Phenotyping the Responses to Systemic Corticosteroids in the Management of Asthma Attacks (PRISMA): protocol for an observational and translational pilot study
Bibliographic record
Abstract
Introduction Asthma and its associated exacerbation are heterogeneous. Although severe asthma attacks are systematically prescribed corticosteroids and often antibiotics, little is known about the variability of response to these therapies. Blood eosinophils and fractional exhaled nitric oxide (FeNO) are type 2 inflammation biomarkers that have established mechanistic, prognostic and theragnostic values in chronic asthma, but their utility in acute asthma is unclear. We speculate that the clinical and biological response to those treatments varies according to inflammometry and microbiological test results. Methods and analysis An observational longitudinal pilot study with multimodal clinical and translational assessments will be performed on 50 physician-diagnosed ≥12-year-old asthmatics presenting with an asthma attack and 12 healthy controls, including blood eosinophil count (venous and point-of-care (POC) capillary blood), FeNO and testing for airway infection (sputum cultures and POC nasopharyngeal swabs). People with asthma will be assessed on day 0 and after a 7-day corticosteroid course, with home monitoring performed in between. The primary analysis will be the change in the forced expiratory volume in 1 s according to type 2 inflammatory status (blood eosinophils ≥0.15×109/L and/or FeNO ≥25 ppb) after treatment. Key secondary analyses will compare changes in symptom scores and the proportion of patients achieving a minimal clinically important difference. Exploratory analyses will assess the relationship between clinical, lung function, inflammatory and microbiome parameters; satisfaction plus reliability indices of POC tests; and sex–gender variability in treatment response. Ultimately, this pilot study will serve to plan a larger trial comparing the clinical and biological response to systemic corticosteroids according to inflammatory biomarkers, offering valuable guidance for more personalised therapeutic strategies in asthma attacks. Ethics and dissemination The protocol has been approved by the Research Ethics Committee of the CIUSSS de l'Estrie–CHUS, Sherbrooke, Quebec, Canada (#2023-4687). Results will be communicated in an international meeting and submitted to a peer-reviewed journal. Trial registration number ClinicalTrials.gov Registry ( NCT05870215 ).
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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 | 0.055 | 0.038 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.046 | 0.013 |
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".