Clinical measurement of walking balance in people post stroke: a systematic review
Bibliographic record
Abstract
OBJECTIVE: To identify walking balance measures which have been established for use with ambulatory people post stroke and reflect the balance requirements of community walking. DATA SOURCES: MEDLINE, Embase, AMED. REVIEW METHODS: Measures reflecting walking balance, with tasks that include a stepping action in standing, used with people post stroke were reviewed. Measures with clinical utility were evaluated for psychometric properties, including reliability, validity and clinical interpretation. RESULTS: Nine measures (24 papers) were identified that met the requirement of measuring walking balance in people post stroke with demonstrated clinical utility. Outcome measures with multiple tasks (Brunel Balance Assessment, Modified Emory Functional Ambulation Profile, Dynamic Gait Index, Community Balance and Mobility Scale, and mini-Balance Evaluation Systems Test) as opposed to single task measures (Step Test, Side Step Test and Four Square Step Test, Timed Up and Go), reflect a broader range of walking balance required to accommodate the variable challenges which may be expected at the community level of walking. Most tools report excellent reliability when used by physiotherapists. Validity remains far more challenging to establish. Evaluation of clinical interpretation is limited for all measures. CONCLUSION: The multiple-task outcome measures reviewed reflected walking balance activities often undertaken during community mobility. Single-task measures may be useful as screening measures, identifying walking balance deficits associated with basic/lower levels of walking balance. Construct validity and clinical interpretability of each measure in ambulatory people post stroke requires further research to identify the level of community mobility represented by each measure of walking balance.
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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 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.004 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".