Exercise Ventilation in COPD: Influence of Systolic Heart Failure
Bibliographic record
Abstract
Systolic heart failure is a common and disabling co-morbidity of chronic obstructive pulmonary disease (COPD) which may increase exercise ventilation due to heightened neural drive and/or impaired pulmonary gas exchange efficiency. The influence of heart failure on exercise ventilation, however, remains poorly characterized in COPD. In a prospective study, 98 patients with moderate to very severe COPD [41 with coexisting heart failure; ‘overlap’ (left ventricular ejection fraction < 50%)] underwent an incremental cardiopulmonary exercise test (CPET). Compared to COPD, overlap had lower peak exercise capacity despite higher FEV1. Overlap showed lower operating lung volumes, greater ventilatory inefficiency and larger decrements in end-tidal CO2 (PETCO2) (P < 0.05). These results were consistent with those found in FEV1-matched patients. Larger areas under receiver operating characteristic curves to discriminate overlap from COPD were found for ventilation (E)-CO2 output CO2) intercept, E-CO2 slope, peak E/CO2 ratio and peak PETCO2. Multiple logistic regression analysis revealed that CO2 intercept ≤ 3.5 L/minute [odds ratios (95% CI) = 7.69 (2.61–22.65), P < 0.001] plus E-CO2 slope ≥ 34 [2.18 (0.73–6.50), P = 0.14] or peak E/CO2 ratio ≥ 37 [5.35 (1.96–14.59), P = 0.001] plus peak PETCO2 ≤ 31 mmHg [5.73 (1.42–23.15), P = 0.01] were indicative of overlapping. Heart failure increases the ventilatory response to metabolic demand in COPD. Variables reflecting excessive ventilation might prove useful to assist clinical interpretation of CPET responses in COPD patients presenting heart failure as co-morbidity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".