Translating the Interplay of Cognition and Physical Performance in COPD and Interstitial Lung Disease
Bibliographic record
Abstract
TOPIC IMPORTANCE: Cognitive and physical limitations are common in individuals with chronic lung diseases, but their interactions with physical function and activities of daily living are not well characterized. Understanding these interactions and potential contributors may provide insights on disability and enable more tailored rehabilitation strategies. REVIEW FINDINGS: This review summarizes a 2-day meeting of patient partners, clinicians, researchers, and lung associations to discuss the interplay between cognitive and physical function in people with chronic lung diseases. This report covers four areas: (1) cognitive-physical limitations in patients with chronic lung diseases; (2) cognitive assessments; (3) strategies to optimize cognition and motor control; and (4) future research directions. Cognitive and physical impairments have multiple effects on quality of life and daily function. Meeting participants acknowledged the need for a standardized cognitive assessment to complement physical assessments in patients with chronic lung diseases. Dyspnea, fatigue, and age were recognized as important contributors to cognition that can affect motor control and daily physical function. Pulmonary rehabilitation was highlighted as a multidisciplinary strategy that may improve respiratory and limb motor control through neuroplasticity and has the potential to improve physical function and quality of life. SUMMARY: There was consensus that cognitive function and the cognitive interference of dyspnea in people with chronic lung diseases contribute to motor control impairments that can negatively affect daily function, which may be improved with pulmonary rehabilitation. The meeting generated several key research questions related to cognitive-physical interactions in individuals with chronic lung diseases.
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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".