糖化血红蛋白测定与口服葡萄糖耐量试验在中国人群中诊断2型糖尿病的比较
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摘要
背景
传统上用血浆葡萄糖诊断糖尿病。糖化血红蛋白反映近期3个月的血浆葡萄糖水平。流行病学研究显示在非糖尿病成人中糖化血红蛋白水平可以预测糖尿病的发生、心血管疾病的发生和死亡率。糖化血红蛋白反映一段时间内的血浆葡萄糖水平,与糖尿病慢性并发症的相关性比单次血浆葡萄糖水平更强,因此可能是糖尿病诊断的更好的生化指标,可以作为诊断标准之一。2009年美国糖尿病协会在糖尿病的诊疗标准中规定糖化血红蛋白大于等于6.5%可以诊断糖尿
目的
在中国的高危人群中以OGTT为金标准检验糖化血红蛋白诊断糖尿病的敏感性、特异性和一致性,并对两种诊断结果不同人群的心血管危险因素进行比较,以了解哪个标准更能预测心血管危险因素。
研究设计和方法
研究对象：从2007年6月至2008年5月,我们完成了山东省的《全国糖尿病及代谢综合征调查》工作,研究方案经过齐鲁医院伦理委员会通过,所有受试者均签署知情同意书。我们选择其中年龄大于45岁的未诊断糖尿病的701人。
研究设计：患者空腹至少8小时,做口服葡萄糖耐量试验,测定空腹血浆葡萄糖和2小时血浆葡萄糖。填问卷调查表,其中包括高血压,心血管疾病和糖尿病家族史等内容。测身高、体重,并计算体重指数(BMI),测血压。取静脉血测定空腹血浆葡萄糖和糖化血红蛋白,总胆固醇(TC),低密度脂蛋白胆固醇(LDL-c),甘油三酯(TG)和高密度脂蛋白胆固醇(HDL-c).用葡萄糖脱氢酶方法测定血浆葡萄糖水平,用高压液相色谱仪(HPLC)测定HbAIC。
根据2009年ADA诊断标准,将受试者分为4组：真糖尿病组(两种方法均阳性),OGTT-糖尿病(空腹血浆葡萄糖水平大于等于7. Ommol/L或2小时血浆葡萄糖水平大于等于11. lmmol/L), HbAlc-糖尿病(糖化血红蛋白水平大于等于6.5%),非糖尿病(两种方法均阴性)。
以口服葡萄糖耐量试验为金标准,用敏感性(OGTT阳性患者中HbAlc也阳性者所占的百分比)、特异性(OGTT阴性患者中HbAlc也阴性者所占的百分比)、阳性预测率(HbAlc阳性患者中OGTT也阳性者所占的百分比)、阴性预测率(HbAlc阴性患者中OGTT也阴性者所占的百分比)评价糖化血红蛋白诊断糖尿病的价值。为了了解两个标准哪一个能更好的预测心血管危险因素,我们对四组人群(真糖尿病组,OGTT-糖尿病组,HbAlc-糖尿病组,非糖尿病组)的血压、体重指数、总胆固醇水平、甘油三酯、高密度脂蛋白胆固醇和低密度脂蛋白胆固醇水平进行了比较。
统计学方法
用SPSS v11.5 (SPSS Inc., Chicago, IL)完成统计学分析.连续性正态分布资料用均数加减标准差表示,偏态分布资料用中位数表示(甘油三酯,高密度脂蛋白胆固醇),分类资料用百分数表示。用Wilcoxon rank sum和Kruskal-Wallis tests比较四组中甘油三酯和高密度脂蛋白胆固醇水平。年龄为协变量,用协方差分析比较四组中血压、体重指数、总胆固醇水平和低密度脂蛋白胆固醇水平,双侧P值小于0.05.为有统计学差异。用ROC曲线描述糖化血红蛋白检测OGTT糖尿病的敏感性和特异性。
结果
共检测701人,平均年龄52±11岁(45-83岁)(女性392[56%]).平均体重指数26±3 kg/m2,糖化血红蛋白水平5.34±0.61%。
在701个进行口服葡萄糖耐量试验的人中,检出94(13%)个糖尿病患者,236(34%)个糖尿病前期患者。在同样的人群中进行糖化血红蛋白测定,根据糖化血红蛋白大于等于6.5%诊断糖尿病,检出65(9%)的糖尿病患者,123(18%)个糖尿病前期患者,所以口服葡萄糖耐量试验比糖化血红蛋白测定能检出更多的糖尿病患者。
用糖化血红蛋白预测OGTT-糖尿病ROC曲线下面积为0.843(95%的可信区间为0.798-0.888)。糖化血红蛋白大于等于5.1%预测糖尿病的敏感性为98.7%,特异性为33%,阳性预测值为18%,阴性预测值为99%。糖化血红蛋白大于等于7.0%时,预测糖尿病的敏感性为24%,特异性为99.7%,阳性预测率为92%,阴性预测率为89%。糖化血红蛋白大于等于6.5%预测糖尿病的敏感性为48.2%,特异性为97.8%,阳性预测率69%,阴性预测率92%。糖化血红蛋白和口服葡萄糖耐量试验两种诊断方法不完全一致。糖化血红蛋白大于等于6.5%的患者中30.7%未达到口服葡萄糖耐量试验诊断标准,52%的口服葡萄糖耐量试验诊断的糖尿病患者糖化血红蛋白小于6.5%,未达到糖化血红蛋白诊断糖尿病的标准。
为了比较糖化血红蛋白测定和口服葡萄糖耐量试验与糖尿病并发症的关系,我们比较了四组人群的心血管危险因素,尤其关注两种诊断方法结果不一致的人群,以判断哪种诊断方法更能反映心血管病因素。三组糖尿病人群的年龄均大于非糖尿病组,校正了年龄的影响后,四组人群中除了舒张压和高密度脂蛋白胆固醇,其余的危险因子水平有明显区别。除了舒张压,真糖尿病组(两种方法均阳性)的所有心血管危险因素均高于非糖尿病组。除了高密度脂蛋白胆固醇和舒张压,HbAlc-and OGTT-糖尿病组所有的血脂水平、体重指数和收缩压均高于非糖尿病组,而两组的心血管危险因素水平没有差别。
结论
通过本研究,我们发现与OGTT比较,糖化血红蛋白大于等于6.5%做诊断糖尿病的标准特异性高,敏感性低。糖化血红蛋白测定和口服葡萄糖耐量试验两种诊断方法不完全一致。两种诊断标准反映了相同的心血管危险因子水平。
我们的结果显示用糖化血红蛋白做诊断标准较OGTT检出的糖尿病患者减少,两者不一致。本研究中,糖化血红蛋白大于等于6.5%的患者中30.7%未达到口服葡萄糖耐量试验诊断标准,52%的口服葡萄糖耐量试验诊断的糖尿病患者糖化血红蛋白小于6.5%,未达到糖化血红蛋白诊断糖尿病的标准。本研究中糖化血红蛋白大于等于6.5%诊断糖尿病与OGTT的一致性为68.3%。
根据我们的数据,心血管危险因子水平在HbAlc-和OGTT-糖尿病组水平相似而且都高于非糖尿病组。这是第一个比较HbAlc-和OGTT-糖尿病两组患者心血管危险因子的研究。
根据我们的结果,用糖化血红蛋白测定代替OGTT试验将导致52%的OGTT糖尿病漏诊,这些患者已经存在较高的心血管危险因子水平。另一方面,只做OGTT试验将使30.7% HbAlc-糖尿病漏诊,这些患者可能已经存在糖尿病视网膜病变。所以没有哪一种方法可以作为诊断糖尿病的金标准。
总之,在中国高危人群中,糖化血红蛋白测定诊断糖尿病敏感性有限,用它代替OGTT将使大约一半的已经存在心血管危险因子的患者漏诊。
创新点和和限制性
创新点：
1),本课题对糖化血红蛋白诊断糖尿病进行了系统研究,并对两种诊断方法的一致性进行研究。
2),本研究首次比较了两种诊断标准不一致人群的心血管危险因素水平,得出两者相似的结论。
3)根据以上结果首次得出结论：用糖化血红蛋白测定代替口服葡萄糖耐量试验将使大约一半已经存在心血管危险因子的患者漏诊。
限制性
1)由于条件所限,例数较少。
2)本课题为横断面研究,所以缺乏预测性,有条件应进行前瞻性研究。
背景
在中国大约60.7%的糖尿病患者没有确诊,因为他们中的大多数在疾病早期没有明显症状。糖尿病大血管和微血管并发症在疾病的早期甚至在糖尿病前期已经存在,中国的大庆研究和国外的研究均证实提前发现高危人群并进行饮食及生活方式的干预可以有效防止糖尿病的发生发展,可以有效预防并发症,所以早发现早诊断成为预防及治疗糖尿病及其并发症的关键。
现有的糖尿病诊断标准为空腹血浆葡萄糖大于等于≥7.Ommol/L或葡萄糖负荷后2小时血浆葡萄糖大于等于≥11.1mmol/L.空腹血浆葡萄糖较容易测定,可用于糖尿病的筛查,但是空腹血浆葡萄糖小于7.Ommol/L的患者往往被漏诊,中国目前单独2小时血浆葡萄糖大于等于11.lmmol/L的患者所占比例为46.6%。口服葡萄糖耐量试验费时又不方便操作,临床不易被患者接受。研究发现糖化血红蛋白与糖尿病特异性视网膜病变联系更密切,最近国际专家委员会建议将糖化血红蛋白做为诊断标准之一。然而一些研究提示以糖化血红蛋白做诊断标准,与口服葡萄糖耐量试验相比检出的糖尿病患者会减少。一些研究报告了空腹血浆葡萄糖结合糖化血红蛋白筛查糖尿病的结果,但是他们所用的空腹血糖受损的标准为6.1-6.9mmol/L，诊断糖尿病的标准为空腹血浆葡萄糖大于等于7.Ommol/L或2小时血浆葡萄糖大于等于11.lmmol/L。我们的研究用2009年美国糖尿病协会新标准：糖化血红蛋白大于等于6.5%,或空腹血浆葡萄糖大于等于7.Ommol/L,或2小时血浆葡萄糖大于等于11.lmmol/L。用新标准诊断糖尿病,我们评价空腹血浆葡萄糖结合糖化血红蛋白测定是否提高糖尿病的检出率,以找出一个简单易行的筛查糖尿病的方法。
研究目的
评价空腹血浆葡萄糖结合糖化血红蛋白是否能提高糖尿病的检出率,并据此找出更可行的筛查糖尿病的方法。
1研究设计和方法
1.1研究对象
从2007年6月至2008年5月,我们完成了山东省的《全国糖尿病及代谢综合征调查》工作,研究方案经过齐鲁医院伦理委员会通过,所有受试者均签署知情同意书。我们选择年龄大于45岁的未诊断糖尿病的700人。
1.2研究设计
患者空腹至少8小时,做口服葡萄糖耐量试验,测定空腹血浆葡萄糖和2小时血浆葡萄糖。填问卷调查表,其中包括高血压,心血管疾病和糖尿病家族史等内容。测身高、体重,并计算体重指数(BMI),测血压。取静脉血测定空腹血浆葡萄糖和糖化血红蛋白,总胆固醇(TC),低密度脂蛋白胆固醇(LDL-c),甘油三酯(TGs)和高密度脂蛋白胆固醇(HDL-c).用葡萄糖脱氢酶方法测定血浆葡萄糖水平,用高压液相色谱仪(HPLC)测定HbAIC。
采用2009美国糖尿病协会新标准：糖尿病诊断标准：糖化血红蛋白大于等于6.5%,或空腹血浆葡萄糖大于等于7. Ommol/L,或2小时血浆葡萄糖大于等于11. lmmol/L。空腹血糖受损：空腹血浆葡萄糖在5.6-6.9 mmol/1之间;葡萄糖耐量受损：葡萄糖负荷后2小时血浆葡萄糖7.8-11.1 mmol/L
1.3统计学方法
用SPSS vll.5 (SPSS Inc., Chicago, IL)完成统计学分析.连续性正态分布资料用均数加减标准差表示。用ROC曲线计算空腹血糖和糖化血红蛋白预测OGTT糖尿病的敏感性、特异性和切点。敏感性和特异性之和最大处即为最佳切点。分类资料的比较用chi-square test。
2结果
共检测700人,平均年龄52±11岁(45-83岁)(女性392[56%]).平均体重指数26±3 kg/m2,糖化血红蛋白水平5.34±0.61%.
