Relationship between the Serum Cartilage Oligomeric Matrix Protein Concentration against Degree of Knee Osteoarthritis Pain in Elderly Patients at the Public Health Service Clinic
Bibliographic record
Abstract
This study aims to assess the relationship between the serum concentration of Cartilage Oligomeric Matrix Protein (COMP) and the degree of osteoarthritis pain in elderly patients. The study was conducted at a public health service clinic, Faculty of Medicine, Syarif Hidayatullah State Islamic University (UIN) Jakarta, Indonesia. The indexes used to assess patients with OA in the knee are the Western Ontario and Mcmaster University Osteoarthritis Index (WOMAC). Sampling using the cross-sectional technique as many as 146 respondents with elderly knee OA patients. First, a physical and radiological examination is performed to confirm the diagnosis of knee OA. Second, measuring the degree of pain WOMAC. Third, the measurement of the COMP serum concentration used the ELISA test. Based on the Spearman correlation test, it was found that there was a statistically significant relationship between the COMP serum concentration and the degree of knee OA pain with the WOMAC scale in the elderly (p = 0.012). From the results of the study, it is suggested that patients maintain effective health management. Elderly patients come to community health service clinics to carry out routine/periodic checks to reduce pain. The main reason is that there is no truly effective and consistent method to prevent and cure this disease, especially for patients with age-related risk factors, excessive joint load, and a history of joint injury. AO also has an impact on a person's psychosocial well-being. These findings contribute to the study of the risk of degenerative diseases and the use of biomarkers with a level of evidence that will be more valid in the future.
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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) | 0.002 | 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".