Airway autoimmunity and response to a 14-day course of oral corticosteroids in patients with severe eosinophilic asthma
Bibliographic record
Abstract
Background: Recent studies have suggested airway autoimmunity underlying persistent eosinophilia in prednisone-dependent severe asthma. In vitro studies report autoantibody (aAb)-mediated eosinophilia unresponsive to corticosteroids. Aim: To determine the treatment (Rx) response of oral corticosteroids (OCS, prednisolone) on eosinophil suppression in autoimmune-prone asthmatic airways, without the confounder of patients already on OCS. Methods: We evaluated 23 eosinophilic (≥3% sputum eosinophils) patients with severe asthma (per ERS/ATS guidelines) not maintained on OCS, post 14 days of 37.5mg prednisolone. Anti-eosinophil peroxidase (EPX) IgG was measured in the sputa (ELISA) as a marker of airway autoimmunity and compared with clinical measures of eosinophilia pre- and post Rx. Results: Five (21.7%) patients tested positive for anti-EPX IgG. This subgroup had significantly higher blood eosinophil counts (median 0.70 x 109/L (range 0.38–2.40) vs. 0.27 (0.08–0.75), p=0.0019), sputum free eosinophil granules (FEGs) (median 3.00 (range 2.00–3.00) vs. 0.00 (0.00-2.00), p<0.001) and a trend towards higher sputum eosinophils (p=0.12) at baseline compared with patients with low/no anti-EPX IgG. Post Rx, reduction in blood and sputum eosinophils was comparable (p<0.001 for both groups and p=0.62 and p=0.32 across groups) while anti-EPX titers were suppressed in 4/5 patients. Conclusions: We detected sputum aAbs in a subgroup of severe asthma patients (not on daily OCS) with blood eosinophilia and airway eosinophil activity (FEGs). Our data suggests that airway autoimmune responses in severe asthma may be curbed by a course of prednisolone with concurrent suppression of eosinophilia.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".