Epicardial Fat and Coronary Vulnerability
Author:
Affiliation:
1. University of Medicine , Pharmacy, Science and Technology , Târgu Mureş , Romania
Publisher
Walter de Gruyter GmbH
Subject
General Earth and Planetary Sciences,General Environmental Science
Link
https://www.sciendo.com/pdf/10.2478/jim-2019-0026
Reference29 articles.
1. 1. Oikonomou EK, Williams MC, Kotanidis CP, et al. A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography. Eur Heart J. 2019;pii:ehz592.10.1093/eurheartj/ehz592
2. 2. Timmis A, Townsend N, Gale C, et al. ESC Scientific Document Group. European Society of Cardiology: cardiovascular disease statistics 2017. Eur Heart J. 2018;39:508-579.10.1093/eurheartj/ehx628
3. 3. Mathers CD, Loncar D. Projections of Global Mortality and Burden of Disease from 2002 to 2030. PLoS Med. 2006;3:e442.10.1371/journal.pmed.0030442
4. 4. Reed GW, Rossi JE, Cannon CP. Acute myocardial infarction. Lancet. 2017;389197-210.10.1016/S0140-6736(16)30677-8
5. 5. Stefanadis C, Antoniou C, Tsiachris D, Pietri P. Coronary Atherosclerotic Vulnerable Plaque: Current Perspectives. J Am Heart Assoc. 2017;6 e005543.10.1161/JAHA.117.005543
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