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Diagnostic Capabilities of 64 Slice CT Coronography Compared to Classic in Coronary Disease Detection
INTRODUCTION: Cardiovascular disease, among which the most common is coronary disease of the hearth are the main cause of death at middle aged persons in the majority of European countries. Percent of cardiovascular disease in overall mortality among our population is even more than 50%. Up to 55 ye...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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AVICENA
2013
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3804482/ https://www.ncbi.nlm.nih.gov/pubmed/24167394 http://dx.doi.org/10.5455/aim.2013.21.208-210 |
Sumario: | INTRODUCTION: Cardiovascular disease, among which the most common is coronary disease of the hearth are the main cause of death at middle aged persons in the majority of European countries. Percent of cardiovascular disease in overall mortality among our population is even more than 50%. Up to 55 years of live myocardial infarction is by 5-6 times more common among men, and up to age of 75 years that difference decreases to 2.5 times. GOAL: The goal of this study is to determine the diagnostic value of 64 slices computerized tomography in detection of coronary disease compared to classic, invasive coronography. MATERIAL AND METHODS: Study included 50 patients, of both genders, at average age of 60 years. Patients underwent CT coronography as well as classic coronography. RESULTS: Our research prove that the sensitivity of MSCT coronography 92% with positive predictive value of 86%. Mayor difference was in the analysis of CX artery in the evaluation of significant and non-significant stenosis in application of these two methods. During the analysis of LAD and RCA artery there was no statistically significant difference in findings of these two methods. CONCLUSION: CT coronography is non-invasive, comfortable and reliable method in coronary disease diagnostics. Thanks to its high sensitivity and PPV it enables reliable exclusion of coronary disease and takes significant place in a cardiovascular diseases diagnostic algorithm. |
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