1. Introduction

Coronary heart disease (CHD) is a manifestation of intravascular stenosis or obstruction of the coronary arteries due to atherosclerosis or other lesions in the walls of the main coronary arteries and major branch vessels; this in turn causes inadequate or absent blood supply, resulting in myocardial ischemia and even necrosis in the corresponding regions.[1,2] In recent years, the aging population of China and the rapid transformation process of rural to urban areas has resulted in an increase in the number of patients with CHD.[3] The risk factors for CHD are numerous, with abnormal lipid levels, history of hypertension and diabetes mellitus, and long-term heavy smoking being the most frequently reported.[4–6] Central arterial pressure (CAP) is a physiological parameter based on left ventricular ejection and central arterial pulse waves; it is influenced by a combination of vascular filling and peripheral resistance and comprises central systolic pressure (CSP), diastolic pressure (CDP), and pulse pressure (CPP).[7] CSP reflects the magnitude of the left ventricular systolic afterload, and CDP determines true coronary perfusion. Several clinical trials have confirmed that central arterial hemodynamics are independently associated with hypertensive target organ damage and cardiovascular diseases.[8,9]

Thus, CAP is fundamental to the blood perfusion of vital organs, has important pathophysiological significance, and has a much higher predictive value than peripheral arterial pressure for the onset and progression of cardiovascular disease and its associated complications.[10,11] Recent studies have suggested that CAP, independent of peripheral arterial pressure, holds significant predictive value for the occurrence, development, and clinical outcomes of cardiovascular diseases, making it a crucial risk factor for cardiovascular conditions.[12,13] Roman et al found a notable increase in the cardiovascular event rate among individuals with CAP values exceeding 50 mm Hg.[14] Furthermore, a meta-analysis conducted by Vlachopoulos et al identified pulse pressure, particularly CPP, as an independent predictor of cardiovascular events and all-cause mortality.[15] Therefore, this study aimed to explore the correlation between CAP-related parameters and the severity of atherosclerotic lesions in the coronary arteries.

2. Materials and Methods 2.1. Study design and participants

A retrospective analysis was conducted using data from medical records between January 2021 and January 2022. Patients were categorized into 2 groups according to the following inclusion criteria: no CHD group: elderly patients with coronary angiography (CAG) findings suggesting no coronary lesions or < 50% coronary stenosis and diagnosed as no CHD; and CHD group:[16] patients with CHD diagnosed according to the results of CAG. The exclusion criteria were as follows: incomplete clinical data; concomitant cardiovascular diseases including congenital heart disease, large atrial septal defects, severe viral myocarditis and other myocarditis, severe heart valve disease, various types of intra-aortic coarctation, severe heart failure, and malignant arrhythmias; serious chronic disorders, such as liver, kidney, and lung organ insufficiency, serious blood-related disorders, cancer, malignancy, hyperthyroidism, and hypothyroidism; a history of trauma, surgery, or organismal infection within 3 months; cerebral infarction, cerebral hemorrhage, and other obvious cerebrovascular lesions or peripheral vascular disease within 6 months; autoimmune diseases and mental disorders; and recent administration of hormones, immune-modulating drugs, and immunosuppressive drugs. This study was approved by the Ethics Committee of the Hengyang Hospital of Traditional Chinese Medicine (no. 20220109A).

A total of 224 patients were included in this study. The degree of intravascular stenosis of the coronary arteries was evaluated according to the internal diameter method using CAG, whereby major coronary lesions or one or more lesions of one or more major branches were diagnosed as CHD. Patients with CAG results suggesting normal or < 50% coronary internal diameter stenosis were designated as CHD-free and enrolled into the non-CHD group. Patients in the CHD group were categorized into 3 different groups based on the Gensini scoring system, which assesses the severity of coronary artery lesions using CAG: the low score group with 0–30 points (n = 65), medium score group with 30–60 points (n = 44), and high score group with > 60 points (n = 35).[17] The patients were also divided into 3 groups according to the number of coronary lesions identified by CAG: single (n = 36), double (n = 38), and multiple (n = 70) coronary lesions.

