Establishment of a nomogram prediction model for coronary artery disease risk in elderly patients with acute myocardial infarction
10.3760/cma.j.cn121430-20200604-00797
- VernacularTitle:加重老年急性心肌梗死患者冠状动脉病变风险的列线图预测模型建立
- Author:
Yanmei YANG
1
;
Dongliang YANG
;
Wentao ZHAO
;
Xuejuan HE
;
Xin WANG
;
Jiawang WANG
;
Fan LIU
;
Qinglan MENG
Author Information
1. 沧州医学高等专科学校，河北沧州 061001
- Keywords:
Elderly;
Myocardial infarction;
Coronary artery disease;
Risk factor;
Nomogram
- From:
Chinese Critical Care Medicine
2021;33(8):967-972
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To establish a nomogram model for predicting the risk of coronary artery disease in elderly patients with acute myocardial infarction (AMI).Methods:The clinical data of elderly patients with AMI who underwent coronary angiography in the department of cardiology of Cangzhou Central Hospital from July 2015 to March 2020 were analyzed, including age, gender, smoking history, underlying diseases, family history, blood pressure, left ventricular ejection fraction (LVEF), and several biochemical indicators at admission, such as total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), lipoprotein [Lp(a)], apolipoproteins (ApoA, ApoB), ApoA/B ratio, total bilirubin (TBil), direct bilirubin (DBil), indirect bilirubin (IBil), fasting blood glucose (FBG) and uric acid (UA). Patients were divided into model group (2 484 cases) and validation group (683 cases) according to the ratio of 8∶2. According to Gensini score, the model group and validation group were divided into mild lesion group (0-20 points) and severe lesion group (≥81 points). The differences of each index between different coronary lesion degree groups were compared. Lasso regression and Logistic regression were used to analyze the risk factors of aggravating coronary lesion risk in elderly patients with AMI, and then the nomogram prediction model was established for evaluation and external validation.Results:① In the model group, there were significant differences in the family history of coronary heart disease, FBG and HDL-C between the mild lesion group (411 cases) and the severe lesion group (417 cases) [family history of coronary heart disease: 3.6% vs. 7.7%, FBG (mmol/L): 5.88±1.74 vs. 6.43±2.06, HDL-C (mmol/L): 1.48±0.69 vs. 1.28±0.28, all P < 0.05]. In the validation group, there were significant differences between the mild lesion group (153 cases) and the severe lesion group [132 cases; FBG (mmol/L): 5.58±0.88 vs. 6.85±0.79, HDL-C (mmol/L): 1.59±0.32 vs. 1.16±0.21, both P < 0.05]. ② Lasso regression analysis showed that family history of coronary heart disease, FBG, and HDL-C were risk factors of coronary artery disease in elderly patients with AMI, with coefficients 0.118, 0.767, and -0.558, respectively. Logistic regression analysis showed that FBG [odds ratio ( OR) = 1.479, 95% confidence interval (95% CI) was 1.051-2.082, P = 0.025] and HDL-C ( OR = 0.386, 95% CI was 0.270-0.553, P < 0.001] were independent risk factors of coronary artery disease in elderly patients with AMI. ③ According to the rank score of FBG and HDL-C, the nomogram prediction risk model of aggravating coronary artery disease degree was established for each patient. It was concluded that the risk of coronary artery disease in elderly people with higher FBG level and (or) lower HDL-C level was significantly increased. ④ The nomogram model constructed with the model group data predicted the risk concordance index (C-index) was 0.689, and the C-index of the external validation group was 0.709. Conclusions:FBG and HDL-C are independent risk factors for aggravating coronary artery disease in elderly patients with AMI. The nomogram model of aggravating coronary artery disease in elderly patients with AMI has good predictive ability, which can provide more intuitive research methods and clinical value for preventing the aggravation of coronary artery disease in elderly patients.
