Factors influencing cognitive function in COPD
Bibliographic record
Abstract
Objective:Cognitive impairment may frequently be seen in patients with COPD.The goal of this study was to assess relationships clinical parameters and cognition in people with COPD. Methods:We studied 52 patients with stable COPD. Cognitive states were investigated by the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA). Age, BMI, the Modified Cumulative Illness Rating Scale(MCIRS), 6-min walk distance, AKG, and PFT were assessed. Results:The rate of cognitive impairment measured by MoCA was 30.8 percent while 25% with the MMSE. MMSE and MoCA scores are associated with 6-min walk distance and comorbidity index in COPD patients. General cognitive function, measured by the MoCA, was negatively correlated with the comorbidity index, while was positively associated with 6-min walk distance in COPD patients,after controlling for possible confounding factors. The none of the COPD severity measures such as pulmonary function tests and arterial blood gases were associated with the risk of cognitive impairment Table 1: Predictor of Cognitive Functions Cognitive function values with MOCA Cognitive function values with MMSE beta p value beta p value Age -0.22 0.06 -0.38 0.004 Gender(male) 0.46 0.0001 0.35 0.006 BMI -0.07 0.5 -0.25 0.04 6-min walk distance 0.36 0.002 0.18 0.1 MCIRS -0.32 0.007 -0.12 0.3 FEV1% 0.02 0.8 0.05 0.6 PaO2 0.01 0.9 -0.03 0.7 . Conclusions: Cognitive impairment in patients with COPD is common. COPD patients with better functional capacity and lower comorbidity had a better cognitive functions. MoCA s used in conjunction with the MMSE may provide additional information about the cognitive functions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.001 |
| 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".