Determinants of balance impairment in individuals with Chronic Obstructive Pulmonary Disease: A secondary analysis of a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Balance impairment is common in individuals with Chronic Obstructive Pulmonary Disease (COPD), increasing fall risk and reducing functional independence. This study investigated functional, clinical, and demographic determinants of balance performance in individuals with COPD. METHODS: This secondary analysis included participants from a randomized controlled trial involving pulmonary rehabilitation centers. Balance was evaluated using the Berg Balance Scale (BBS) and Balance Evaluation Systems Test (BESTest). Functional assessments comprised the 30-Second Chair Stand Test (30s CST) and Six-Minute Walk Test (6-MWT). Clinical variables included lung function, dyspnea, comorbidities, medications, fall history, supplemental oxygen, and gait aid use. Multiple regression analyses were conducted to evaluate associations between balance, functional, clinical, and demographic factors. RESULTS: Of the 244 participants (mean age: 71 ± 9 years; 57 % male), 87 % reported balance deficits and 50 % had at least one fall in the past year. Functional capacity was strongly correlated with balance scores (r > 0.5, p < 0.001). Clinical factors, including dyspnea, comorbidities, gait aid, and supplemental oxygen use, were also significant. The full regression model explained 58 % of the variance in BESTest scores and 51 % in BBS scores. Each additional 30s CST repetition predicted a 1.22-point increase in BESTest scores and a 0.59-point increase in BBS scores. Less severe dyspnea was associated with higher scores on both balance measures. CONCLUSION: Balance performance in individuals with COPD is influenced by both clinical and functional parameters. Identification of these factors supports the development of targeted interventions to address balance impairment and improve patient outcomes in this population.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".