Vascular Pathology and Osteoarthritis: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: Vascular pathology (changes in blood vessels) and osteoarthritis (OA) are both common chronic conditions associated with aging and obesity, but whether vascular pathology is a risk factor for OA is unclear. The aim of this study was to systematically review the evidence for an association between vascular pathology and risk of joint-specific OA. METHODS: Scopus, Ovid Medline, and EMBASE were searched from inception to February 2019. MeSH terms and keywords were used to identify studies examining the association between vascular pathology and OA. Two reviewers independently extracted the data and assessed the methodological quality. Qualitative evidence synthesis was performed. RESULTS: Fifteen studies with high (n = 3), fair (n = 3), or low (n = 9) quality were included. Features of vascular pathology included atherosclerosis, vascular stiffness, and endothelial dysfunction in different vascular beds. There was evidence for an association between vascular pathology and risk of hand OA in women but not men, and between vascular pathology and risk of knee OA in both men and women. Only 2 studies examined hip OA showing no association between vascular pathology and risk of hip OA. CONCLUSION: There is evidence suggesting an association between vascular pathology and risk of hand and knee OA, with a potential causal relationship for knee OA. Based on the limited evidence, it is hard to conclude an association for hip OA. Further stronger evidence is needed to determine whether there is a causal relationship.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".