The association between chronic venous disease and knee osteoarthritis.
Bibliographic record
Abstract
OBJECTIVE: Chronic venous disease (CVD) and knee osteoarthritis (KOA) are two common diseases in the elderly. Both share common risk factors, such as age, sex, and obesity, and are believed to be associated with inflammatory conditions and venous stasis. However, studies of the association between CVD and KOA are limited, especially in the elderly. To investigate the association between CVD and KOA and their effects on pain and functional status in the elderly at the Rheumatology Clinic of University Medical Center Ho Chi Minh City (HCMC). PATIENTS AND METHODS: This cross-sectional study included 222 elderly patients (aged ≥60 years) at the Rheumatology Clinic of University Medical Center HCMC from December 2019 to June 2020, including 167 with and 55 without KOA. Patient data were collected for both groups, including demographics, symptoms, clinical signs, and diagnostic tests for KOA and CVD, including knee radiographs and duplex scanning of the lower extremity veins. RESULTS: CVD was a common comorbidity among elderly patients with KOA (73.65% vs. 58.18%; p = 0.030). CVD symptoms did not differ significantly between patients with and without KOA. After adjusting for age, sex, body mass index, and some comorbid conditions, the differences in CVD incidence between the groups remained significant (odds ratio = 2.46, 95% confidence interval: 1.20-5.06; p = 0.014). Visual Analog Scale and Western Ontario and McMaster Universities Osteoarthritis Index pain scores were higher in elderly patients with KOA and CVD. CONCLUSIONS: CVD is common in elderly patients with KOA. While age, sex, and weight are risk factors for both conditions, there is an independent association between them. Patients comorbid with KOA and CVD have more pain and limited functional status.
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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 | 0.001 |
| 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) | 0.003 | 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".