Integrating blood eosinophils and exhaled nitric oxide (FeNO) in asthma diagnostic pathways for adults and children: the PROPULSION SANTÉ observational study with translational sub-studies (DIVE, DIVE2)—protocols
Bibliographic record
Abstract
INTRODUCTION: Diagnosing asthma requires confirmation by bronchodilator reversibility (BDR) with or without bronchial provocation testing (BPT). Despite being needed in 80% of suspected cases following BDR, BPT access remains limited in Canada. Type-2 (T2) inflammatory biomarkers (fractional exhaled nitric oxide (FeNO) and blood eosinophil count (BEC)) may be underutilised for BPT prioritisation and are insufficiently studied to support asthma diagnosis in real-world primary care, especially in children. We aimed to explore whether T2 biomarker-based prioritisation of BPT reduces diagnostic delays, and improves triage efficiency and guidance based on exacerbation risk. METHODS AND ANALYSIS: Three academic centres in Québec will measure inflammatory biomarkers alongside BDR and/or BPT interpretation for patients with suspected asthma referred by primary care providers (PROPULSION SANTÉ, NCT06981169). Consenting patients aged ≥6 years will undergo FeNO, BEC and BDR testing. If BDR is non-diagnostic, subsequent BPT will be prioritised for patients with ≥1 elevated biomarker (BEC ≥300 /µL, (FeNO ≥25 ppb if ≥12 years or FeNO ≥20 ppb if <12 years)); others will follow usual timelines. Reports to the referring healthcare providers will include standard interpretation of BDR/BPT and biomarker results to state exacerbation risk and suggested corticosteroid dosage. Asthma control and quality of life will be assessed at baseline and remotely at 4, 8 and 12 months. The primary outcome will be the delay from the reception of test request for the diagnosis of asthma patients with versus without elevated biomarker(s). Secondary outcomes include biomarkers' diagnostic performance, asthma control, quality of life, health benefits, cost-effectiveness, environmental impact and patient satisfaction. We aim to recruit 1500 patients to PROPULSION SANTÉ, with optional biobanking for translational sub-studies for 123 adults (DIVE, NCT05992519) and 123 children (DIVE2, NCT07011394). ETHICS AND DISSEMINATION: Study protocols were ethically approved CIUSSS de l'Estrie-CHUS #MP-31-2025-5593/MP-31-2024-5346; 2023-4791). Results will be communicated and submitted to peer-reviewed journals. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov (NCT06981169; NCT05992519; NCT07011394).
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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 | 0.031 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".