2.1用空腹血浆葡萄糖筛查糖尿病的结果。共检出93个OGTT糖尿病,其中46人FPG≥7.Ommol/L,47人空腹血浆葡萄糖小于7. Ommol/L。根据ROC曲线分析结果,空腹血浆葡萄糖大于等于5.6mmol/L为预测2小时OGTT糖尿病的最佳切点,在此切点敏感性为78.0%,特异性为73.3%。空腹血浆葡萄糖小于4.8mmol/L有98.7%的准确性排除糖尿病,空腹血浆葡萄糖大于等于6.7mmol/L有99%的准确性诊断2小时OGTT糖尿病。根据以上结果,将研究对象根据空腹血浆葡萄糖分为以下4组：FPG≥7.Ommol/L,6.9-5.6mmol/L,5.5-4.8mmol/L,和<4.8mmol/L(表1)。在FPG 6.9-5.6mmol/L组,为了检出35个糖尿病患者,需要给193个人做OGTT;在FPG 5.5-4.8mmol/L组,为了检出9个患者,368人需要做OGTT,而FPG<4.8mmol/L组的92人中只有一位糖尿病患者,故可以不做OGTT直接排除糖尿病。
2.2用糖化血红蛋白筛查糖尿病的结果。共检出98位糖尿病,其中54人糖化血红蛋白大于等于6.5%可以直接诊断糖尿病,44位糖化血红蛋白小于6.5%。根据ROC曲线分析结果(图1),糖化血红蛋白大于等于5.6%预测OGTT糖尿病的敏感性为80.0%,特异性为77.0%。糖化血红蛋白小于5.0%排除糖尿病的准确性达到98.7%。根据以上资料和参考文献,将研究对象分为以下4组,HbAlc≥6.5%,6.4-5.6%,5.5-5.0%,和<5.0%.(表2).在HbAlc5.6-6.4%组,为了检出30位糖尿病,157人需要做OGTT,在HbAlc 5.0-5.5%组,,为了检出7位糖尿病,203人需要做OGTT。285糖化血红蛋白小于5%的人中只有2位糖尿病,可以不需要做OGTT直接排除糖尿病。
2.3用FPG +HbAlc筛查糖尿病的结果。共检出98位糖尿病,其中64位糖化血红蛋白大于等于≥6.5%或者空腹血浆葡萄糖大于等于7. Ommol/L,这些人可以直接诊断糖尿病。在179个空腹血糖受损的人中,当HbAlc5.6-6.4%时,为了检出18位糖尿病患者,68人需要做OGTT;当HbAlc 5.5-5.0%时,为了检出6个糖尿病患者,64人需要做OGTT,而47位糖化血红蛋白小于5%的人不需要做OGTT可以直接排除糖尿病。在空腹血浆葡萄糖小于5.6 mmol/L的人中,当HbAlc5.6-6.4%时,为了检出8个糖尿病患者,80人需要做OGTT：377位糖化血红蛋白小于5.6%的人中只有2个糖尿病患者,可以不做OGTT而直接排除糖尿病。在此组研究者中,共有424位不需要做OGTT直接排除糖尿病。
2.4对3种筛查糖尿病的方法进行比较。根据空腹血浆葡萄糖筛查糖尿病,49.5%的患者可以直接确诊,14%高危人群可以直接排除糖尿病,为了检出82个糖尿病患者,193人需要做OGTT;而根据糖化血红蛋白或者FPG+HbAlc筛查糖尿病,52.7%,和65.3%的糖尿病患者可以直接确诊,40%和61%的高危人群可以直接排除糖尿病,根据糖化血红蛋白筛查糖尿病,为了检出88位糖尿病患者,158人需要做OGTT,根据FPG+HbAlc筛查糖尿病,为了检出82位糖尿病患者,只有68人需要做OGTT。根据FPG+HbAlc可以比FPG直接诊断更多的糖尿病(P<0.05),并且根据FPG+HbAlc可以比FPG或HbAlc直接排除更多的糖尿病(P<0.01)。FPG+HbAlc可以明显减少做OGTT的人数。
3结论
FPG结合HbAlc是一个在高危人群中筛查糖尿病的有效方法。根据我们的结果,我们可以建议以下的方式筛查糖尿病：1)在高危人群中同时测定FPG和HbAlc,2)如果FPG≥7.Ommol/L或HbAlc≥6.5%,诊断糖尿病；3)如果FBG< 4.8mmol/L或HbAlc<5.0%,或者FPG<5.6mmol/L并且HbAlc 5.5-5.0%,可以直接排除糖尿病；4)如果FPG 5.6-6.9mmol/L并且HbAlc 5.6-6.4%,做OGTT; 5)如果只有IFG或HbAlc5.6-6.4%,,参考危险因素,越多发生糖尿病的可能性越大。
背景
肥胖是心血管疾病和2型糖尿病的重要危险因素之一。流行病学研究已经证明升高的体重指数和腰围是2型糖尿病、冠心病和高血压的独立危险因子。然而,肥胖的定义缺乏一致的标准,主要的分歧集中在全身性肥胖和脂肪组织分布异常哪一个是导致心血管疾病的主要原因。流行病学研究显示反映全身性肥胖的体重指数(BMI)是预测心血管疾病的有效指标,然而,一些研究表明反映中心性肥胖的指标腰围(WC)也能预测心血管疾病,并且其他的反映内脏脂肪的指标如腰围／身高(WHtR)比体重指数能更好的预测心血管及代谢指标异常。美国和欧洲关于这方面的研究较多,在中国尤其山东这方面的大型流行病学研究很少。
研究目的
在中国山东找出体重指数、腰围、腰围身高比值预测高血压、血脂异常、代谢综合征和2型糖尿病的最佳切点,并比较它们对高血压、血脂异常、代谢综合征和2型糖尿病的预测价值。
研究方法
研究人群
从2007年6月至2008年5月,我们完成了山东省的《全国糖尿病及代谢综合征调查》工作,研究方案经过齐鲁医院伦理委员会通过,所有受试者均签署知情同意书。采取分层抽样方法对山东省的济南、泰安、济宁以及淄博等地的自然人群就糖尿病及代谢综合征患病率进行了调查。共选取3700人,年龄20-74,3400人参加了调查,供本分析的完整资料为3006人。
受试者至少空腹8小时到指定医院,完成第一部分所示的调查问卷并进行各项检查。用标准方法测血压、体重、腰围,体重指数的计算方法：体重(千克)除以身高(米)的平方。
实验室检查
取静脉血测定空腹血浆葡萄糖,总胆固醇(TC),低密度脂蛋白胆固醇(LDL-c),甘油三酯(TGs)和高密度脂蛋白胆固醇(HDL-c).用葡萄糖脱氢酶方法测定血浆葡萄糖水平,然后口服75克葡萄糖,2小时取血测定血浆葡萄糖。用胆固醇氧化酶法测定总胆固醇,用酶法测定甘油三酯,用直接法测定高密度脂蛋白胆固醇,低密度脂蛋白胆固醇用Friedewald公式计算。
统计分析
男性女性资料分别统计。另外,对45岁以上的高危人群单独进行分析。连续变量用均数加减标准差表示,分类资料用百分数表示。组之间的比较连续变量用Student ttest,分类资料用chi-square tes。用ROC分析每个指标预测不同危险因素的敏感性、特异性,并找出最佳切点,用曲线下面积表示每个指标的预测价值。曲线下面积越大越好,曲线下面积为1时代表此指标在最佳切点能将正常者和异常者完全分开,曲线下面积为0.5时代表词指标没有预测价值。曲线上敏感性和特异性之和最大的点为最佳切点。用SPSS v11.5 (SPSS Inc., Chicago, IL)完成统计分析,两个AUCs的比较用Z值：Z> 1.96, P< 0.05, Z> 2.58, P< 0.01.比较女性和男性的同一指标的AUCs时,用以下公式：Z=(AA-AB)/√(SEA2+SEB2),在此SE是标准误；比较两个不同指标预测同一危险因素的AUCs时,用以下公式：Z=(AA-AB)/√(SEA2+SEB2-2γSEA SEB),在此γ是AA和AB的相关系数,SE是标准误。
结果
受试者的基本资料
研究样本的特点见表1。男性的平均体重指数、腰围、腰围身高比值、收缩压、舒张压、空腹血浆葡萄糖、高密度脂蛋白胆固醇、低密度脂蛋白胆固醇、甘油三酯和总胆固醇均高于女性。年龄和2小时血浆葡萄糖水平男女两性相似。在男性,代谢综合征和高血压患病率高于女性,糖尿病和血脂异常患病率两性相似。
人体侧指标与心血管危险因素
男性女性不同人体测量指标的切点见表2。在男性体重指数预测高血压、2型糖尿病、血脂异常和代谢综合征的最佳切点是从24.5到25 kg/m2,腰围预测高血压、2型糖尿病、血脂异常和代谢综合征的最佳切点是从87.5到89.5 cm,腰围与身高的比值最佳切点为从0.52到0.53。在女性体重指数预测高血压、2型糖尿病、血脂异常和代谢综合征的最佳切点是从24.5到25 kg/m2,腰围预测高血压、2型糖尿病、血脂异常和代谢综合征的最佳切点是从82.5到83.5 cm,腰围与身高的比值最佳切点为从0.52到0.53。
在女性,WHtR预测糖尿病和血脂异常的AUC值高于WC和BMI,预测高血压和代谢综合征时,WHtR和WC的AUC值相似,两者均高于BMI。在男性,WHtR预测糖尿病和代谢综合征的AUC值高于WC和BMI；预测血脂异常时,WHtR和WC的AUC值相似,两者均高于BMI；然而,预测高血压时,BMI的AUCA值高于WHtR。
在女性BMI, WC和WHtR预测高血压、糖尿病和代谢综合征的AUC值均高于男性,预测血脂异常时无差别。然而,在女性WC和WHtR预测高血压和代谢综合征的AUC值明显高于男性。
结论
在中国山东地区在男性和女性超重的BMI切点24.5 kg/m2,腹型肥胖的腰围切点男性为88.5 cm,女性为83.5 cm,在男性和女性WHtR的最佳切点为0.52。在男女两性,与体重指数相比,反映中心性肥胖的指标,特别是腰围和身高比值与肥胖相关的心血管危险因素联系更密切,在男性高血压例外。
创新点
1,在山东地区首次开展对代谢综合征和糖尿病的大型流调,找出预测糖尿病、高血压、代谢综合征和血脂异常的最佳切点。
2,对中心性肥胖和全身性肥胖进行比较,发现中心性肥胖,特别是腰围身高比值在中国人群中与糖尿病和代谢综合征联系更密切。
Background
Historically, the glucose measurement has been used to diagnose diabetes. Measurement of haemoglobin Ale (HbAlc) level is an integrated measure of circulating glucose levels and tracks well in subjects over time. Epidemiological studies have shown that HbAlc levels in nondiabetic adults can predict incident diabetes, cardiovascular disease morbidity and mortality, and total mortality. A reliable measure of chronic glycemic levels such as measurement of HbAlc levels, which captures the degree of glucose exposure over time and is related more intimately to the risk of complications than measurement of single or episodic measures of glucose levels, may be a better biochemical marker of diabetes and should be considered a diagnostic tool. Therefore, HbAlc≥6.5% was defined as one of the criteria for the diagnosis of diabetes by the American Diabetes Association (ADA).
Objective
To examine the sensitivity and specificity of HbAlc testing for the diagnosis of type 2 diabetes in high-risk adults in China and to compare the cardiovascular risk factors between 2 groups of patients with glycemic status classified by the 2 different tests.
Research design and method
Subjects
We estimated the prevalence of diabetes among Chinese adults in a national study from June 2007 through May 2008 and conducted the current study in Jinan, Shandong. We included subjects above 45 years but without diagnosed diabetes. The Ethics Committee of the Qilu Hospital approved the protocol. Informed consent was obtained from all volunteers.
