Physical Function Tests to Assess Postural Balance in Patients on Dialysis: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: This systematic review evaluated physical function tests used to assess postural balance in patients on dialysis and described their measurement properties. METHODS: The study was registered in PROSPERO (#CRD42020186578). Seven databases were searched from inception to August 2023. Observational and experimental studies including at least one physical function test for postural balance in patients on hemodialysis or peritoneal dialysis were eligible. Two independent researchers selected studies, assessed methodological quality using the Critical Review Form-Quantitative Studies, and extracted data. RESULTS: Of the 21 studies analyzed, 42.9% were cross-sectional, and 38.1% demonstrated good methodological quality. The one-leg standing Test was the most common physical function test (used in 47.6% of studies), with variations in protocol, such as eyes open or closed and durations ranging from 5 to 60 s or unspecified. Other tests included the Berg balance scale, balance evaluation systems test, brief-balance evaluation systems test, mini-balance evaluation systems test, stork balance test, standing balance test, functional reach test, and frailty and injuries cooperative studies of intervention technique-4. Reliability, standard error of measurement, and minimal detectable change were reported for only the one-leg standing test, balance evaluation systems test, brief-balance evaluation systems test, and mini-balance evaluation systems test. CONCLUSIONS: The one-leg standing test was the most frequently used physical function test for assessing postural balance in patients on dialysis. Additionally, the measurement properties of these tests remain understudied 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 | 0.012 | 0.059 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| 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".