2.2. Study data collection 2.2.1. General clinical data.

The following clinical data were retrospectively retrieved from patient medical records: age; sex; body mass index (BMI); patient-reported history of smoking and alcohol consumption; history of hypertension, diabetes, malignant arrhythmia, severe liver and kidney failure, and hematological system tumors; current level of glycemic control; and medication history in the past 6 months. Serology and relevant auxiliary examination indices (total cholesterol [TC], triglycerides [TG], low-density lipoprotein [LDL], high-density lipoprotein [HDL], lipoprotein a, homocysteine [HCY], and glycohemoglobin [HbA1c]) were collected, elbow venous blood was drawn after fasting for more than 12h, and relevant results were recorded. CAG results corresponding to the severity of coronary lesions were recorded, and the Gensini system was used to calculate the corresponding score for the severity of coronary lesions in each elderly patient with CHD. The results of the relevant auxiliary examination indices were uniformly provided by the laboratory department of our hospital.

2.2.2. Noninvasive CAP.

noninvasive CAP parameters were measured using the SphygmoCor pulse wave analysis system. Before the test, the subject relaxed the whole body and rested calmly for 5 minutes in a supine position with deep breathing; the right upper limb was externally rotated and abducted, and the torso was at 45°. The strongest fluctuation was first found in the right radial artery of the patient, and the instrument probe was then placed on it. A continuous radial arterial pulse wave of ≥ 12 s was recorded in real time and then converted into a central arterial pulse wave using a computerized conversion function system, from which the CSP, CDP, and CPP were deduced.

2.2.3. Selective CAG and Gensini scoring.

According to the American College of Cardiology/American Heart Association guidelines,[18] a multi-angle, multi-directional 7-position imaging approach using the Judkins method was performed via the radial or femoral artery, and 2 or more experienced physicians assessed the lesions on the resulting images. Coronary Gensini scores[19] were determined for the CHD group according to their coronary lesion sites and degree of stenosis, and scores were used for further categorization.

2.3. Statistical analysis

Data were analyzed using SPSS 22.0. Count data were expressed as n (%) and compared using the chi-square test. Continuous data were expressed as mean ± standard deviation and compared using t-tests. Correlations were analyzed using Pearson correlation coefficients, and multivariate logistic regression analysis was used for risk factor analysis. Statistical differences were considered significant at P < .05.

3. Results 3.1. Comparison of general information between the CHD and non-CHD groups

The non-CHD and CHD groups were significantly different in terms of age; history of hypertension, diabetes mellitus, and smoking; TC, TG, LDL, lipoprotein A, HCY, and HbA1c levels; CSP; CDP; and CPP (P < .05). No significant differences were observed between the 2 groups with respect to sex, BMI, or HDL levels (Table 1).

Table 1 - Comparison of general information between the 2 groups. Items Non-CHD group (n = 80) CHD group (n = 144) t/χ2 P value Gender (male/female) 56/24 92/52 0.857 .355 Age (yr) 59.24 ± 12.34 62.50 ± 9.87 2.162 .032 BMI (kg/m2) 25.36 ± 2.87 25.64 ± 3.26 0.642 .521 History of hypertension (%) 18 (22.50) 57 (39.58) 6.739 .009 History of diabetes (%) 23 (28.75) 68 (47.22) 7.275 .007 Smoking history (%) 25 (31.25) 71 (49.31) 6.846 .009 TC (mmol/L) 3.84 ± 0.56 4.25 ± 1.04 3.27 .001 TG (mmol/L) 1.12 ± 0.73 1.51 ± 0.64 4.153 <.001 HDL (mmol/L) 1.17 ± 0.57 1.05 ± 0.46 1.715 .088 LDL (mmol/L) 2.63 ± 0.82 2.96 ± 0.81 2.909 .004 Lipoprotein A 0.11 ± 0.06 0.14 ± 0.07 3.23 .014 HCY 2.23 ± 0.87 2.54 ± 0.74 2.819 .005 HbA1c (%) 5.70 ± 0.32 6.01 ± 0.41 5.844 <.001 CSP (mm Hg) 113.22 ± 10.87 119.82 ± 18.01 2.988 .003 CDP (mm Hg) 85.36 ± 7.23 81.63 ± 10.98 2.726 .007 CPP (mm Hg) 29.95 ± 8.13 38.19 ± 19.99 3.526 .001

CDP = central diastolic pressure, CPP = central pulse pressure, CSP = central systolic pressure.

