Anxiety and depression impact exertional breathlessness in daily life and during exercise testing: the CanCOLD study
Bibliographic record
Abstract
Background Exertional breathlessness is a limiting symptom that often coexists with anxiety and depression. We tested the hypothesis that anxiety and depression negatively impact exertional breathlessness in daily life and during standardised cardiopulmonary exercise testing (CPET). Methods Analysis of people aged ≥40 years undergoing incremental cycle CPET. Exertional breathlessness in daily life was assessed using the Modified Medical Research Council (mMRC) scale and CPET normative reference equations. CPET abnormal exertional breathlessness was defined as a breathlessness (Borg 0–10) intensity rating above the upper limit of normal at peak exercise. Associations of anxiety and depression (Hospital Anxiety and Depression Scale (HADS)) with exertional breathlessness were analysed using multivariable regression models adjusting for anthropometrics, smoking, comorbidities, and lung function at rest and during CPET. Results Across 1155 participants (42% women; 66±10 years), 12% had anxiety and 6% had depression (HADS≥8), 5% experienced exertional breathlessness in daily life (mMRC≥2), and 22% and 16% showed abnormal breathlessness on CPET by power output ( W ) and minute ventilation ( V ′ E ). Worse anxiety and depression scores were independently associated with perceiving worse breathlessness in daily life (anxiety: OR 1.08, 95% CI 0.98–1.19; depression: OR 1.18, 95% CI 1.06–1.31) and with more abnormal breathlessness on CPET in relation to W and V ′ E (p<0.001 for all analyses). Conclusion This is the first study to show that the association of anxiety and depression with worse breathlessness in daily life persists during standardised CPET, independent of a wide range of disease severity markers – making these psychological symptoms important therapeutical targets.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".