de la Hera Jesús M, Vegas José M, Hernández Ernesto, Lozano Iñigo, García-Ruiz José M, Fernández-Cimadevilla Oliva C, Carro Amelia, Avanzas Pablo, Torres Francisco, Bayón Jeremías, Menéndez Teresa, Jiménez-Navarro Manuel, Delgado Elías
Departamento de Cardiología, Hospital Universitario Central de Asturias, Oviedo, Asturias, España.
Rev Esp Cardiol. 2011 Sep;64(9):759-65. doi: 10.1016/j.recesp.2011.03.034. Epub 2011 Jul 12.
Traditionally, the oral glucose tolerance test has been useful to diagnose unknown diabetes. Recently, the American Diabetes Association committee has accepted glycated hemoglobin ≥ 6.5% as a criterion for unknown diabetes. The aim was to determine the benefit of glycated hemoglobin for diagnosing unknown diabetes and also create a predictive model that adjusts the indication for oral glucose tolerance test in coronary patients.
We examined the glycemic profile of 338 coronary patients without previous diagnosis of diabetes, applying 2010 American Diabetes Association criteria. A unknown diabetes risk predictive model was developed using logistic regression analysis, and then validated in another cohort.
Using the glycated hemoglobin criteria and/or fasting plasma glucose, unknown diabetes was diagnosed in 26 patients. The remaining patients were classified according to oral glucose tolerance test as follows: unknown diabetes 53 (17%), prediabetes 144 (46.2%), and normoglycemic 115 (36.8%). The diagnostic method for unknown diabetes was fasting plasma glucose in 25.3%, glycated hemoglobin in 7.6%, and oral glucose tolerance test in 67.1%. A risk model including fasting plasma glucose, glycated hemoglobin, left ventricular ejection fraction, age, and noncoronary vascular disease was shown to effectively predict unknown diabetes after oral glucose tolerance test: area under the ROC curve 0.8 (95% confidence interval: 0.74-0.87). When the oral glucose tolerance test is restricted to patients with a risk score >6 (31% of our sample) we properly identify 83% of unknown diabetes cases (sensitivity: 75%, specificity: 73%, positive predictive value: 40%, negative predictive value: 93%). The model was adequately validated in another cohort of 115 patients (area under the ROC curve 0.84 [95% confidence interval: 0.74-0.95]).
In coronary patients, glycated hemoglobin alone failed to detect many cases of unknown diabetes. However, its inclusion in a risk prediction model leads to optimizing the usefulness of oral glucose tolerance test.
传统上，口服葡萄糖耐量试验对于诊断隐匿性糖尿病很有用。最近，美国糖尿病协会委员会已将糖化血红蛋白≥6.5%作为隐匿性糖尿病的诊断标准。目的是确定糖化血红蛋白在诊断隐匿性糖尿病方面的益处，并建立一个预测模型，以调整冠心病患者口服葡萄糖耐量试验的指征。
我们应用2010年美国糖尿病协会标准，对338例既往未诊断糖尿病的冠心病患者的血糖情况进行了检查。使用逻辑回归分析建立了隐匿性糖尿病风险预测模型，然后在另一队列中进行验证。
根据糖化血红蛋白标准和/或空腹血糖，诊断出26例隐匿性糖尿病患者。其余患者根据口服葡萄糖耐量试验分类如下：隐匿性糖尿病53例（17%），糖尿病前期144例（46.2%），血糖正常115例（36.8%）。隐匿性糖尿病的诊断方法中，空腹血糖占25.3%，糖化血红蛋白占7.6%，口服葡萄糖耐量试验占67.1%。一个包括空腹血糖、糖化血红蛋白、左心室射血分数、年龄和非冠状动脉血管疾病的风险模型显示，在口服葡萄糖耐量试验后能有效预测隐匿性糖尿病：ROC曲线下面积为0.8（95%置信区间：0.74 - 0.87）。当口服葡萄糖耐量试验仅限于风险评分>6的患者（占我们样本的31%）时，我们能正确识别83%的隐匿性糖尿病病例（敏感性：75%，特异性：73%，阳性预测值：40%，阴性预测值：93%）。该模型在另一组115例患者中得到了充分验证（ROC曲线下面积为0.84 [95%置信区间：0.74 - 0.95]）。
在冠心病患者中，仅糖化血红蛋白未能检测出许多隐匿性糖尿病病例。然而，将其纳入风险预测模型可优化口服葡萄糖耐量试验的效用。
