Cognitive Impairment in Patients with Severe COPD: A Cross-Sectional Study
Bibliographic record
Abstract
Background/Objectives: Cognitive impairment (CI) in patients with chronic obstructive pulmonary disease (COPD) has been associated with reduced physical activity and decreased adherence to inhalation therapy. The primary aim of this study is to examine the prevalence of CI in patients with severe COPD and secondly compare outcomes with non-COPD comparators. Methods: Patients with severe COPD defined as forced expiratory volume in first second (FEV1) <50% were recruited between January 2021 to January 2023 along with non-COPD comparators. CI was defined as a MoCA score < 26, adding one point for participants with ≤12 years of education. Additionally, two functional cognitive tests were included: the Continuous Reaction Time test (CRT) and a driving simulator. Results: Eighty patients with COPD (mean age 64 years) and 22 non-COPD comparators (mean age 61 years) participated. CI was identified in 32 patients with COPD (40%) and six non-COPD comparators (27%) with a 0.87 non-significant difference (95% CI: −0.15–1.88). The functional tests showed a 0.267 difference in CRT index (95% CI: 0.023–0.511) and a 0.056 difference in standard deviation from center of the road (95% CI: 0.002–0.11) revealing a significantly poorer performance in functional tests among patients compared to non-COPD comparators. Nineteen patients with COPD and one non-COPD comparator failed the driving test (p = 0.04). Conclusions: CI was found in 40% of patients with severe COPD based on MoCA score. While MoCA score did not differ between the two groups, functional tests demonstrated significantly reduced abilities in patients compared with non-COPD comparators.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".