Is cognitive function, disease severity or quality of life related to dual tasking in COPD?
Bibliographic record
Abstract
Background: Chronic Obstructive Pulmonary Disease (COPD), the third leading cause of morbidity and mortality globally, is associated with cognitive and motor impairments that can affect multitasking required for daily activities. Aim: To assess the association between cognitive function, quality of life and disease severity on dual task (DT) performance, doing two things simultaneously in persons with COPD. Methods: 19 stable COPD outpatients (9M:10F) completed spirometry, Medical Research Council (MRC), St George’s Respiratory Questionnaire (SGRQ), COPD Assessment Test (CAT), and TestMyBrain (TMB), a neurocognitive battery (Choice reaction time, Trail A and Trail B). Gait speed was evaluated during a 20-meter single task (ST) walk and during DT combined with an auditory Stroop task (AST). Results: Dual tasking reduced gait speed (p=0.04) and AST accuracy (p=0.01) while increasing the AST reaction time (p=0.004). While ST gait speed was correlated with FEV1 %pred, DT gait speed correlated with MRC dyspnea, CAT (disease impact) and showed stronger correlations with SGRQ domains of impact and total scores (Table 1). Correlations between DT gait speed and TMB scores were not significant. erj;66/suppl_69/PA4895/F1 F1 F1 Conclusion: DT compared to ST walking was slower and more strongly related to disease impact (CAT) and health related quality of life (SGRQ). DT assessment may be an informative marker of performing daily activities.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".