Atopic dermatitis associated with autoimmune, cardiovascular and mental health comorbidities: a systematic review and meta-analysis
Bibliographic record
Abstract
Previous studies have reported conflicting estimates of associations between atopic dermatitis (AD) and autoimmune, cardiovascular and mental health comorbidities.Our objective was to determine and report these global associations based on a systematic literature review.A systematic search of studies published in PubMed/MEDLINE and Cochrane Library (January 1990 - April 2020) including patients with physician-diagnosed AD and concurrent populations, were identified. The metanalysis (random-effect model) included 37 studies. Studies originated from Europe, UK, Asia, The USA and Canada, including 237,226,993 patients and subjects with 20 autoimmune, eight cardiovascular and eight mental illnesses.Pooled analyses revealed significantly higher overall odds of autoimmune diseases (OR: 1.74; 95% CI: 1.55-1.94, p < 0.001; I2: 98.39%) and mental illnesses (OR: 1.62; 95% CI: 1.53-1.72; p < 0.001; I2: 98.86%) and a smaller increased risk for cardiovascular diseases (OR: 1.08; 95% CI: 0.01-1.16, p < 0.001; I2: 99.45%).Our systematic review highlights that AD patients are at significantly increased risk for many autoimmune diseases and mental illnesses and at a relatively lower risk for cardiovascular diseases. Updated global estimates should encourage physician/patient empowerment to seek further medical and wellness interventions for optimal patient care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.029 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".