Why the study?
Does a combined cut-off of EATT, CIMT, and Total cholesterol/HDL ratio accurately detect the presence of coronary artery disease?
Does a combined cut-off of EATT, CIMT, and Total cholesterol/HDL ratio accurately detect the presence of coronary artery disease?
A combined cut-off using epicardial adipose tissue thickness, carotid intima media thickness, and total cholesterol/HDL ratio provides high sensitivity and specificity for detecting coronary artery disease.
EATT and CIMT may aid early CAD detection; leaves open reliable cut-offs and clinical utility pending prospective studies.
One of the important aspect in dealing with coronary artery disease (CAD) is the ability to identify the individuals in early stage of CAD, before development of any adverse clinical event, chronic disability or death. The ability of Epicardial Adipose Tissue Thickness (EATT) and Carotid Intima Media Thickness (CIMT) to predict presence and severity of CAD. To try and establish a reliable cut-off for detecting coronary artery disease. It is a single centre, retrospective case-control study. 244 patients who underwent coronary angiogram were enrolled for the study. Echocardiographic of assessment of EATT was done by 2 cardiologists and CIMT measurement was done by experienced radiologist who were blinded to the clinical or the angiographic data. The mean EATT and CIMT in CAD and control group were 4.59 ± 1.75 and 2.38 ± 1.47 P < 0.001 and 0.97 ± 0.2 and 0.63 ± 0.18 P < 0.001, respectively. EATT cut off 3.35 mm predicted CAD with a sensitivity of 81.4% and 80.3% specificity. The CIMT cut off to predict CAD showed significant correlation (P < 0.001; OR: 19.1, 95% C.I: 6.6–55.1) with a sensitivity of 83.6% and a specificity of 80.3%. The combined cut off (EATT, CIMT and Total cholesterol/HDL ratio) showed a significantly better sensitivity of 88% and a specificity of 85.2% in its ability to predict CAD. The combined cut off could serve as an effective and useful tool for detecting CAD.
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P et al. (2018) studied this question.
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