發(fā)布時(shí)間：2018-06-22 07:36

  本文選題：動(dòng)態(tài)血糖監(jiān)測(cè) + 血糖波動(dòng)幅度評(píng)估參數(shù)�。� 參考：《南方醫(yī)科大學(xué)》2017年碩士論文

【摘要】：繼心腦血管病變、腫瘤之后,糖尿病已成為第三大嚴(yán)重威脅人類(lèi)健康的慢性疾病,給個(gè)人健康和社會(huì)經(jīng)濟(jì)帶來(lái)了嚴(yán)重影響,由糖尿病引發(fā)的慢性并發(fā)癥是威脅糖尿病患者生命和健康的主要因素。研究表明,血糖波動(dòng)是糖尿病慢性并發(fā)癥發(fā)生、發(fā)展的潛在獨(dú)立危險(xiǎn)因素。若血糖長(zhǎng)期波動(dòng)過(guò)大,會(huì)增加患者罹患糖尿病慢性并發(fā)癥的危險(xiǎn)性,因此對(duì)糖尿病患者進(jìn)行血糖波動(dòng)的監(jiān)測(cè)與控制是減少糖尿病慢性并發(fā)癥發(fā)生的有效手段。為了更好的對(duì)血糖波動(dòng)進(jìn)行監(jiān)測(cè)與控制,必須要準(zhǔn)確地量化評(píng)估血糖波動(dòng)幅度。目前已有許多參數(shù)被提出用于血糖波動(dòng)幅度評(píng)估,主要包括:血糖值的平均值(MBG)、標(biāo)準(zhǔn)差(SDBG)、四分位距(IQR)、M值(M-value)、變異系數(shù)(%CV)、J系數(shù)(J-index)、最大血糖波動(dòng)幅度(LAGE)、低血糖系數(shù)(LBG1)、高血糖系數(shù)(HBG1)、血糖風(fēng)險(xiǎn)評(píng)估(GRADE)、日均風(fēng)險(xiǎn)值(ADRR)、平均血糖波動(dòng)幅度(MAGEA、日間血糖平均絕對(duì)差(MODD)、連續(xù)24小時(shí)血糖凈作用(CONGAn=24)等,但迄今為止還沒(méi)有統(tǒng)一公認(rèn)的最佳指標(biāo)。隨著動(dòng)態(tài)血糖監(jiān)測(cè)技術(shù)(CGM)的發(fā)展及可靠性的提高,且MAGE在反映血糖波動(dòng)與氧化應(yīng)激反應(yīng)有其獨(dú)特的優(yōu)勢(shì),而氧化應(yīng)激反應(yīng)有可能是導(dǎo)致糖尿病慢性并發(fā)癥發(fā)生的機(jī)制,目前該參數(shù)已被越來(lái)越多的臨床工作者認(rèn)可,被認(rèn)為可能是反映日內(nèi)血糖波動(dòng)的“金標(biāo)準(zhǔn)”。CGM為血糖波動(dòng)評(píng)估帶來(lái)了大量的血糖數(shù)據(jù),然而CGM系統(tǒng)自身卻并未提供目前所有血糖波動(dòng)幅度評(píng)估參數(shù)的計(jì)算功能,當(dāng)使用CGM數(shù)據(jù)進(jìn)行以上評(píng)估參數(shù)的計(jì)算時(shí),工作量將十分巨大,不利于參數(shù)的快速獲得。尤其是進(jìn)行MAGE參數(shù)計(jì)算,因?yàn)樵谂R床上一般只能通過(guò)人工比較的方式篩選數(shù)據(jù)進(jìn)行計(jì)算。若同時(shí)對(duì)多名患者CGM數(shù)據(jù)進(jìn)行計(jì)算,參數(shù)計(jì)算的工作量將大大的增加,十分耗費(fèi)時(shí)間。此外,臨床研究人員必須要進(jìn)行MAGE參數(shù)計(jì)算的相關(guān)專(zhuān)業(yè)培訓(xùn)方可確保數(shù)據(jù)篩選的準(zhǔn)確性,否則容易導(dǎo)致計(jì)算結(jié)果存在一定的誤差。目前國(guó)內(nèi)外已經(jīng)針對(duì)MAGE參數(shù)提出了幾種自動(dòng)計(jì)算方法及相關(guān)計(jì)算軟件,但并未獲得臨床的廣泛認(rèn)可,主要是因?yàn)榕R床上缺乏計(jì)算結(jié)果準(zhǔn)確性的檢驗(yàn)標(biāo)準(zhǔn),并且這些方法都缺乏數(shù)學(xué)理論的支撐使得計(jì)算結(jié)果的準(zhǔn)確性易受到臨床的質(zhì)疑;同時(shí)這些自動(dòng)計(jì)算軟件并未囊括其他評(píng)估參數(shù)不利于多角度綜合評(píng)估血糖波動(dòng)情況。因此,為解決所存在的問(wèn)題,本研究提出了動(dòng)態(tài)血糖波動(dòng)幅度評(píng)估參數(shù)的自動(dòng)計(jì)算算法,很好地解決了現(xiàn)有評(píng)估參數(shù)的自動(dòng)計(jì)算問(wèn)題。尤其針對(duì)MAGE的自動(dòng)計(jì)算,算法在MAGE定義的基礎(chǔ)上,結(jié)合完善的有效血糖波動(dòng)判斷標(biāo)準(zhǔn),構(gòu)建了應(yīng)用差分進(jìn)化算法求解的基于非線(xiàn)性整數(shù)規(guī)劃的M4GE計(jì)算數(shù)學(xué)模型。為使算法進(jìn)一步應(yīng)用于臨床,利用C#語(yǔ)言在VS2010的編程環(huán)境中對(duì)算法進(jìn)行開(kāi)發(fā),開(kāi)發(fā)了相應(yīng)的可以在Windows下安裝使用的自動(dòng)計(jì)算軟件。該自動(dòng)計(jì)算軟件實(shí)現(xiàn)了現(xiàn)有評(píng)估參數(shù)的快速計(jì)算,同時(shí)該軟件方便易操作、靈活的界面使得沒(méi)有經(jīng)過(guò)相關(guān)專(zhuān)業(yè)培訓(xùn)的人亦可以導(dǎo)入需要分析的CGM數(shù)據(jù)計(jì)算出參數(shù)值。為克服MAGE參數(shù)計(jì)算沒(méi)有檢驗(yàn)標(biāo)準(zhǔn)的難題,本研究通過(guò)統(tǒng)計(jì)學(xué)分析比較分別使用傳統(tǒng)人工篩選數(shù)據(jù)的計(jì)算方法和自動(dòng)計(jì)算算法對(duì)大量的不同類(lèi)型的糖尿病患者的CGM臨床數(shù)據(jù)的計(jì)算結(jié)果以驗(yàn)證自動(dòng)計(jì)算算法的準(zhǔn)確性,分析顯示自動(dòng)計(jì)算與手動(dòng)計(jì)算結(jié)果之間具有高度相關(guān)性和一致性,從而驗(yàn)證了自動(dòng)算法計(jì)算MAGE值的準(zhǔn)確性。研究算法使血糖波動(dòng)幅度評(píng)估參數(shù)值的獲取更加簡(jiǎn)單方便與客觀(guān)準(zhǔn)確,大大地縮短了計(jì)算時(shí)間,提高了臨床的效率,也為臨床工作者同時(shí)綜合利用多個(gè)參數(shù)評(píng)估血糖波動(dòng)提供了可能,進(jìn)一步推動(dòng)血糖波動(dòng)評(píng)估研究的開(kāi)展。
