Impact of Long-term Stability on Mental Health in Adults with Atopic Dermatitis: A Cohort Study with Unsupervised Cluster Analysis
Atopic dermatitis (AD) is a heterogeneous disease characterized by unpredictable flares, potentially leading to impaired mental health. Adult patients with a dermatologist-verified AD diagnosis received after their 18th birthday were grouped according to patient-reported flare activity between 2018...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Medical Journals Sweden
2025-07-01
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| Series: | Acta Dermato-Venereologica |
| Subjects: | |
| Online Access: | https://medicaljournalssweden.se/actadv/article/view/43071 |
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| Summary: | Atopic dermatitis (AD) is a heterogeneous disease characterized by unpredictable flares, potentially leading to impaired mental health. Adult patients with a dermatologist-verified AD diagnosis received after their 18th birthday were grouped according to patient-reported flare activity between 2018 and 2023. The k-means clustering algorithm was used in combination with dynamic time warping and barycenter averaging. Clusters were analysed according to current levels of anxiety and depression and severity across the 4 time points. The clustering method divided the 262 patients into 4 groups. Cluster 1 was characterized by a disease course with an average of < 6 annual flares, a median (interquartile range) anxiety and depression score of 3.0 (1.0–6.3), and 1.0 (0.0–4.0), respectively. Clusters 2 and 3 were characterized by annual flares ranging from 4 to 16 and anxiety scores of 6.0 (3.0–8.5) and 4.0 (2.0–7.0) and depression scores of 3.0 (1.0–6.0) and 2.0 (1.0–5.0), respectively. Cluster 4 was characterized by an unstable disease course with an average of ≥ 14 yearly flares, and anxiety and depression scores similar to cluster 2. Patients characterized by an unstable moderate disease course were more burdened compared with patients with a stable disease course (p = 0.03). This emphasizes the importance of long-term flare patterns in clinical decision-making.
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| ISSN: | 0001-5555 1651-2057 |