参考文献/References:
[1] American Diabetes Association Professional Practice Committee.10.Cardiovascular disease and risk management:standards of medical care in diabetes2022[J].Diabetes Care, 2022, 45(Suppl 1):S144S174.DOI: 10.2337/dc22S010.
[2] 白颖,丛佳林,程淑莉,等.急性心肌梗死患者中糖尿病人群的临床特点及随访研究[J].中华流行病学杂志,2019,40(6):692-696.DOI:10.3760/cma.j.issn.0254-6450.2019.06.017.
[3] Hecht HS,Cronin P,Blaha MJ,et al.2016 SCCT/STR guidelines for coronary artery calcium scoring of noncontrast noncardiac chest CT scans:a report of the Society of Cardiovascular Computed Tomography and Society of Thoracic Radiology[J].J Cardiovasc Comput Tomogr,2017,11(1):74-84.DOI:10.1016/j.jcct.2016.11.003.
[4] Cademartiri F,Maffei E,Palumbo A,et al.Coronary calcium score and computed tomography coronary angiography in high-risk asymptomatic subjects:assessment of diagnostic accuracy and prevalence of non-obstructive coronary artery disease[J].Eur Radiol,2010,20(4):846-854.DOI:10.1007/s00330-009-1612-2.
[5] Dzaye O,Dudum R,Mirbolouk M,et al.Validation of the Coronary Artery Calcium Data and Reporting System(CAC-DRS):Dual importance of CAC score and CAC distribution from the Coronary Artery Calcium(CAC)consortium[J].J Cardiovasc Comput Tomogr,2020,14(1):12-17.DOI:10.1016/j.jcct.2019.03.011.
[6] Detrano R,Guerci A,Carr J,et al.Coronary calcium as a predictor of coronary events in four racial or ethnic groups[J].N Engl J Med,2008,358(13):1336-1345.DOI:10.1056/NEJMoa072100.
[7] Knuuti J,Ballo H,Juarez-Orozco LE,et al.The performance of non-invasive tests to rule-in and rule-out significant coronary artery stenosis in patients with stable angina:a meta-analysis focused on post-test disease probability[J].Eur Heart J,2018,39(35):3322-3330.DOI:10.1093/eurheartj/ehy267.
[8] Beller E,Meinel FG,Schoeppe F,et al.Predictive value of coronary computed tomography angiography in asymptomatic individuals with diabetes mellitus:systematic review and meta-analysis[J].J Cardiovasc Comput Tomogr,2018,12(4):320-328.DOI:10.1016/j.jcct.2018.04.002.
[9] Zhang HW,Jin JL,Cao YX,et al.Association of diabetes mellitus with clinical outcomes in patients with different coronary artery stenosis[J].Cardiovasc Diabetol,2021,20(1):214.DOI:10.1186/s12933-021-01403-6.
[10] Sheng Z,Zhou P,Liu C,et al.Relationships of coronary culprit-plaque characteristics with duration of diabetes mellitus in acute myocardial infarction:an intravascular optical coherence tomography study[J].Cardiovasc Diabetol,2019,18(1):136.DOI:10.1186/s12933-019-0944-8.
[11] Andreini D,Conte E,Mushtaq S,et al.Plaque assessment by coronary CT angiography may predict cardiac events in high risk and very high risk diabetic patients:a long-term follow-up study[J].Nutr Metab Cardiovasc Dis,2022,32(3):586-595.DOI:10.1016/j.numecd.2021.11.013.
[12] Oikonomou EK,Marwan M,Desai MY,et al.Non-invasive detection of coronary inflammation using computed tomography and prediction of residual cardiovascular risk(the CRISP CT study):a post-hoc analysis of prospective outcome data[J].Lancet,2018,392(10151):929-939.DOI:10.1016/s0140-6736(18)31114-0.
