Prevalence of anxiety and depression symptoms and their associated factors in mild COPD patients from community settings, Shanghai, China: a cross-sectional study
Bibliographic record
Abstract
Chronic obstructive pulmonary disease (COPD) is a serious disease frequently accompanied by anxiety and depression. Few studies have focused on anxiety and depression for mild COPD patients in China. This study aimed to assess the prevalence and associated factors for anxiety and depression among patients with mild COPD in urban communities. A cross-sectional survey of 275 mild COPD patients was conducted in 6 communities randomly sampled from Pudong New Area of Shanghai, China, in 2016. Data on socioeconomic factors and health conditions were acquired through a face-to-face interview as well as a physical examination. The Hospital Anxiety and Depression Scale (HAD) and EQ-5D visual analogue (EQ-5D vas ) were applied to evaluate their mental health and quality of life, respectively. Logistic regression model was used to estimate adjusted odds ratios (aORs) and their 95% confidential intervals (CI) for risk factors associated with anxiety or depression. Among 275 subjects, 8.1% had anxiety and 13.4% had depression. Logistic regression analysis indicated that female patients were more likely to suffer from anxiety than male patients (aOR = 6.41, 95% CI:1.73 - 23.80). Poor health status (EQ-5D vas score < 70) was significantly associated with increased risks of anxiety (aOR = 5.99, 95% CI: 2.13-16.82) and depression (aOR = 2.67, 95% CI: 1.29-5.52). There were increased risks of anxiety and depression in mild COPD patients living in urban communities. Female sex and poor health status were significantly correlated to anxiety or depression. More interventions should be developed to reduce the risks of anxiety and depression at the early stage of COPD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".