Inspiratory and Expiratory Resistive Loading as a Model of Dyspnea in Asthma
Bibliographic record
Abstract
20 ambulatory asthmatics were questioned regarding their perception of the dyspnea of acute asthmatic attacks; in particular, its relationship to the phase of respiration. 19 (95%) stated that inspiration was more difficult than expiration although 5 (25%) reported that they had been taught that the reverse was 'correct'. In order to explore further these observations, we applied psychophysical methods to determine the phase relationship of the conscious perception of resistive loads in healthy volunteers. 14 subjects of similar age and sex distribution to the asthmatics estimated numerically the magnitude of resistive loads applied in random sequence to either the inspiratory or expiratory arm of a low-resistance breathing circuit. The relationship between perceived magnitude (psi) and physical magnitude (phi) was described by Steven's law: psi = k phi n, where k and n are constants. The mean exponent (n) for inspiratory resistances was 0.69 +/- 0.28 (+/- SD) and for expiratory resistances was 0.51 +/- 0.27 (p less than 0.01 by two-tailed, paired t test). There was a positive correlation (r = 0.82) between inspiratory and expiratory exponents within individuals. In 12 of 14 subjects, the perceived magnitude of inspiratory loads was greater than the perceived magnitude of expiratory loads for all resistances greater than 10 cm H2O/l/s. At a load of 25 cm H2O/l/s, the inspiratory sensation of load exceeded the expiratory sensation in all subjects. Our findings that normal subjects scaled greater breathlessness with inspiratory versus expiratory flow resistive loads were consistent with the clinical observation that inspiratory, rather than expiratory difficulty contributed more to the dyspnea of 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".