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Value of serum glycated albumin and high-sensitivity C-reactive protein levels in the prediction of presence of coronary artery disease in patients with type 2 diabetes.

Pu LJ, Lu L, Xu XW, Zhang RY, Zhang Q, Zhang JS, Hu J, Yang ZK, Ding FH, Chen QJ, Lou S, Shen J, Fang DH, Shen WF - Cardiovasc Diabetol (2006)

Bottom Line: Serum glycated albumin and hs-CRP levels were significantly increased in diabetic patients with CAD.Logistic regression model was defined as: P/(1-P) = EXP(-1.5 + 1.265 gender + 0.812 age + 1.24 glycated albumin + 0.953 hs-CRP + 0.902 lipoprotein(a) + 1.918 creatinine).The optimal probability value for predicting CAD in type 2 diabetic patients was 0.648 (sensitivity 82.3%, specificity 68.6%).

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Cardiology, Institute of Cardiovascular Diseases, Rui Jin Hospital, Jiaotong Univerisity Medical School, Shanghai, People's Republic of China. Plj476@yahoo.com.cn

ABSTRACT

Background: Coronary artery disease (CAD) is a major vascular complication of diabetes mellitus and reveals high mortality. Up to 30% of diabetic patients with myocardial ischemia remain asymptomatic and are associated with worse prognosis compared to non-diabetic counterpart, which warrants routine screening for CAD in diabetic population. The purpose of this study was to evaluate the clinical value of serum glycated albumin and high-sensitivity C-reactive protein (hs-CRP) levels in predicting the presence of CAD in patients with type 2 diabetes.

Methods: Three hundred and twenty-four patients with type 2 diabetes were divided into two groups based on presence (CAD group, n = 241) or absence (control group, n = 83) of angiographically-documented CAD (lumen diameter narrowing > or =70%). Serum levels of glycated albumin and hs-CRP as well as serum concentrations of glucose, lipids, creatinine, blood urea nitrogen and uric acid were measured in both groups. Predictors of CAD were determined using multivariate logistic regression model and receiver-operating characteristic (ROC) curves.

Results: Serum glycated albumin and hs-CRP levels were significantly increased in diabetic patients with CAD. Multivariate regression analysis revealed that male gender, age, serum levels of glycated albumin, hs-CRP, creatinine and lipoprotein (a) were independent predictors for CAD. Areas under the curve of glycated albumin and hs-CRP and for regression model were 0.654 (95%CI 0.579-0.730, P < 0.001), 0.721 (95%CI 0.658-0.785, P < 0.001) and 0.824 (95% CI 0.768-0.879, P < 0.001), respectively. The optimal values of cut-off point were 18.7% (sensitivity 67.9%, specificity 60.0%) for glycated albumin and 5.2 mg/l (sensitivity 72.2%, specificity 60.0%) for hs-CRP to predict CAD. Logistic regression model was defined as: P/(1-P) = EXP(-1.5 + 1.265 gender + 0.812 age + 1.24 glycated albumin + 0.953 hs-CRP + 0.902 lipoprotein(a) + 1.918 creatinine). The optimal probability value for predicting CAD in type 2 diabetic patients was 0.648 (sensitivity 82.3%, specificity 68.6%).

Conclusion: Serum glycated albumin and hs-CRP levels were significantly elevated in patients with type 2 diabetes and CAD. The logistic regression model incorporating with glycated albumin, hs-CRP and other major risk factors of atherosclerosis may be useful for screening CAD in patients with type 2 diabetes.

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ROC curve for glycated albumin, hs-CRP and logistic regression model for predicting coronary artery disease in patients with type 2 diabetes.
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Figure 1: ROC curve for glycated albumin, hs-CRP and logistic regression model for predicting coronary artery disease in patients with type 2 diabetes.

Mentions: ROC plot was calculated to test predictive value of glycated albumin and hs-CRP, and the effectiveness of logistic regression model was also evaluated by constructing ROC plot. A larger area under the curve of hs-CRP was observed compared to glycated albumin. The optimal value of cut-off point for hs-CRP and probability value of regression model to predict CAD in patients with type 2 diabetes were 5.2 mg/l and 0.648, respectively. When using hs-CRP as a single predictor, 67 out of 241 diabetic patients with CAD (27.8%) could be missed (sensitivity 72.2%, specificity 60.0%). The use of regression model may cause 43 out of 241 CAD cases (17.7%) missed (sensitivity 82.3%, specificity 68.6%). The ROC plot showed that the optimal cut-off point of regression model for diagnosis of CAD was 0.865, with only 6 out of 83 cases (7.1%) without CAD being falsely recognized as CAD (sensitivity 54.5%, specificity 92.9%) (Figure 1, Table 4).


