IJCS | Volume 31, Nº5, September / October 2018

493 Azevedo et al. ASCVD risk estimator to estimate CVD risk Int J Cardiovasc Sci. 2018;31(5)492-498 Original Article Several risk scores and algorithms have been developed to estimate the severity of CVD, such as the Framingham score. This instrument estimates the 10-year risk of AMI or death for coronary disease in individuals with no history of clinical atherosclerosis and identifies those at high and low risk. 4,5 With the development of portable technology and new mobile phone apps, combined with the increase in information access, the ASCVD Risk Estimator was created. This instrument follows the American Heart Association andAmerican College of Cardiology (AHA/ ACC) guideline (2013) on the assessment of cardiovascular risk and the 2013 ACC/AHA Cardiovascular Risk Guideline on the treatment of dyslipidemia to reduce the cardiovascular risk in adults. 6,7 Considering the relevance of the prevention of CVD risk factors and high rates of mortality, this study aimed to evaluate cardiovascular risk in patients hospitalized in the internal medicinewards of Gaffrée e Guinle University Hospital (HUGG) using theASCVDRiskEstimator, classify them into high, moderate and high risk, as well as identify associated (modifiable and non-modifiable) risk factors. Methods This was an observational, prospective, cross-sectional study conducted at the HUGG from March 2015 to January 2016. Eligible patients were aged between 40 and 79 of both sexes, hospitalized in the internal medicine wards of the HUGG, with their hospital admission report attached to the medical record, and laboratory blood test results including lipid profile before admission or from 2 to 5 days of hospitalization. Patients admitted for cardiovascular conditions such as AMI, ischemic or hemorrhagic stroke, and thromboembolismand its complications, patientswith total cholesterol lower than 130 mg/dL and HDL lower than 20 mg/dL (due to the score calculation restrictions), and patients with LDL higher than 190 mg/dL and previously diagnosed atherosclerotic disease (due to the high / confirmed risk of atherosclerotic disease) were excluded. All inclusion and exclusion criteria followed the ASCVD Risk Estimator recommendations for estimation of the 10-year risk. Patients’ medical records were examined during the 11-month period of the study. The variables necessary for risk estimation were collected – age, sex, race/ethnicity, chronic diseases (DM and HBP) being treated, systolic BP (SBP) at admission, smoking habits, total and HDL cholesterol levels, cause of admission, weight and height, regularly usedmedications for DM and HBP, and family history (FamH) of CVD. Data collection was started after ethical approval was obtained in Plataforma Brasil , the national integrated database of study projects involving human beings. Weekly visits were made to the internal medicine wards for review of the medical records. Data were weekly recorded and updated in Excel spreadsheets, separated by ward. The number of individuals who were not included in the study was added to the total number of admissions and the reason for exclusion registered for further analysis. For risk classification, each patient’s data were entered in the fields of the ASCVD Risk Estimator (Figure 1). Patients were considered at high risk if they had an estimated 10-year risk ≥ 20%, at moderate risk if they had an estimated 10-year risk > 10% and < 20%, and at low risk if they had an estimated 10-year risk ≤ 10%, following the AHA/ACC criteria. Patients were considered hypertensive and diabetic if they were under medication for these conditions, and dyslipidemic if they showed LDL levels > 160 mg/dL and/or HDL< 40 mg/dL. During this analysis, we also identified the main factor that may be related to high risk, including sex, age, comorbidities (HBP, DM, dyslipidemia), smoking, FamH of CVD. Patient’s 10-year risk with optimal risk factors was also calculated; these factors included total cholesterol values of 170 mg/dL, HDL of 50 mg/dL and SBP of 110 mmHg in non-hypertensive patients, non- diabetic patients and non-smokers. Results are expressed as absolute values and percentages. Statistical analysis was performed by chi- square test using the GraphPad Instat 3 software; p-value, relative risk and confidence interval were analyzed. The study received no external funding. Results A total of 339 medical records were reviewed in the period from March 2015 to January 2016; 267 (78.8%) were excluded considering the inclusion and exclusion criteria (Graph 1). Seventy-two patients were included, 35 men and 37 women. Thirty-five patients were aged between 40 and 59 years and 37 between 60 and 79 years.