Pathogenesis of hyperinflation in chronic obstructive pulmonary disease
Bibliographic record
Abstract
Chronic obstructive pulmonary disease (COPD) is a preventable and treatable lung disease characterized by airflow limitation that is not fully reversible. In a significant proportion of patients with COPD, reduced lung elastic recoil combined with expiratory flow limitation leads to lung hyperinflation during the course of the disease. Development of hyperinflation during the course of COPD is insidious. Dynamic hyperinflation is highly prevalent in the advanced stages of COPD, and new evidence suggests that it also occurs in many patients with mild disease, independently of the presence of resting hyperinflation. Hyperinflation is clinically relevant for patients with COPD mainly because it contributes to dyspnea, exercise intolerance, skeletal muscle limitations, morbidity, and reduced physical activity levels associated with the disease. Various pharmacological and nonpharmacological interventions have been shown to reduce hyperinflation and delay the onset of ventilatory limitation in patients with COPD. The aim of this review is to address the more recent literature regarding the pathogenesis, assessment, and management of both static and dynamic lung hyperinflation in patients with COPD. We also address the influence of biological sex and obesity and new developments in our understanding of hyperinflation in patients with mild COPD and its evolution during progression of the disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".