Combined Point-of-Care Assessment Using Oscillometry, Spirometry, and FeNO to Optimally Identify an At-Risk Asthma Phenotype
Bibliographic record
Abstract
Abstract Rationale: Asthma is characterized by airflow obstruction and type 2 inflammation. Oscillometry identifies small airways dysfunction as resistance between 5 and 20Hz (Rrs5-20). We hypothesized whether integrating point-of-care physiological and inflammatory measures might better stratify exacerbation risk and poor symptom control. Objectives: A proof-of-concept study to assess whether combining oscillometry, as Rrs5-20, spirometry as FEV1 and type 2 inflammation as FeNO, may identify an at-risk asthma phenotype. Methods: 617 participants with moderate to severe asthma were included from two severe asthma centers in Dundee, UK and Bergamo, Italy as part of the Oscillometry Asthma Registry (OAR). Oscillometry was considered abnormal if resistance between 5Hz and 20Hz as ≥0.10kPa/L/s. Spirometry was impaired as FEV1<80% predicted. FeNO was considered elevated as ≥25ppb. Symptom control was assessed either using the GINA symptom assessment tool (n=360) or ACQ (n=257). Measurements and Main Results: Individuals with the triple asthma phenotype characterized by FEV1, Rrs5-20 and FeNO had the greatest likelihood for ≥2 severe exacerbations and poor symptom control (figure 1a/b). The triple phenotype was associated with an 89% and 98% greater likelihood of ≥2 severe asthma exacerbations and poor symptom control respectively. Conclusions: The present results highlight the importance of fully characterizing asthma phenotypes using a combination of airway physiology and type 2 inflammation. If refined and validated, this composite score could be used as a rapid point-of-care clinical risk-stratification tool. Figure 1 (a) Likelihood of ≥2 severe exacerbations using composite of Rrs5-20, FEV1 and FeNO. Green denotes aOR between 1 – 3.99; orange 4 – 7.99; red ≥8. (b) Likelihood of uncontrolled symptoms using Rrs5-20, FEV1 and FeNO. Green denotes aOR between 1 – 4.99; yellow 5 – 14.99; orange 15 – 39.99; red ≥40. Cut points: FeNO≥25ppb; FEV1<80%; and Rrs5-20≥0.10kPa/L/s. [asterisk][asterisk]p<0.01 [asterisk][asterisk][asterisk]p<0.001
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".