The role of cardiopulmonary exercise testing in the diagnosis of psychogenic dyspnoea
Bibliographic record
Abstract
Introduction: Cardiopulmonary exercise testing (CPET) has long been used in the assessment of chronic dyspnoea. The aim of this study was to evaluate the role of CPET in the diagnosis of psychogenic dyspnoea in patients undergoing investigation of unexplained breathlessness. Methods: Patients performed ramp-incremental CPET on cycle-ergometer as workup evaluation of unexplained dyspnoea (UD) between 2010 and 2015. Detailed clinical history, complementary diagnostic tests, and final diagnosis were recorded. Results: Forty-seven patients with UD were identified. Mean age was 46 yo (17–71) and the majority were women (64%), with a mean BMI of 28.7 (16.9–43). CPET suggested central cardiac limitation to exercise in 5 patients, ventilatory limitation was inferred in 3 of them and deconditioning was considered to be the cause of limitation in 6 cases. Erratic breathing or persistent tachypnoea throughout exercise, consistent with Primary Hyperventilation Syndrome, was observed in 14 subjects (29%). In addition, 6 of 19 patients with normal CPET were also ultimately considered to have psychogenic dyspnoea by the referring physician in light of unremarkable physical examination as well as laboratory and radiologic evaluation ruling out organic causes of dyspnoea. The frequency of psychogenic dyspnoea was similar for both genders (41.2% male vs. 43.3% female), but interestingly erratic breathing was more commonly seen among women (11) than men (3). Conclusions: CPET was helpful in the diagnosis of psychogenic dyspnoea in patients with unexplained dyspnoea not only by identifying erratic and uncoupled ventilatory-metabolic responses, but also by excluding cardiorespiratory or metabolic abnormalities.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".