Using breath-by-breath volumetric capnography to link gas exchange to exertional ventilatory efficiency in mild-moderate COPD
Bibliographic record
Abstract
Background: Elevated ventilation relative to CO2 output (↑V̇E/V̇CO2) is associated with exertional dyspnoea across the COPD spectrum. The precise determinants of ↑V̇E/V̇CO2 in milder disease remain incompletely understood. Aim: To use continuous assessment of gas exchange efficiency by breath-by-breath volumetric capnography to better understand the physiologic basis of ↑V̇E/V̇CO2 in mild-moderate COPD. Methods: 18 patients (9M; FEV1=78%, DLCO=77%) and 17 sex- and age-matched healthy controls completed an incremental exercise test, with continuous volumetric capnography and transcutaneous PCO2 (PtcCO2). Results: Patients had poorer exercise capacity and higher peak dyspnoea/work rate than controls (p<0.05). They also showed higher V̇E/V̇CO2 nadir (35±5 vs. 30±4, p=0.008; Fig A); 45% of patients had V̇E/V̇CO2 nadir > 34 vs. 17% of controls. All markers of poor gas exchange efficiency were consistently higher in patients (Fig B-D), whereas PtcCO2 and end-tidal PCO2 were lower (Fig E-F). Multiple linear regression showed that dead space/tidal volume ratio (standardized β= 0.62) and PtcCO2 (-0.45) explained ∼ 70% of V̇E/V̇CO2 nadir variance (p<0.001). erj;66/suppl_69/PA5188/F1 F1 F1 Conclusions: Continuous, breath-by-breath assessment of gas exchange efficiency during exercise indicates that alveolar hyperventilation and increased wasted ventilation in poorly-perfused lung contribute to ↑V̇E/V̇CO2 in mild-moderate 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 | 0.000 | 0.001 |
| 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".