Study design
After an overnight fast, participants underwent the oral glucose tolerance test (OGTT), and fasting and 2-h glucose levels were measured; a questionnaire was completed to document the presence of hypertension, cardiovascular disease, and whether there was a first-degree relative with diabetes. Height and weight were measured, body mass index (BMI) was calculated, and blood pressure was measured as described. Blood samples were taken from the antecubital vein for measurement of fasting plasma glucose (FPG) and levels of HbAlc, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), triglycerides (TG) and high-density lipoprotein cholesterol (HDL-c). Plasma glucose was measured by the glucose dehydrogenase method and levels of HbAlc by high-performance liquid chromatography, TC by the cholesterol oxidase method, TG by the enzymatic method and HDL-c by the direct method. LDL-c level was calculated by the Friedewald equation for subjects with triacylglycerol concentrations< 4.53 mmol/L:LDL-c=(total cholesterol-HDL-c-triacylglycerols)/5.
Following 2009 ADA criteria, subjects were classified into 4 groups as follows: OGTT-diabetes (FPG≥7.0mmol/l or 2-h PG≥11.1mmol/l; HbAlc-diabetes (HbAlc leve1≥6.5%); true-diabetes (both criteria positive); non-diabetes (neither of the criteria positive).
HbAlc level for diagnosis was evaluted by sensitivity (percentage of subjects with OGTT-diabetes and a positive HbAlc screening test), specificity (percentage of subjects without OGTT-diabetes and a negative screening test), positive predictive value (PPV) (percentage of subjects with a positive HbAlc screening test with OGTT-diabetes), negative predictive value (NPV) (percentage of subjects with a negative screening test without OGTT-diabetes). To understand which test could best predict cardiovascular risk factors, we compared blood pressure, BMI and levels of TC, TG, LDL-c, and HDL-c among the 4 groups (true-diabetes, OGTT-diabetes, HbA1c-diabetes, nondiabetes).
Statistical methods
Analyses involved use of SPSS v11.5 for Windows (SPSS Inc., Chicago, IL). General characteristics of patients are summarized with means±SD for continuous data, median (interquartile range) for TG and HDL-C levels, and number (%) for categorical data. To compare the TG and HDL-C levels among the 4 groups, the Wilcoxon rank sum and Kruskal-Wallis tests were used. To compare blood pressure, BMI, TC, and LDL-C levels among the 4 groups, we used analysis of covariance, with age as a covariate to adjust for potential confounding, and obtained least-square means±SE. Two-sided p values of＜0.05 were considered significant. The receiver operating characteristic was used to describe the sensitivities and specifities of the HbA1c test in determining the presence of type 2 diabetes as defined by the OGTT.
Results
We included 701 subjects with mean age 52±11 years (range 21-83 years) (392 [56%] women). The mean BMI was 26±3 kg/m2, and HbA1c level was 5.34±0.61%.
Among 701 high-risk subjects who underwent OGTT,94 (13%) had diabetes, and 236 (34%) had pre-diabetes. Among the same 701 high-risk subjects who underwent HbA1c testing,65 (9%) had diabetes, and 123 (18%) pre-diabetes, so OGTT could detect more diabetic patients than HbA1c.
The area under the receiver operating characteristics curve for detecting undiagnosed diabetes was 0.843 (95% confidence interval 0.798 to 0.888) for HbA1c (figurel). Compared with the OGTT, with HbAlc≥5.1%, the sensitivity was 98.7% and specificity 33%, PPV 18% and NPV 99%(Table 1). With HbAlc≥7.0%, the sensitivity was 24% and specificity 99.7%, PPV 92%, and NPV 89%. With HbAlc≥6.5%, the sensitivity was 48.2% and specificity 97.8%, PPV 69% and NPV 92%.
There was not full concordance between HbAlc and OGTT (Table 2).30.7% of participants with HbAlc≥6.5% were classified as non-type 2 diabetes by OGTT criteria, and 52% subjects with type 2 diabetes according to the OGTT criteria had HbAlc<6.5%.
To compare HbAlc and OGTT criteria with a type 2 diabetes complication, we considered cardiovascular risk factors.
Subjects in the 3 diabetes groups were older than those in the non-diabetes group (Table 3). When adjusting for age, the values of every risk factor measured varied among the 4 groups with the exception of diastolic pressure and HDL-c concentrations. All risk factors, except for diastolic pressure, were higher for the true-diabetes group than for the nondiabetes group. All lipid levels, except HDL-c, were higher for the HbAlc-and OGTT-diabetes groups than for the nondiabetes group, with no difference between the HbAlc-and OGTT-diabetes groups.
Conclusions
We found high specificity and low sensitivity with use of HbAlc level≥6.5% to diagnose diabetes mellitus. The HbAlc test and OGTT did not reach full concordance. The 2 diagnostic criteria reflect similar levels of cardiovascular risk factors.
Our results showed diabetes prevalence lower with the HbAlc-based diagnostic method than the OGTT criteria, we found HbAlc and OGTT criteria without full concordance. In the present study,30.7% of participants with A1C≥6.5% were not classified as diabetic by OGTT criteria and 52% of the participants with diabetes by OGTT criteria would be classified as normoglycemic by AlC; the corresponding probability of AlC≥6.5% among diabetic case subjects based on an OGTT was 68.3% in our study, which was higher than in Denmark, the U.K., Australia, Greenland, Kenya study(17-42%).
To compare HbAlc and OGTT criteria with a type 2 diabetes macro vascular complication, we considered cardiovascular risk factors., In our data, levels of cardiovascular risk factors were similar for the HbAlc- and OGTT-diabetes groups and higher in the 2 groups than in the non-diabetes group. To our knowledge, this is the first study of cardiovascular risk factors between HbAlc- and OGTT-diagnosed subjects with diabetes.
According to our data, only performing HbAlc instead of OGTT would miss 52% of those who are diabetes and have higher levels of cardiovascular risk factors.On the other hand, only performing OGTT would miss 30.7% of those with high HbAlc levels who are possibly diabetic retinopathy, so there is no single assay for hyperglycemia that can be considered the gold standard.
In conclusion, the limited sensitivity of the AlC test may miss about half of patients who are diabetes and have higher levels of cardiovascular risk factors among Chinese.
Background
About 60.7% of diabetic subjects remain undiagnosed because most of them have not typical symptoms in early stage of the disease.The diabetic microvascular or macrovascular complications have already existed in early stage, even in pre-diabetes stage, and some clinical trials have shown the diabetes and its complications could be delayed or even prevented by early interferences, so the diagnoses should be done as earlier as possible.
The guideline screening for diabetic subjects in high-risk individuals has been presented by 2009 ADA, either fasting plasma glucose (FPG)≥7.0mmol/L or 2-h postload glucose (2hPG)≥11.lmmol/L define diabetes independently. The FPG level is easy to obtain and can be used for diabetes screening criteria, however, subjects with FPG<7.0mmol/Land diagnosed by the 2hPG criteria were ignored and a part of diabetes could not be detected.. OGTT is time wasting and inconvenient,so it is difficult to get physicians and patients to use the oral glucose tolerance test (OGTT). HbAlc has been suggested as the diagnostic or screening criteria for diabetes, however, several studies have shown diabetes prevalence was lower with the HbA1c-based diagnostic criteria. Using FPG and HbAlc screening diabetes were reported by several articles, but the IFG criteria were 6.1-6.9mmol/L and old diagnostic criteria only FPG>7.0mmol/L or 2-h postload glucose (2hPG)≥11.lmmol/L were used.Using 2010 ADA criteria, individuals with HbAlc≥6.5%, FPG≥7.0mmol/L or 2-h postload glucose (2hPG)≥11.1mmol/L can be diagnosed as diabetes independently, we evaluated whether the combination of FPG and HbA1c measurements enhanced the detection of diabetes in high-risk individuals.
1.Objective
The aim of this study was to evaluate the use of HbA1c and FPG as predictors of type 2 diabetes and, accordingly, to develop a rational approach to screening for type 2 diabetes.
2. Methods
2.1 Subjects
The national study from June 2007 through May 2008 to estimate the prevalence of diabetes among Chinese adults was conducted in China, and we conducted the study in Jinan and Zibo, Shandong. We collected individuals with risk factors for diabetes but without diagnosed diabetes from the total people. According to 2009 ADA,700 adults who were above 45years were included(5). The Ethics Committee of the Qilu Hospital approved the protocol. Informed consent was obtained from all individuals.
2.2 Study design
After an overnight fast, participants underwent an oral glucose-tolerance test, and fasting and 2-hour glucose levels were measured, detailed method has been reported (15). we measured HbAlc in the high-risk individuals. HbA1c was measured by high-pressure liquid chromatography, plasma glucose was measured by glucose dehydrogenase method. Using 2010 ADA criteria (14)，Participants were classified as having diabetes if they had either HbAlc≥6.5% or FPG≥7.0mmol/L or 2hPG≥11.1mmol/L, FPG<5.6 mmol/L= normal fasting glucose(NFG); FPG 5.6-6.9 mmol/1 = IFG (impaired fasting glucose); 2-h postload glucose<7.8 mmol/L = normal glucose tolerance (NGT);2-h postload glucose 7.8-11.1 mmol/L = IGT (impaired glucose tolerance).
2.3 Statistical methods
Data are presented as mean±SD. Receiver operating characteristic curves were constructed to calculate sensitivity and specificity of HbAlc cut points for type 2 diabetes diagnosis.Cut points were defined as that point on the curve where the sum of sensitivity and specificity was highest. Comparisons between groups were performed using the chi-square test for categorical data.
3. Results
A total of 700 subjects aged 21-83 years (52±11) were studied. There were 392 (56%) women and 308 (44%) men.The body mass index was 26±3 kg/m2.
3.1 The data of using FPG to screening diabetes were presented in table 1. There were 93 diabetes were detected, among them 46 subjects with FPG≥7.0mmol/L,47 diabetes with FPG< 7.0mmol/L.According to ROC analysis(figure 1), FPG≥5.6mmol/L predicted diabetes with a sensitivity of 78.0% and a specificity of 73.3%. FPG levels<4.8mmol/L and≥6.7mmol/L have 98.7% and 99% accuracy for predicting the absence and presence of type 2 diabetes, respectively. Based on the above results and reference (14), FPG was divided into the following groups:≥7.0mmol/L, 6.9-5.6mmol/L, 5.5-4.8mmol/L, and <4.8mmol/L (table 1). At FPG 6.9-5.6mmol/L, in order to find 35 patients with diabetes,193 people need to do OGTT; at FPG5.5-4.8mmol/L, in order to find 9 patients with diabetes, 368 people need to do OGTT. While 92 individuals with FPG<4.8mmol/L need not to do OGTT and can be rule out diabetes directly.
3.2 The data of using HbA1c to screening diabetes were presented in table2. There were 98 diabetes were detected, among them 54 subjects with HbA1c≥6.5%,44 diabetes with HbA1c<6.5%. According to ROC analysis(figure 1), HbA1c≥5.6% predicted type 2 diabetes with a sensitivity of 86.0% and a specificity of 77.0%. HbA1c levels<5.0 and >6.5% have 98.7% and 99% accuracy for predicting the absence and presence of type 2 diabetes, respectively. Based on the above results and references(7,8), HbA1c was divided into the following groups:≥7.0%,6.9-6.5%,6.4-5.6%(impaired HbA1c),5.5-5.0%,<5.0%. (table 2). At HbA1c 5.6-6.4%, in order to find 30 patients with diabetes,157 people need to do OGTT; and at HbA1c 5.0-5.5%, in order to find 7 patients with diabetes,203 people need to do OGTT. While 284 individuals with HbAlc<5.0% do not need to do OGTT and can be rule out diabetes directly.
33 The data of using FPG +HbA1c to screening diabetes were presented in table 3. There were 98 diabetes were detected, among them 64 subjects with HbA1c≥6.5% or FPG>7.0mmol/L, these people can be diagnosed as diabetes directly. Based on figure 1 results, we used HbA1c screening for diabetes in 179 IFG group. In individuals with HbAlc5.6-6.4%, in order to find 18 patients with diabetes, 68 people need to do OGTT; in individuals with HbAlc 5.5-5.0%, in order to find 6 patients with diabetes, 64 people need to do OGTT; while 47 individuals with HbAlc<5.0% do not need to do OGTT and can be rule out diabetes directly. We also used HbAlc to screen diabetes in individuals with FBG<5.6mmol/L. In individuals with HbAlc5.6-6.4%, in order to find 8 patients with diabetes, 80 people need to do OGTT; 372 individuals with HbAlc<5.6% do not need to do OGTT and can be rule out diabetes directly.
