药效仿真支持的心衰治疗模型研究

发布时间：2018-01-27 01:45

本文关键词： 心力衰竭指南结构化多目标优化快速参数估计药效仿真　出处：《浙江大学》2012年硕士论文　论文类型：学位论文

【摘要】：在临床治疗中,心力衰竭的控制率很低,死亡率居高不下。造成以上问题的原因之一就是缺乏有效实施的心力衰竭疾病治疗规范和优化治疗方案。本课题旨在运用工程建模技术,建立药效仿真支持的心力衰竭疾病治疗模型：将心衰临床指南与多目标优化决策模型相结合构造心衰决策模型,并通过药效仿真模型预测治疗效果,从而实现心力衰竭疾病的有效治疗控制。课题具体实现的工作内容如下： 1)对临床数据进行分析,筛选出与心力衰竭密切相关的特征参数。 2)对心衰指南和临床经验进行知识梳理,采用结构化流程表征。 3)运用多目标优化模型对心衰状况细化评估,并据此给予相应治疗方案：首先利用聚类分析方法将生理参数划分为六个子类,采用隶属函数获取生理参数的模糊隶属度,依据最小二乘估计原则和最大熵原理确定各参数的权系数,进而对各类生理参数的模糊隶属度加权求和产生一级指标值,最后根据六个一级指标所反应的心衰各层面状况给予相应的药物治疗。 4)对药物治疗效果进行仿真预测。基于心血管建模技术和相关文献报道,建立了药效仿真模型和ACEI类药物作用曲线。依据药效曲线和患者基础信息,即可以通过模型仿真方法得到某药物作用下的血流动力学预测情况。研究中建立了一种快速参数估计算法,通过可测的血压参数估计模型参数值,进而加快了整个药效仿真的效率。 5)将得到的模型应用于临床病例试验,验证模型效果。对临床病例的测试结果表明：心力衰竭疾病治疗模型能全面的评估心衰状况,依据心力衰竭各层面具体的严重程度给予相应的治疗方案,与实际给药的吻合度达到91%,满足临床需求,是一种有效的个性化的治疗方案。本课题建立的心力衰竭疾病治疗模型为心力衰竭治疗提供了一种新思路,具有良好的应用前景。
[Abstract]:In clinical treatment, the control rate of heart failure is very low. Mortality remains high. One of the causes of these problems is the lack of effective implementation of heart failure treatment standards and optimization of treatment programs. The purpose of this project is to use engineering modeling technology. To establish the model of heart failure treatment supported by pharmacodynamics simulation: combining the clinical guidelines of heart failure with the multi-objective optimization decision model, the decision model of heart failure was constructed, and the therapeutic effect was predicted by the simulation model of drug efficacy. In order to achieve effective treatment and control of heart failure disease. 1) the clinical data were analyzed and the characteristic parameters closely related to heart failure were screened out. 2) combing the knowledge of heart failure guidelines and clinical experience, using structured process representation. 3) the multi-objective optimization model was used to evaluate the state of heart failure, and the corresponding treatment plan was given. Firstly, the physiological parameters were divided into six subgroups by cluster analysis. The membership function is used to obtain the fuzzy membership degree of physiological parameters, and the weight coefficient of each parameter is determined according to the least square estimation principle and the maximum entropy principle. Furthermore, the weighted sum of fuzzy membership degree of various physiological parameters produces the first-order index value. Finally, the corresponding drug treatment is given according to the state of heart failure at each level reflected by the six first-class indexes. Based on cardiovascular modeling technology and related literature, the simulation model of drug efficacy and the action curve of ACEI drugs were established. According to the drug efficacy curve and patient basic information. In this paper, a fast parameter estimation algorithm is established to estimate the model parameters through measurable blood pressure parameters. Furthermore, the efficiency of the whole drug effect simulation is accelerated. 5) the model was applied to clinical trials to verify the effectiveness of the model. The results of clinical cases showed that: heart failure treatment model can comprehensively assess the state of heart failure, according to the specific severity of each level of heart failure to give the corresponding treatment. It is an effective and individualized treatment scheme to meet the clinical needs. The model of heart failure treatment provided a new idea for the treatment of heart failure, and has a good application prospect.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：R312

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