398-9995
• DOI: 10.1111/all.15895

Background Skin barrier dysfunction is associated with the development of atopic dermatitis (AD), however methods to assess skin barrier function are limited. We investigated the use of electrical impedance spectroscopy (EIS) to detect skin barrier dysfunction in children with AD of the CARE (Childhood AlleRgy, nutrition, and Environment) cohort. Methods EIS measurements taken at multiple time points from 4 months to 3‐year‐old children, who developed AD (n = 66) and those who did not (n = 49) were investigated. Using only the EIS measurement and the AD status, we developed a machine learning algorithm that produces a score (EIS/AD score) which reflects the probability that a given measurement is from a child with active AD. We investigated the diagnostic ability of this score and its association with clinical characteristics and age. Results Based on the EIS/AD score, the EIS algorithm was able to clearly discriminate between healthy skin and clinically unaffected skin of children with active AD (area under the curve 0.92, 95% CI 0.85–0.99). It was also able to detect a difference between healthy skin and AD skin when the child did not have active AD. There was no clear association between the EIS/AD score and the severity of AD or sensitisation to the tested allergens. The performance of the algorithm was not affected by age. Conclusions This study shows that EIS can detect skin barrier dysfunction and differentiate skin of children with AD from healthy skin and suggests that EIS may have the ability to predict future AD development. This study investigates the use of electrical impedance spectroscopy to detect skin barrier dysfunction in children with AD of the CARE cohort. Based on the EIS/AD score, EIS algorithm is able to clearly differentiate healthy skin and clinically unaffected skin of 4 months to 3‐year‐old children with active AD. EIS/AD score is also different between healthy skin, skin of children with non‐active AD (before onset orafter onset of AD but without active symptoms) and active AD.Abbreviations: AD, atopic dermatitis; AUC, area under the curve; CARE, Childhood AlleRgy, nutrition and Environment; CI, confidence interval; EIS, electrical impedance spectroscopy; EIS/AD score, the score given by the machine learning algorithm that reflects the probability that a given EIS measurement is from a child with active AD