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Electrical impedance spectroscopy detects skin barrier dysfunction in childhood atopic dermatitis
Mari Sasaki1, Mathilda Sundberg2, Remo Frei3,4,5
1University Children's Hospital Zürich, Zürich, Switzerland.
Insights
Electrical impedance spectroscopy (EIS) can detect skin barrier dysfunction in children, differentiating atopic dermatitis (AD) affected skin from healthy skin. This method shows potential for predicting future AD development in children.
Area of Science:
- Dermatology
- Biomedical Engineering
- Pediatrics
Background:
- Skin barrier dysfunction is a known factor in atopic dermatitis (AD) development.
- Current methods for assessing skin barrier function are limited.
- Electrical impedance spectroscopy (EIS) is explored as a novel assessment tool.
Purpose of the Study:
- To investigate the utility of EIS in detecting skin barrier dysfunction in children with AD.
- To develop and validate a machine learning algorithm using EIS for AD diagnosis.
- To assess the association of EIS measurements with clinical characteristics and age.
Main Methods:
- EIS measurements were collected from infants and young children (4 months to 3 years) in the CARE cohort.
- A machine learning algorithm (EIS/AD score) was developed using EIS data and AD status.
- The diagnostic performance of the EIS/AD score was evaluated and compared to clinical data.
Main Results:
- The EIS algorithm effectively distinguished between healthy skin and clinically unaffected skin of children with active AD (AUC 0.92).
- EIS detected differences even in children without active AD, indicating subclinical changes.
- No significant association was found between the EIS/AD score and AD severity or allergen sensitization; age did not affect performance.
Conclusions:
- EIS is a viable method for detecting skin barrier dysfunction in children.
- EIS can differentiate between healthy and AD-affected skin, with potential for predicting future AD development.
- The EIS/AD score demonstrates diagnostic capability irrespective of age or disease severity.
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.
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