title: Can retinal changes predict coronary artery disease in elderly hypertensive patients presenting with angina?
abstract: BACKGROUND
  The prevalence of coronary artery disease (CAD) has been increasing in India, and so is the population of elderly patients with hypertension. In the predominantly resource-poor setting prevailing in India, this study is an effort to analyze the accuracy of retinal changes in predicting CAD among a cohort of elderly patients with hypertension presenting to the emergency department with angina.
  
  
  METHODS
  A total of 72 elderly patients with hypertension older than 65 years presenting to the emergency department with acute angina were studied. Optic fundi were assessed for retinopathy after pupillary dilatation, which were photographed. All patients underwent coronary angiogram, and the presence or absence of CAD was determined.
  
  
  RESULTS
  Mean +/- SD age of the participants was 72.95 +/- 6.51 years, and there were 39 men (54.2%) and 33 women (45.8%). Prevalence of CAD and retinopathy was 40.8% and 30.6%, respectively. Coronary artery disease showed a strong association with retinopathy (P < .0001). Male sex (P = .035), microalbuminuria (P = .025), and increased high-sensitivity C-reactive protein (P = .001) were identified as risk factors for CAD. Tests of accuracy for retinopathy as a predictor of CAD showed a likelihood ratio of a positive test and likelihood ratio of a negative test of 3.92 and 0.52, respectively. Area under the receiver operating characteristics curve was 70.6%.
  
  
  CONCLUSIONS
  Prevalence of CAD (40.8%) and retinopathy (30.6%) was quite high in our cohort of elderly patients with hypertension. Retinal changes of any grade have a moderate accuracy in predicting CAD and, hence, may be used as an early screening tool in a resource poor setting.
authors.affiliation: General Medicine Department, Sri Ramachandra University, Chennai, Tamilnadu 600087, India. drpssghanshyam@yahoo.co.in
authors.forename: Ghanshyam Palamaner Subash
authors.initials: GP
authors.lastname: Shantha
authors.forename: Yadav
authors.initials: Y
authors.lastname: Srinivasan
authors.forename: Anita A
authors.initials: AA
authors.lastname: Kumar
authors.forename: Shihas
authors.initials: S
authors.lastname: Salim
authors.forename: Suhas
authors.initials: S
authors.lastname: Prabakhar
authors.forename: Anish George
authors.initials: AG
authors.lastname: Rajan
authors.forename: T R
authors.initials: TR
authors.lastname: Muralidharan
mesh_terms: D000367:Age Factors; D000368:Aged; D000787:Angina Pectoris / Q000209:etiology*; D016009:Chi-Square Distribution; D016001:Confidence Intervals; D003324:Coronary Artery Disease / Q000150:complications*; D004562:Electrocardiography; D005260:Female; D006801:Humans; D006973:Hypertension / Q000150:complications*; D016013:Likelihood Functions; D016015:Logistic Models; D008297:Male; D016017:Odds Ratio; D012372:ROC Curve; D012164:Retinal Diseases / Q000150:complications*; D012737:Sex Factors; D012907:Smoking / Q000009:adverse effects; D013997:Time Factors