The Impaired Balance Systems Identified by the BESTest in Older Patients With Knee Osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Balance decreases and activities of daily living (ADLs) deteriorate in older people with knee osteoarthritis (KOA); however, little is known about the systems underlying poor balance control and how those impaired systems are related to decreased ADL. OBJECTIVES: To explore which balance systems are particularly impaired and to examine the relationship between physical ADL and balance in older people with KOA. DESIGN: Case-control study. SETTING: Outpatient clinic. PARTICIPANTS: Thirty people with KOA (mean age: 75.4 years) and 30 age-matched healthy adults (mean age: 75.4 years). METHODS: The Balance Evaluation Systems Test (BESTest), consisting of 6 sections to evaluate theoretically driven balance control systems, was used for balance assessment. BESTest section scores were compared by use of the Wilcoxon rank-sum test. Pain and physical ADL in the KOA group were evaluated with the Japanese edition of the Western Ontario and McMaster Universities Osteoarthritis Index. Spearman correlation coefficients and partial rank correlation coefficients were used to investigate the relationship between physical ADL and the BESTest scores, pain, radiography findings, and body mass index. MAIN OUTCOME MEASUREMENTS: The BESTest total and section scores. RESULTS: Compared with controls, 5 of 6 BESTest section scores were significantly lower in the KOA group. Physical ADL was significantly correlated with the total BESTest score (r = -0.484, P = .007), pain (r = 0.635, P < .001), Kellgren and Lawrence grade (r = 0.601, P < .001), and body mass index (r = 0.403, P = .027). Partial rank correlation coefficients between physical ADL and the total BESTest score (r = -0.443, P = .021) or section VI-Stability in Gait (r = -0.466, P = .014) were significant after we controlled for other variables. CONCLUSIONS: Most balance systems were impaired in older people with KOA, and this impairment was associated independently with decreased physical ADL.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".