Postural Control Is Impaired in People with COPD: An Observational Study
Bibliographic record
Abstract
PURPOSE: We investigated deficits in postural control and fall risk in people with chronic obstructive pulmonary disease (COPD). METHOD: Twenty people with moderate to severe COPD (mean age 72.3 years, standard deviation [SD] 6.7 years) with a mean forced expiratory volume in 1 second (FEV(1)) of 46.7% (SD 13%) and 20 people (mean age 68.2 years, SD 8.1) who served as a comparison group were tested for postural control using the Sensory Organization Test (SOT). A score of zero in any trial of the SOT was registered as a fall. On the basis of the SOT results, participants were categorized as frequent fallers (two or more falls) or as fallers (one fall). To explore the potential influence of muscle weakness on postural control, knee extensors concentric muscle torque was assessed with an isokinetic dynamometer. Physical activity level was assessed with the Physical Activity Scale for the Elderly. RESULTS: People with COPD showed a 10.8% lower score on the SOT (p=0.016) and experienced more falls (40) than the comparison group (12). The proportion of frequent fallers and fallers during the SOT was greater (p=0.021) in the COPD group (four of 10) than in the comparison group (two of seven). People with COPD showed deficits in knee extensors muscle strength (p=0.01) and a modest trend toward reduced physical activity level. However, neither of these factors explained the deficits in postural control observed in the COPD group. CONCLUSIONS: People with COPD show deficits in postural control and increased risk of falls as measured by the SOT. The deficits in postural control appear to be independent of muscle weakness and level of physical activity. Postural control interventions and fall risk strategies in the pulmonary rehabilitation of COPD are recommended.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".