Somlak Chuengsamarn1, Suthee Rattanamongkolgul2, Gunya Sittithumcharee3, Siwanon Jirawatnotai3. 1. Division of Endocrinology and Metabolism, Faculty of Medicine, HRH Princess Maha Chakri Sirindhorn Medical Center, Srinakharinwirot University, Nakornnayok, Thailand. Electronic address: somlukc@hotmail.com. 2. Department of Preventive and Social Medicine, Faculty of Medicine, HRH Princess Maha Chakri Sirindhorn Medical Center, Srinakharinwirot University, Nakornnayok, Thailand. 3. Laboratory for Systems Pharmacology, Department of Pharmacology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Abstract
AIMS: To determine an association between hs-CRP and metabolic control/diabetic chronic vascular complications (DCVCCxs) in the patients with type 2 diabetes (DM). In addition, the possibility of using hs-CRP levels to predict risk of DCVCCxs will also be validated. METHODS: This cohort study randomly enrolled 608 patients with DM during the 2007-2008 study period. We also recorded basic laboratory findings at baseline and at one year, to include fasting plasma glucose, HbA1c, triglyceride, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and hs-CRP. RESULTS: Logistic regressions of odds ratios between hs-CRP and DCVCCxs (coronary arterial disease, cerebrovascular disease, diabetic nephropathy, diabetic retinopathy, and diabetic peripheral neuropathy) showed significant correlations, except for cerebrovascular disease, as follows 0.2 (0.11-0.38), 0.09 (0.01-0.77), 0.06 (0.02-0.16), 0.31 (0.12-0.82), and 0.17 (0.07-0.43), respectively. Linear regression for changes in hs-CRP were significantly correlated with HbA1c (r=0.38), fasting plasma glucose (r=0.40), triglyceride (r=0.20), low-density lipoprotein cholesterol (r=0.12), and high-density lipoprotein cholesterol (r=-0.12). No correlation was found for total cholesterol (r=0.06). Based on receiver operating characteristic (ROC) analysis, the cut-off points for hs-CRP levels for prediction of DCVCCxs were 2.89, 2.25, 2.10, 2.25, and 2.82mg/L, for coronary arterial disease, cerebrovascular disease, diabetic nephropathy, diabetic retinopathy, and diabetic peripheral neuropathy, respectively. CONCLUSIONS: Our data showed that DCVCCxs were associated with hs-CRP in patients with DM. The cut-off point for hs-CRP can be used to predict association with DCVCCxs. Well-controlled metabolic components in diabetic patients, especially HbA1c, fasting plasma glucose, and triglyceride may reduce the level of hs-CRP.
AIMS: To determine an association between hs-CRP and metabolic control/diabetic chronic vascular complications (DCVCCxs) in the patients with type 2 diabetes (DM). In addition, the possibility of using hs-CRP levels to predict risk of DCVCCxs will also be validated. METHODS: This cohort study randomly enrolled 608 patients with DM during the 2007-2008 study period. We also recorded basic laboratory findings at baseline and at one year, to include fasting plasma glucose, HbA1c, triglyceride, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and hs-CRP. RESULTS: Logistic regressions of odds ratios between hs-CRP and DCVCCxs (coronary arterial disease, cerebrovascular disease, diabetic nephropathy, diabetic retinopathy, and diabetic peripheral neuropathy) showed significant correlations, except for cerebrovascular disease, as follows 0.2 (0.11-0.38), 0.09 (0.01-0.77), 0.06 (0.02-0.16), 0.31 (0.12-0.82), and 0.17 (0.07-0.43), respectively. Linear regression for changes in hs-CRP were significantly correlated with HbA1c (r=0.38), fasting plasma glucose (r=0.40), triglyceride (r=0.20), low-density lipoprotein cholesterol (r=0.12), and high-density lipoprotein cholesterol (r=-0.12). No correlation was found for total cholesterol (r=0.06). Based on receiver operating characteristic (ROC) analysis, the cut-off points for hs-CRP levels for prediction of DCVCCxs were 2.89, 2.25, 2.10, 2.25, and 2.82mg/L, for coronary arterial disease, cerebrovascular disease, diabetic nephropathy, diabetic retinopathy, and diabetic peripheral neuropathy, respectively. CONCLUSIONS: Our data showed that DCVCCxs were associated with hs-CRP in patients with DM. The cut-off point for hs-CRP can be used to predict association with DCVCCxs. Well-controlled metabolic components in diabeticpatients, especially HbA1c, fasting plasma glucose, and triglyceride may reduce the level of hs-CRP.