Associations among bullous pemphigoid and various neurological diseases: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Bullous pemphigoid is a common autoimmune bullous skin disease of the elderly. The objective of this meta‐analysis was to assess the association of bullous pemphigoid with neurological disease. We conducted a systematic search of three databases, screening for articles with relevant search terms from database inception until August 01, 2020. The Newcastle‐Ottawa quality assessment scale was used to evaluate the quality of the retained articles. Random effects models were applied to calculate the pooled odds ratio and confidence intervals. Publication bias was evaluated by funnel plot and Egger's test. A total of 25 studies with 44,726 BP patients were included in this meta‐analysis. Patients with BP were significantly more likely to have any neurological disease [odds ratio (OR): 4.5, 95% confidence interval (CI): 3.2–6.5]. This was true for: stroke (OR: 2.7, 95% CI: 2.2–3.4), Parkinson's disease (OR: 2.7, 95% CI: 2.2–3.2), dementia (OR: 4.1, 95% CI: 3.0–5.7), Alzheimer's disease (OR: 2.3, 95% CI: 1.2–4.4), epilepsy (OR: 2.4, 95% CI: 1.6–3.5), and multiple sclerosis (OR: 3.3, 95% CI: 2.1–5.2), compared to controls. Bullous pemphigoid patients have an increased prevalence of neurological disease. Clinicians should be aware of this increased prevalence, its possible implications, and preventive measures for patients.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.032 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".