Fast Parameters Estimation in Medication Efficacy Assessment Model for Heart Failure Treatment

• Published in: Computational and mathematical methods in medicine 2012-01, Vol.2012 (2012), p.1-9
• Main Authors: Ren, Yinzi, Fu, Xiao, Pan, Qing, Lin, Chengyu, Yang, Guiqiu, Li, Li, Gong, Shijin, Cai, Guolong, Yan, Jing, Ning, Gangmin
• Format: Article
• Language: English
• Subjects: Algorithms; Angiotensin-Converting Enzyme Inhibitors - pharmacology; Blood Pressure; Cardiology - methods; Computer Simulation; Decision Making; Decision Support Systems, Clinical; Enalapril - pharmacology; Heart Failure - drug therapy; Hemodynamics; Humans; Lisinopril - pharmacology; Models, Statistical; Models, Theoretical; Regression Analysis; Signal Processing, Computer-Assisted; Treatment Failure; Treatment Outcome; Vascular Resistance
• ISSN: 1748-670X; 1748-6718; 1748-6718
• DOI: 10.1155/2012/608637

Introduction. Heart failure (HF) is a common and potentially fatal condition. Cardiovascular research has focused on medical therapy for HF. Theoretical modelling could enable simulation and evaluation of the effectiveness of medications. Furthermore, the models could also help predict patients’ cardiac response to the treatment which will be valuable for clinical decision-making. Methods. This study presents a fast parameters estimation algorithm for constructing a cardiovascular model for medicine evaluation. The outcome of HF treatment is assessed by hemodynamic parameters and a comprehensive index furnished by the model. Angiotensin-converting enzyme inhibitors (ACEIs) were used as a model drug in this study. Results. Our simulation results showed different treatment responses to enalapril and lisinopril, which are both ACEI drugs. A dose-effect was also observed in the model simulation. Conclusions. Our results agreed well with the findings from clinical trials and previous literature, suggesting the validity of the model.