本文關(guān)鍵詞：非傳統(tǒng)糖代謝指標(biāo)（GA、FA、1，，5-AG）的臨床應(yīng)用研究　出處：《安徽醫(yī)科大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 性能評估 糖化白蛋白 溴甲酚綠 改良溴甲酚紫 免疫比濁法 糖尿病 線性回歸 非線性擬合 糖代謝指標(biāo) 糖化白蛋白糖化血清蛋白1 5-脫水葡萄糖醇參考區(qū)間

【摘要】：第一部分酶法檢測糖化白蛋白主要方法學(xué)性能評估及白蛋白檢測對糖化白蛋白檢測的影響目的評估液態(tài)酶法檢測血清糖化白蛋白(Glycated albumin,GA)的主要方法學(xué)性能;探討溴甲酚綠法(BCG法)、改良溴甲酚紫法(m BCP法)檢測血清白蛋白(Alb)對GA測定的影響;比較BCG法、m BCP法與免疫比濁法(ITA法)檢測血清Alb結(jié)果的差異。方法評估液態(tài)酶法檢測血清GA的準(zhǔn)確度、精密度、線性范圍、回收試驗(yàn)、參考區(qū)間;隨機(jī)抽取306份不同白蛋白(Alb)濃度新鮮血清標(biāo)本,分別用溴甲酚綠法(BCG)、改良溴甲酚紫法(m BCP)、免疫比濁法(ITA)檢測Alb濃度,液態(tài)酶法檢測GA,并計(jì)算GA值(100*GA/Alb)。結(jié)果液態(tài)酶法檢測血清GA的準(zhǔn)確度良好,以批內(nèi)均值為測得值計(jì)算GA的平均偏倚為2.75%;GA各濃度的重復(fù)性及實(shí)驗(yàn)室內(nèi)精密度的CV值均小于試劑盒聲明的精密度(3%);所選40例正常體檢對象的GA水平也均在廠商說明書提供的參考范圍(11%~16%)內(nèi)。線性范圍評價(jià)中,回歸方程為Y=1.0153X+0.1608,R2=0.9991,GA濃度在0.45g/L~31.2g/L范圍內(nèi)呈線性,滿足線性要求;回收試驗(yàn)中,對照樣本與加標(biāo)樣本間平均偏差為1.57g/L,加標(biāo)平均回收率為102.46%。正常Alb濃度(Alb≥40 g/L)時(shí),BCG法與m BCP法、BCG法與ITA法、m BCP法與ITA法檢測結(jié)果比較,臨床差異不明顯且GABCG與GAm BCP結(jié)果間差異無統(tǒng)計(jì)學(xué)意義(p=0.537);低Alb濃度(Alb40 g/L)時(shí),BCG法與m BCP、ITA法間差異有統(tǒng)計(jì)學(xué)意義(p0.01),GABCG明顯低于GAm BCP(p0.01)。結(jié)論該法分析性能良好,滿足臨床需求。正常Alb濃度時(shí),BCG法、m BCP法與ITA法三者結(jié)果差異無明顯臨床意義,各法用于GA計(jì)算無明顯差異;但低Alb濃度時(shí),m BCP法與ITA法二者一致性優(yōu)于BCG法與ITA法,若使用BCG法則GA結(jié)果可能被低估。第二部分線性回歸、非線性擬合評估糖代謝指標(biāo)間關(guān)系及糖代謝指標(biāo)對糖尿病診斷性能比較目的比較線性擬合和非線性擬合評估糖代謝指標(biāo)間關(guān)系,并比較糖代謝指標(biāo)診斷糖尿病性能。方法回顧性分析549例住院患者的糖化血紅蛋白(Hb A1c)、空腹血糖(fasting glucose,FPG)、GA以及糖化血清蛋白(fructosamine,FA)間關(guān)系。非線性擬合模型中,采用確定系數(shù)確定最適擬合方法。線性擬合及非線性擬合間差異采用費(fèi)歇爾Z轉(zhuǎn)化。應(yīng)用受試者特征工作曲線(ROC曲線)分析糖代謝指標(biāo)診斷糖尿病的曲線下面積(the weighted area under the curve,AUC)。結(jié)果GA,FA與Hb A1c,FPG相關(guān)性高。線性回歸及非線性擬合中,GA與Hb A1c相關(guān)性均要強(qiáng)于GA與FA(均p0.001)�？傮w上,與線性回歸相比,最佳非線性擬合GA與Hb A1c相關(guān)性由0.828提高至0.871(p0.05),GA與FPG相關(guān)性由0.618提高至0.792(p0.01)。糖尿病組中,線性回歸與非線性擬合評估糖代謝指標(biāo)間關(guān)系性能相當(dāng)。而非糖尿組中,非線性擬合較線性回歸更好地評估糖代謝指標(biāo)間關(guān)系。以患者臨床診斷為糖尿病診斷依據(jù)時(shí),Hb A1c的AUC最大為0.831(0.796~0.867),其次為GA 0.811(0.774~0.849)、FA 0.758(0.717~0.798),FPG最小為0.695(0.651~0.740)。結(jié)論與線性回歸相比,非線性擬合可能更適用于評估GA,FA與Hb A1c,FPG關(guān)系。GA、FA可作為Hb A1c和FPG的良好補(bǔ)充,甚至為糖尿病潛在診斷指標(biāo)。第三部分適合本地區(qū)人群的非傳統(tǒng)糖代謝指標(biāo)參考區(qū)間研究目的建立適合本地區(qū)人群GA、FA及1,5-脫水葡萄糖醇(1,5-AG)的參考區(qū)間。方法收集458例健康體檢者,為參考人群。其中男226例,女232例,年齡在20~79歲(中位年齡43歲)。根據(jù)性別(男、女)、年齡(20~39歲、40~59歲及60~79歲)分組,結(jié)合Lathi算法以及適當(dāng)?shù)呐R床考慮評估參考區(qū)間分組必要性。結(jié)果GA性別間差異有統(tǒng)計(jì)學(xué)意義(p0.001),但參考區(qū)間上限的絕對差異僅0.31%,不足以納入臨床考慮。GA水平在三個年齡分組中差異有統(tǒng)計(jì)學(xué)意義(p0.001),Lathi算法建議就20~59歲及60~79歲分組,故建議GA參考區(qū)間分別為10.38~13.89%,10.23~14.79%。1,5-AG水平男性要顯著高于女性(p0.001),平均水平絕對差異為51μmol/L(8.5μg/m L),故按照性別分組,男性為107~367μmol/L,女性為79~306μmol/L。FA性別間參考下限絕對差異僅為7μmol/L,年齡間差異無統(tǒng)計(jì)學(xué)意義(P0.05),故FA參考區(qū)間為220~298μmol/L.結(jié)論成功建立適合本地區(qū)人群的非傳統(tǒng)糖代謝指標(biāo)參考區(qū)間。