Value of serum glycated albumin and high-sensitivity C-reactive protein levels in the prediction of presence of coronary artery disease in patients with type 2 diabetes.

Pu LJ, Lu L, Xu XW, Zhang RY, Zhang Q, Zhang JS, Hu J, Yang ZK, Ding FH, Chen QJ, Lou S, Shen J, Fang DH, Shen WF - Cardiovasc Diabetol (2006)

ROC curve for glycated albumin, hs-CRP and logistic regression model for predicting coronary artery disease in patients with type 2 diabetes.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC1764721&req=5

Figure 1: ROC curve for glycated albumin, hs-CRP and logistic regression model for predicting coronary artery disease in patients with type 2 diabetes.
Mentions: ROC plot was calculated to test predictive value of glycated albumin and hs-CRP, and the effectiveness of logistic regression model was also evaluated by constructing ROC plot. A larger area under the curve of hs-CRP was observed compared to glycated albumin. The optimal value of cut-off point for hs-CRP and probability value of regression model to predict CAD in patients with type 2 diabetes were 5.2 mg/l and 0.648, respectively. When using hs-CRP as a single predictor, 67 out of 241 diabetic patients with CAD (27.8%) could be missed (sensitivity 72.2%, specificity 60.0%). The use of regression model may cause 43 out of 241 CAD cases (17.7%) missed (sensitivity 82.3%, specificity 68.6%). The ROC plot showed that the optimal cut-off point of regression model for diagnosis of CAD was 0.865, with only 6 out of 83 cases (7.1%) without CAD being falsely recognized as CAD (sensitivity 54.5%, specificity 92.9%) (Figure 1, Table 4).

Bottom Line: Serum glycated albumin and hs-CRP levels were significantly increased in diabetic patients with CAD.Logistic regression model was defined as: P/(1-P) = EXP(-1.5 + 1.265 gender + 0.812 age + 1.24 glycated albumin + 0.953 hs-CRP + 0.902 lipoprotein(a) + 1.918 creatinine).The optimal probability value for predicting CAD in type 2 diabetic patients was 0.648 (sensitivity 82.3%, specificity 68.6%).

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Cardiology, Institute of Cardiovascular Diseases, Rui Jin Hospital, Jiaotong Univerisity Medical School, Shanghai, People's Republic of China. Plj476@yahoo.com.cn

ABSTRACT

Background: Coronary artery disease (CAD) is a major vascular complication of diabetes mellitus and reveals high mortality. Up to 30% of diabetic patients with myocardial ischemia remain asymptomatic and are associated with worse prognosis compared to non-diabetic counterpart, which warrants routine screening for CAD in diabetic population. The purpose of this study was to evaluate the clinical value of serum glycated albumin and high-sensitivity C-reactive protein (hs-CRP) levels in predicting the presence of CAD in patients with type 2 diabetes.

Methods: Three hundred and twenty-four patients with type 2 diabetes were divided into two groups based on presence (CAD group, n = 241) or absence (control group, n = 83) of angiographically-documented CAD (lumen diameter narrowing > or =70%). Serum levels of glycated albumin and hs-CRP as well as serum concentrations of glucose, lipids, creatinine, blood urea nitrogen and uric acid were measured in both groups. Predictors of CAD were determined using multivariate logistic regression model and receiver-operating characteristic (ROC) curves.

Results: Serum glycated albumin and hs-CRP levels were significantly increased in diabetic patients with CAD. Multivariate regression analysis revealed that male gender, age, serum levels of glycated albumin, hs-CRP, creatinine and lipoprotein (a) were independent predictors for CAD. Areas under the curve of glycated albumin and hs-CRP and for regression model were 0.654 (95%CI 0.579-0.730, P < 0.001), 0.721 (95%CI 0.658-0.785, P < 0.001) and 0.824 (95% CI 0.768-0.879, P < 0.001), respectively. The optimal values of cut-off point were 18.7% (sensitivity 67.9%, specificity 60.0%) for glycated albumin and 5.2 mg/l (sensitivity 72.2%, specificity 60.0%) for hs-CRP to predict CAD. Logistic regression model was defined as: P/(1-P) = EXP(-1.5 + 1.265 gender + 0.812 age + 1.24 glycated albumin + 0.953 hs-CRP + 0.902 lipoprotein(a) + 1.918 creatinine). The optimal probability value for predicting CAD in type 2 diabetic patients was 0.648 (sensitivity 82.3%, specificity 68.6%).

Conclusion: Serum glycated albumin and hs-CRP levels were significantly elevated in patients with type 2 diabetes and CAD. The logistic regression model incorporating with glycated albumin, hs-CRP and other major risk factors of atherosclerosis may be useful for screening CAD in patients with type 2 diabetes.

Show MeSH
Related in: MedlinePlus