The relationship between arterial stiffness index and coronary heart disease and its severity

We selected 933 patients with suspected CHD who were hospitalized in the Department of Cardiology, Affiliated Hospital of Yangzhou University from January 2019 to December 2020, finally, 726 patients were selected. Among these patients, patients with AMI mainly come from emergency department, and other patients mainly come from cardiology outpatient department. The exclusion criteria are as follows: 1. Severe liver, kidney and pancreatic diseases; 2. Chronic wasting diseases and malignant tumors; 3. Frequent ectopic arrhythmias; 4. Those who do not cooperate with the inspection. All the subjects underwent coronary angiography based on the requirements of the American Heart College (ACC)/American Heart Association (AHA) coronary angiography guidelines. We mainly observed the lesions of left anterior descending (LAD) branch, left circumflex (LCX) branch, right coronary artery (RCA) and their main branches [9], as shown in Fig. 1a. The severity of coronary artery disease was evaluated according to the results of the examination [10]. According to the number of diseased branches of coronary artery (degree of stenosis ≥ 50%), all the subjects were assigned into three groups, including the control group (no vascular with stenosis degree ≥ 50%), and the single-vessel disease group (one vessel with stenosis degree ≥ 50%), multi-vessel disease group (two or more blood vessels with stenosis degree ≥ 50%). In addition, according to the results of color Doppler echocardiography, electrocardiogram, myocardial enzyme spectrum, and patient's clinical manifestations, the subjects were assigned into four groups, including the control group (coronary heart disease was excluded), the SA group, the UA group, and the AMI group. All the subjects signed the informed consent form for clinical research. This research was approved by the Ethics Committee of Yangzhou University.

Related risk factors such as gender, weight, age, smoking history, diabetes history, hypertension history, etc. were obtained from all the subjects through questionnaire surveys according to protocols [9].

Venous blood samples were obtained in the early morning after admission. By using the fully automatic biochemical analyser (OLYMPUS AU2700, JAPAN), related blood biochemical indicators were detected, including cholesterol (TC, mmol/L), triglycerides (TG, mmol/L), high-density lipoprotein cholesterol (HDL-C, mmol/L), low-density cholesterol lipoprotein (LDL-C, mmol/L), lipoprotein(a)[LP(a), mmol/L], uric acid (UA, mmol/L), etc. All tests were performed at the Clinical Laboratory Center of the Affiliated Hospital of Yangzhou University. The laboratory quality control standards were met in this test.

Basic principles Our study was to record the pressure shock wave when blood pressure was measured by oscillometry with an arterial meter. In the process of blood pressure measurement, the inflation pressure in the cuff gradually decreased after reaching the predetermined maximum value, and the arterial blood flow pressure wave detected in the cuff showed regular changes. When the cuff pressure was higher than the systolic pressure, the brachial artery blood flow was completely blocked. The brachial artery above the cuff expanded due to cardiac contraction, so the cuff pressure showed small fluctuations. When the cuff pressure was lower than the systolic pressure, with the gradual opening of the brachial artery below the cuff, the blood flow increased gradually, and the cuff pressure fluctuation amplitude recorded also increased gradually. When the cuff pressure was equal to the average pressure, the pressure fluctuation in the cuff reached the maximum. After that, the cuff pressure decreased gradually, and the pressure fluctuation decreased accordingly. When the cuff pressure was equal to the diastolic pressure, the pressure fluctuation amplitude decreased significantly. After that, as the blood flow was completely unblocked, and the pressure fluctuation amplitude in the cuff tensed to be stable. The ASI value was defined as the width value of the pressure fluctuation diagram corresponding to 80% of the peak height of the maximum pressure wave multiplied by 10, We also designed the basic schematic diagram, as shown in Fig. 1b.

Medcalc software was used to draw the ROC. The area under the curve (AUC) was compared and the cut-off value of ASI evaluated, which were used to determine the occurrence and severity of CHD. The severity of CHD was mainly judged by comparing single-vessel lesions with multiple-vessel lesions.

In this study, SPSS 22.0 (Chicago, IL, USA) statistical software package was used for data analysis. For the data conforming to the normal distribution, mean ± standard deviation was used. One-way analysis of variance or independent sample t test was applied to compare the differences between groups. The chi-square test was used in analyzing the proportional data. For the data not conforming to the normal distribution, the median and interquartile range was used. Univariate and multivariate regression analysis was used to evaluate the relationship between the severity of CHD and ASI value. The P value was two-sided, and P ≤ 0.05 was considered statistically significant.

As shown in Table 1, according to the number of diseased branches of coronary artery, all the participants were assigned into three groups. Compared with the control group, the participants were elder in single-vessel stenosis group and the multi-vessel stenosis group. In addition, hypertension, FBG, and ASI levels were significantly elevated in the single-vessel stenosis group, and there was no significant difference in other aspects. In the multi-vessel stenosis group, the levels of LDL-C, Lp(a), URIC, FBG, ASI were significantly increased, and there was no significant difference in other aspects. Compared with the single-vessel stenosis group, age, hypertension severity, Lp(a), LDL-C, URIC, and ASI were remarkably increased in the multiple-vessel disease group. After adjusting for baseline data such as male, age, BMI, smoking, hypertension, diabetes, HDL-C, LDL-C, TC, TG, Lp(a), URIC, and FBG, there was still an independent correlation between ASI level and the severity of coronary artery disease, with an odd ratio (OR) of 1.031 (multi-vessel stenosis group vs control group, 95% confidence interval (CI) 1.023–1.040, P < 0.05).

According to the severity of clinical manifestations, all the participants were assigned into four groups (Table 2). Compared with the control group, FBG and ASI levels were significantly elevated in the SA group. In the UA group, age, hypertension, URIC, FBG, and ASI etc. were remarkably increased. Age, hypertension levels, TG, FBG, ASI, etc. were dramatically higher in the AMI group. Compared with the SA group, age, h hypertension, URIC, ASI in the UA group were significantly increased. Age, hypertension, TG, and ASI were remarkably elevated in the AMI group. Compared with the UA group, BMI, TG, etc. were significantly increased in the AMI group, but there was no significant difference in ASI. After adjusting for baseline data such as male, age, BMI, smoking, hypertension, diabetes, HDL-C, LDL-C, TC, TG, Lp(a), URIC, and FBG, there was still an independent correlation between ASI level and the severity of clinical manifestations, with odd ratio (OR) of 1.029 (AMI group vs control group, 95% confidence interval (CI) 1.020–1.038, P < 0.05).

ROC analysis was used to determine the role of ASI in diagnosing CHD and assessing its severity (Fig. 2). The areas under the curve (AUC) in Fig. 2a and b was 0.795 and 0.668, respectively. The sensitivity and specificity of ASI were 71.0% and 85.4% in diagnosing CHD. The sensitivity and specificity of ASI were 72.1% and 57.9% in predicting the severity of CHD.