Factors Influencing Cognitive Function in Subjects With COPD
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to assess the association between cognitive function and age, pulmonary function, comorbidity index, and the 6-min walk distance in subjects with COPD as well as to compare the Mini Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) in terms of their ability to identify cognitive dysfunction in subjects with COPD. METHODS: A total of 52 individuals with stable COPD were included in this study. Cognitive function was assessed using MMSE and MoCA. Age, body mass index, the Modified Cumulative Illness Rating Scale, 6-min walk distance, arterial blood gases, and pulmonary function tests were assessed and recorded. RESULTS: The range and SD of scores in subjects with COPD were larger with MoCA than with MMSE. MMSE and MoCA scores are associated with 6-min walk distance and comorbidity index in subjects with COPD. General cognitive function measured by MoCA was negatively correlated with the comorbidity index but was positively associated with 6-min walk distance in subjects with COPD after controlling for possible confounding factors in the multivariate model. However, general cognitive function measured by MMSE was not correlated with the comorbidity index and 6-min walk distance in subjects with COPD, after controlling for possible confounding factors in the multivariate model. CONCLUSIONS: MoCA may be a more reliable screening test than MMSE in detecting cognitive impairment in subjects with COPD. The addition of cognitive tests on assessment of subjects with COPD can provide further benefit.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".