Biomarkers and clinical characteristics of autoimmune chronic spontaneous urticaria: Results of the PURIST Study
Bibliographic record
Abstract
BACKGROUND: Autoimmune chronic spontaneous urticaria (aiCSU) is an important subtype of chronic spontaneous urticaria (CSU) in which functional IgG autoantibodies to IgE or its high-affinity receptor (FcεRI) induces mast cell degranulation and subsequent symptom development. However, it has not been tightly characterized. This study aimed to better define the clinical and immunological features and to explore potential biomarkers of aiCSU. METHODS: This was a multinational, multicenter study of 182 CSU patients. The clinical features studied included: urticaria activity and impact (UAS7 and quality of life); autologous serum skin test (ASST); IgG anti-FcεRI and IgG anti-IgE; IgG-anti-thyroperoxidase (IgG anti-TPO); total serum IgE; and basophil reactivity (BASO) using the basophil activation test (BAT) and basophil histamine release assay (BHRA). RESULTS: Of the 182 patients, 107 (59%) were ASST+, 46 (25%) were BASO+, and 105 (58%) were IgG anti-FcεRI+/IgE+. Fifteen patients (8%) fulfilled all three criteria of aiCSU. aiCSU patients appeared more severe (UAS7 21 vs 9 P < 0.016) but showed no other clinical or demographic differences from non-aiCSU patients. aiCSU patients also had markedly lower total IgE levels (P < 0.0001) and higher IgG anti-TPO levels (P < 0.001). Of biomarkers, positive BAT and BHRA tests were 69% and 88% predictive of aiCSU, respectively. CONCLUSIONS: aiCSU is a relatively small but immunologically distinct subtype of CSU that cannot be identified by routine clinical parameters. Inclusion of BHRA or BAT in the diagnostic workup of CSU patients may aid identification of aiCSU patients, who may have a different prognosis and benefit from specific management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".