Abstract
This study aimed to analyze the risk factors of adverse cardiovascular events (ACVEs) in elderly patients with coronary heart disease (CHD) after percutaneous coronary intervention (PCI) using the intravascular ultrasound (IVUS) images based on the deep learning of convolutional neural networks (CNNs). This study included 90 patients with coronary heart disease as the research object. All the patients were randomly divided into a control group (group C) and an experimental group (group E), and all were treated with PCI. The patients in group C were diagnosed by angiography, and patients in group E underwent IVUS examination under deep learning. The levels of blood lipids and inflammatory factors between the two groups before and after PCI were compared, and the sensitivity, specificity, and positive predictive value (PPV) were recorded. Compared with angiography diagnosis, ultrasound diagnosis based on deep learning algorithm had higher sensitivity (92.3% vs. 81.4%), specificity (90.1% vs. 88.6%), and PPV (94.8% vs. 75.3%) ( P < 0.05 ). Compared with group C, patients in group E had a higher narrowest lesion diameter (2.54 ± 0.18 mm vs. 2.21 ± 0.19 mm) and detection rate of eccentric plaques (80.1% vs. 45.3%) ( P < 0.05 ). High-density lipoprotein cholesterol (HDL-C) after PCI in the two groups was significantly higher than that before surgery, while low-density lipoprotein cholesterol (LDL-C), tumor necrosis factor (TNF), and C-reactive protein (CRP) were significantly lower than those before surgery, and the difference was statistically significant ( P < 0.05 ). In short, the ultrasonic detection method based on deep learning algorithm has high sensitivity, specificity, and accuracy for CHD detection; PCI can improve the patient’s blood lipid level, relieve the patient’s inflammation, and reduce the occurrence of ACVEs in the patient.
Highlights
Introduction e expansion ofcoronary heart disease (CHD) is coronary atherosclerotic heart disease
All the patients were randomly divided into a control group and an experimental group, and all were treated with percutaneous coronary intervention (PCI). e patients in group C were diagnosed by angiography, and patients in group E underwent intravascular ultrasound (IVUS) examination under deep learning. e levels of blood lipids and inflammatory factors between the two groups before and after PCI were compared, and the sensitivity, specificity, and positive predictive value (PPV) were recorded
Patients in group C were diagnosed by angiography; those in group E were diagnosed by IVUS under deep learning. e study had been approved by the Ethics Committee of the hospital, and the patients and their families had understood the contents and methods of the study and agreed to sign the corresponding informed consent forms
Summary
It is caused by the accumulation of fat in the arterial wall, and the calcium-containing substances in the arterial wall gradually accumulate as the accumulated fat increases and deposits. Calcium-containing substance deposition in the inner wall of blood vessels to form atherosclerosis process, medically known as atherosclerosis [2]. E main incidence of atherosclerosis occurs in adult men over 30 or patients with dyslipidemia, hypertension, diabetes, and severe obesity. It has a high incidence in China, and the incidence increases with age, and the incidence in women is relatively low [4]
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