Enhanced airway dilation by positive-pressure inflation of the lungs compared with active deep inspiration in patients with asthma
Bibliographic record
Abstract
Deep inspiration temporarily reduces induced airways obstruction in healthy subjects. This bronchodilatory effect of deep inspiration is impaired in asthma. Passive machine-assisted lung inflation may augment bronchodilation compared with an active deep inspiration in patients with asthma by either opening closed airways or by reducing fluid flux across the airway wall during deep inspiration, and thereby increasing the tethering forces on the airway wall. We recruited 24 patients with asthma [18-46 yr old, forced expiratory volume in 1 s (FEV(1)) > 70% predicted; provocative concentration of methacholine inducing a 20% fall in FEV(1) (PC(20)) < 8 mg/ml], with either an impaired (n = 12) or an intact (n = 12) bronchodilatory response to deep inspiration. Two methacholine challenges were performed on separate days. At a 50% increase in respiratory resistance (forced oscillation technique at 8 Hz), the change in resistance by a positive-pressure inflation (computer-driven syringe) or an active deep inspiration was measured in randomized order. The reduction in resistance by positive-pressure inflation was significantly greater than by active deep inspiration in the impaired deep inspiration response group (mean change +/- SE: -0.6 +/- 0.1 vs. -0.03 +/- 0.2 cmH(2)O.l(-1).s, P = 0.002). No significant difference was found between positive-pressure inflation and active deep inspiration in the intact deep inspiration response group (-0.6 +/- 0.2 vs. -1.0 +/- 0.3 cmH(2)O.l(-1).s, P = 0.18). Positive-pressure inflation of the lungs can significantly enhance deep inspiration-induced bronchodilation in patients 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".