The Clinical Significance of Exhaled Nitric Oxide in Asthma
Bibliographic record
Abstract
Asthma is an inflammatory disease of the airways, for which many therapeutic options are available. Guidelines for the management of asthma suggest a stepwise approach to pharmacotherapy based on assessment of asthma severity and control. However, the assessment of asthma control presently relies on surrogate measures, such as the frequency of symptoms or the frequency of use of short-acting beta2-adrenergic agonists. There is no simple, noninvasive technique for the assessment of severity of actual airway inflammation in asthma. The collection and analysis of nitric oxide (NO) levels in exhaled breath has recently become feasible in humans. Based on increased exhaled NO (eNO) levels in patients with asthma, eNO analysis has been proposed as a novel, noninvasive approach to the assessment and monitoring of airway inflammation, and as a basis for adjustments in asthma therapy. In the present paper, the relationship of elevated eNO levels in asthma with inflammatory, physiological and clinical markers of asthma in adults was reviewed. Use of eNO is a promising tool for diagnosing asthma, for monitoring asthma control and for guiding optimal anti-inflammatory asthma therapy. However, because of many unresolved questions, eNO cannot be recommended at present for routine clinical management of adults 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".