Vasoactive Drug Therapy and Clinical Nursing of Patients with Cardiovascular Disease. (21st September 2022)

• Record Type: Journal Article
• Authors: Li, Menglin; Xu, Meixiang; Feng, Minfang; Ren, Lingyan
• Other Names: Mishra Sandip K. Academic Editor.
• Is Part Of: Contrast media & molecular imaging. Volume 2022(2022)
• Publication Date: 2022-09-21
• Subjects: Diagnostic imaging -- Periodicals; Magnetic resonance imaging -- Periodicals; Contrast media (Diagnostic imaging) -- Periodicals; Contrast Media -- Periodicals; Diagnostic Imaging -- Periodicals; Substances de contraste -- Périodiques; Diagnostics moléculaires -- Périodiques; Imagerie médicale; Substance de contraste; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.0754
• DOI: 10.1155/2022/5659513
• Languages: English
• ISSNs: 1555-4309

Abstract

Abstract : Cardiovascular disease (CVD) is a common human disease with a large number of patients. Vasoactive drugs have a good effect on the contraction and expansion of blood vessels, which can provide certain help for the management of cardiovascular diseases. However, the clinical care of cardiovascular disease has always been based on the superficial resistance level of body fat, weight, and so on, which is unfavorable for the real recovery of patients with cardiovascular disease. This article aims to quantitatively evaluate the effects of clinical care based on vasoactive drug therapy and intrinsic factors of cardiovascular disease. For the treatment of vasoactive drugs, this paper selects the principle of action of the adrenal hormone to judge and analyze the expansion and contraction of the cardiovascular disease. For the clinical nursing of patients with cardiovascular disease, based on multivariate logistic regression, this paper selects internal factors such as age and blood pressure to model the nursing effect. Experiments have shown that the logistic regression model established in this paper can evaluate well the recovery effect of patients with cardiovascular disease. The AUC value of the model reached around 0.9. This showed that the clinical care of patients with cardiovascular disease can not only rationally judge the recovery effect through the model but also adjust the physical and mental conditions of patients with cardiovascular disease according to the coefficients of the model to achieve the best recovery effect.