Excess ventilation and exertional dyspnoea in heart failure and pulmonary hypertension
Bibliographic record
Abstract
Increased ventilation relative to metabolic demands, indicating alveolar hyperventilation and/or increased physiological dead space (excess ventilation), is a key cause of exertional dyspnoea. Excess ventilation has assumed a prominent role in the functional assessment of patients with heart failure (HF) with reduced (HFrEF) or preserved (HFpEF) ejection fraction, pulmonary arterial hypertension (PAH) and chronic thromboembolic pulmonary hypertension (CTEPH). We herein provide the key pieces of information to the caring physician to 1) gain unique insights into the seeds of patients' shortness of breath and 2) develop a rationale for therapeutically lessening excess ventilation to mitigate this distressing symptom. Reduced bulk oxygen transfer induced by cardiac output limitation and/or right ventricle-pulmonary arterial uncoupling increase neurochemical afferent stimulation and (largely chemo-) receptor sensitivity, leading to alveolar hyperventilation in HFrEF, PAH and small-vessel, distal CTEPH. As such, interventions geared to improve central haemodynamics and/or reduce chemosensitivity have been particularly effective in lessening their excess ventilation. In contrast, 1) high filling pressures in HFpEF and 2) impaired lung perfusion leading to ventilation/perfusion mismatch in proximal CTEPH conspire to increase physiological dead space. Accordingly, 1) decreasing pulmonary capillary pressures and 2) mechanically unclogging larger pulmonary vessels (pulmonary endarterectomy and balloon pulmonary angioplasty) have been associated with larger decrements in excess ventilation. Exercise training has a strong beneficial effect across diseases. Addressing some major unanswered questions on the link of excess ventilation with exertional dyspnoea under the modulating influence of pharmacological and nonpharmacological interventions might prove instrumental to alleviate the devastating consequences of these prevalent diseases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".