title: The relationship between cardiovascular disease risk prediction scores and vascular function and morphology in rheumatoid arthritis.
abstract: OBJECTIVE
  Patients with rheumatoid arthritis (RA) are at an increased risk for cardiovascular disease (CVD) resulting from impairments in vascular function and morphology. CVD risk prediction scores can identify patients at high risk of CVD, but little is known about whether they relate with assessments of vascular function and morphology which provide early indication of subclinical atherosclerosis. The objective of the present study was to examine the relationship of several CVD risk prediction scores with assessments of vascular function and morphology in patients with RA.
  
  
  METHODS
  Framingham risk score, Systematic Coronary Risk Evaluation for total cholesterol and ratio of total cholesterol to high-density lipoprotein, as well as Reynolds Risk Score, and QRISK2 were calculated in 201 RA patients (155 females, median (25th to 75th percentile) age: 61 (53-67)) who were examined at baseline (2006). The European League Against Rheumatism (EULAR) multiplication factor was also applied to the algorithms. At a 6-year follow-up (2012) visit the patients underwent assessments of microvascular and macrovascular endothelium-dependent and endothelium-independent function, along with assessment of carotid atherosclerosis.
  
  
  RESULTS
  All five CVD risk prediction scores measured at baseline were significantly correlated with vascular function and morphology at follow-up. Application of the EULAR multiplication factor did not change any of the associations.
  
  
  CONCLUSIONS
  Five commonly used CVD risk prediction scores associate with assessments of vascular function and morphology over a 6-year follow-up period suggesting that these CVD risk prediction scores may also reflect subclinical atherosclerotic changes.
authors.affiliation: Department of Rheumatology, Dudley Group of Hospitals NHS Trust, Russells Hall Hospital, Dudley, UK. aamer.sandoo@dgh.nhs.uk.
authors.forename: Aamer
authors.initials: A
authors.lastname: Sandoo
authors.forename: Neil
authors.initials: N
authors.lastname: Chanchlani
authors.forename: James
authors.initials: J
authors.lastname: Hodson
authors.forename: Jacqueline P
authors.initials: JP
authors.lastname: Smith
authors.forename: Karen M
authors.initials: KM
authors.lastname: Douglas
authors.forename: George D
authors.initials: GD
authors.lastname: Kitas
mesh_terms: D000368:Aged; D000465:Algorithms; D001172:Arthritis, Rheumatoid / Q000097:blood / Q000150:complications* / Q000175:diagnosis; D015415:Biomarkers / Q000097:blood; D002318:Cardiovascular Diseases / Q000097:blood / Q000175:diagnosis / Q000209:etiology* / Q000503:physiopathology; D002340:Carotid Artery Diseases / Q000175:diagnosis / Q000209:etiology; D003661:Decision Support Techniques; D004730:Endothelium, Vascular / Q000503:physiopathology*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011379:Prognosis; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors
chemical_list: D015415:Biomarkers