FACTORS AFFECTING THE FALL RISK AND ASSISTIVE WALKING DEVICE USE OF PATIENTS WITH KNEE OSTEOARTHRITIS
Bibliographic record
Abstract
Objective In this study, we aimed to investigate the risk of falling in patients with advanced-stage knee osteoarthritis and the rates of assistive walking device use, and the factors affecting the use of these devices in such patients. Materials and Methods In this prospective, cross-sectional, observational study, we included 79 patients (72 females, 7 males; median age 60 years; range, 40 to 75) with advancedstage knee osteoarthritis. We assessed the balance status of the patients with the Berg Balance Scale, pain levels with the Numeric Rating Scale, selfreported disability scores with the Western Ontario and McMaster Universities Osteoarthritis Index. Our primary outcome measurements were balance status, and assistive walking device usage rates of the patients. Secondary outcome measures were age, obesity, disease severity, pain levels, disability scores, and fall history. Results According to Berg Balance Scale, 40 (50.6 %) patients had a risk of fall. Assistive walking device usage rates were 21.5 % and 42.5 % for the total of the patients and for the patients at risk of falling, respectively. There was a statistically significant difference in assistive walking device use between those at risk of falling and those without (P
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".