[Abstract]:The first part mainly enzymatic detection of glycated albumin detection method performance evaluation and effect on albumin glycated albumin detection to evaluate serum glycated albumin (Glycated enzymatic method albumin, GA) the main method performance study; bromocresol green method (BCG method), modified bromocresol purple method (m BCP method) to detect serum albumin (Alb) effect on the determination of the GA; BCG m method, BCP method and immunoturbidimetry (ITA) differences in detection of serum Alb results. The evaluation method of the detection of serum GA liquid enzymatic method for accuracy, precision, linear range, recovery test and reference interval; 306 random samples of different albumin (Alb) concentrations of fresh serum samples respectively by bromocresol green method (BCG), modified bromocresol purple method (m BCP), immune turbidimetric method (ITA) to detect the concentration of Alb, detection of GA liquid enzymatic method, and calculate the GA value (100 *GA/Alb). The detection of serum GA liquid enzymatic method accurately Well, the batch mean measured value calculated the average bias of 2.75% GA; repeatability of different concentration of GA and laboratory precision CV values were less than the precision of the kit statement (3%); the reference range of the selected 40 cases of normal healthy object GA levels also are provided in the instructions of the manufacturer (11%~16%). The linear range of the evaluation, the regression equation was Y=1.0153X+0.1608, R2=0.9991, GA concentration was linear in the range of 0.45g/L~31.2g/L, to meet the requirements of linear; recovery test, the average deviation control samples and spiked samples was 1.57g/L, the average recovery rate of 102.46%. in normal Alb concentration (Alb = 40, g/L) BCG method and m BCP method, BCG method and ITA method, comparison of the test results of M BCP method and ITA method, no significant difference in clinical difference is not obvious and the GABCG and GAm results between BCP (p=0.537); low concentration of Alb (Alb40 g/L), BCG and m BCP, there was statistically significant difference between the ITA method Yi (P0.01), GABCG was significantly lower than that of GAm BCP (P0.01). Conclusion the method has good performance, meet the clinical needs. The normal concentration of Alb, BCG method, the results of the three m BCP method and ITA method were not obvious clinical significance, the method for calculation of GA had no significant difference; but the low concentration of Alb, m BCP method and ITA method two is more consistent than the BCG method and ITA method, if using the BCG rule GA results may be underestimated. In the second part, linear regression, nonlinear fitting evaluation index the relationship between glucose metabolism and glucose metabolism in diabetes mellitus to compare the diagnostic performance of linear fitting and nonlinear fitting evaluation indexes of glucose metabolism and the relationship between. Comparison of glucose metabolism index in the diagnosis of diabetes performance. Methods: a retrospective analysis of 549 cases of hospitalized patients with HbA1c (Hb A1c), fasting blood glucose (fasting, glucose, FPG, GA) and glycosylated serum protein (fructosamine, FA). The relationship between nonlinear fitting model in mining With the coefficient