109 INVESTIGATING GAIT AND COGNITION IN ELDERLY COPD PATIENTS HOSPITALISED WITH AN ACUTE EXACERBATION
Bibliographic record
Abstract
Background With advancing age, Chronic Obstructive Pulmonary Disease (COPD) can place an individual at greater risk of reduced participation in society and mortality (1). Survival in older adults increases with gait speed but little is known about gait in COPD (2). The objective of this study was to monitor gait of patients admitted to hospital with an acute exacerbation of COPD (AECOPD), their cognitive performance and to examine the relationships with clinical improvement. Methods Gait speed was acquired in 29 patients admitted to hospital with an AECOPD, with a mean age of 71.6 ±8.1 years. Gait speed was acquired employing the 4-metre gait speed test on day 1 of hospitalisation, day of hospital discharge and at 30 days follow-up. Montreal Cognitive assessment (MOCA) scores were recorded on day of admission. Linear regression was performed to assess correlations and between-group differences were assessed using student t-tests. Results Gait speed improved significantly from day 1 of hospitalisation (0.69 ±0.29 ms-1) to follow-up at day 30 (1.01 ±0.31 ms-1) (p = 0.0031). Slower gait speeds on day 1 of hospitalisation were significantly correlated with longer durations of hospital stay (p = 0.0014). There was no significant correlation between gait speed and MOCA score. Conclusions These results illustrate that gait speed is significantly slower during an exacerbation at admission to hospital, compared to 30 day follow-up. Furthermore, the novelty of these results is that gait speed at hospital admission predicts length of hospital stay. Future work should investigate if objective lung function and gait measures are more sensitive at predicting changes during hospitalisation and at 30 day follow-up.
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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 | 0.001 |
| 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".