Prevalence of depression and anxiety in patients with chronic obstructive pulmonary disease and their association with psychosocial outcomes: A cross-sectional study from Pakistan
Bibliographic record
Abstract
OBJECTIVES: Chronic obstructive pulmonary disease contributes to substantial health and economic burden worldwide. Co-morbid depression and anxiety are highly prevalent in patients with chronic obstructive pulmonary disease. Depressive symptoms in chronic obstructive pulmonary disease are associated with poorer survival, longer hospitalisation and impaired quality of life. Literature on chronic obstructive pulmonary disease is largely derived from high-income countries; yet 90% of deaths related to chronic obstructive pulmonary disease occur in low- and middle-income countries. We aimed to establish the prevalence of anxiety and depression in patients with chronic obstructive pulmonary disease, as well as the association with psychosocial outcomes. METHODS: This was a cross-sectional study of chronic obstructive pulmonary disease patients attending outpatient primary care clinics in Karachi, Pakistan. The Patient Health Questionnaire-9 was used to assess depression and the Generalised Anxiety Disorder-7 scale was used for the assessment of anxiety. Health-related quality of life was assessed with EuroQol-Five Dimensions, social support with Oslo-3 and social stress with Life Events Checklist. We recruited 293 subjects. RESULTS: = 59), respectively. Depressed chronic obstructive pulmonary disease patients reported significantly lower health-related quality of life scores as compared to non-depressed patients. Participants with depression had significantly higher levels of anxiety, less social support, higher social stress and more subjective impairment in quality of life. CONCLUSION: Given the association with reduced social support and increased perceived stress, the role of psychosocial interventions must be explored in improving outcomes of chronic obstructive pulmonary disease patients in Pakistan.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".