心臟外科手術之相關風險因子分析;Analysis of correlations and risk factors in heart surgeries

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Title:	心臟外科手術之相關風險因子分析;Analysis of correlations and risk factors in heart surgeries
Authors:	陳亭妤;Chen,Ting-shu
Contributors:	系統生物與生物資訊研究所
Keywords:	心臟外科;關聯性;冠狀動脈繞道手術;生存率;heart surgery;relevance;relation;survival;CABG
Date:	2014-07-18
Issue Date:	2014-10-15 14:45:10 (UTC+8)
Publisher:	國立中央大學
Abstract:	心臟病占我國十大死因的第二位，影響國人的健康。目前除了服藥、氣球擴張之外，外科手術為一種治療心臟病有效的方式。此次計畫共有三種不同的手術，分別是冠狀動脈繞道手術(CABG)、更換心臟瓣膜手術(VALVE)以及主動脈手術(AO)。將這三種手術的內容個別來做分析，不同手術有不同的內容，而手術的內容主要包括了病患的基本資料，例如：生日、身高、體重、性別…等，除了基本資料外，還有病患術前、手術中及術後的資料，例如：病患血壓、服用的藥物廠牌以及次數、手術次數、病患心臟是否衰竭以及衰竭程度、是否有併發症…等，藉由這些資料可以分析出病患術前、術後的差異，或者服用不同廠牌的藥物對病患是否有影響，以及在手術過程中使用了哪些東西會影響病患生存率…等，分析這些資料後可以藉由醫生術後的用藥、病患術前以及手術過程中的狀態預測出病患術後可能的改變，除了術前、術後的差異之外，在術後是否需要二次開刀、是否有併發症以及對病患的觀察可以預測出其生存率，除了使醫生較為便利了解病患情況之外，甚至可能藉此降低病患的死亡率以及減緩醫生在手術過程中的錯誤率，對未來的心臟外科有幫助，也可以使病患以及病患家屬對手術增加信心。;Heart disease is the second of leading cause of death in Taiwan affect people′s health. Except for taking medicine and Percutaneous Transluminal Coronary Angioplasty (PTCA), cardiac surgery is an effective way to treat heart disease. There are three different types of surgeries which are coronary artery bypass graft surgery (CABG), heart valve surgery (VALVE) and aortic surgery (AO) here. Different surgery contains different factors, using the factors in each surgery to do data mining, the factors including patient’s basic information, such as: birthday, height, weight, gender…etc. Besides patient’s basic information, patient’s data before, during and after surgery are included, for example: blood pressure, the brand and frequency of drugs, number of surgeries, if patients with heart failure or complications or not...etc. Mining this data can analyze the different of patient’s status between before and after surgery, whether different brand of drug will influent patient or not, and using what things will affect patient’s survival...etc. After analysis of these data, doctor can estimate patients’ possible changes after surgery by postoperative medication and states before and during surgery. Not only can predict preoperative and postoperative differences, but also can estimate patients’ survival rate by their condition, such as: if the patient need secondary surgery or get complications after surgery or not. In addition to let doctors understand patients’ conditions conveniently, even are able to reduce the mortality rate of patients and error of surgery. It is good for the future of cardiac surgery and can make the surgical patients and patients′ families increase confidence of surgery.
Appears in Collections:	[Institute of Systems Biology and Bioinformatics] Electronic Thesis & Dissertation

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