Differences in Cardiovascular Risk Prediction Scoring in Individuals with Autoimmune Rheumatic Diseases

Autor: Banerjee, Srikanta, Patel, Raxit
Rok vydání: 2016
DOI: 10.5281/zenodo.3559004
Popis: Individuals with autoimmune rheumatic diseases (ARD) have a higher risk of cardiovascular disease than the general population. However, the classic 10-year cardiovascular risk scoring systems have not adequately incorporated this heightened risk into the prediction equations. The growing number of peer-reviewed articles in the professional literature is an indication of how individuals in the scholastic arena are expanding in the awareness of the link between ARDs and cardiovascular disease (CVD). By dissemination of best practices, other health care practitioners can learn about the specific needs of this specific subgroup of patients with ARD. The purpose of the literature review conducted here was to describe the status of the peer-reviewed literature pertaining to ARD versus CVD and raise awareness about what variables need to be included to adequately include the ARD subgroup. A literature search was conducted using the CINAHL, Medline, and PubMed databases. Inclusion criteria included publication date from January 1, 1995 through July 31, 2015, written in the English language, and a focus on cardiovascular disease as the primary discipline. Cardiovascular risk score was searched as an overarching discipline; articles focused on sub-disciplines or other health professions disciplines were excluded. The search resulted in 265 articles. Each of the authors reviewed the abstracts for all articles and read full articles when necessary. The result was 13 articles that were then considered in depth. The articles were categorized according to their primary theme: risk scoring method (N=6); link between ARD and CVD (N=3); physician knowledge about ARD and CVD link (N=2); limitations of scoring system (N=2). Year of publication and journal were also examined. The results of the literature search lead to several observations about how the peer-reviewed literature has been used to date and how it could be used to create more robust scoring methods on predicting CVD.
Databáze: OpenAIRE