ABSTRACT
BACKGROUND: Risk stratification assessment of patients with non-ST elevation acute coronary syndrome (NSTE ACS) plays an important role in optimal management and defines the patient's prognosis. This study aimed to evaluate the ability of CHA2DS2-VASc-HSF score (comprising of the components of the CHA2DS2-VASc score with a male instead of female sex category, hyperlipidemia, smoking, and family history of coronary artery disease respectively) to predict the severity and complexity of CAD and its efficacy in stratification for major adverse cardiovascular events (MACE) in patients with NSTE ACS without known atrial fibrillation. METHODS: This study included 200 patients (males 72.5%, mean age 55.8 ± 10.1 years) who were admitted with NSTE ACS. CHA2DS2-VASC-HSF score was calculated on admission. Patients were classified into three groups according to their CHA2DS2-VASC-HSF score: low score group (< 2; 29 patients), intermediate score group (2-4; 83 patients), and high score group (≥ 5; 88 patients). Coronary angiography was conducted and the Syntax score (SS) was calculated. Clinical follow-up at 6 months of admission for the development of MACE was recorded. RESULTS: SS was significantly high in the high CHA2DS2-VASc-HSF score group compared with low and intermediate score groups. CHA2DS2-VASc-HSF score had a significant positive strong correlation with syntax score (r = 0.64, P < 0.001). Smoking, vascular disease, hyperlipidemia, and CHA2DS2-VASc-HSF score were independent predictors of high SS. For the prediction of severe and complex CAD, CHA2DS2-VASc-HSF score had a good predictive power at a cut-off value ≥ 5 with a sensitivity of 86% and specificity of 65%. Hypertension, vascular disease, high SS, and CHA2DS2-VASc-HSF score were independent predictors of MACE. CHA2DS2-VASC-HSF score ≥ 4 was identified as an effective cut-off point for the development of MACE with 94% sensitivity and 70% specificity. CONCLUSIONS: CHA2DS2-VASC-HSF score is proposed to be a simple bedside score that could be used for the prediction of the severity and complexity of CAD as well as a risk stratification tool for the development of MACE in NSTE ACS patients.
