Anxiety and depression in end-stage COPD
Bibliographic record
Abstract
Although feelings of anxiety and depression are common in patients with chronic obstructive pulmonary disease (COPD), estimates of their prevalence vary considerably. This probably reflects the variety of scales and methods used to measure such symptoms. Regardless of whether anxiety and depression are considered separately or as a single construct, their impact on COPD patients is important. A heightened experience of dyspnoea is likely to be a contributing factor to anxiety. Feelings of depression may be precipitated by the loss and grief associated with the disability of COPD. Smoking has been associated with nicotine addiction, and the factors that contribute to smoking may also predispose to anxiety and depressive disorders. Randomised controlled trials indicate that exercise training and carefully selected pharmacological therapy are often effective in ameliorating anxiety and depression. Most medical illnesses are influenced by the psychological responses and coping mechanisms that patients use. However, anxiety and depression are associated with dyspnoea, fatigue and altered sleep, all of which also occur in COPD. An understanding of the psychological history and coping mechanisms of patients and the role of anxiety and depressive reactions to illness may enable clinicians to reduce these symptoms and improve quality of life among patients with chronic obstructive pulmonary disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| 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".