Validating Short Balance Screening Tests for Assessing Fall Risk in People with Chronic Obstructive Pulmonary Disease (COPD)
Bibliographic record
Abstract
Background: People with COPD have significant balance impairments and an increased risk of falls. The psychometric properties of short balance screening tests to inform fall risk assessment in COPD have not been studied. The objective of this study was to compare the validity of four short balance tests suitable for fall risk screening to identify the most optimal screening tool(s). Methods: Participants at least 60 years old with COPD attended a single physical assessment with completion of questionnaires. Correlation coefficients were used to describe relationships between the Brief Balance Evaluation Systems Test (Brief BESTest), Single-Leg Stance (SLS), Timed Up and Go (TUG) and Timed Up and Go Dual-Task (TUG-DT) tests, and other measures of balance, measures of muscle strength, exercise tolerance, functional limitation, disability and prognosis. Independent t-tests or Mann-Whitney U tests were used to examine differences between groups with respect to fall risk. Receiver operating characteristic curves were plotted to examine the ability to of the screening tests to identify individuals with previous falls. Results: Seventy-three participants with COPD completed the study (age 73.0 ± 6.9 years; FEV1 47.0 ± 19.8% predicted). All balance screening tests demonstrated moderate to strong correlations with the Berg Balance Scale (r= 0.47 to 0.80, p<0.05) and Activities-specific Balance Confidence scale (r= 0.44 to 0.61, p<0.05). The Brief BESTest and SLS showed the strongest correlations with other balance measures and demonstrated the most consistent ability to discriminate between fall risk groups. The Brief BESTest was the only screening test that identified individuals who reported a previous fall with acceptable accuracy (AUC= 0.7). Conclusions: The Brief BESTest and SLS show the most promise as balance screening tools for fall risk assessment in older adults with COPD. These results will need to be prospectively confirmed with a larger sample size.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".