Systemic sclerosis and risk of cardiovascular disease
Bibliographic record
Abstract
BACKGROUND: Systemic sclerosis (SSc) is an autoimmune disorder leading to extensive fibrosis and microvascular injury. Macrovascular disease is well documented in other autoimmune rheumatic diseases such as systemic lupus erythematosus and rheumatoid arthritis. However, the link is unclear between SSc and macrovascular disease, particularly atherosclerotic cardiovascular disease (CVD). This meta-analysis aimed to investigate the association between SSc and CVD. METHODS: A thorough literature search was conducted in the Cochrane, Embase, Medline, and PubMed to identify all cohort studies comparing the risk of CVD with and without SSc. The pooled hazard ratios (HRs) with 95% confidence intervals (CIs) of cardiovascular end points were calculated. The risk of bias of included studies was assessed by the Newcastle-Ottawa scale. RESULTS: Seven cohort studies with a total of 14,813 study participants were included. In a comparison of SSc patients versus non-SSc controls, the pooled HR for cardiovascular disease was 2.36 (95% CI 1.97-2.81); for peripheral vascular disease was 5.27 (95%CI 4.27-6.51); for myocardial infarction was 2.36 (95% CI 1.71-3.25); and for stroke was 1.52 (95% CI 1.18-1.96). CONCLUSION: This meta-analysis revealed that SSc was associated with an increased risk of CVD. Clinicians who manage patients with SSc should be aware of the increased cardiovascular burden and undertake preventive measures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".