Sedentary Time and Cognitive Impairment in Patients Using Long-Term Oxygen Therapy: A Cross-Sectional Study
Bibliographic record
Abstract
Physical inactivity is a predictor of death in patients with chronic respiratory disease. Cognitive impairment is common among patients with chronic respiratory disease. However, the association between sedentary time and cognitive impairment in patients with chronic respiratory disease using long-term oxygen therapy is unclear. This study aimed to determine the relationship between sedentary time and cognitive impairment in patients on long-term oxygen therapy. This cross-sectional study included 96 patients with chronic respiratory disease on long-term oxygen therapy (mean age 77.3 years; female, 22%). The primary outcomes measured were sedentary time (Japanese version of the International Physical Activity Questionnaire Short Form), cognitive function (Montreal Cognitive Assessment), and dyspnea (modified Medical Research Council scale). The factors associated with sedentary time were confirmed by multiple regression analysis. The median sedentary time was 600.0 min. The median Montreal Cognitive Assessment score was 24.0 points, and 67 (70%) patients had mild cognitive impairment. In multiple regression analysis, sedentary time was associated with dyspnea (β = 0.397, p < 0.001) and cognitive function (β = −0.239, p = 0.020). This study indicates that sedentary time in patients on long-term oxygen therapy was associated with dyspnea and cognitive impairment.
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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) | 0.000 | 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 | 0.000 |
| 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".