[Abstract]:Following the cardiovascular and cerebrovascular diseases, after the tumor, diabetes has become the third major chronic disease that seriously threatens human health. It has a serious impact on personal health and social economy. The chronic complications caused by diabetes are the main factors that threaten the life and health of diabetics. The risk of chronic complications of diabetes can be increased if the long-term fluctuation of blood sugar is too large. Therefore, monitoring and control of blood glucose fluctuation in diabetic patients is an effective means to reduce the occurrence of diabetic chronic complications. It is necessary to accurately quantify the amplitude of blood glucose fluctuations. Many parameters have been proposed to assess the amplitude of blood glucose fluctuations, including the average blood sugar value (MBG), standard deviation (SDBG), four division distance (IQR), M value (M-value), variation coefficient (%CV), J number (J-index), maximum blood glucose fluctuation amplitude (LAGE), hypoglycemia coefficient (LBG1), hyperglycemia system Number (HBG1), blood glucose risk assessment (GRADE), average daily risk value (ADRR), average blood glucose fluctuation range (MAGEA, mean absolute difference of blood glucose (MODD), 24 hours of blood glucose net action (CONGAn=24), but so far there is no unified best indicator. With the development and reliability of dynamic glucose monitoring (CGM), MAGE is in the opposite direction. Hyperglycemic fluctuations and oxidative stress reactions have their unique advantages, and oxidative stress may be the mechanism that causes chronic diabetic complications. At present, this parameter has been recognized by more and more clinical workers. It is believed that the "golden standard".CGM, which may reflect the fluctuation of blood sugar in the day, has brought a lot of blood glucose fluctuations. Blood glucose data, however, the CGM system itself does not provide the computing function of all the parameters of the current blood glucose fluctuation assessment. When using the CGM data to calculate the above evaluation parameters, the workload will be very large, not conducive to the rapid acquisition of parameters, especially for the MAGE parameter calculation, because it is generally only by manual comparison in clinical. If the number of patients' CGM data is calculated at the same time, the workload of the parameter calculation will be greatly increased and time consuming. In addition, the relevant professional trainers who have to calculate the MAGE parameters to the clinical researchers can ensure the accuracy of the data screening, otherwise it will easily lead to the calculation results. At present, several automatic calculation methods and