Han Pengxi, Tang Jinyan, Wang Ximing, Su Yuwen, Li Guijie, Deng Kai
Department of Radiology, the First Affiliated Hospital of Shandong First Medical University, Jinan, China.
Department of Pediatrics, Xiangxi Autonomous Prefecture People's Hospital, Jishou, China.
Quant Imaging Med Surg. 2021 Jul;11(7):3274-3285. doi: 10.21037/qims-20-901.
This study aimed to establish a non-invasive and simple screening model of coronary atherosclerosis burden based on the associations between multiple blood parameters and total plaque score (TPS), segment-stenosis score (SSS), coronary artery disease severity (CADS) in coronary artery disease (CAD) and thus reduce unnecessary coronary angiography (CAG).
A total of 1,366 patients with suspected CAD who underwent CAG were included in this study. The clinical risk factors [age, gender, systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol (TC), high-density lipoprotein (HDL), triglyceride (TG), low-density lipoprotein (LDL), fasting plasma glucose (FPG), and glycated hemoglobin (GHB)] were collected. The presence of plaques and lumen stenosis was assessed based on CAG imaging. The TPS, SSS, and CADS were calculated, and the distribution spectrum of atherosclerotic plaques was described. Kruskal-Wallis test for multiple comparison tests was performed to analyze the differences in groups of different risk factors. The selected independent predictors were put into a multivariate logistic model, and the variables were further screened by stepwise regression to establish a screening model. Finally, the receiver operating characteristic (ROC) curve was used to evaluate the selected model's discriminant effect.
The distributions of TPS and SSS scores were both right-skewed. Among males, both TPS and SSS scores were higher than in females (χ=46.7659, P<0.0001, χ=51.6603, P<0.0001). Both TPS and SSS scores increased with age (χ=123.4456, P<0.0001, χ=123.4456, P<0.0001). For TPS, the most common position was proximal left anterior descending artery (P-LAD, 51.39%). In SSS, the P-LAD plaque was highest: 0: 48.61%, 1: 10.32%, 2: 9.15%, and 3: 31.92%. The TPS score >5, SSS score >5, and CAD >0 were valuable indicators for SBP, FPG, TG, HDL, and GHB. In the model, TPS score >5, SSS score >5, and CADS >0, the area under ROC curve (AUC) was 0.753 [95% confidence interval (CI): 0.713 to 0.789], 0.728 (95% CI: 0.687 to 0.766), and 0.756 (95% CI: 0.717 to 0.793), respectively.
The most common site of lesions was P-LAD. These models can be used as non-invasive and simple initial screening tools without CAG.
本研究旨在基于多种血液参数与冠状动脉疾病（CAD）中的总斑块评分（TPS）、节段狭窄评分（SSS）、冠状动脉疾病严重程度（CADS）之间的关联，建立一种无创且简单的冠状动脉粥样硬化负担筛查模型，从而减少不必要的冠状动脉造影（CAG）。
本研究纳入了1366例接受CAG的疑似CAD患者。收集临床危险因素[年龄、性别、收缩压（SBP）、舒张压（DBP）、总胆固醇（TC）、高密度脂蛋白（HDL）、甘油三酯（TG）、低密度脂蛋白（LDL）、空腹血糖（FPG）和糖化血红蛋白（GHB）]。基于CAG成像评估斑块和管腔狭窄的存在情况。计算TPS、SSS和CADS，并描述动脉粥样硬化斑块的分布谱。进行Kruskal-Wallis检验进行多重比较，以分析不同危险因素组之间的差异。将选定的独立预测因子纳入多变量逻辑模型，并通过逐步回归进一步筛选变量以建立筛查模型。最后，使用受试者工作特征（ROC）曲线评估所选模型的判别效果。
TPS和SSS评分的分布均为右偏态。在男性中，TPS和SSS评分均高于女性（χ=46.7659，P<0.0001，χ=51.6603，P<0.0001）。TPS和SSS评分均随年龄增加而升高（χ=123.4456，P<0.0001，χ=123.4456，P<0.0001）。对于TPS，最常见的部位是左前降支近端（P-LAD，51.39%）。在SSS中，P-LAD斑块最高：0级：48.61%，1级：10.32%，2级：9.15%，3级：31.92%。TPS评分>5、SSS评分>5和CAD>0是SBP、FPG、TG、HDL和GHB的有价值指标。在模型中，TPS评分>5、SSS评分>5和CADS>0时，ROC曲线下面积（AUC）分别为0.753[95%置信区间（CI）：0.713至0.789]、0.728（95%CI：0.687至0.766）和0.756（95%CI：0.717至0.793）。
最常见的病变部位是P-LAD。这些模型可作为无需CAG的无创且简单的初始筛查工具。
