Ventilatory response to exercise in cardiopulmonary disease: the role of chemosensitivity and dead space
Bibliographic record
Abstract
The lungs and heart are irrevocably linked in their oxygen (O2) and carbon dioxide (CO2) transport functions. Functional impairment of the lungs often affects heart function andvice versa. The steepness with which ventilation (V′E) rises with respect to CO2production (V′CO2) (i.e.theV′E/V′CO2slope) is a measure of ventilatory efficiency and can be used to identify an abnormal ventilatory response to exercise. TheV′E/V′CO2slope is a prognostic marker in several chronic cardiopulmonary diseases independent of other exercise-related variables such as peak O2uptake (V′O2). TheV′E/V′CO2slope is determined by two factors: 1) the arterial CO2partial pressure (PaCO2) during exercise and 2) the fraction of the tidal volume (VT) that goes to dead space (VD) (i.e.the physiological dead space ratio (VD/VT)). An alteredPaCO2set-point and chemosensitivity are present in many cardiopulmonary diseases, which influenceV′E/V′CO2by affectingPaCO2. Increased ventilation–perfusion heterogeneity, causing inefficient gas exchange, also contributes to the abnormalV′E/V′CO2observed in cardiopulmonary diseases by increasingVD/VT. During cardiopulmonary exercise testing, thePaCO2during exercise is often not measured andVD/VTis only estimated by taking into account the end-tidal CO2partial pressure (PETCO2); however,PaCO2is not accurately estimated fromPETCO2in patients with cardiopulmonary disease. Measuring arterial gases (PaO2andPaCO2) before and during exercise provides information on the real (and not “estimated”)VD/VTcoupled with a true measure of gas exchange efficiency such as the difference between alveolar and arterial O2partial pressure and the difference between arterial and end-tidal CO2partial pressure during exercise.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".