Multidimensional analysis of anxiety symptoms in patients with chronic obstructive pulmonary disease (COPD)
Bibliographic record
Abstract
To explore the potential classes of anxiety symptoms in patients with chronic obstructive pulmonary disease (COPD) and analyze their distinct characteristics. Convenience sampling was used to select 211 cases of COPD from 12 hospitals in Hebei Province. The following scales were used: General Information Questionnaire, Anxiety Inventory for Respiratory Disease (AIR), BODE index, Montreal Cognitive Assessment (MoCA), and SF-36 Quality of Life scale. Latent profile analysis (LPA) was conducted on the anxiety symptoms of the survey subjects, and univariate analysis and ordinal logistic regression were used to analyze the risk factors of different profiles. Anxiety symptoms among COPD patients were classified into three types: low-risk anxiety type (57.8%), moderate anxiety-fear type (23.2%), and high anxiety-fear type (19.0%). Ordered multinomial logistic regression analysis revealed that the duration of disease, BODE index, MoCA scores, and SF-36 scores were identified as independent risk factors for the potential classes of anxiety symptoms in COPD patients (p < 0.05). There is heterogeneity in anxiety symptoms among COPD patients. Medical staff can provide targeted interventions based on the characteristics and risk factors of different populations to alleviate anxiety symptoms.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 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".