Assessment of Risk of Falls in Elderly Patients with Osteoarthritis of the Knee and Low Back Pain
Bibliographic record
Abstract
This study aimed identify which groups of elderly are at higher risk of falls, with osteoarthritis (OA), low back pain or both conditions.29 elderly were distributed in three groups: OA of the Knee (OAK), Low Back Pain (LBP) and the two events concomitantly (OL).Evaluation tools applied were: Mini Mental State Examination (MMSE), Visual Analogue Scale (VAS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Roland Morris Functional Performance Questionnaire, Gait Speed (GS), Timed Get Up and Go Test (TGUGT) and Berg Balance Scale (BBS).No differences were found in the three groups for assessment by GS, TGUGT and BBS instruments.A significative difference was found by RMQ in groups LPB and OL, WOMAC found difference in pain domain between groups OL and OAK and VAS analysis showed significative difference between group OL to the others groups.No significative difference was found between groups by the assessment of 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".