Endothelial Dysfunction and Arterial Stiffness in Patients with Inflammatory Bowel Disease: A Systematic Review and Meta-Analysis.
Hao WuMeihua XuHong HaoMichael A HillCanxia XuZhenguo LiuPublished in: Journal of clinical medicine (2022)
Population-based studies have suggested that patients with inflammatory bowel disease (IBD) might be at an increased risk for cardiovascular diseases. A meta-analysis was performed on clinical studies to evaluate endothelial function, arterial stiffness, and carotid intima-media thickness (cIMT) in patients with IBD, after searching PubMed, Embase, Cochrane library, and Web of Science databases. A random-effects model was used to allow for the pooling of studies and for determination of the overall effect. After exclusion, a total of 41 eligible studies with 2330 patients with IBD and 2032 matched controls were identified and included for the analysis. It was found that cIMT was significantly increased in patients with IBD as compared with that in matched controls (Cohen's d: 0.63; 95% CI: 0.34, 0.93; I 2 = 91.84%). The carotid-femoral pulse wave velocity was significantly higher in patients with IBD compared to that in matched controls (Cohen's d: 0.76; 95% CI: 0.54, 0.98; I 2 = 70.03%). The augmentation index was also significantly increased in patients with IBD compared to matched control subjects (Cohen's d: 0.35; 95% CI: 0.08, 0.63; I 2 = 61.37%). Brachial artery flow-mediated dilatation was significantly decreased in patients with IBD than that in matched controls (Cohen's d: -0.73; 95% CI: -1.10, -0.36; I 2 = 81.02%). Based on the meta-analysis, it was found that patients with IBD exhibit significant endothelial dysfunction, increased arterial stiffness, and cIMT. Thus, patients with IBD may benefit from aggressive risk stratification for cardiovascular diseases.
Keyphrases
- patients with inflammatory bowel disease
- ulcerative colitis
- cardiovascular disease
- blood pressure
- systematic review
- case control
- public health
- type diabetes
- coronary artery disease
- big data
- cardiovascular risk factors
- mass spectrometry
- machine learning
- optical coherence tomography
- deep learning
- artificial intelligence
- blood flow
- meta analyses
- data analysis