Exploring the clinical utility of measuring reversibility in mid expiratory flow and its relationship with FEV1 reversibility in patients with asthma
Bibliographic record
Abstract
Background: Despite the measurement of mid expiratory flow (MEF) being routinely recorded as part of standard testing of spirometry, the clinical interpretation and relevance of detecting small and medium airways dysfunction and the degree of improvement following administration of a bronchodilator that defines a significant bronchodilator response is unknown [1,2]. Objectives: Determine the clinical utility of MEF reversibility (MEFrev) by measuring the frequency of reversibility at ≥12%, ≥15%, ≥20% and ≥30% in patients with asthma and comparing this with a significant bronchodilator response in FEV1 (FEVrev) measured according to published guidelines [1]. Methods: We undertook a retrospective audit of 500 consecutive spirometry results, performed as part of routine care at Western Health. Results: Baseline results (Mean (SD)): Age 58.5 (15) years; 47% male; non/ex-smokers 74%; FEV1 2.1 (0.95) L. In patients with asthma (n=82), the MEFrev12% was noted in 35% individuals compared with 7.3% in FEVrev. MEFrev12% had 73% specificity for the diagnosis of asthma compared with FEVrev at 92%. When MEFrev was defined as 15%, 20% and 30% reversibility, the specificity increased to 74%, 84% and 92% respectively. Conclusion: This pilot study demonstrates that MEFrev may have a role in providing support for a clinical diagnosis of asthma. The clinical utility will require further characterisation. References 1. Miller, M.R. et al. Eur Respir J 2005; 26(2):319-38. 2. Timmins, S.C. et al. Chest 2012; 142(2):312-9.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".