Analyzing the History of Falls in Patients with Severe Knee Osteoarthritis
Bibliographic record
Abstract
Background: One out of three adults over the age of 65 years and one out of two over the age of 80 falls annually. Fall risk increases for older adults with severe knee osteoarthritis, a matter that should be further researched. The main purpose of this study was to investigate the history of falls including frequency, mechanism and location of falls, activity during falling and injuries sustained from falls examining at the same time their physical status. The secondary purpose was to determine the effect of age, gender, chronic diseases, social environment, pain elsewhere in the body and components of health related quality of life such as pain, stiffness, physical function, and dynamic stability on falls frequency in older adults aged 65 years and older with severe knee osteoarthritis. Methods: An observational longitudinal study was conducted on 68 patients (11 males and 57 females) scheduled for total knee replacement due to severe knee osteoarthritis (grade 3 or 4) and knee pain lasting at least one year or more. Patients were person-ally interviewed for fall history and asked to complete self-administered questionnaires, such as the 36-item Short Form Health Survey (SF-36) and the Western Ontario and McMaster Universities Arthritis Index (WOMAC), and physical performance test was performed. Results: The frequency of falls was 63.2 % for the past year. The majority of falls took place during walking (89.23%). The main cause of falling was stumbling (41.54%). There was a high rate of injurious falling (29.3%). The time patients needed to complete the physical performance test implied the presence of disability and frailty. The high rates of fall risk, the high disability levels, and
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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 | 0.003 |
| 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 | 0.000 |
| 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".