Exhaled nitric oxide as a marker of asthma control in smoking patients
Bibliographic record
Abstract
Exhaled nitric oxide fraction (F(eNO)), which is a reliable marker of eosinophilic airway inflammation, is partially suppressed by tobacco smoking. Consequently, its potential as a biomarker in asthma management has never been evaluated in smoking patients. In the present study, the authors tested the validity of F(eNO) to predict asthma control in this population. F(eNO) and the Asthma Control Questionnaire (ACQ) were recorded at least once in 411 nonsmoking (345 with at least two visits) and 59 smoking (51 with at least two visits) asthma patients. Despite similar mean ACQ scores (1.5 versus 1.7), F(eNO) was reduced in smoking asthmatics (18.1 ppb versus 33.7 ppb). A decrease in F(eNO) of <20% precludes asthma control improvement in nonsmoking (negative predictive value (NPV) 78%) and in smoking patients (NPV 72%). An increase in F(eNO) <30% is unlikely to be associated with deterioration in asthma control in both groups of patients (NPV = 86% and 84% in nonsmoking and smoking patients, respectively). It is concluded that, even in smokers, sequential changes in F(eNO) have a relationship with asthma control. The present study is the first to indicate that cigarette smoking does not obviate the clinical value of measuring F(eNO) in asthma among smokers.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".