Dynamic Hyperinflation and Exercise Intolerance in Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
The role of dynamic hyperinflation (DH) in exercise limitation in chronic obstructive pulmonary disease (COPD) remains to be defined. We examined DH during exercise in 105 patients with COPD (FEV(1) = 37 +/- 13% predicted; mean +/- SD) and studied the relationships between resting lung volumes, DH during exercise, and peak oxygen consumption (VO(2)). Patients completed pulmonary function tests and incremental cycle exercise tests. We measured the change in inspiratory capacity (Delta IC) during exercise to reflect changes in DH. During exercise, 80% of patients showed significant DH above resting values. IC decreased 0.37 +/- 0.39 L or 14 +/- 15% predicted during exercise (p < 0.0005), but with large variation in range. Delta IC correlated best with resting IC, both expressed %predicted (r = -0.50, p < 0.0005). Peak VO(2) (%predicted maximum) correlated best with the peak tidal volume attained (VT standardized as % of predicted vital capacity) (r = 0.68, p < 0.0005), which, in turn, correlated strongly with IC at peak exercise (r = 0.79, p < 0.0005) or at rest (r = 0.75, p < 0.0005). The extent of DH during exercise in COPD correlated best with resting IC. DH curtailed the VT response to exercise. This inability to expand VT in response to increasing metabolic demand contributed importantly to exercise intolerance in COPD.
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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 | 0.000 | 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".