Co-morbidity and cardio-metabolic risk factors in patients with osteoarthrosis
Bibliographic record
Abstract
Aim. To study co-morbidity prevalence, as well as metabolic effects on atherosclerosis progression and cardiovascular risk, in patients with osteoarthrosis (OA).Material and methods. In total, 83 patients with confirmed OA diagnosis (American College of Rheumatology criteria). The age of participants was 45-70 years (mean age 58,35+12,5 years), and OA duration was 1-24 years (mean duration 9,8±4,7 years). The examination included pain syndrome assessment with visual analog scale (VAS), calculation of WOMAC (Western Ontario and McMaster Universities) index and body mass index (BMI), measurement of waist and hip circumference (WC, HC) and WC/HC ratio. Joint ultrasound examination (Phillips HD-11) was used to assess periarticular tissue status and visualise articular cartilage and bone surfaces. Serum levels of C-reactive protein (CRP) and interleukin-6 (IL-6) were measured by immune-enzyme method.Results. Obesity was diagnosed in 51 OA patients (67,64%). These participants demonstrated higher synovitis prevalence, higher values of algo-functional indices, and elevated IL-6 and CRP levels, as well as higher frequency of cardiovascular disease and cardiovascular events in anamnesis.Conclusion. In OA patients, obesity was more prevalent. Compared to those with BMI<30 kg/m2, obese individuals with OA showed higher levels of triglycerides and CRP, lower concentration of high-density lipoproteins, and higher prevalence of Caro index <0,33 (insulin resistance marker). Therefore, the combination of OA and obesity was characterised by clustering of cardiovascular risk factors.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".