Pogosova N V, Yufereva Y M, Kachanova N P, Metelskaya V A, Koltunov I Y, Voronina V P, Mazaev A P, Arutyunov A A, Vygodin V A
National Medical Research Center for Cardiology of the Ministry of Healthcare, Moscow, Russia.
State Budgetary Institution City Polyclinic #180, Moscow, Russia.
Kardiologiia. 2020 Mar 5;60(2):75-82. doi: 10.18087/cardio.2020.2.n964.
Objective To develop a diagnostic rule for detection of patients (pts) with high probability of subclinical atherosclerosis among those with high or very high cardiovascular (CV) risk.Materials and Methods This cross-sectional study enrolled 52 pts (32 men [62 %]), aged 40 to 65 years [mean age 54.6±8.0]) with high or very high CV risk (5-9 and ≥10 % by The Systematic Coronary Risk Estimation Scale [SCORE], respectively). All participants underwent cardiac computed tomography (CT) angiography and calcium scoring. Traditional risk factors (RFs) (family history of premature CVD, smoking, overweight / obesity and abdominal obesity, hypertension, type 2 diabetes mellitus, lipids parameters (total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides) and lipids-related markers (apolipoprotein A1, apolipoprotein B, ApoB / ApoA1 ratio), biomarkers of inflammation (high-sensitivity C-reactive protein [hs CRP], fibrinogen), indicator carbohydrate metabolism (glucose), ankle-brachial index, stress-test, carotid plaques according to ultrasound were evaluated in all pts. Psychological RFs were evaluated using Hospital Anxiety and Depression Scale and DS-14 for type D personality.Results All pts were divided into 2 groups according to the CT angiography results: pts in the main group (n=21) had any non-obstructive lesions or calcium score >0, pts in the control group (n=31) had intact coronary arteries. The groups did not differ in age or gender. 26 multiple linear logistic models for any subclinical atherosclerosis were developed based on obtained diagnostic features. Taking into account R-square = 0.344 (p=0.0008), the best fitting model was follows: subclinical coronary atherosclerosis= -1.576 + 0.234 x SCORE ≥5 % + 0.541 x hs CRP >2 g / l +0.015 x heart rate (bpm) +0.311 family history of premature CVD. The developed algorithm had sensitivity of 63 % and specificity of 80 %.Conclusion The created diagnostic model diagnostic model suggests the presence of subclinical coronary atherosclerosis in patients with high / very high CV risk with a high degree of probability. This easy-to-use method can be used in routine clinical practice to improve risk stratification and management choices in high-risk pts.
目的 制定一种诊断规则，用于在心血管（CV）风险高或极高的患者中检测亚临床动脉粥样硬化可能性高的患者。
材料与方法 这项横断面研究纳入了52例患者（32例男性[62%]），年龄在40至65岁之间（平均年龄54.6±8.0岁），CV风险高或极高（分别根据系统性冠状动脉风险评估量表[SCORE]为5-9%和≥10%）。所有参与者均接受了心脏计算机断层扫描（CT）血管造影和钙化评分。评估了所有患者的传统风险因素（RFs）（早发性心血管疾病家族史、吸烟、超重/肥胖和腹型肥胖、高血压、2型糖尿病、血脂参数（总胆固醇、高密度脂蛋白胆固醇、低密度脂蛋白胆固醇、甘油三酯）和血脂相关标志物（载脂蛋白A1、载脂蛋白B、ApoB/ApoA1比值）、炎症生物标志物（高敏C反应蛋白[hs CRP]、纤维蛋白原）、碳水化合物代谢指标（葡萄糖）、踝臂指数、应激试验、根据超声检查的颈动脉斑块）。使用医院焦虑抑郁量表和D型人格的DS-14评估心理RFs。
结果 根据CT血管造影结果将所有患者分为2组：主要组（n=21）的患者有任何非阻塞性病变或钙化评分>0，对照组（n=31）的患者冠状动脉正常。两组在年龄或性别上无差异。基于获得的诊断特征建立了26个关于任何亚临床动脉粥样硬化的多元线性逻辑模型。考虑到R平方=0.344（p=0.0008），最佳拟合模型如下：亚临床冠状动脉粥样硬化=-1.576 + 0.234 x SCORE≥5% + 0.541 x hs CRP>2 g/l +0.015 x心率（bpm）+0.311 x早发性心血管疾病家族史。所开发的算法敏感性为63%，特异性为80%。
结论 所创建的诊断模型表明，CV风险高/极高的患者中存在亚临床冠状动脉粥样硬化的可能性很大。这种易于使用的方法可用于常规临床实践，以改善高危患者的风险分层和管理选择。