3.2. Comparison of CAP parameters between single-, double-, and multi-branch lesion groups

As shown in Figure 1, CSP and CDP were not significantly different between the single-, double-, and multi-branch lesion groups (P > .05). Similarly, CPP did not differ significantly between the single- and double-branch lesion groups or between the double- and multi-branch lesion groups (P > .05). However, CPP was significantly higher in the multi-branch lesion group than in the single-branch lesion group (P < .05).

Figure 1.:

Comparison of CAP parameters between groups with different number of coronary lesions in CHD group. Note: *P < .05 compared with the single-branch lesion group. CAP = central artery pressure, CHD = coronary heart disease.

3.3. Comparison of CAP parameters between low, medium, and high Gensini score groups

CSP, CDP, and CPP were significantly higher in the high Gensini score group than in the low Gensini score group, and CSP and CPP in the high Gensini score group were significantly higher than those in the medium Gensini score group (P < .05). The CSP, CDP, and CPP of the medium Gensini score group were not significantly different from those of the low Gensini score group (P > .05) (Fig. 2).

Figure 2.:

Comparison of CAP parameters among different Gensini score groups in the CHD group. Note: *P < .05 compared with low score group; & P < .5 compared with medium score group. CAP = central artery pressure, CHD = coronary heart disease.

3.4. Correlation analysis of CAP parameters and Gensini scores

Pearson correlation analysis showed that CSP and CPP were positively correlated with the Gensini score of coronary artery lesions in patients with CHD (R = 0.407, P < .001 and R = 0.471, P < .001, respectively), whereas CDP was negatively correlated with the Gensini score of coronary artery lesions in patients with CHD (r = –0.190, P = .036) (Fig. 3).

Figure 3.:

Scatter plot of the correlation between CAP parameters and Gensini score of coronary lesions. (A) CSP; (B) CDP; (C) CPP. CAP = central artery pressure, CDP = central diastolic pressure, CPP = central pulse pressure, CSP = central systolic pressure.

3.5. Multivariate regression analysis with high Gensini scores as the dependent variable

The risk factors for severe coronary artery lesions were screened by including significant indices identified in section 3.1 in a univariate logistic regression analysis model with a high Gensini score as the dependent variable; age; history of hypertension, diabetes, and smoking; HCY, HbA1c, TC, TG, and LDL levels; CSP; CDP; and CPP were risk factors for a high Gensini score. After correcting for age, history of hypertension and smoking, HCY, HbA1c, TC, TG, and LDL, the multivariate logistic regression analysis showed that a history of diabetes (odds ratio [OR] = 2.134, 95% CI: 1.056–4.356, P = .027), CSP (OR = 1.196, 95% CI: 1.016–1.407, P = .038), CDP (OR = 1.846, 95% CI: 1.190–2.863, P = .030), and CPP (OR = 3.073, 95% CI: 1.382–6.839, P = .008) were independent risk factors for severe atherosclerotic lesions in coronary arteries (Table 2).

Table 2 - Multiple regression analysis with Gensini score high-score lesions as the dependent variable. Factors B E Wald value P value OR 95% CI History of diabetes 0.758 0.364 5.823 .027 2.134 1.056–4.356 CSP 0.179 0.083 4.236 .038 1.196 1.016–1.407 CDP 0.613 0.224 4.603 .03 1.846 1.190–2.863 CPP 1.123 0.408 7.213 .008 3.073 1.382–6.839

CDP = central diastolic pressure, CPP = central pulse pressure, CSP = central systolic pressure.

