Vascular endothelial dysfunction in pediatric rheumatic diseases: a systematic review and meta-analysis
Bibliographic record
Abstract
Objectives Endothelial dysfunction is associated with increased cardiovascular risk in individuals with autoimmune diseases. This systematic review and meta-analysis included studies assessing endothelial function with functional methods in children with rheumatic diseases versus controls.Methods Literature search involved PubMed and Scopus databases (from inception to February 2024) and manual reference screening. Studies assessing endothelial function by all available functional methods were eligible. Study quality was evaluated via Newcastle–Ottawa scale.Results Twenty-four studies (880 children with rheumatic diseases, 784 controls) were included in meta-analysis. Pooled analysis showed significantly impaired endothelial function in patients versus controls (SMD: −0.74, 95%CI −1.10 to −0.39) but with high heterogeneity (I2 = 91%, p < 0.001); sensitivity analysis including only high-quality studies confirmed this finding (SMD: −0.83, 95%CI −1.20 to −0.46). In subgroup analyses according to type of rheumatic disease, significantly impaired endothelial function was showed for patients with juvenile idiopathic arthritis (SMD: −1.05, 95%CI −1.84 to −0.25), vasculitis (SMD: −0.74, 95%CI −1.11 to −0.37) and juvenile systemic sclerosis (SMD −2.48, 95%CI −4.34 to −0.61).Conclusions Children with rheumatic diseases show impaired endothelial function. Future studies are needed to elucidate whether endothelial dysfunction is involved in high cardiovascular risk of these patients.PROSPERO registration number CRD42023413799
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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 | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.033 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".