P31 Association of atopic dermatitis with thyroid diseases: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Atopic dermatitis (AD) and thyroid diseases have shared immune abnormalities, but their association was largely unclear. Objective To systematically examine the association of AD with thyroid diseases. Methods A systematic review was performed and the PubMed and Embase databases were searched on 26th August 2023. The risk of bias was assessed by using the Newcastle-Ottawa Scale. A random-effects model meta-analysis was performed and a subgroup analysis based on age groups was executed. Results The database searches yielded 205 records after removing duplicates. Nine case-controll studies with 5,367,891 subjects were included. The risk of bias of included was generally low to unclear. AD was significantly associated with thyroid diseases (pooled odds ratio (OR) 1.50, 95% confidence interval (CI) 1.23−1.85; studies = 6; I2 = 85%), which was present in both adults and children (pooled OR being 1.46 (95% CI 1.20−1.78; studies = 2; I2 = 63%) and 3.46 (95% CI 1.15−10.45; studies = 3; I2 = 63%). AD was also associated with Hashimoto disease (pooled OR 2.00, 95% CI 0.91−4.40, I2 = 95%; studies = 2) and Graves disease (pooled OR 2.21, 95% CI 0.59−8.31 I2 = 93%; studies = 2). Conclusions AD is associated with an increase of thyroid diseases. AD may be associated with Hashimoto and Graves diseases, but did not reach significance due to high statistical heterogeneity and paucity of evidence. Endocrinological consultation may be considered when AD patients present with thyroid symptoms.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.030 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".