4. Discussion

CHD is a chronic disease that seriously affects quality of life. Several theories regarding the pathogenesis of CHD have been proposed; multiple factors may lead to vascular endothelial cell damage, continuous lipid infiltration, and an inflammatory response, which results in the formation of atheromatous plaques and eventually leads to continuous narrowing or even occlusion of the coronary arteries.[20,21] However, none of these theories can fully explain the formation and development of CHD. Therefore, exploring the pathogenesis of coronary artery disease is crucial for its prevention and treatment.

CAP generally refers to the systolic pressure at the root of the ascending aorta. In recent years, prospective clinical studies have shown a very close relationship between CAP and atherosclerosis.[22,23] As a CAP parameter, CPP has been shown to be an independent risk factor for the development of cardiovascular events (especially CHD) in middle-aged and elderly patients.[24] Moreover, CSP and CPP were both positively associated with the development of CHD, and CPP was superior to CSP and CDP in predicting the risk of CHD in middle-aged and elderly individuals.

The magnitude of CPP depends on the cardiac blood volume per beat, the ventricular ejection velocity, and the elasticity of the arterial wall; as the stiffness of the transmitting vessels increases with age and the effect of repetitive circulatory stress, the compliance decreases. This leads to an increase in the transmission velocity of the pulse wave in the duct, which shortens the time for the forward pressure wave to pass from the aorta and peripheral arteries to the various reflection points and back to the heart. Consequently, the reflected wave returns earlier and reaches the central artery in the systolic phase instead of the diastolic phase, thus elevating the CSP, decreasing the CDP, and increasing the CPP.[25–27] Increased CPP leads to greater strain on the arterial vasculature, which increases arterial wall tension and predisposes elastic fibers to fatigue and fracture, as well as vascular endothelial cell damage, thereby promoting or accelerating the development and progression of atherosclerosis.[28,29] The results of this study showed an increasing trend of CSP and a decreasing trend of CDP with the increase in the number of branches of coronary lesions; however, neither of these reached statistical significance, which may be related to the small number of patients in this study. In contrast, the CPP of the multi-branch lesion group was significantly higher than that of the double- and single-branch lesion groups, which is consistent with the results of Kim et al,[30] indicating that CPP is clinically important for assessing the severity of coronary lesions.

In addition, we explored the relationship between CAP and the Gensini score of coronary vascular lesions and demonstrated that CSP and CPP showed an increasing trend and CDP showed a decreasing trend with increasing Gensini scores. The CSP and CPP of the high Gensini score group were significantly higher than those of the low and medium score groups, and the CDP was significantly lower than that of the low Gensini score group. Further correlation analysis showed that the Gensini score was positively associated with CSP and CPP and negatively correlated with CDP. This suggests that CAP parameters reflect the stiffness of hair vessels and provide a good assessment of the severity of coronary artery disease. Logistic regression analysis confirmed that elevated CSP and CPP and decreased CDP were independent risk factors for a high Gensini score, and CAP parameters were good indicators for assessing coronary lesion severity.

In summary, noninvasive central artery-related indices, such as CSP, CDP, and CPP, were independently correlated with and predictors of the severity of coronary lesions in patients with CHD. These parameters can thus be used to improve the clinical diagnosis rate of CHD and guide clinical diagnosis and treatment.

Author contributions

Conceptualization: Fang Fang.

Data curation: Fang Fang.

Formal analysis: Fang Fang.

Funding acquisition: Fang Fang, Ying Huang.

Investigation: Fang Fang, Ying Huang, Zhiyong Liu.

Methodology: Fang Fang, Ying Huang.

Project administration: Zhiyong Liu.

Software: Xuemei Liu, Xiaoyun Huang.

Resources: Xiaoyun Huang.

Supervision: Xiaoyun Huang.

Validation: Xiaoyun Huang.

Visualization: Xiaoyun Huang.

Writing – original draft: Xiaoyun Huang.

Writing – review & editing: Xiaoyun Huang.

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