3.4 The comparison of three methods to screen diabetes were presented in table 4. According to FPG, 49.5% patients with diabetes were directly diagnosed, and 14% individuals with risk factors for diabetes can be directly rule out diabetes, in order to find 82 patients with diabetes, 193 people need to do OGTT; while according to HbAlc or FPG+HbAlc, 52.7%, and 65.3% patients with diabetes were directly diagnosed respectively, and 40% and 60.5% individuals with risk factors for diabetes can be directly rule out diabetes, according to HbAlc, in order to find 88 patients with diabetes, 158 people need to do OGTT, according to FPG+HbAlc in order to find 82 patients with diabetes, only 68 people need to do OGTT. More patients with diabetes were directly diagnosed by FPG+HbAlc than by FPG(P<0.05), and more individuals with risk factors for diabetes were directly rule out diabetes by FPG+HbAlc than by FPG or HbAlc(P<0.01). FPG+HbAlc significantly reduced the number of people to do OGTT.
4 Conclusion
FPG combined with HbA1c may be a useful strategy to identify diabetes in individuals with risk factors for diabetes.
According to our result, we can advice the procedure for diabetes screening as the following:1) give measurements of FPG and HbA1c in the individuals with high-risk factors defined by 2009 ADA,2) If FP≥7.0mmol/L or HbAlc≥6.5%,the individuals have diabetes; 3) if FBG< 4.8mmol/L or HbAlc<5.0%, or FPG<5.6mmol/L and HbAlc 5.5-5.0%, diabetes can be excluded.4) if FPG 5.6-6.9mmol/L and HbAlc 5.6-6.4%, OGTT is needed to find diabetes;5) if only IFG or impaired HbAlc, refering the high-risk factors, the more risk factors for diabetes the greater the likelihood should be.
Backgroud
Obesity is a major risk factor for cardiovascular diseases and diabetes. Prospective epidemiological studies have shown increased body mass index (BMI) and waist circumference (WC) to be independent risk factors for type 2 diabetes mellitus, coronary artery disease (CAD), and hypertension. However, the definition of obesity lacks consensus, as does the specific aspects of obesity that contribute to cardiovascular disease. The major disagreement centers on whether it is the total amount or the distribution of adipose tissue that confers a greater risk of cardiovascular disease. Epidemiologic studies have shown that body mass index (BMI), a general measure of obesity, is a powerful predictor of cardiovascular disease. However, a growing body of evidence indicates that waist circumference (WC)—measure of central obesity—also provides information on the risk of cardiovascular disease, and other visceral adiposity measures such as ratio of waist to height (WHtR) appear to be better predictors of cardio-metabolic risk factors than BMI. Many studies of the association of total amount or distribution of adipose tissue and cardiovascular risk factors are performed in the United States and Europe; few data are from mainland China, so knowledge of risk factors are lacking in China.
Objective
We aimed to evaluate the predictive value of the body mass index (BMI), waist circumference (WC), and ratio of waist to height (WHtR) for the presence of several cardiovascular risk conditions -- hypertension, dyslipidemia, metabolic syndrome, and type 2 diabetes--in a Chinese population in Jinan, China.
Methods
Study Participants
The China National Diabetes and Metabolic Disorders Study, conducted from June 2007 through May 2008, was a cross-sectional study designed to provide current, reliable data on the prevalence of diabetes and associated metabolic risk factors in the adult population in China13; we completed the survey in Jinan, Shandong. We used a stratified sampling method to select a representative sample of the general population in 6 districts of Jinan, Shandong. A total of 3400 individuals aged 20-74 years took part in the survey. At elephone appointment was made a week before the survey, and all participants received an agenda the day before the survey. After excluding data for 18 people lacking data on 2-hr plasma glucose levels, we included data for 3,006 people in the final analysis. The participants were mainly of Han ethnicity. The Ethics Committee of Qilu Hospital Shandong University approved the protocol. Informed consent was obtained from all subjects.
After fasting overnight, subjects were required to arrive at the community clinic in every district before 7:00 and were asked to complete a questionnaire to document the presence of hypertension, cardiovascular disease, diabetes and the treatment of these diseases.
Blood pressure and anthropometric measurements
Blood pressure, body weight, height, and WC were measured by standard methods 14. Body mass index was calculated as weight (Kg) divided by height squared (m2). Trained technicians performed the interview in community clinics in the subjects'residential areas.
Laboratory tests
A blood sample was drawn from the antecubital vein for measuring fasting plasma glucose (FPG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), triglycerides (TGs) and high density lipoprotein cholesterol (HDL-C). Thereafter, subjects received 75 g glucose orally, and 5 ml blood was collected at 2 hr for measurement of plasma glucose. Plasma glucose was measured by the glucose dehydrogenase method, TC by the cholesterol oxidase method, TGs by the enzymatic method and HDL-C by the direct method; LDL-C concentrations were calculated by the Friedewald equation.
Statistical analysis
Data for subjects were analyzed separately by sex. Additionally, we analyzed high-risk age groups as defined by the American Diabetes Association16 with the ages≥45 yr in men and women. Continuous variables are expressed as mean±SD, and discrete variables are expressed as numbers and percentages. Comparisons between groups involved Student t test for continuous variables and chi-square test for categorical data. Sensitivity and specificity were examined by ROC analysis, and the areas under the ROC curve (AUC) cut-off values were calculated for each anthropometrical parameter and risk condition. An AUC of 1 indicates perfect separation between affected and nonaffected subjects, and an AUC of 0.5 indicates no discriminative value of the test. Individual cutoffs were defined as the point on the curve where the sum of sensitivity and specificity was highest. All data analyses involved use of SPSS v11.5 (SPSS Inc., Chicago, IL). Differences between 2 AUCs were tested with Z values: with Z> 1.96, P is< 0.05, and with Z> 2.58, P is< 0.01. For the comparison of corresponding AUCs for males and females, Z=(AA-AB)/√(SEA2+SEB2), where SE is standard error; for comparing AUCs for anthropometric indicators in predicting the same binary condition17, Z=(AA-AB)/√(SEA2+SEB2-2γSEA SEB), whereγis the correlation coefficient of AA and AB.
Results
Basic characteristics of the study subjects
The characteristics of the study sample are in Table 1. Mean BMI, WC, WHtR, systolic and diastolic blood pressures, FPG, HDL-C, LDL-C, TG, and TC were higher among men than women. The age and 2-hr plasma glucose of OGTT were similar between women and men. The prevalence of metabolic syndrome and hypertension was higher in men than women, that of diabetes and dyslipidemia was similar between men and women (Table 1), and the prevalence increased in the high-risk age groups.
Anthropometric variables and cardiovascular risk conditions The AUC cutoff values are in Table 2 for men and women. For men, the optimal cutoffs for BMI associated with hypertension, diabetes, dyslipidemia, and metabolic syndrome ranged from 24.5 to 25 kg/m2, for WC from 87.5 to 89.5 cm, and for WHtR from 0.52 to 0.53. For women, the optimal cutoffs for BMI varied from 24.5 to 25 kg/m2, for WC from 82.5 to 83.5 cm, and for WHtR from 0.52 to 0.53.
ROC curves for the discriminating hypertension, diabetes, dyslipidemia, and metabolism syndrome by BMI, WC, and WHtR for males and females are in Figures 1-8) and their associations is in Table 3.
