QUALITY OF LIFE OF ELDERLY WOMEN WITH KNEE OSTEOARTHRITIS
Bibliographic record
Abstract
Elderly women who had the symptoms of knee osteoarthritis are reported to have a higher, more pain, and loss of knee function related to quality of life (27.5%) compared to elderly males (21.8%). The purpose of this study was to examine the quality of life of elderly women with knee osteoarthritis. Method, this study is a cross sectional research design with a linear regression analysis method. The population were all elderly women with osteoarthritis (age> 45 years) in General Hospital of Bekasi as many as 80 elderly women were taken by consecutive sampling. Data was collected by interviews with a questionnaire. The Variables analyzed demographic characteristics such as age, body mass index (BMI), education, exercise routine, a history of osteoarthritis in their family, employment status, and the use of walking aids to determines about factors that associated with osteoarthritis index through the instrument of WOMAC (the Western Ontario and McMaster Universities Osteoarthritis Index) as a measuring instrument joint pain and disability of osteoarthritis patients,we correlate the osteoarthritis index to the quality of life through a questionnaire WHOQOL-OLD. The average score obtained is 2.71 in the Standardized Total Score (range 1-5) in the WHOQOL-OLD guide, which means they have a poor quality of life with the correlation value obtained from the relationship of the Osteoratritis Index with quality of life is r = - 0.601 (p value <0.001). Elderly women with knee osteoarthritis are in a position of poor quality of life. Keywords: elderly, osteoarthritis, hospital
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".