related computing software have been proposed for MAGE parameters at home and abroad, but it has not been widely accepted in clinical practice, mainly because of the lack of testing standards for the accuracy of the results of calculation, and these methods lack the support of mathematical theory so that the accuracy of the calculation results is easily subject to clinical practice. At the same time, the automatic calculation software does not include other evaluation parameters which are not conducive to multi angle comprehensive evaluation of blood glucose fluctuations. Therefore, in order to solve the problems, this study proposes an automatic calculation algorithm for the dynamic parameters of the fluctuation of blood glucose fluctuation, which is a good solution to the problem of the automatic calculation of the existing evaluation parameters. On the basis of the definition of MAGE and on the basis of the definition of MAGE, the algorithm constructs a mathematical model of M4GE computing based on nonlinear integer programming, which is solved by differential evolution algorithm. In order to make the algorithm further applied to the clinic, the algorithm is developed in the VS2010 programming environment by using the C# language. The automatic computing software which can be installed and used under the Windows is sent. The automatic calculation software realizes the rapid calculation of the existing evaluation parameters. At the same time, the software is convenient and easy to operate. The flexible interface makes the people without the related professional training can also import the CGM data that needs analysis to calculate the parameters. In order to overcome the MAGE parameters, the software can also be used to overcome the parameters. The calculation of CGM clinical data of a large number of different types of diabetic patients was compared with the results of the calculation method of traditional artificial screening data and automatic calculation algorithm to verify the accuracy of the automatic calculation algorithm, and the analysis showed that the automatic calculation and manual calculation were shown by the statistical analysis. There is a high correlation and consistency between the fruits, which verifies the accuracy of the MAGE value calculated by the automatic algorithm. The research algorithm makes the acquisition of the parameter value of the blood glucose fluctuation range more simple and more objective and accurate, greatly shortens the calculation time, improves the clinical efficiency, and uses multiple parameters for the clinical workers to evaluate the parameters simultaneously. It is possible to estimate the fluctuation of blood glucose and further promote the research of blood glucose fluctuation assessment.
【學(xué)位授予單位】：南方醫(yī)科大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：R587.2

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