The effect of coexisting chronic heart failure (CHF) in exercise ventilatory inefficiency in patients with COPD
Bibliographic record
Abstract
Background: Increase in “wasted” ventilation (VE) during exercise – as a consequence of large dead space to tidal volume ratio – is a common feature of chronic obstructive pulmonary disease (COPD) and CHF. Coexistence of COPD and CHF, therefore, could be associated with greater increases in exercise VE relative to both oxygen uptake (VO 2 ) and carbon dioxide output (VCO 2 ) compared to COPD alone. Objective: To investigate the role of ventilatory inefficiency during incremental exericse in suggesting the presence of CHF in patients with established COPD. Methods: Twenty-four males (13 with COPD-CHF (FEV 1 = 59.6 ± 17.5 % pred; left ventricle ejection fraction (LVEF) = 34 ± 6 %) and 10 with COPD alone (FEV 1 = 48.6 ± 16.0 % pred; LVEF= 64 ± 4 %) were submitted to a ramp-incremental cardiopulmonary exercise test. Results : COPD-CHF patients had shallower Δ VO 2 /Δ work rate (WR) and lower peak VO 2 than their counterparts ( p <0.05). In line with our hypotheses, measures of excessive exercise ventilation relative to both VO 2 and VCO 2 were more disturbed in COPD-CHF than COPD patients (ΔVE/ΔVCO 2 = 39± 10 vs . 30 ± 6 ( p <0.05) and VO 2 efficiency slope (OUES, L/min/log)= 1.35± 0.38 vs. 1.76 ± 0.42 ( p <0.01), respectively. In addition, decreases in ΔVO 2 /ΔWR and OUES were more closely related to peak VO 2 in COPD-CHF than in COPD (r= 0.72 vs. 0.24 and 0.80 vs. 0.68, respectively). Conclusions : Pulmonary ventilation increases out of proportion of both VCO 2 and VO 2 during progressive exercise in COPD plus CHF patients compared to COPD alone. These results suggest that ventilatory inefficiency variables might be helpful in indicating the coexistence of CHF in COPD patients.
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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 | 0.004 |
| 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 | 0.001 | 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".