Assessment of cardiovascular risk factors in patients with idiopathic inflammatory myopathies: a systematic review.
Jucier Gonçalves JúniorSamuel Katsuyuki ShinjoPublished in: Clinical rheumatology (2023)
We performed a systematic review of cardiovascular risk factors in idiopathic inflammatory myopathies (IIMs) and their cardiovascular outcomes, including acute coronary syndrome and stroke. A qualitative systematic review was conducted from January 1956 to December 2022 according to the PRISMA protocol using three electronic databases: PubMed, Web of Science, and Scopus. The studies were analyzed based on the following eligibility criteria: at least one combination of the terms described in the search strategy appeared in the title, written in English, Portuguese, or Spanish, and addressed risk factors for cardiovascular diseases in IIMs. Brief reports, reviews, papers addressing juvenile IIMs, congress proceedings, monographs, and dissertations were excluded. Twenty articles were included. According to the literature, most patients with IIMs are middle-aged North American or Asian women, with dyslipidemia and hypertension. The prevalence of the cardiovascular risk factors was generally low in IIMs, but with a high incidence of acute myocardial infarction. Further theoretical and prospective studies are needed to define the actual impact of each variable (e.g., hypertension, diabetes, smoking, alcoholism, obesity, and dyslipidemia) on the cardiovascular risk of patients with IIMs.
Keyphrases
- cardiovascular risk factors
- cardiovascular disease
- systematic review
- meta analyses
- metabolic syndrome
- acute myocardial infarction
- blood pressure
- acute coronary syndrome
- middle aged
- type diabetes
- percutaneous coronary intervention
- risk factors
- randomized controlled trial
- case control
- oxidative stress
- insulin resistance
- weight loss
- atrial fibrillation
- public health
- antiplatelet therapy
- glycemic control
- adipose tissue
- high fat diet induced
- left ventricular
- coronary artery disease
- emergency department
- machine learning
- body mass index
- cardiovascular events
- heart failure
- brain injury
- artificial intelligence