of determination of the optimum fitting method. The difference between the linear fitting and nonlinear fitting using Fischer Z transformation. By using the receiver operating characteristic curve (ROC curve) analysis of glucose metabolism index in the diagnosis of diabetic area under the curve (the weighted area under the curve, AUC). The results of GA, FA and Hb A1c, FPG correlation high. Linear regression and nonlinear fitting, the correlation between GA and Hb A1c were stronger than GA and FA (p0.001). On the whole, compared with the linear regression, nonlinear fitting and Hb A1c GA the best correlation is increased from 0.828 to 0.871 (P0.05), GA and FPG correlation increased from 0.618 to 0.792 (P0.01). The diabetes group, linear regression and nonlinear fitting evaluation indexes of glucose metabolism. The relationship between the performance and non diabetes group compared with the linear regression, nonlinear fitting better assessment indexes of glucose metabolism. The relationship between the clinical diagnosis of patients with diabetes diagnosis, Hb A1c A The maximum UC was 0.831 (0.796~0.867), followed by GA 0.811 (0.774~0.849), FA 0.758 (0.717~0.798) FPG, the minimum was 0.695 (0.651~0.740). Conclusion compared with linear regression, nonlinear fitting may be more suitable for the evaluation of GA, FA and Hb A1c, FPG.GA, FA can be used as a good supplement of Hb A1c and FPG even as a potential diagnostic index, diabetes. Non traditional Glycmetabolism reference interval objective third part for the local population to establish local populations of GA, FA and 1,5- Ag (1,5-AG) of the reference interval. Methods 458 healthy subjects, as the reference population. There were 226 male and 232 female patients and at the age of 20~79 years (median age 43 years). According to gender (male, female), age (20~39 years, 40~59 years and 60~79 years) group, combined with the Lathi algorithm and the appropriate clinical assessment is necessary to consider the reference interval of packet. There was a significant difference in GA between sexes (P results 0.001), but the absolute difference of reference range limit is only 0.31%, not enough to consider in clinical.GA level difference was statistically significant in three age groups (p0.001), the proposed Lathi algorithm of 20~59 and 60~79 years old group, it is suggested that the GA reference intervals were 10.38~13.89%, 10.23~14.79%.1,5-AG levels of male is significantly higher than that of female (p0.001) the average absolute difference, 51 mol/L (8.5 g/m L), it is grouped according to the gender, the male is 107~367 mol/L, mol/L.FA 79~306 for female gender difference is only the absolute reference limit of 7 mol/L, there was no significant difference between the age (P0.05), the FA reference range for 220~298 mol/L. successfully. The establishment of non traditional Glycmetabolism reference interval region suitable for the population.

【學(xué)位授予單位】：安徽醫(yī)科大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：R587.1

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