Commentary on Epidemiology of mental health comorbidity in patients with atopic dermatitis: An analysis of global trends from 1998 to 2022
Bibliographic record
Abstract
Individuals with atopic dermatitis describe living with a disease which impacts on much more than just the skin. A massive 98% of people living with skin disease1 relate the psycho-social co-morbidities of living with their cutaneous disease. In addition, it works both ways. The skin disease leads to psychological distress and psychological distress initiates or propagates skin disease in a genetically predisposed individual. In this issue, Xiao-ce Cai2 reports the epidemiology of mental health comorbidity in patients with atopic dermatitis: an analysis of global trends from 1998 to 2022 in an extensive meta-analysis by assessing the prevalence of Attention Deficit and Hyperactivity Disorder (ADHD), anxiety, depression and suicidality in patients with atopic dermatitis (AD) in seven electronic databases from their inception to date. The analysis used the Agency for Healthcare Research and Quality (AHRQ) and Newcastle–Ottawa Scale (NOS) tools to assess the quality of observational studies and checked the statistical significance of reported outcomes using contemporaneous software. The issue of the psycho-social co-morbidities of living with AD is relevant for four major reasons. Firstly, the incidence of AD is thought to be increasing globally, and the reasons for this increase remain poorly understood. Secondly, the impact of the psycho-social co-morbidities of AD on the patient and their family and loved ones is huge. Thirdly, the epidemiology of the psycho-social co-morbidities of AD has been studied in many diverse nations, regions, and continents,3 but this is the first attempt to assess the global impact of the psycho-social co-morbidities on individuals with AD. Finally, AD affects adults and children (<18 years of age) differently in terms of the prevalence of the disease, the physical disease itself, and the psychological impact of the disease. It is especially interesting that Cai et al.'s study explores the different literature reporting the psycho-social co-morbidities of living with AD for both adults and children (aged <18 years). This study, which identified 775 studies of which 43 were fully subject to meta-analysis, and which is published in the JEADV, indicates that the global prevalence rates of ADHD, depression, anxiety, and suicidal ideation in all patients with AD were 7%, 17%, 21%, and 13%, respectively, between 1998 and October 2022. Among children (aged <18 years), North American children with AD had the highest prevalence rates of ADHD (10%), depression (13%) and anxiety (20%). Among the adult (aged ≥18 years) patients with AD Africa had the highest prevalence rates of depression (36%) and anxiety (44%), while Asian adults with AD had the highest 78 prevalence rates of ADHD (7%) and suicidal ideation (20%). It is clear, then, that globally the psycho-social co-morbidities of anxiety, depression, suicidality, and (possibly) ADHD are more common in patients of all ages with AD. The reasons for the regional variations are speculative, for example, regional conflict, war, culture, and reporting artefact are all possible contributory factors. The authors of the paper are not able to draw conclusions about the global psycho-social co-morbidity variations. But the report matters clinically as dermatology healthcare professionals (HCPs), even more than ever, should recognize these psycho-social co-morbidities, and where possible commence treatment or signpost to appropriate psychodermatology services. It also supports work from organizations such as the European Society for Dermatology and Psychiatry (ESDaP) and the European Academy of Dermatology and Venereology (EADV) psychodermatology task force, both of which have advocated the need for psychodermatology services to be available at least regionally across the globe.4 Currently, this is certainly not the case. Finally, the authors allude to the growing body of evidence, which was discussed in many of the papers subject to their meta-analysis, for neuro-inflammatory processes in the elicitation of the psycho-social co-morbidities of living with AD. This matters because it shifts the focus of the psycho-social co-morbidities from the patient to the disease itself. Prof Bewley has ad hoc consultancy/travel/lecturing agreements with AbbVie, Almirall, BMS, Galderma, Eli Lilly, Janssen, Leo-Pharma, Novartis, Pfizer, Sanofi, UCB. Data sharing is not applicable to this article as no new data were created or analyzed in this study.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.092 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.008 | 0.002 |
| Research integrity | 0.021 | 0.019 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".