For women, regarding diabetes and dyslipidemia, the AUC values for WHtR were significantly higher than for WC and BMI; regarding hypertension and metabolism syndrome, the AUC values for WHtR and WC were were similar, and both were higher than for BMI.
For men, regarding diabetes and metabolic syndrome, the AUC values for WHtR were significantly higher than for WC and BMI; regarding dyslipidemia, the AUC values for WHtR and WC were similar, and both were higher than for BMI. However, regarding hypertension, the AUC value for BMI was significantly higher than for WHtR. In the high-risk age groups, there were significant differences for dyslipidemia for females, and for diabetes and metabolic syndrome for males.
The AUC values for BMI, WC, and WHtR were all higher for women than for men for all risk factors except dyslipidemia; however, the AUC values for WC and WHtR were significently higher for women than men only for hypertension and metabolic syndrome.
Conclusions A BMI of 24.5 kg/m2 for both men and women, a WC of 88.5 cm for men and 83.5 cm for women, and a WHtR of 0.52 for both men and women were found optimal cutoffs for defining overweight and central adiposity in this population. As compared with BMI, measures of central obesity, particularly WHtR, show a better association with obesity-related cardiovascular risk conditions for both sexes, except for hypertension in males, in Shandong, China.
传统上用血浆葡萄糖诊断糖尿病。糖化血红蛋白反映近期3个月的血浆葡萄糖水平。流行病学研究显示在非糖尿病成人中糖化血红蛋白水平可以预测糖尿病的发生、心血管疾病的发生和死亡率。糖化血红蛋白反映一段时间内的血浆葡萄糖水平,与糖尿病慢性并发症的相关性比单次血浆葡萄糖水平更强,因此可能是糖尿病诊断的更好的生化指标,可以作为诊断标准之一。2009年美国糖尿病协会在糖尿病的诊疗标准中规定糖化血红蛋白大于等于6.5%可以诊断糖尿
目的
在中国的高危人群中以OGTT为金标准检验糖化血红蛋白诊断糖尿病的敏感性、特异性和一致性,并对两种诊断结果不同人群的心血管危险因素进行比较,以了解哪个标准更能预测心血管危险因素。
研究设计和方法
研究对象：从2007年6月至2008年5月,我们完成了山东省的《全国糖尿病及代谢综合征调查》工作,研究方案经过齐鲁医院伦理委员会通过,所有受试者均签署知情同意书。我们选择其中年龄大于45岁的未诊断糖尿病的701人。
研究设计：患者空腹至少8小时,做口服葡萄糖耐量试验,测定空腹血浆葡萄糖和2小时血浆葡萄糖。填问卷调查表,其中包括高血压,心血管疾病和糖尿病家族史等内容。测身高、体重,并计算体重指数(BMI),测血压。取静脉血测定空腹血浆葡萄糖和糖化血红蛋白,总胆固醇(TC),低密度脂蛋白胆固醇(LDL-c),甘油三酯(TG)和高密度脂蛋白胆固醇(HDL-c).用葡萄糖脱氢酶方法测定血浆葡萄糖水平,用高压液相色谱仪(HPLC)测定HbAIC。
根据2009年ADA诊断标准,将受试者分为4组：真糖尿病组(两种方法均阳性),OGTT-糖尿病(空腹血浆葡萄糖水平大于等于7. Ommol/L或2小时血浆葡萄糖水平大于等于11. lmmol/L), HbAlc-糖尿病(糖化血红蛋白水平大于等于6.5%),非糖尿病(两种方法均阴性)。
以口服葡萄糖耐量试验为金标准,用敏感性(OGTT阳性患者中HbAlc也阳性者所占的百分比)、特异性(OGTT阴性患者中HbAlc也阴性者所占的百分比)、阳性预测率(HbAlc阳性患者中OGTT也阳性者所占的百分比)、阴性预测率(HbAlc阴性患者中OGTT也阴性者所占的百分比)评价糖化血红蛋白诊断糖尿病的价值。为了了解两个标准哪一个能更好的预测心血管危险因素,我们对四组人群(真糖尿病组,OGTT-糖尿病组,HbAlc-糖尿病组,非糖尿病组)的血压、体重指数、总胆固醇水平、甘油三酯、高密度脂蛋白胆固醇和低密度脂蛋白胆固醇水平进行了比较。
统计学方法
用SPSS v11.5 (SPSS Inc., Chicago, IL)完成统计学分析.连续性正态分布资料用均数加减标准差表示,偏态分布资料用中位数表示(甘油三酯,高密度脂蛋白胆固醇),分类资料用百分数表示。用Wilcoxon rank sum和Kruskal-Wallis tests比较四组中甘油三酯和高密度脂蛋白胆固醇水平。年龄为协变量,用协方差分析比较四组中血压、体重指数、总胆固醇水平和低密度脂蛋白胆固醇水平,双侧P值小于0.05.为有统计学差异。用ROC曲线描述糖化血红蛋白检测OGTT糖尿病的敏感性和特异性。
结果
共检测701人,平均年龄52±11岁(45-83岁)(女性392[56%]).平均体重指数26±3 kg/m2,糖化血红蛋白水平5.34±0.61%。
在701个进行口服葡萄糖耐量试验的人中,检出94(13%)个糖尿病患者,236(34%)个糖尿病前期患者。在同样的人群中进行糖化血红蛋白测定,根据糖化血红蛋白大于等于6.5%诊断糖尿病,检出65(9%)的糖尿病患者,123(18%)个糖尿病前期患者,所以口服葡萄糖耐量试验比糖化血红蛋白测定能检出更多的糖尿病患者。
用糖化血红蛋白预测OGTT-糖尿病ROC曲线下面积为0.843(95%的可信区间为0.798-0.888)。糖化血红蛋白大于等于5.1%预测糖尿病的敏感性为98.7%,特异性为33%,阳性预测值为18%,阴性预测值为99%。糖化血红蛋白大于等于7.0%时,预测糖尿病的敏感性为24%,特异性为99.7%,阳性预测率为92%,阴性预测率为89%。糖化血红蛋白大于等于6.5%预测糖尿病的敏感性为48.2%,特异性为97.8%,阳性预测率69%,阴性预测率92%。糖化血红蛋白和口服葡萄糖耐量试验两种诊断方法不完全一致。糖化血红蛋白大于等于6.5%的患者中30.7%未达到口服葡萄糖耐量试验诊断标准,52%的口服葡萄糖耐量试验诊断的糖尿病患者糖化血红蛋白小于6.5%,未达到糖化血红蛋白诊断糖尿病的标准。
为了比较糖化血红蛋白测定和口服葡萄糖耐量试验与糖尿病并发症的关系,我们比较了四组人群的心血管危险因素,尤其关注两种诊断方法结果不一致的人群,以判断哪种诊断方法更能反映心血管病因素。三组糖尿病人群的年龄均大于非糖尿病组,校正了年龄的影响后,四组人群中除了舒张压和高密度脂蛋白胆固醇,其余的危险因子水平有明显区别。除了舒张压,真糖尿病组(两种方法均阳性)的所有心血管危险因素均高于非糖尿病组。除了高密度脂蛋白胆固醇和舒张压,HbAlc-and OGTT-糖尿病组所有的血脂水平、体重指数和收缩压均高于非糖尿病组,而两组的心血管危险因素水平没有差别。
结论
通过本研究,我们发现与OGTT比较,糖化血红蛋白大于等于6.5%做诊断糖尿病的标准特异性高,敏感性低。糖化血红蛋白测定和口服葡萄糖耐量试验两种诊断方法不完全一致。两种诊断标准反映了相同的心血管危险因子水平。
我们的结果显示用糖化血红蛋白做诊断标准较OGTT检出的糖尿病患者减少,两者不一致。本研究中,糖化血红蛋白大于等于6.5%的患者中30.7%未达到口服葡萄糖耐量试验诊断标准,52%的口服葡萄糖耐量试验诊断的糖尿病患者糖化血红蛋白小于6.5%,未达到糖化血红蛋白诊断糖尿病的标准。本研究中糖化血红蛋白大于等于6.5%诊断糖尿病与OGTT的一致性为68.3%。
根据我们的数据,心血管危险因子水平在HbAlc-和OGTT-糖尿病组水平相似而且都高于非糖尿病组。这是第一个比较HbAlc-和OGTT-糖尿病两组患者心血管危险因子的研究。
根据我们的结果,用糖化血红蛋白测定代替OGTT试验将导致52%的OGTT糖尿病漏诊,这些患者已经存在较高的心血管危险因子水平。另一方面,只做OGTT试验将使30.7% HbAlc-糖尿病漏诊,这些患者可能已经存在糖尿病视网膜病变。所以没有哪一种方法可以作为诊断糖尿病的金标准。
总之,在中国高危人群中,糖化血红蛋白测定诊断糖尿病敏感性有限,用它代替OGTT将使大约一半的已经存在心血管危险因子的患者漏诊。
创新点和和限制性
创新点：
1),本课题对糖化血红蛋白诊断糖尿病进行了系统研究,并对两种诊断方法的一致性进行研究。
2),本研究首次比较了两种诊断标准不一致人群的心血管危险因素水平,得出两者相似的结论。
3)根据以上结果首次得出结论：用糖化血红蛋白测定代替口服葡萄糖耐量试验将使大约一半已经存在心血管危险因子的患者漏诊。
限制性
1)由于条件所限,例数较少。
2)本课题为横断面研究,所以缺乏预测性,有条件应进行前瞻性研究。
背景
在中国大约60.7%的糖尿病患者没有确诊,因为他们中的大多数在疾病早期没有明显症状。糖尿病大血管和微血管并发症在疾病的早期甚至在糖尿病前期已经存在,中国的大庆研究和国外的研究均证实提前发现高危人群并进行饮食及生活方式的干预可以有效防止糖尿病的发生发展,可以有效预防并发症,所以早发现早诊断成为预防及治疗糖尿病及其并发症的关键。
现有的糖尿病诊断标准为空腹血浆葡萄糖大于等于≥7.Ommol/L或葡萄糖负荷后2小时血浆葡萄糖大于等于≥11.1mmol/L.空腹血浆葡萄糖较容易测定,可用于糖尿病的筛查,但是空腹血浆葡萄糖小于7.Ommol/L的患者往往被漏诊,中国目前单独2小时血浆葡萄糖大于等于11.lmmol/L的患者所占比例为46.6%。口服葡萄糖耐量试验费时又不方便操作,临床不易被患者接受。研究发现糖化血红蛋白与糖尿病特异性视网膜病变联系更密切,最近国际专家委员会建议将糖化血红蛋白做为诊断标准之一。然而一些研究提示以糖化血红蛋白做诊断标准,与口服葡萄糖耐量试验相比检出的糖尿病患者会减少。一些研究报告了空腹血浆葡萄糖结合糖化血红蛋白筛查糖尿病的结果,但是他们所用的空腹血糖受损的标准为6.1-6.9mmol/L，诊断糖尿病的标准为空腹血浆葡萄糖大于等于7.Ommol/L或2小时血浆葡萄糖大于等于11.lmmol/L。我们的研究用2009年美国糖尿病协会新标准：糖化血红蛋白大于等于6.5%,或空腹血浆葡萄糖大于等于7.Ommol/L,或2小时血浆葡萄糖大于等于11.lmmol/L。用新标准诊断糖尿病,我们评价空腹血浆葡萄糖结合糖化血红蛋白测定是否提高糖尿病的检出率,以找出一个简单易行的筛查糖尿病的方法。
研究目的
评价空腹血浆葡萄糖结合糖化血红蛋白是否能提高糖尿病的检出率,并据此找出更可行的筛查糖尿病的方法。
1研究设计和方法
1.1研究对象
从2007年6月至2008年5月,我们完成了山东省的《全国糖尿病及代谢综合征调查》工作,研究方案经过齐鲁医院伦理委员会通过,所有受试者均签署知情同意书。我们选择年龄大于45岁的未诊断糖尿病的700人。
1.2研究设计
患者空腹至少8小时,做口服葡萄糖耐量试验,测定空腹血浆葡萄糖和2小时血浆葡萄糖。填问卷调查表,其中包括高血压,心血管疾病和糖尿病家族史等内容。测身高、体重,并计算体重指数(BMI),测血压。取静脉血测定空腹血浆葡萄糖和糖化血红蛋白,总胆固醇(TC),低密度脂蛋白胆固醇(LDL-c),甘油三酯(TGs)和高密度脂蛋白胆固醇(HDL-c).用葡萄糖脱氢酶方法测定血浆葡萄糖水平,用高压液相色谱仪(HPLC)测定HbAIC。
采用2009美国糖尿病协会新标准：糖尿病诊断标准：糖化血红蛋白大于等于6.5%,或空腹血浆葡萄糖大于等于7. Ommol/L,或2小时血浆葡萄糖大于等于11. lmmol/L。空腹血糖受损：空腹血浆葡萄糖在5.6-6.9 mmol/1之间;葡萄糖耐量受损：葡萄糖负荷后2小时血浆葡萄糖7.8-11.1 mmol/L
1.3统计学方法
用SPSS vll.5 (SPSS Inc., Chicago, IL)完成统计学分析.连续性正态分布资料用均数加减标准差表示。用ROC曲线计算空腹血糖和糖化血红蛋白预测OGTT糖尿病的敏感性、特异性和切点。敏感性和特异性之和最大处即为最佳切点。分类资料的比较用chi-square test。
2结果
共检测700人,平均年龄52±11岁(45-83岁)(女性392[56%]).平均体重指数26±3 kg/m2,糖化血红蛋白水平5.34±0.61%.
2.1用空腹血浆葡萄糖筛查糖尿病的结果。共检出93个OGTT糖尿病,其中46人FPG≥7.Ommol/L,47人空腹血浆葡萄糖小于7. Ommol/L。根据ROC曲线分析结果,空腹血浆葡萄糖大于等于5.6mmol/L为预测2小时OGTT糖尿病的最佳切点,在此切点敏感性为78.0%,特异性为73.3%。空腹血浆葡萄糖小于4.8mmol/L有98.7%的准确性排除糖尿病,空腹血浆葡萄糖大于等于6.7mmol/L有99%的准确性诊断2小时OGTT糖尿病。根据以上结果,将研究对象根据空腹血浆葡萄糖分为以下4组：FPG≥7.Ommol/L,6.9-5.6mmol/L,5.5-4.8mmol/L,和<4.8mmol/L(表1)。在FPG 6.9-5.6mmol/L组,为了检出35个糖尿病患者,需要给193个人做OGTT;在FPG 5.5-4.8mmol/L组,为了检出9个患者,368人需要做OGTT,而FPG<4.8mmol/L组的92人中只有一位糖尿病患者,故可以不做OGTT直接排除糖尿病。
2.2用糖化血红蛋白筛查糖尿病的结果。共检出98位糖尿病,其中54人糖化血红蛋白大于等于6.5%可以直接诊断糖尿病,44位糖化血红蛋白小于6.5%。根据ROC曲线分析结果(图1),糖化血红蛋白大于等于5.6%预测OGTT糖尿病的敏感性为80.0%,特异性为77.0%。糖化血红蛋白小于5.0%排除糖尿病的准确性达到98.7%。根据以上资料和参考文献,将研究对象分为以下4组,HbAlc≥6.5%,6.4-5.6%,5.5-5.0%,和<5.0%.(表2).在HbAlc5.6-6.4%组,为了检出30位糖尿病,157人需要做OGTT,在HbAlc 5.0-5.5%组,,为了检出7位糖尿病,203人需要做OGTT。285糖化血红蛋白小于5%的人中只有2位糖尿病,可以不需要做OGTT直接排除糖尿病。
2.3用FPG +HbAlc筛查糖尿病的结果。共检出98位糖尿病,其中64位糖化血红蛋白大于等于≥6.5%或者空腹血浆葡萄糖大于等于7. Ommol/L,这些人可以直接诊断糖尿病。在179个空腹血糖受损的人中,当HbAlc5.6-6.4%时,为了检出18位糖尿病患者,68人需要做OGTT;当HbAlc 5.5-5.0%时,为了检出6个糖尿病患者,64人需要做OGTT,而47位糖化血红蛋白小于5%的人不需要做OGTT可以直接排除糖尿病。在空腹血浆葡萄糖小于5.6 mmol/L的人中,当HbAlc5.6-6.4%时,为了检出8个糖尿病患者,80人需要做OGTT：377位糖化血红蛋白小于5.6%的人中只有2个糖尿病患者,可以不做OGTT而直接排除糖尿病。在此组研究者中,共有424位不需要做OGTT直接排除糖尿病。
2.4对3种筛查糖尿病的方法进行比较。根据空腹血浆葡萄糖筛查糖尿病,49.5%的患者可以直接确诊,14%高危人群可以直接排除糖尿病,为了检出82个糖尿病患者,193人需要做OGTT;而根据糖化血红蛋白或者FPG+HbAlc筛查糖尿病,52.7%,和65.3%的糖尿病患者可以直接确诊,40%和61%的高危人群可以直接排除糖尿病,根据糖化血红蛋白筛查糖尿病,为了检出88位糖尿病患者,158人需要做OGTT,根据FPG+HbAlc筛查糖尿病,为了检出82位糖尿病患者,只有68人需要做OGTT。根据FPG+HbAlc可以比FPG直接诊断更多的糖尿病(P<0.05),并且根据FPG+HbAlc可以比FPG或HbAlc直接排除更多的糖尿病(P<0.01)。FPG+HbAlc可以明显减少做OGTT的人数。
3结论
FPG结合HbAlc是一个在高危人群中筛查糖尿病的有效方法。根据我们的结果,我们可以建议以下的方式筛查糖尿病：1)在高危人群中同时测定FPG和HbAlc,2)如果FPG≥7.Ommol/L或HbAlc≥6.5%,诊断糖尿病；3)如果FBG< 4.8mmol/L或HbAlc<5.0%,或者FPG<5.6mmol/L并且HbAlc 5.5-5.0%,可以直接排除糖尿病；4)如果FPG 5.6-6.9mmol/L并且HbAlc 5.6-6.4%,做OGTT; 5)如果只有IFG或HbAlc5.6-6.4%,,参考危险因素,越多发生糖尿病的可能性越大。
背景
肥胖是心血管疾病和2型糖尿病的重要危险因素之一。流行病学研究已经证明升高的体重指数和腰围是2型糖尿病、冠心病和高血压的独立危险因子。然而,肥胖的定义缺乏一致的标准,主要的分歧集中在全身性肥胖和脂肪组织分布异常哪一个是导致心血管疾病的主要原因。流行病学研究显示反映全身性肥胖的体重指数(BMI)是预测心血管疾病的有效指标,然而,一些研究表明反映中心性肥胖的指标腰围(WC)也能预测心血管疾病,并且其他的反映内脏脂肪的指标如腰围／身高(WHtR)比体重指数能更好的预测心血管及代谢指标异常。美国和欧洲关于这方面的研究较多,在中国尤其山东这方面的大型流行病学研究很少。
研究目的
在中国山东找出体重指数、腰围、腰围身高比值预测高血压、血脂异常、代谢综合征和2型糖尿病的最佳切点,并比较它们对高血压、血脂异常、代谢综合征和2型糖尿病的预测价值。
研究方法
研究人群
从2007年6月至2008年5月,我们完成了山东省的《全国糖尿病及代谢综合征调查》工作,研究方案经过齐鲁医院伦理委员会通过,所有受试者均签署知情同意书。采取分层抽样方法对山东省的济南、泰安、济宁以及淄博等地的自然人群就糖尿病及代谢综合征患病率进行了调查。共选取3700人,年龄20-74,3400人参加了调查,供本分析的完整资料为3006人。
