A pilot study of cognitive disorders, depression and anxiety in obstructive lung disease
Bibliographic record
Abstract
Introduction: The association of cognition, anxiety and depression with respiratory conditions, are nowadays of key interest in research. Understanding the correlation between the psychiatric symptoms and lung diseases will improve the quality of life for patients. Aims and Objectives: The study aims to establish possible links between psychiatric pathologies and pulmonary obstructive diseases. Methods: After obtaining ethical approval, we enrolled 52 subjects (20-86 years old) whom expressed written consent, with a history of obstructive lung disease, admitted at Leamna Pulmonology Hospital (October 2022-February 2023). We used the Mini Mental State Examination, Montreal Cognitive Assessment, Hamilton Anxiety-Depression Scale to evaluate cognitive, depression and anxiety levels. Results: We found 19 (36.5%) with a history asthma (6 had severe asthma) and 33 (63.5%) with COPD (22 classified GOLD D). Of all, 10 (19.2%) patients had psychiatric history and medication. Patients without knowledge of inhaling medication performed poorly in the psychiatric questionnaires. Even though they had distinctive characteristics, the gravity of the psychiatrics pathology was inversely proportional with level of education and directly proportional with the severity of the respiratory pathology in all patients. Surprisingly, patients with a higher hospitalization rate were less likely to have severe depression or anxiety. Conclusions: The COPD group performed poorly in the applied questioners compared to the Asthma group. Some subjects that had significant changes in psychiatric questioners, were not known with depressive, anxiety or cognitive disorders and needed psychiatric referrals.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".