Chronic urticaria and thyroid autoimmunity: a meta-analysis of case–control studies
Bibliographic record
Abstract
Abstract Purpose Autoimmunity has been implicated in some patients with idiopathic chronic urticaria (CU). Because of the frequency of autoimmune thyroid diseases, their association with CU deserves special attention. We tested both the existence and the extent of an association between thyroid autoimmunity and CU. Methods A thorough search of PubMed, Scopus, Web of Science, and Cochrane databases was performed. Studies reporting the positivity rate for anti-thyroperoxidase antibodies (TPOAbs) in people with (cases) and without CU (controls) were included. Quality of the studies was assessed by the Newcastle–Ottawa Scale. Between-study heterogeneity was assessed by Cochrane Q and I2 tests, and the odds ratio (OR) for TPOAbs positivity was combined using random-effects models. Results Nineteen studies provided information about TPOAbs positivity on 14,351 patients with CU and 12,404 controls. The pooled estimate indicated a more than fivefold increased risk of exhibiting TPOAbs positivity in the group with CU (pooled OR 5.18, 95% CI 3.27, 8.22; P < 0.00001). Correction for publication bias had a negligible effect on the overall estimate (pooled adjusted OR: 4.42, 95% CI 2.84, 6.87, P < 0.0001). Between‑study heterogeneity was established (I2 = 62%, Pfor heterogeneity = 0.0002) and when, according to meta‑regression models, a sensitivity analysis was restricted to the 16 studies with the highest quality scores, the OR for TPOAbs positivity rose to 6.72 (95% CI 4.56, 9.89; P < 0.00001) with no significant heterogeneity (I2 = 31%, Pfor heterogeneity = 0.11). Conclusions Patients with CU have a five-to-nearly sevenfold higher risk of displaying TPOAbs positivity. All patients with CU may well be offered a screening for thyroid autoimmunity.
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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 | 0.022 | 0.047 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.047 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".