Phenotyping the responses to systemic corticosteroids in the management of asthma attacks (PRISMA)
Bibliographic record
Abstract
Background Asthma attacks are heterogeneous. It is not known whether the response to oral corticosteroids (OCS) in acute asthma varies according to type 2 (T2) inflammatory biomarkers, blood eosinophil count (BEC) and fractional exhaled nitric oxide ( F ENO ). We aimed to explore the relationship between T2 biomarkers and response to OCS in acute asthma. Methods We conducted a longitudinal observational study of people experiencing an asthma attack evaluated before and after a 7-day OCS course. The primary outcome was post-bronchodilator change in forced expiratory volume in 1 s (FEV 1 ) according to ordinal BEC- F ENO three-group categories (T2-Low/Low: BEC <0.15×10 9 cells·L −1 and F ENO <25 ppb; T2-High/High: BEC ≥0.30×10 9 cells·L −1 and F ENO ≥35 ppb; T2-Mid: not meeting Low/Low or High/High criteria). A key secondary outcome was the change in Asthma Control Questionnaire-5 score. Exploratory outcomes included OCS-attributable adverse events. Results 53 people were enrolled, with 16 (30%) T2-Low/Low, 27 (51%) T2-Mid and 10 (19%) T2-High/High asthma attacks. Post-bronchodilator FEV 1 changes increased with combined BEC- F ENO elevation (p for interaction=0.007), peaking in the T2-High/High phenotype (0.390±0.512 L, p for trend<0.0001). Conversely, T2-Low/Low attacks showed nonsignificant FEV 1 changes (0.017±0.153 L). In univariable and multivariable analyses, only ordinal BEC- F ENO stratification, not symptoms nor FEV 1 , predicted subsequent post-bronchodilator FEV 1 improvement. All patients had improved Asthma Control Questionnaire-5 score, numerically peaking in the T2-High/High phenotype (−1.58±0.60, p for trend=0.08). All groups experienced similar OCS-attributable adverse events, with 33 patients (62%) reporting at least one event. Conclusions We found that objective improvement following OCS is confined to T2-High events. As in chronic asthma, greater T2 burden identifies a distinct clinical and therapeutic trajectory, whereas OCS‑related adverse events are uniformly distributed.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".