An overview of the quality of life of Knee osteoarthritis patients at the Surakarta Orthopedic Hospital
Bibliographic record
Abstract
ABSTRACT Background: Osteoarthritis is a chronic degenerative disease of the joints. Functional limitations experienced by people with knee osteoarthritis are related to changes in quality of life. Knee Osteoarthritis needs to be assessed as a whole which includes several domains of quality of life, namely the domains of pain, stiffness and physical function. This study was conducted to determine the correlation between pain intensity and quality of life in patients with knee osteoarthritis. Methods: a quantitative study using an analytic observational method with a cross-sectional approach. Population of 70 patients, a sample of 33 patients. The research was conducted in October 2020 at the Orthopedic Hospital in Surakarta City, Central Java, Indonesia. Data were collected by direct interviews to assess pain intensity based on the Numeric Rating Scale (NRS) and assess quality of life based on the Western Ontario McMaster Universities Osteoarthritis Index (WOMAC) questionnaire. Normality test using Sapiro Wilk because the data is normaly distributed. Hipotesis test using Pearson correlation. Results: Age range of patients with knee osteoarthritis mostly occurred at the age of 56-60 years, women had a greater frequency of experiencing knee osteoarthritis with a frequency of 78.8%, the most incidence of knee osteoarthritis was experienced by patients with normal BMI, namely 54.5%, The results of the Pearson correlation test showed a significance value of Sig. (2-tailed) is 0.000149 <0.05, which means that there is a significant correlation between the variables between pain and quality of life. Has a positive relationship and strong relationship strength (r = 0.613). Conclusion: There is a significant correlation between pain intensity and quality of life in patients with osteoarthritis
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".