受试者至少空腹8小时到指定医院,完成第一部分所示的调查问卷并进行各项检查。用标准方法测血压、体重、腰围,体重指数的计算方法：体重(千克)除以身高(米)的平方。
实验室检查
取静脉血测定空腹血浆葡萄糖,总胆固醇(TC),低密度脂蛋白胆固醇(LDL-c),甘油三酯(TGs)和高密度脂蛋白胆固醇(HDL-c).用葡萄糖脱氢酶方法测定血浆葡萄糖水平,然后口服75克葡萄糖,2小时取血测定血浆葡萄糖。用胆固醇氧化酶法测定总胆固醇,用酶法测定甘油三酯,用直接法测定高密度脂蛋白胆固醇,低密度脂蛋白胆固醇用Friedewald公式计算。
统计分析
男性女性资料分别统计。另外,对45岁以上的高危人群单独进行分析。连续变量用均数加减标准差表示,分类资料用百分数表示。组之间的比较连续变量用Student ttest,分类资料用chi-square tes。用ROC分析每个指标预测不同危险因素的敏感性、特异性,并找出最佳切点,用曲线下面积表示每个指标的预测价值。曲线下面积越大越好,曲线下面积为1时代表此指标在最佳切点能将正常者和异常者完全分开,曲线下面积为0.5时代表词指标没有预测价值。曲线上敏感性和特异性之和最大的点为最佳切点。用SPSS v11.5 (SPSS Inc., Chicago, IL)完成统计分析,两个AUCs的比较用Z值：Z> 1.96, P< 0.05, Z> 2.58, P< 0.01.比较女性和男性的同一指标的AUCs时,用以下公式：Z=(AA-AB)/√(SEA2+SEB2),在此SE是标准误；比较两个不同指标预测同一危险因素的AUCs时,用以下公式：Z=(AA-AB)/√(SEA2+SEB2-2γSEA SEB),在此γ是AA和AB的相关系数,SE是标准误。
结果
受试者的基本资料
研究样本的特点见表1。男性的平均体重指数、腰围、腰围身高比值、收缩压、舒张压、空腹血浆葡萄糖、高密度脂蛋白胆固醇、低密度脂蛋白胆固醇、甘油三酯和总胆固醇均高于女性。年龄和2小时血浆葡萄糖水平男女两性相似。在男性,代谢综合征和高血压患病率高于女性,糖尿病和血脂异常患病率两性相似。
人体侧指标与心血管危险因素
男性女性不同人体测量指标的切点见表2。在男性体重指数预测高血压、2型糖尿病、血脂异常和代谢综合征的最佳切点是从24.5到25 kg/m2,腰围预测高血压、2型糖尿病、血脂异常和代谢综合征的最佳切点是从87.5到89.5 cm,腰围与身高的比值最佳切点为从0.52到0.53。在女性体重指数预测高血压、2型糖尿病、血脂异常和代谢综合征的最佳切点是从24.5到25 kg/m2,腰围预测高血压、2型糖尿病、血脂异常和代谢综合征的最佳切点是从82.5到83.5 cm,腰围与身高的比值最佳切点为从0.52到0.53。
在女性,WHtR预测糖尿病和血脂异常的AUC值高于WC和BMI,预测高血压和代谢综合征时,WHtR和WC的AUC值相似,两者均高于BMI。在男性,WHtR预测糖尿病和代谢综合征的AUC值高于WC和BMI；预测血脂异常时,WHtR和WC的AUC值相似,两者均高于BMI；然而,预测高血压时,BMI的AUCA值高于WHtR。
在女性BMI, WC和WHtR预测高血压、糖尿病和代谢综合征的AUC值均高于男性,预测血脂异常时无差别。然而,在女性WC和WHtR预测高血压和代谢综合征的AUC值明显高于男性。
结论
在中国山东地区在男性和女性超重的BMI切点24.5 kg/m2,腹型肥胖的腰围切点男性为88.5 cm,女性为83.5 cm,在男性和女性WHtR的最佳切点为0.52。在男女两性,与体重指数相比,反映中心性肥胖的指标,特别是腰围和身高比值与肥胖相关的心血管危险因素联系更密切,在男性高血压例外。
创新点
1,在山东地区首次开展对代谢综合征和糖尿病的大型流调,找出预测糖尿病、高血压、代谢综合征和血脂异常的最佳切点。
2,对中心性肥胖和全身性肥胖进行比较,发现中心性肥胖,特别是腰围身高比值在中国人群中与糖尿病和代谢综合征联系更密切。
Background
Historically, the glucose measurement has been used to diagnose diabetes. Measurement of haemoglobin Ale (HbAlc) level is an integrated measure of circulating glucose levels and tracks well in subjects over time. Epidemiological studies have shown that HbAlc levels in nondiabetic adults can predict incident diabetes, cardiovascular disease morbidity and mortality, and total mortality. A reliable measure of chronic glycemic levels such as measurement of HbAlc levels, which captures the degree of glucose exposure over time and is related more intimately to the risk of complications than measurement of single or episodic measures of glucose levels, may be a better biochemical marker of diabetes and should be considered a diagnostic tool. Therefore, HbAlc≥6.5% was defined as one of the criteria for the diagnosis of diabetes by the American Diabetes Association (ADA).
Objective
To examine the sensitivity and specificity of HbAlc testing for the diagnosis of type 2 diabetes in high-risk adults in China and to compare the cardiovascular risk factors between 2 groups of patients with glycemic status classified by the 2 different tests.
Research design and method
Subjects
We estimated the prevalence of diabetes among Chinese adults in a national study from June 2007 through May 2008 and conducted the current study in Jinan, Shandong. We included subjects above 45 years but without diagnosed diabetes. The Ethics Committee of the Qilu Hospital approved the protocol. Informed consent was obtained from all volunteers.
Study design
After an overnight fast, participants underwent the oral glucose tolerance test (OGTT), and fasting and 2-h glucose levels were measured; a questionnaire was completed to document the presence of hypertension, cardiovascular disease, and whether there was a first-degree relative with diabetes. Height and weight were measured, body mass index (BMI) was calculated, and blood pressure was measured as described. Blood samples were taken from the antecubital vein for measurement of fasting plasma glucose (FPG) and levels of HbAlc, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), triglycerides (TG) and high-density lipoprotein cholesterol (HDL-c). Plasma glucose was measured by the glucose dehydrogenase method and levels of HbAlc by high-performance liquid chromatography, TC by the cholesterol oxidase method, TG by the enzymatic method and HDL-c by the direct method. LDL-c level was calculated by the Friedewald equation for subjects with triacylglycerol concentrations< 4.53 mmol/L:LDL-c=(total cholesterol-HDL-c-triacylglycerols)/5.
Following 2009 ADA criteria, subjects were classified into 4 groups as follows: OGTT-diabetes (FPG≥7.0mmol/l or 2-h PG≥11.1mmol/l; HbAlc-diabetes (HbAlc leve1≥6.5%); true-diabetes (both criteria positive); non-diabetes (neither of the criteria positive).
HbAlc level for diagnosis was evaluted by sensitivity (percentage of subjects with OGTT-diabetes and a positive HbAlc screening test), specificity (percentage of subjects without OGTT-diabetes and a negative screening test), positive predictive value (PPV) (percentage of subjects with a positive HbAlc screening test with OGTT-diabetes), negative predictive value (NPV) (percentage of subjects with a negative screening test without OGTT-diabetes). To understand which test could best predict cardiovascular risk factors, we compared blood pressure, BMI and levels of TC, TG, LDL-c, and HDL-c among the 4 groups (true-diabetes, OGTT-diabetes, HbA1c-diabetes, nondiabetes).
Statistical methods
Analyses involved use of SPSS v11.5 for Windows (SPSS Inc., Chicago, IL). General characteristics of patients are summarized with means±SD for continuous data, median (interquartile range) for TG and HDL-C levels, and number (%) for categorical data. To compare the TG and HDL-C levels among the 4 groups, the Wilcoxon rank sum and Kruskal-Wallis tests were used. To compare blood pressure, BMI, TC, and LDL-C levels among the 4 groups, we used analysis of covariance, with age as a covariate to adjust for potential confounding, and obtained least-square means±SE. Two-sided p values of＜0.05 were considered significant. The receiver operating characteristic was used to describe the sensitivities and specifities of the HbA1c test in determining the presence of type 2 diabetes as defined by the OGTT.
Results
We included 701 subjects with mean age 52±11 years (range 21-83 years) (392 [56%] women). The mean BMI was 26±3 kg/m2, and HbA1c level was 5.34±0.61%.
Among 701 high-risk subjects who underwent OGTT,94 (13%) had diabetes, and 236 (34%) had pre-diabetes. Among the same 701 high-risk subjects who underwent HbA1c testing,65 (9%) had diabetes, and 123 (18%) pre-diabetes, so OGTT could detect more diabetic patients than HbA1c.
The area under the receiver operating characteristics curve for detecting undiagnosed diabetes was 0.843 (95% confidence interval 0.798 to 0.888) for HbA1c (figurel). Compared with the OGTT, with HbAlc≥5.1%, the sensitivity was 98.7% and specificity 33%, PPV 18% and NPV 99%(Table 1). With HbAlc≥7.0%, the sensitivity was 24% and specificity 99.7%, PPV 92%, and NPV 89%. With HbAlc≥6.5%, the sensitivity was 48.2% and specificity 97.8%, PPV 69% and NPV 92%.
There was not full concordance between HbAlc and OGTT (Table 2).30.7% of participants with HbAlc≥6.5% were classified as non-type 2 diabetes by OGTT criteria, and 52% subjects with type 2 diabetes according to the OGTT criteria had HbAlc<6.5%.
To compare HbAlc and OGTT criteria with a type 2 diabetes complication, we considered cardiovascular risk factors.
Subjects in the 3 diabetes groups were older than those in the non-diabetes group (Table 3). When adjusting for age, the values of every risk factor measured varied among the 4 groups with the exception of diastolic pressure and HDL-c concentrations. All risk factors, except for diastolic pressure, were higher for the true-diabetes group than for the nondiabetes group. All lipid levels, except HDL-c, were higher for the HbAlc-and OGTT-diabetes groups than for the nondiabetes group, with no difference between the HbAlc-and OGTT-diabetes groups.
Conclusions
We found high specificity and low sensitivity with use of HbAlc level≥6.5% to diagnose diabetes mellitus. The HbAlc test and OGTT did not reach full concordance. The 2 diagnostic criteria reflect similar levels of cardiovascular risk factors.
