Aims: Clinical experience suggests that atherosclerotic disease is common in individuals with coeliac disease, but epidemiological studies have had contradicting findings. To summarise the currently available evidence, we systematically reviewed and analysed observational studies of the association of coeliac disease or dermatitis herpetiformis with coronary heart disease (CHD) or stroke.
Data Synthesis: We searched for studies comparing CHD or stroke outcomes with individuals with and without coeliac disease or dermatitis herpetiformis. Three investigators independently searched electronic databases, identified relevant studies and extracted data. Study-specific results were combined in random-effects meta-analyses, and heterogeneity was quantified using the I(2) statistic and meta-regression. Twenty-one studies were included in our systematic review and 18 in the meta-analyses. For CHD, the pooled hazard ratio for incident disease was 1.05 (95% confidence interval (CI): 0.93, 1.19) and the overall standardised mortality ratio was 1.21 (0.99, 1.49). For stroke and brain haemorrhage, the corresponding estimates were 1.10 (95% CI: 1.00, 1.21) and 1.43 (0.97, 2.10), respectively. There was moderate to considerable heterogeneity among the study-specific estimates. In addition, many estimates were based on small numbers of outcomes and they had limitations in terms of adjustment for potential confounders.
Conclusion: Our meta-analyses lend some support to an association between coeliac disease and CHD or cerebrovascular disease, but the evidence base was heterogeneous and had limitations. Our systematic review highlighted a need in this area for adequately powered prospective studies with appropriate adjustment for potentially confounding factors.
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http://dx.doi.org/10.1016/j.numecd.2015.05.004 | DOI Listing |
Am J Gastroenterol
January 2025
Department of Internal Medicine and Medical Therapeutics, University of Pavia, Italy.
Introduction: Long-term prognosis of non-celiac enteropathies (NCEs) is poorly understood. We aimed to evaluate long-term outcomes and develop a prognostic score for NCEs.
Methods: NCEs patients from an international multicenter cohort (4 Italian centers,1 UK, 1 French,1 Norwegian,1 USA,1 Indian) followed-up over 30 years were enrolled.
Nat Rev Gastroenterol Hepatol
January 2025
Takeda Pharmaceuticals, Cambridge, MA, USA.
Coeliac disease is an autoimmune disease characterized by small intestinal villus atrophy and inflammation upon exposure to gluten. It has a global prevalence of approximately 1%. Although the gluten-free diet can be an effective treatment, this diet is burdensome with practical difficulties and frequent inadvertent gluten exposure.
View Article and Find Full Text PDFAm J Reprod Immunol
February 2025
Department of Gynecology and Obstetrics, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China.
Background: Observational studies suggested celiac disease (CD) possibly be a risk factor for premature ovarian failure (POF). However, causality remains unclear. And hypothyroidism and systemic lupus erythematosus may be the mediating factors.
View Article and Find Full Text PDFJ Hum Nutr Diet
February 2025
School of Life and Health Sciences, University of Roehampton, London, UK.
Introduction: A gluten-free (GF) diet, the only treatment for people living with coeliac disease (CD), is challenging, and international guidelines highlight the valuable role of healthcare professionals in enabling self-management. The study aimed to explore the acceptability of telephone and online video consultations for adults with CD.
Methods: A cross-sectional study consisting of an online and paper survey was promoted to adults with CD.
J Imaging Inform Med
January 2025
Department of Radiation Oncology, Henry Ford Health, Detroit, MI, USA.
Automatic segmentation of angiographic structures can aid in assessing vascular disease. While recent deep learning models promise automation, they lack validation on interventional angiographic data. This study investigates the feasibility of angiographic segmentation using in-context learning with the UniverSeg model, which is a cross-learning segmentation model that lacks inherent angiographic training.
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