Oscillometry in the diagnosis, assessment, and monitoring of asthma in children and adults
Bibliographic record
Abstract
Diagnosing asthma typically relies on clinical history, physical examination, and objective lung function test results. Spirometry, the gold standard for assessing lung function, is universally recommended for the diagnostic, assessment, and monitoring of asthma. It requires maximal respiratory effort that limits cooperation in certain populations and has limitations in detecting small airway dysfunction. Oscillometry requires minimal patient effort, is noninvasive, and provides valuable information on both large and small airways. Recent task force reports have suggested oscillometry as an alternative or a complementary lung function test to spirometry in the management of individuals with asthma. This review explores the scientific evidence and psychometric properties regarding oscillometry in the main purposes served by lung function testing in asthma, namely diagnosis, assessment of control and future risk, as well as longitudinal monitoring, including clinical utility. Furthermore, it addressed challenges and facilitators to implementation and future directions regarding its positioning as lung function testing in individuals with asthma.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".