Our results showed diabetes prevalence lower with the HbAlc-based diagnostic method than the OGTT criteria, we found HbAlc and OGTT criteria without full concordance. In the present study,30.7% of participants with A1C≥6.5% were not classified as diabetic by OGTT criteria and 52% of the participants with diabetes by OGTT criteria would be classified as normoglycemic by AlC; the corresponding probability of AlC≥6.5% among diabetic case subjects based on an OGTT was 68.3% in our study, which was higher than in Denmark, the U.K., Australia, Greenland, Kenya study(17-42%).
To compare HbAlc and OGTT criteria with a type 2 diabetes macro vascular complication, we considered cardiovascular risk factors., In our data, levels of cardiovascular risk factors were similar for the HbAlc- and OGTT-diabetes groups and higher in the 2 groups than in the non-diabetes group. To our knowledge, this is the first study of cardiovascular risk factors between HbAlc- and OGTT-diagnosed subjects with diabetes.
According to our data, only performing HbAlc instead of OGTT would miss 52% of those who are diabetes and have higher levels of cardiovascular risk factors.On the other hand, only performing OGTT would miss 30.7% of those with high HbAlc levels who are possibly diabetic retinopathy, so there is no single assay for hyperglycemia that can be considered the gold standard.
In conclusion, the limited sensitivity of the AlC test may miss about half of patients who are diabetes and have higher levels of cardiovascular risk factors among Chinese.
Background
About 60.7% of diabetic subjects remain undiagnosed because most of them have not typical symptoms in early stage of the disease.The diabetic microvascular or macrovascular complications have already existed in early stage, even in pre-diabetes stage, and some clinical trials have shown the diabetes and its complications could be delayed or even prevented by early interferences, so the diagnoses should be done as earlier as possible.
The guideline screening for diabetic subjects in high-risk individuals has been presented by 2009 ADA, either fasting plasma glucose (FPG)≥7.0mmol/L or 2-h postload glucose (2hPG)≥11.lmmol/L define diabetes independently. The FPG level is easy to obtain and can be used for diabetes screening criteria, however, subjects with FPG<7.0mmol/Land diagnosed by the 2hPG criteria were ignored and a part of diabetes could not be detected.. OGTT is time wasting and inconvenient,so it is difficult to get physicians and patients to use the oral glucose tolerance test (OGTT). HbAlc has been suggested as the diagnostic or screening criteria for diabetes, however, several studies have shown diabetes prevalence was lower with the HbA1c-based diagnostic criteria. Using FPG and HbAlc screening diabetes were reported by several articles, but the IFG criteria were 6.1-6.9mmol/L and old diagnostic criteria only FPG>7.0mmol/L or 2-h postload glucose (2hPG)≥11.lmmol/L were used.Using 2010 ADA criteria, individuals with HbAlc≥6.5%, FPG≥7.0mmol/L or 2-h postload glucose (2hPG)≥11.1mmol/L can be diagnosed as diabetes independently, we evaluated whether the combination of FPG and HbA1c measurements enhanced the detection of diabetes in high-risk individuals.
1.Objective
The aim of this study was to evaluate the use of HbA1c and FPG as predictors of type 2 diabetes and, accordingly, to develop a rational approach to screening for type 2 diabetes.
2. Methods
2.1 Subjects
The national study from June 2007 through May 2008 to estimate the prevalence of diabetes among Chinese adults was conducted in China, and we conducted the study in Jinan and Zibo, Shandong. We collected individuals with risk factors for diabetes but without diagnosed diabetes from the total people. According to 2009 ADA,700 adults who were above 45years were included(5). The Ethics Committee of the Qilu Hospital approved the protocol. Informed consent was obtained from all individuals.
2.2 Study design
After an overnight fast, participants underwent an oral glucose-tolerance test, and fasting and 2-hour glucose levels were measured, detailed method has been reported (15). we measured HbAlc in the high-risk individuals. HbA1c was measured by high-pressure liquid chromatography, plasma glucose was measured by glucose dehydrogenase method. Using 2010 ADA criteria (14)，Participants were classified as having diabetes if they had either HbAlc≥6.5% or FPG≥7.0mmol/L or 2hPG≥11.1mmol/L, FPG<5.6 mmol/L= normal fasting glucose(NFG); FPG 5.6-6.9 mmol/1 = IFG (impaired fasting glucose); 2-h postload glucose<7.8 mmol/L = normal glucose tolerance (NGT);2-h postload glucose 7.8-11.1 mmol/L = IGT (impaired glucose tolerance).
2.3 Statistical methods
Data are presented as mean±SD. Receiver operating characteristic curves were constructed to calculate sensitivity and specificity of HbAlc cut points for type 2 diabetes diagnosis.Cut points were defined as that point on the curve where the sum of sensitivity and specificity was highest. Comparisons between groups were performed using the chi-square test for categorical data.
3. Results
A total of 700 subjects aged 21-83 years (52±11) were studied. There were 392 (56%) women and 308 (44%) men.The body mass index was 26±3 kg/m2.
3.1 The data of using FPG to screening diabetes were presented in table 1. There were 93 diabetes were detected, among them 46 subjects with FPG≥7.0mmol/L,47 diabetes with FPG< 7.0mmol/L.According to ROC analysis(figure 1), FPG≥5.6mmol/L predicted diabetes with a sensitivity of 78.0% and a specificity of 73.3%. FPG levels<4.8mmol/L and≥6.7mmol/L have 98.7% and 99% accuracy for predicting the absence and presence of type 2 diabetes, respectively. Based on the above results and reference (14), FPG was divided into the following groups:≥7.0mmol/L, 6.9-5.6mmol/L, 5.5-4.8mmol/L, and <4.8mmol/L (table 1). At FPG 6.9-5.6mmol/L, in order to find 35 patients with diabetes,193 people need to do OGTT; at FPG5.5-4.8mmol/L, in order to find 9 patients with diabetes, 368 people need to do OGTT. While 92 individuals with FPG<4.8mmol/L need not to do OGTT and can be rule out diabetes directly.
3.2 The data of using HbA1c to screening diabetes were presented in table2. There were 98 diabetes were detected, among them 54 subjects with HbA1c≥6.5%,44 diabetes with HbA1c<6.5%. According to ROC analysis(figure 1), HbA1c≥5.6% predicted type 2 diabetes with a sensitivity of 86.0% and a specificity of 77.0%. HbA1c levels<5.0 and >6.5% have 98.7% and 99% accuracy for predicting the absence and presence of type 2 diabetes, respectively. Based on the above results and references(7,8), HbA1c was divided into the following groups:≥7.0%,6.9-6.5%,6.4-5.6%(impaired HbA1c),5.5-5.0%,<5.0%. (table 2). At HbA1c 5.6-6.4%, in order to find 30 patients with diabetes,157 people need to do OGTT; and at HbA1c 5.0-5.5%, in order to find 7 patients with diabetes,203 people need to do OGTT. While 284 individuals with HbAlc<5.0% do not need to do OGTT and can be rule out diabetes directly.
33 The data of using FPG +HbA1c to screening diabetes were presented in table 3. There were 98 diabetes were detected, among them 64 subjects with HbA1c≥6.5% or FPG>7.0mmol/L, these people can be diagnosed as diabetes directly. Based on figure 1 results, we used HbA1c screening for diabetes in 179 IFG group. In individuals with HbAlc5.6-6.4%, in order to find 18 patients with diabetes, 68 people need to do OGTT; in individuals with HbAlc 5.5-5.0%, in order to find 6 patients with diabetes, 64 people need to do OGTT; while 47 individuals with HbAlc<5.0% do not need to do OGTT and can be rule out diabetes directly. We also used HbAlc to screen diabetes in individuals with FBG<5.6mmol/L. In individuals with HbAlc5.6-6.4%, in order to find 8 patients with diabetes, 80 people need to do OGTT; 372 individuals with HbAlc<5.6% do not need to do OGTT and can be rule out diabetes directly.
3.4 The comparison of three methods to screen diabetes were presented in table 4. According to FPG, 49.5% patients with diabetes were directly diagnosed, and 14% individuals with risk factors for diabetes can be directly rule out diabetes, in order to find 82 patients with diabetes, 193 people need to do OGTT; while according to HbAlc or FPG+HbAlc, 52.7%, and 65.3% patients with diabetes were directly diagnosed respectively, and 40% and 60.5% individuals with risk factors for diabetes can be directly rule out diabetes, according to HbAlc, in order to find 88 patients with diabetes, 158 people need to do OGTT, according to FPG+HbAlc in order to find 82 patients with diabetes, only 68 people need to do OGTT. More patients with diabetes were directly diagnosed by FPG+HbAlc than by FPG(P<0.05), and more individuals with risk factors for diabetes were directly rule out diabetes by FPG+HbAlc than by FPG or HbAlc(P<0.01). FPG+HbAlc significantly reduced the number of people to do OGTT.
4 Conclusion
FPG combined with HbA1c may be a useful strategy to identify diabetes in individuals with risk factors for diabetes.
According to our result, we can advice the procedure for diabetes screening as the following:1) give measurements of FPG and HbA1c in the individuals with high-risk factors defined by 2009 ADA,2) If FP≥7.0mmol/L or HbAlc≥6.5%,the individuals have diabetes; 3) if FBG< 4.8mmol/L or HbAlc<5.0%, or FPG<5.6mmol/L and HbAlc 5.5-5.0%, diabetes can be excluded.4) if FPG 5.6-6.9mmol/L and HbAlc 5.6-6.4%, OGTT is needed to find diabetes;5) if only IFG or impaired HbAlc, refering the high-risk factors, the more risk factors for diabetes the greater the likelihood should be.
Backgroud
Obesity is a major risk factor for cardiovascular diseases and diabetes. Prospective epidemiological studies have shown increased body mass index (BMI) and waist circumference (WC) to be independent risk factors for type 2 diabetes mellitus, coronary artery disease (CAD), and hypertension. However, the definition of obesity lacks consensus, as does the specific aspects of obesity that contribute to cardiovascular disease. The major disagreement centers on whether it is the total amount or the distribution of adipose tissue that confers a greater risk of cardiovascular disease. Epidemiologic studies have shown that body mass index (BMI), a general measure of obesity, is a powerful predictor of cardiovascular disease. However, a growing body of evidence indicates that waist circumference (WC)—measure of central obesity—also provides information on the risk of cardiovascular disease, and other visceral adiposity measures such as ratio of waist to height (WHtR) appear to be better predictors of cardio-metabolic risk factors than BMI. Many studies of the association of total amount or distribution of adipose tissue and cardiovascular risk factors are performed in the United States and Europe; few data are from mainland China, so knowledge of risk factors are lacking in China.
Objective
We aimed to evaluate the predictive value of the body mass index (BMI), waist circumference (WC), and ratio of waist to height (WHtR) for the presence of several cardiovascular risk conditions -- hypertension, dyslipidemia, metabolic syndrome, and type 2 diabetes--in a Chinese population in Jinan, China.
Methods
Study Participants
The China National Diabetes and Metabolic Disorders Study, conducted from June 2007 through May 2008, was a cross-sectional study designed to provide current, reliable data on the prevalence of diabetes and associated metabolic risk factors in the adult population in China13; we completed the survey in Jinan, Shandong. We used a stratified sampling method to select a representative sample of the general population in 6 districts of Jinan, Shandong. A total of 3400 individuals aged 20-74 years took part in the survey. At elephone appointment was made a week before the survey, and all participants received an agenda the day before the survey. After excluding data for 18 people lacking data on 2-hr plasma glucose levels, we included data for 3,006 people in the final analysis. The participants were mainly of Han ethnicity. The Ethics Committee of Qilu Hospital Shandong University approved the protocol. Informed consent was obtained from all subjects.
After fasting overnight, subjects were required to arrive at the community clinic in every district before 7:00 and were asked to complete a questionnaire to document the presence of hypertension, cardiovascular disease, diabetes and the treatment of these diseases.
Blood pressure and anthropometric measurements
Blood pressure, body weight, height, and WC were measured by standard methods 14. Body mass index was calculated as weight (Kg) divided by height squared (m2). Trained technicians performed the interview in community clinics in the subjects'residential areas.