[13] Ichikawa K,Miyoshi T,Osawa K,et al.High pericoronary adipose tissue attenuation on computed tomography angiography predicts cardiovascular events in patients with type 2 diabetes mellitus:post-hoc analysis from a prospective cohort study[J].Cardiovasc Diabetol,2022,21(1):44.DOI:10.1186/s12933-022-01478-9.
[14] Mancio J,Azevedo D,Saraiva F,et al.Epicardial adipose tissue volume assessed by computed tomography and coronary artery disease:a systematic review and meta-analysis[J].Eur Heart J Cardiovasc Imaging,2018,19(5):490-497.DOI:10.1093/ehjci/jex314.
[15] Archer JM,Raggi P,Amin SB,et al.Season and clinical factors influence epicardial adipose tissue attenuation measurement on computed tomography and may hamper its utilization as a risk marker[J].Atherosclerosis,2021,321:8-13.DOI:10.1016/j.atherosclerosis.2021.01.025.
[16] Svanteson M,Holte KB,Haig Y,et al.Coronary plaque characteristics and epicardial fat tissue in long term survivors of type 1 diabetes identified by coronary computed tomography angiography[J].Cardiovasc Diabetol,2019,18(1):58.DOI:10.1186/s12933-019-0861-x.
[17] 中华医学会放射学分会质量控制与安全管理专业委员会,江苏省医学会放射学分会智能影像与质量安全学组.冠状动脉CT血流储备分数应用中国专家建议[J].中华放射学杂志,2020,54(10):925-933.DOI:10.3760/cma.j.cn112149-20191108-00896.
[18] Celeng C,Leiner T,Maurovich-Horvat P,et al.Anatomical and functional computed tomography for diagnosing hemodynamically significant coronary artery disease:a meta-analysis[J].JACC Cardiovasc Imaging,2019,12(7 Pt 2):1316-1325.DOI:10.1016/j.jcmg.2018.07.022.
[19] Patel MR,Nørgaard BL,Fairbairn TA,et al.1-Year impact on medical practice and clinical outcomes of FFRCT:the ADVANCE registry[J].JACC Cardiovasc Imaging,2020,13(1 Pt 1):97-105.DOI:10.1016/j.jcmg.2019.03.003.
[20] Kim KH,Doh JH,Koo BK,et al.A novel noninvasive technology for treatment planning using virtual coronary stenting and computed tomography-derived computed fractional flow reserve[J].JACC Cardiovasc Interv,2014,7(1):72-78.DOI:10.1016/j.jcin.2013.05.024.
[21] Nous FMA,Coenen A,Boersma E,et al.Comparison of the diagnostic performance of coronary computed tomography angiography-derived fractional flow reserve in patients with versus without diabetes mellitus(from the MACHINE Consortium)[J].Am J Cardiol,2019,123(4):537-543.DOI:10.1016/j.amjcard.2018.11.024.
[22] Xue Y,Zheng MW,Hou Y,et al.Influence of diabetes mellitus on the diagnostic performance of machine learning-based coronary CT angiography-derived fractional flow reserve:a multicenter study[J].Eur Radiol,2022,32(6):3778-3789.DOI:10.1007/s00330-021-08468-7.
[23] Kitabata H,Leipsic J,Patel MR,et al.Incidence and predictors of lesion-specific ischemia by FFRCT:Learnings from the international ADVANCE registry[J].J Cardiovasc Comput Tomogr,2018,12(2):95-100.DOI:10.1016/j.jcct.2018.01.008.
[24] Tomizawa N,Fujino Y,Kamitani M,et al.Longer diabetes duration reduces myocardial blood flow in remote myocardium assessed by dynamic myocardial CT perfusion[J].J Diabetes Complications,2018,32(6):609-615.DOI:10.1016/j.jdiacomp.2018.03.003.
[25] 中华医学会内分泌学分会,中国成人2型糖尿病降压治疗目标研究工作组.2型糖尿病早期大血管病变无创性检查的中国专家共识[J].中华内分泌代谢杂志,2022,38(6):465-474.DOI:10.3760/cma.j.cn311282-20220518-00321.
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