Prevalence of Depressive Symptoms and Depression in Patients With Severe Oxygen-Dependent Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
PURPOSE: To measure the prevalence rate of significant depressive symptoms and depression and examine their consequences on quality of life in patients with severe oxygen-dependent chronic obstructive pulmonary disease (COPD). METHODS: Between November 1997 and March 1998, the authors conducted a cross-sectional study among the COPD patients registered at the Quebec City area respiratory home care service. Depression and quality of life were assessed using the Geriatric Depression Scale and the Medical Outcome Survey--Short Form 36 (SF-36). RESULTS: 109 patients (63 men; mean age: 71) with severe COPD (median FEV1: 34%) were surveyed. Of them, 105 were on long-term oxygen therapy (LTOT), which had been introduced (median) 19 months earlier. Sixty-two patients (57%; 95% Cl: 47-66) demonstrated significant depressive symptoms; in addition, 20 patients (18%; Cl: 12-27) were severely depressed. Only 6% of those patients who met the criteria for depression were taking an antidepressant drug. We found significant and moderate correlations between the scores obtained from the Geriatric Depression Scale and 7 of the 8 domains of the SF-36. CONCLUSION: Significant depressive symptoms and depression are highly prevalent in patients with severe COPD on LTOT. There is strong evidence that depression is under-recognized and under-treated in this group of patients.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".