Bullous pemphigoid and diabetes mellitus: a systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract We aimed to systematically review and meta‐analyze the association between diabetes mellitus (DM) and bullous pemphigoid (BP). Bullous pemphigoid (BP) is a prevalent autoimmune subepidermal blistering disease. Comorbid health conditions like neurological diseases and malignancies have been associated with BP. Growing evidence suggests that type 2 diabetes mellitus (T2DM) may increase the risk of developing BP. This review aims to synthesize this evidence. A systematic literature review was performed using Medline, PubMed, and Scopus in March 2022. Studies exploring the association between BP and DM were included. Data were extracted, and quality was assessed using the Newcastle–Ottawa scale. Meta‐analysis was conducted to identify the odds ratio (OR) and 95% confidence intervals (CI) of the association. Seventeen studies were included, most being case–control studies from Europe and Asia. The pooled OR was 2.06 (95% CI: 1.61–2.62), suggesting a significant association between DM and BP. However, strong heterogeneity ( I 2 = 88%) was observed. Evidence consolidates a significant relationship between DM and BP, potentially due to alterations in the immune system and skin properties caused by diabetes. Strengths of this review include a comprehensive search, rigorous methodology, large sample size, and heterogeneity evaluation. However, varying study quality, potential publication bias, and unaccounted confounding factors present limitations. There is a potential link between T2DM and an increased risk of BP. Further studies are required to understand this association and the underlying mechanisms.
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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 | 0.012 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.031 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".