高血压病心脏功能超声数据模型的初步研究

发布时间：2018-05-17 05:02

本文选题：数据挖掘 + 心脏功能　；参考：《皖南医学院》2014年硕士论文

【摘要】：目的：利用数据挖掘技术对高血压病患者的临床基本信息及心功能常规超声测量指标进行挖掘，揭示出影响高血压病心脏功能的影响因素及特征性指标，揭示正常人及高血压病心脏功能的特征及变化规律或趋势。方法：选择2013年2月至2014年2月来我院行检查的高血压患者和正常健康人，采用高档彩色多普勒超声显像仪，按照统一规范的检查和测量方法获取心脏功能的超声指标，，包括测量计算身高、体重、体表面积等形体指标，通过二维超声心动图获取左室收缩功能（左室短轴缩短率、左室射血分数、左室中层心肌缩短率）、左室舒张功能[二尖瓣血流E、A、E/A、DT、IVRT；肺静脉血流S、D、S/D、SFF（收缩充盈分数）、Ar以及Ar-A（表示Ar与MV A持续时间之差值）；二尖瓣舒张早期血流播散速率；二尖瓣环组织多普勒运动速率e’、a’、E/e’]、右室收缩功能[右室面积变化率、三尖瓣环收缩运动位移、组织多普勒三尖瓣环侧壁点收缩期峰值运动速度、右室Tei指数（MPI指数）]、左心房及右心房容积等。接着将影响高血压病的相关因素，如血压、年龄、体重、性别、血糖、血脂、吸烟、饮酒等情况，与测量心脏功能的各项指标结合建立数据库，利于数据挖掘技术构建高血压病心脏功能超声数据模型。结果：建立高血压病患者的临床基本信息及心脏功能的常规测量指标的关系数据库，通过关联规则挖掘出高血压病心脏功能改变的主要影响因素及特征性指标，初步揭示出高血压病心脏功能之间的演变规律并得出其演变趋势图。结论：利用数据挖掘技术，可以得到影响高血压病的关键性影响因素和心脏功能改变的特征性指标，演变不同病程下的高血压病心脏功能演变的趋势图，对临床的辅助诊疗具有一定的现实意义。
[Abstract]:Objective: to explore the basic clinical information and echocardiographic parameters of hypertension patients by using data mining technology, and to reveal the influencing factors and characteristic indexes of hypertensive heart function. To reveal the characteristics and changes of heart function in normal people and hypertension. Methods: high grade color Doppler ultrasound imaging instrument was used to obtain the echocardiographic parameters of heart function in patients with hypertension and healthy persons who had been examined in our hospital from February 2013 to February 2014. The left ventricular systolic function was obtained by two-dimensional echocardiography (left ventricular shortening rate, left ventricular ejection fraction, etc.) Left ventricular diastolic function, left ventricular diastolic function [mitral flow, E / A, E / A] IVRTT; Pulmonary vein blood flow, S / D, SFF (systolic filling fraction, ar and Ar-A( indicating the difference between ar and MV A duration); early diastolic velocity of mitral valve; Mitral annular tissue Doppler motion rate E / E', right ventricular systolic function [right ventricular area change rate, tricuspid annular systolic movement displacement, tissue Doppler tricuspid annular systolic peak velocity, right ventricular area change rate, tricuspid annular systolic displacement, tissue Doppler tricuspid annular systolic peak velocity, Right ventricular Tei index, left atrium and right atrium volume, etc. Then the related factors, such as blood pressure, age, weight, sex, blood sugar, blood lipid, smoking, drinking, etc., were combined with various indexes to measure heart function. It is helpful to construct ultrasonic data model of hypertensive heart function by data mining technology. Results: the basic clinical information of essential hypertension patients and the relation database of routine measurement indexes of heart function were established. The main influencing factors and characteristic indexes of the changes of heart function in hypertension were found out by association rules. The evolution of heart function in hypertension was revealed and the trend map was obtained. Conclusion: by using data mining technique, the key factors affecting hypertension and the characteristic indexes of heart function change can be obtained, and the trend map of heart function evolution of hypertension under different course of disease can be obtained. It has certain practical significance for clinical auxiliary diagnosis and treatment.
【学位授予单位】：皖南医学院
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：R544.1;R445.1

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