Assessing Exercise Limitation Using Cardiopulmonary Exercise Testing
Bibliographic record
Abstract
The cardiopulmonary exercise test (CPET) is an important physiological investigation that can aid clinicians in their evaluation of exercise intolerance and dyspnea. Maximal oxygen consumption ([Formula: see text]) is the gold-standard measure of aerobic fitness and is determined by the variables that define oxygen delivery in the Fick equation ([Formula: see text] = cardiac output × arterial-venous O(2) content difference). In healthy subjects, of the variables involved in oxygen delivery, it is the limitations of the cardiovascular system that are most responsible for limiting exercise, as ventilation and gas exchange are sufficient to maintain arterial O(2) content up to peak exercise. Patients with lung disease can develop a pulmonary limitation to exercise which can contribute to exercise intolerance and dyspnea. In these patients, ventilation may be insufficient for metabolic demand, as demonstrated by an inadequate breathing reserve, expiratory flow limitation, dynamic hyperinflation, and/or retention of arterial CO(2). Lung disease patients can also develop gas exchange impairments with exercise as demonstrated by an increased alveolar-to-arterial O(2) pressure difference. CPET testing data, when combined with other clinical/investigation studies, can provide the clinician with an objective method to evaluate cardiopulmonary physiology and determination of exercise intolerance.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".