人工智能辅助分析冠状动脉钙化积分与视网膜动脉硬化的相关性
作者:
作者单位:

(东部战区总医院健康医学科,江苏省南京市 210018)

作者简介:

张锐,硕士,住院医师,研究方向为眼底病,E-mail:773566477@qq.com。

基金项目:

中国健康促进基金会项目(D064032);江苏省老年健康科研项目(LKM2023021)


Artificial intelligence assisted analysis of the correlation between coronary calcification score and retinal arteriosclerosis
Author:
Affiliation:

Department of Health Medicine, General Hospital of Eastern Theater Command, Nanjing, Jiangsu 210018, China)

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    摘要:

    目的]应用人工智能(AI)辅助分析软件探究冠状动脉钙化积分(CACS)与视网膜动脉硬化的相关性。 [方法]选择2022年度于东部战区总医院健康医学科体检的511例体检者为研究对象,根据Agatston积分分为冠状动脉钙化(CAC)组(>0分,261例)和无CAC组(=0分,250例),采用独立样本t检验及卡方检验对比两组体检者的临床资料;根据视网膜动脉硬化情况分为视网膜动脉正常组、视网膜动脉弹性减弱组和视网膜动脉硬化组,采用Kruskal-Wallis H检验对比三组间的CACS及视网膜微血管量化指标;采用Spearman相关分析CAC等级与临床指标及视网膜微血管量化指标的相关性;采用二元Logistic回归分析视网膜动脉硬化情况与CAC的相关性。 [结果]CAC组的年龄、吸烟人数、腰围、臀围、腰臀比(WHR)、体质指数(BMI)、收缩压、血肌酐(SCr)、血尿酸(BUA)、尿素氮(BUN)、空腹血糖(FBG)、糖化血红蛋白(HbA1c)及甘油三酯(TG)较无CAC组高,差异有统计学意义(均P<0.05);视网膜动脉正常组、视网膜动脉弹性减弱组和视网膜动脉硬化组的 总CACS、视网膜动静脉比(AVR)差异有统计学意义(均P<0.05),视网膜中央动脉当量(CRAE)、视网膜中央静脉当量(CRVE)差异无统计学意义(均P>0.05);CACS等级、总CACS与年龄、吸烟情况、腰围、臀围、WHR、BMI、收缩压、BUN、SCr、BUA、同型半胱氨酸(Hcy)、FBG、餐后2 h血糖(2h PBG)、HbA1c、TG呈正相关(均P<0.05),与性别、总胆固醇(TC)、高密度脂蛋白胆固醇(HDLC)呈负相关(均P<0.05),与舒张压、低密度脂蛋白胆固醇(LDLC)无相关性(均P>0.05);视网膜动脉硬化程度与年龄、腰围、臀围、WHR、BMI、收缩压、舒张压、左主干(LM)、左前降支(LAD)、左回旋支(LCX)和右冠状动脉(RAC)钙化积分、总CACS、BUN、FBG、2h PBG、HbA1c、TG呈正相关(均P<0.05),与TC、HDLC、LDLC呈负相关(均P<0.05),与性别、吸烟情况、脉搏、SCr、BUA、Hcy无相关性(均P>0.05);CAC等级与AVR呈负相关(r=-0.166,P<0.05),与视网膜动脉硬化等级呈正相关(r=0.199,P<0.05),与CRAE、CRVE无明显相关性(均P>0.05);CAC与视网膜动脉硬化存在相关性(P<0.001)。在校正了年龄、性别、吸烟情况、WHR、BMI、收缩压、FBG、SCr、BUA、BUN、HDLC因素后,CAC与视网膜动脉硬化的相关性依然存在(P=0.048)。 [结论]AI辅助分析CAC与视网膜血管直径、视网膜动脉硬化程度相关,对冠心病风险评估有积极作用。

    Abstract:

    Aim To explore the correlation between coronary artery calcification score (CACS) and retinal arteriosclerosis using artificial intelligence assisted analysis software. Methods 511 examinees who underwent physical examinations in the Department of Health Medicine of General Hospital of Eastern Theater Command in 2022 were selected as the research subjects, they were divided into a coronary artery calcification (CAC) group (>0,1 cases) and a non CAC group (=0,0 cases) based on the Agatston score, the clinical data of the two groups of examinees were compared using independent sample t-tests and chi square tests. According to the condition of retinal arteriosclerosis, the examinees were divided into three groups:normal retinal artery group, weakened retinal artery elasticity group and retinal arteriosclerosis group. Kruskal Wallis H test was used to compare the quantitative indicators of CACS and retinal microvasculature among the three groups; Spearman correlation analysis was used to study the correlation between CAC grading and clinical indicators, as well as quantitative indicators of retinal microvasculature; binary Logistic regression was used to analyze the correlation between retinal arteriosclerosis and CAC. Results The age, number of smokers, waist circumference, hip circumference, waist to hip ratio (WHR), body mass index (BMI), systolic blood pressure, serum creatinine (SCr), blood uric acid (BUA), blood urea nitrogen (BUN), fasting blood glucose (FBG), glycosylated hemoglobin (HbA1c), triglyceride (TG) in the CAC group were higher than those in the non CAC group, and the difference was statistically significant (all P<0.05). There were statistically significant differences in total CACS and AVR among the three groups of normal retina, weakened retinal artery elasticity and retinal arteriosclerosis (all P<0.05), while there was no significant difference in CRAE and CRVE (all P>0.05). The CACS level and total score were positively correlated with age, smoking status, waist circumference, hip circumference, WHR, BMI, systolic blood pressure, BUN, SCr, BUA, homocysteine (Hcy), FBG, 2 hour postprandial blood glucose (2h PBG), HbA1c, TG (all P<0.05), and negatively correlated with gender, total cholesterol (TC), high density lipoprotein cholesterol (HDLC; all P<0.05), but not with diastolic blood pressure and low density lipoprotein cholesterol (LDLC; all P>0.05). The degree of retinal arteriosclerosis was positively correlated with age, waist circumference, hip circumference, WHR, BMI, systolic blood pressure, diastolic blood pressure, calcification scores of left main artery (LM), left anterior descending artery (LAD), left circumflex artery (LCX), right coronary artery (RCA), total CACS, BUN, FBG, 2h PBG, HbA1c and TG (all P<0.05), and negatively correlated with TC, HDLC and LDLC (all P<0.05), but not with gender, smoking status, pulse, SCr, BUA and Hcy (all P>0.05). CAC level was negatively correlated with AVR (r=-0.166, P<0.05), and positively correlated with retinal arteriosclerosis level (r=0.199, P<0.05), but not significantly correlated with CRAE and CRVE (all P>0.05). There was a correlation between CAC and retinal arteriosclerosis (P<0.001). After adjusting for age, gender, smoking status, WHR, BMI, systolic blood pressure, FBG, SCr, BUA, BUN, and HDLC factors, the correlation between CAC and retinal arteriosclerosis still exists (P=0.048). Conclusion AI assisted analysis of retinal vascular diameter and degree of retinal arteriosclerosis is related to CAC, which plays a positive role in risk assessment of atherosclerotic heart disease.

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张锐,周颖,钟勇.人工智能辅助分析冠状动脉钙化积分与视网膜动脉硬化的相关性[J].中国动脉硬化杂志,2024,32(8):690~696.

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  • 收稿日期:2023-10-17
  • 最后修改日期:2023-11-30
  • 在线发布日期: 2024-08-21