Osteoarthritis, mobility-related comorbidities and mortality: an overview of meta-analyses
Bibliographic record
Abstract
Aims: The objective of this review was to examine the relationship between osteoarthritis (OA) and mobility-related comorbidities, specifically diabetes mellitus (DM) and cardiovascular disease (CVD). It also investigated the relationship between OA and mortality. Methods: An overview of meta-analyses was conducted by performing two targeted searches from inception to June 2020. The association between OA and (i) DM or CVD ( via PubMed and Embase); and (ii) mortality ( via PubMed) was investigated. Meta-analyses were selected if they included studies that examined adults with OA at any site and reported associations between OA and DM, CVD, or mortality. Evidence was synthesized qualitatively. Results: Six meta-analyses met inclusion criteria. One meta-analysis of 20 studies demonstrated a statistically significant association between OA and DM, with pooled odds ratio of 1.41 (95% confidence interval: 1.21, 1.65; n = 1,040,175 patients). One meta-analysis of 15 studies demonstrated significantly increased risk of CVD among OA patients, with a pooled risk ratio of 1.24 (1.12, 1.37, n = 358,944 patients). Stratified by type of CVD, OA was shown to be associated with increased heart failure (HF) and ischemic heart disease (IHD) and reduced transient ischemic attack (TIA). There was no association reported for stroke or myocardial infarction (MI). Three meta-analyses did not find a significant association between OA (any site) and all-cause mortality. However, OA was found to be significantly associated with cardiovascular-related death across two meta-analyses. Conclusion: The identified meta-analyses reported significantly increased risk of both DM and CVD (particularly, HF and IHD) among OA patients. It was not possible to confirm consistent directional or causal relationships. OA was found to be associated with increased mortality, but mostly in relation to CVD-related mortality, suggesting that further study is warranted in this area.
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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 | 0.018 | 0.039 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.040 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".