Pemphigus and thyroid disease: A systematic review and meta-analysis
Bibliographic record
Abstract
Objective No consensus exists regarding the association between pemphigus and thyroid disease. To explore the relationship between the two conditions by synthesizing the existing data. Methods We performed this review based on PubMed, Embase and Web of Science (from inception to 2022) and used the Newcastle-Ottawa scale for assessing the quality of studies. The outcome was represented by pooled odds ratios (ORs) with 95% confidence intervals (CI). And the publication bias and sensitivity analyses were developed. Results Our analyze finally included six studies containing 17,567 pemphigus patients. Overall, we revealed that pemphigus is significantly associated with hypothyroidism (OR 1.70, 95% CI 1.54–1.87), while not with thyroid cancer (OR 0.93, 95% CI 0.41–2.11) and autoimmune thyroid disease (AITD) (OR 1.64, 95% CI 0.91–2.95). In subgroup analyses, pemphigus was also not associated with Graves’ disease (OR 0.97, 95% CI 0.63–1.49) and Hashimoto’s thyroiditis (OR 1.32, 95% CI 0.88–1.97). Conclusion Our results reveal a significant association between pemphigus and hypothyroidism. Considering other relevant studies, we also speculate that the prevalence of AITD is higher in pemphigus patients than in the general population.
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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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.030 |
| Bibliometrics | 0.010 | 0.010 |
| 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) | 0.004 | 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".