Laboratory tests
A blood sample was drawn from the antecubital vein for measuring fasting plasma glucose (FPG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), triglycerides (TGs) and high density lipoprotein cholesterol (HDL-C). Thereafter, subjects received 75 g glucose orally, and 5 ml blood was collected at 2 hr for measurement of plasma glucose. Plasma glucose was measured by the glucose dehydrogenase method, TC by the cholesterol oxidase method, TGs by the enzymatic method and HDL-C by the direct method; LDL-C concentrations were calculated by the Friedewald equation.
Statistical analysis
Data for subjects were analyzed separately by sex. Additionally, we analyzed high-risk age groups as defined by the American Diabetes Association16 with the ages≥45 yr in men and women. Continuous variables are expressed as mean±SD, and discrete variables are expressed as numbers and percentages. Comparisons between groups involved Student t test for continuous variables and chi-square test for categorical data. Sensitivity and specificity were examined by ROC analysis, and the areas under the ROC curve (AUC) cut-off values were calculated for each anthropometrical parameter and risk condition. An AUC of 1 indicates perfect separation between affected and nonaffected subjects, and an AUC of 0.5 indicates no discriminative value of the test. Individual cutoffs were defined as the point on the curve where the sum of sensitivity and specificity was highest. All data analyses involved use of SPSS v11.5 (SPSS Inc., Chicago, IL). Differences between 2 AUCs were tested with Z values: with Z> 1.96, P is< 0.05, and with Z> 2.58, P is< 0.01. For the comparison of corresponding AUCs for males and females, Z=(AA-AB)/√(SEA2+SEB2), where SE is standard error; for comparing AUCs for anthropometric indicators in predicting the same binary condition17, Z=(AA-AB)/√(SEA2+SEB2-2γSEA SEB), whereγis the correlation coefficient of AA and AB.
Results
Basic characteristics of the study subjects
The characteristics of the study sample are in Table 1. Mean BMI, WC, WHtR, systolic and diastolic blood pressures, FPG, HDL-C, LDL-C, TG, and TC were higher among men than women. The age and 2-hr plasma glucose of OGTT were similar between women and men. The prevalence of metabolic syndrome and hypertension was higher in men than women, that of diabetes and dyslipidemia was similar between men and women (Table 1), and the prevalence increased in the high-risk age groups.
Anthropometric variables and cardiovascular risk conditions The AUC cutoff values are in Table 2 for men and women. For men, the optimal cutoffs for BMI associated with hypertension, diabetes, dyslipidemia, and metabolic syndrome ranged from 24.5 to 25 kg/m2, for WC from 87.5 to 89.5 cm, and for WHtR from 0.52 to 0.53. For women, the optimal cutoffs for BMI varied from 24.5 to 25 kg/m2, for WC from 82.5 to 83.5 cm, and for WHtR from 0.52 to 0.53.
ROC curves for the discriminating hypertension, diabetes, dyslipidemia, and metabolism syndrome by BMI, WC, and WHtR for males and females are in Figures 1-8) and their associations is in Table 3.
For women, regarding diabetes and dyslipidemia, the AUC values for WHtR were significantly higher than for WC and BMI; regarding hypertension and metabolism syndrome, the AUC values for WHtR and WC were were similar, and both were higher than for BMI.
For men, regarding diabetes and metabolic syndrome, the AUC values for WHtR were significantly higher than for WC and BMI; regarding dyslipidemia, the AUC values for WHtR and WC were similar, and both were higher than for BMI. However, regarding hypertension, the AUC value for BMI was significantly higher than for WHtR. In the high-risk age groups, there were significant differences for dyslipidemia for females, and for diabetes and metabolic syndrome for males.
The AUC values for BMI, WC, and WHtR were all higher for women than for men for all risk factors except dyslipidemia; however, the AUC values for WC and WHtR were significently higher for women than men only for hypertension and metabolic syndrome.
Conclusions A BMI of 24.5 kg/m2 for both men and women, a WC of 88.5 cm for men and 83.5 cm for women, and a WHtR of 0.52 for both men and women were found optimal cutoffs for defining overweight and central adiposity in this population. As compared with BMI, measures of central obesity, particularly WHtR, show a better association with obesity-related cardiovascular risk conditions for both sexes, except for hypertension in males, in Shandong, China.
引文
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2, Harris MI 1993 Undiagnosed NIDDM:clinical and public health issues. Diabetes Care 16:642-652
3, Harris MI, Klein R, Welborn TA, Knuiman MW 1992 Onset of NIDDM occurs at least 4-7 yr before clinical diagnosis. Diabetes Care 15:815-819
4, Thompson TJ, Engelgau MM, Hegazy M, Ali MA, Sous ES, Badran A, Herman WH 1996 The onset of NIDDM and its relationship to clinical diagnosis in Egyptian adults. Diabet Med 13:337-340
5, Nguyen TT, Wang JJ, Wong TY 2007 Retinal vascular changes in pre-diabetes and prehypertension:new findings and their research and clinical implications. Diabetes Care 30:2708-2715
6, Diabetes Prevention Program Research Group 2007 The prevalence of retinopathy in impaired glucose tolerance and recent-onset diabetes in the diabetes prevention program. Diabet Med 24:137-144
7, Sumner CJ, Sheth S, Griffin JW, Cornblath DR, Polydefkis M 2003 The spectrum of neuropathy in diabetes and impaired glucose tolerance. Neurology 60:108-111
8, Li G, Zhang P, Wang J, Gregg EW, Yang W, Gong Q, Li H, Li H, Jiang Y, An Y, Shuai Y, Zhang B, Zhang J, Thompson TJ, Gerzoff RB, Roglic G, Hu Y, Ben-nett PH. The long-term effect of lifestyle interventions to prevent diabetes in the China Da Qing Diabetes Prevention Study:a 20-year fol low-up study. Lancet 2008;371:1783-1789
9, Pan XR, Li GW, Hu YH, Wang JX, Yang WY, An ZX, Hu ZX, Lin J, Xiao JZ, Cao HB, Liu PA, Jiang XG, Jiang YY, Wang JP, Zheng H, Zhang H, BennettPH, Howard BV. Effects of diet and exercise in preventing NIDDM inpeople with impaired glucose tolerance. The Da Qing IGT and Diabe tes Study. Diabetes Care 1997; 20:537-544
10, The Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002; 346:393-403
11, Orchard TJ, Temprosa M, Goldberg R, Haffner S, Ratner R, Marcovina S, Fowler S, for the Diabetes Prevention Program Research G. The effect of Metformin and intensive lifestyle intervention on the metabolic syndrome:The Diabetes Prevention Program Randomized Trial.
12, International Expert Committee.International Expert Committee report on the role of the A1C assay in the diagnosis of diabetes.Diabetes Care.2009 Jul;32(7):1327-34. Epub 2009 Jun 5. No abstract available
13, Devin M. Mann, April P. Carson, Daichi Shimbo, Vivian Fonseca, Caroline S. Fox, and Paul Muntner Impact of A1C Screening Criterion on the Diagnosis of Pre-Diabetes Among U.S. Adults Diabetes Care October 2010 33:2190-2195; published ahead of print July 13,2010, doi:10.2337/dc10-0752
14, Mauri Laakso, Jari Jokelainen, Pirjo Harkonen, Markku Timonen, Sirkka Keinanen-Kiukaanniemi, and Ulla Rajala Postchallenge Glucose, A1C, and Fasting Glucose as Predictors of Type 2 Diabetes and Cardiovascular Disease:A 10-year prospective cohort study Diabetes Care September 2010 33:2077-2083; published ahead of print June 23,2010, doi:10.2337/dc10-0262
15, Darin E. Olson, Mary K. Rhee, Kirsten Herrick, David C. Ziemer, Jennifer G. Twombly, and Lawrence S. Phillips Screening for Diabetes and Pre-Diabetes With Proposed AlC-Based Diagnostic Criteria Diabetes Care October 2010 33:2184-2189; published ahead of print July 16,2010, doi:10.2337/dc 10-0433
16, Carlos Lorenzo, Lynne E. Wagenknecht, Anthony J.G. Hanley, Marian J. Rewers, Andrew J. Karter, and Steven M. Haffner A1C Between 5.7 and 6.4%as a Marker for Identifying Pre-Diabetes, Insulin Sensitivity and Secretion, and Cardiovascular Risk Factors:The Insulin Resistance Atherosclerosis Study (IRAS) Diabetes Care September 2010 33:2104-2109; published ahead of print June 23,2010, doi:10.2337/dc 10-0679
17, April P. Carson, Kristi Reynolds, Vivian A. Fonseca, and Paul Muntner Comparison of A1C and Fasting Glucose Criteria to Diagnose Diabetes Among U.S. Adults Diabetes Care January 2010 33:95-97; published ahead of print October 6,2009, doi:10.2337/dc09-1227
18, Maria Rosario G. Araneta, Andrew Grandinetti, and Healani K. Chang AlC and Diabetes Diagnosis among Filipino-Americans, Japanese-Americans, and Native Hawaiians Diabetes Care published ahead of print September 10,2010, doi:10.2337/dc10-0958
19, Diabetes Prevention Program Research Group 2007 The prevalence of retinopathy in impaired glucose tolerance and recent-onset diabetes in the Diabetes Prevention Program. Diabet Med 24:137-144
20, DECODE Study Group, European Diabetes Epidemiology Group 2003 Is the current definition for diabetes relevant to mortality risk from all causes and cardiovascular and noncardiovascular diseases? Diabetes Care 26:688-696
21, Gerstein HC, Santaguida P, Raina P, Morrison KM, Balion C, Hunt D, Yazdi H, Booker L 2007 Annual incidence and relative risk of diabetes in people with various categories of dysglycemia:a systematic overview and meta-analysis of prospective studies. Diabetes Res Clin Pract 78:305-312
22, David Liao, Pamela J. Asberry, Jane B. Shofer, Holly Callahan, Colleen Matthys, Improvement of BMI, Body Composition, and Body Fat Distribution With Lifestyle Modification in Japanese Americans With lmpaired Glucose Tolerance Diabetes Care September 2002 25:1504-1510
23, Bartnik, L Ryden, K Malmberg, J Ohrvik, K Pyorala, E Standl, R Ferrari, M Simoons, J Soler-Soler on behalf of the Euro Heart Survey Investigators Oral glucose tolerance test is needed for appropriate classification of glucose regulation in patients with coronary artery disease:a report from the Euro Heart Survey on Diabetes and the Heart Heart, Jan 2007; 93:72-77.
24, Christopher D. Saudek, William H. Herman, David B. Sacks, Richard M. Bergenstal, David Edelman, and Mayer B. Davidson A New Look at Screening and Diagnosing Diabetes Mellitus J. Clin. Endocrinol. Metab., Jul 2008; 93: 2447-2453.
25, Performance of HbAlc and fasting capillary blood glucose test for screening newly diagnosed diabetes and pre-diabetes defined by OGTT in Qingdao, China Xianghai Zhou, Zengchang Pang, Weiguo Gao, Shaojie Wang, Lei Zhang, Feng Ning, and Qing Qiao Diabetes Care, Dec 2009; 10.2337/dc09-1410.
26, Caroline K. Kramer, Maria Rosario G Araneta, and Elizabeth Barrett-Connor A1C and Diabetes Diagnosis:The Rancho Bernardo Study Diabetes Care, Jan 2010; 33:101-103.
27, Wenyu Wang, PHD1, Elisa T. Lee, PHD1, Richard Fabsitz, MA2, Thomas K. Welty, MD, MPH3 and Barbara V. Howard, PHD4 Using HbAlc to Improve Efficacy of the American Diabetes Association Fasting Plasma Glucose Criterion in Screening for New Type 2 Diabetes in American Indians The Strong Heart Study Diabetes Care August 2002 vol.25 no.8 1365-1370
28, David R. Jesudason, MBBS, FRACP1, Kerrie Dunstan, RN1, Darryl Leong, MBBS1 and Gary A. Wittert, MBBCH, MD, FRACP12 Macrovascular Risk and Diagnostic Criteria for Type 2 Diabetes Implications for the use of FPG and HbAlc for cost-effective screening Diabetes Care February 2003 vol.26 no.2 485-490
29, Hayrettin Tekumit, Ali Riza Cenal, Adil Polat, Kemal Uzun, Cenk Tataroglu, and Esat Akinci Diagnostic Value of Hemoglobin Alc and Fasting Plasma Glucose Levels in Coronary Artery Bypass Grafting Patients With Undiagnosed Diabetes Mellitus Ann. Thorac. Surg., May 2010; 89:1482-1487.
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