Relation of Indices of Lung Hyperinflation to Dyspnea in Patients with Chronic Obstructive Pulmonary Disease: A Physiologic Assessment and Discussion
Bibliographic record
Abstract
Background: The severity of COPD is commonly assessed by the reduction in forced expiratory volume at one second (FEV1), although more recently prognostic factors influencing survival have also incorporated functional capacity, degree of breathlessness on exertion, and body mass index. Increasingly, the reliability of physiological parameters such as FEV1 to predict patient-centered outcomes has been brought into question. Objectives: To evaluate the relationship between dyspnea as assessed by the Modified Medical Council Dyspnea (MMRC) scale, the Global Initiative for Chronic Obstructive Lung Disease (GOLD 2014) staging and indices of lung hyperinflation and spirometry. Methods: Data were retrospectively analyzed at a 600-bed tertiary care center including spirometry, plethysmographic lung volumes, single breath carbon monoxide diffusion capacity and dyspnea graded according to MMRC, and GOLD staging. Results: Data for 331 patients were analyzed. Differences amongst FEV1, IC, IC/TLC, FRC and RV/TLC were significant between GOLD I/II and GOLD III/IV groups. The closest relationship to GOLD staging was seen with FEV1, FVC and slow vital capacity (SVC). FEV1/FVC, IC, and IC/TLC were inversely associated with MMRC score, while RV/TLC exhibited a positive relation with MMRC score. Conclusions: Indices of lung hyperinflation are closely associated, with dyspnea as assessed by MMRC grading with TLC, RV/TLC and IC exhibiting the closest relations, more so than FEV1. GOLD staging also shows strong correlations with lung volume subdivisions (weakly with TLC), more so than with FEV1. That TLC changed little between GOLD stages can be explained by the presence of collateral interalveolar channels and population characteristics different from those of other studies. These findings further support the concept that more than a reduction in FEV1, lung hyperinflation contributes to the sensation of dyspnea in airflow limitation.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".