Cognitive Impairment in Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
Background/Purpose: Chronic obstructive pulmonary disease (COPD), especially in severe forms, is commonly associated with multiple cognitive problems. Montreal Cognitive Assessment test (MoCA) is used to detect cognitive impairment evaluating several areas: visuospatial, memory, attention and fluency. Our study aim was to evaluate the impact of stable COPD and exacerbation (AECOPD) phases on cognitive status using MoCA questionnaire. Methods: We enrolled 39 patients (pts), smokers with COPD group D (30 stable and 9 in AECOPD) and 13 healthy subjects (control group), having similar level of education and no significant differences regarding the anthropometric measurements. We analyzed the differences in MoCA score between these three groups and also the correlation between this score and inflammatory markers. Results: Patients with AECOPD had a significant (p,0.001) decreased MoCA score (14.663.4) compared to stable COPD (20.262.4) and controls (24.265.8). The differences between groups were more accentuated for the language abstraction and attention (p,0.001) and delayed recall and orientation (p,0.001) sub-topics. No significant variance of score was observed between groups regarding visuospatial and naming score (p = 0.095). The MoCA score was significantly correlated with forced expiratory volume (r = 0.28) and reverse correlated with C-reactive protein (CRP) (r =20.57), fibrinogen (r =2 0.58), erythrocyte sedimentation rate (ESR) (r =20.55) and with the partial pressure of CO2 (r =20.47).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".