Determinants of subclinical diabetic heart disease

Aims/hypothesis: Subclinical left ventricular (LV) dysfunction has been shown by tissue Doppler and strain imaging in diabetic patients in the absence of coronary disease or LV hypertrophy, but the prevalence and aetiology of this finding remain unclear. This study sought to identify the prevalence and the determinants of subclinical diabetic heart disease. Methods: A group of 219 unselected patients with type 2 diabetes without known cardiac disease underwent resting and stress echocardiography. After exclusion of coronary artery disease or LV hypertrophy, the remaining 120 patients ( age 57 +/- 10 years, 73 male) were studied with tissue Doppler imaging. Peak systolic strain of each wall and systolic (Sm) and diastolic ( Em) velocity of each basal segment were measured from the three apical views and averaged for each patient. Significant subclinical LV dysfunction was identified according to Sm and Em normal ranges adjusted by age and sex. Strain and Em were correlated with clinical, therapeutic, echocardiographic and biochemical variables, and significant independent associations were sought using a multiple linear regressionmodel. Results: Significant subclinical LV dysfunction was present in 27% diabetic patients. Myocardial systolic dysfunction by peak strain was independently associated with glycosylated haemoglobin level ( p< 0.001) and lack of angiotensin- converting enzyme inhibitor treatment ( p= 0.003). Myocardial diastolic function ( Em) was independently predicted by age ( p= 0.013), hypertension ( p= 0.001), insulin ( p= 0.008) and metformin ( p= 0.01) treatment. Conclusions/ interpretation: In patients with diabetes mellitus, subclinical LV dysfunction is common and associated with poor diabetic control, advancing age, hypertension and metformin treatment; ACE inhibitor and insulin therapies appear to be protective.

Screening for heart disease in diabetic subjects

Background The prevalence of left ventricular hypertrophy (LVH), coronary artery disease, and subclinical cardiomyopathy in diabetic patients without known cardiac disease is unclear. We sought the frequency of these findings to determine whether plasma brain natriuretic peptide (BNP) could be used as an alternative screening tool to identify subclinical LV dysfunction. Methods Asymptomatic patients with diabetes mellitus without known cardiac disease (n = 10 1) underwent clinical evaluation, measurement of BNP, exercise stress testing, and detailed echocardiographic assessment. After exclusion of overt dysfunction or ischemia, subclinical myocardial function was sought on the basis of myocardial systolic (Sm) and diastolic velocity (Em). Association was. sought between subclinical dysfunction and clinical, biochemical, exercise, and echocardiographic variables. Results Of 101 patients, 22 had LVH and 16 had ischemia evidenced by exercise-induced wall motion abnormalities. Only 4 patients had abnormal BNP levels; BNP was significantly increased in patients with LVH. After exclusion of LVH and coronary artery disease, subclinical cardiomyopathy was identified in 24 of 66 patients: Subclinical disease could not be predicted by BNP. Conclusions Even after exclusion of asymptomatic ischemia and hypertrophy, subclinical systolic and diastolic dysfunction occurs in a significant number of patients with type 2 diabetes. However, screening approaches, including BNP, do not appear to be sufficiently sensitive to identify subclinical dysfunction, which requires sophisticated echocardiographic analysis.

Deriving matrix of peptide-MHC interactions in diabetic mouse by genetic algorithm

Finding motifs that can elucidate rules that govern peptide binding to medically important receptors is important for screening targets for drugs and vaccines. This paper focuses on elucidation of peptide binding to I-A(g7) molecule of the non-obese diabetic (NOD) mouse - an animal model for insulin-dependent diabetes mellitus (IDDM). A number of proposed motifs that describe peptide binding to I-A(g7) have been proposed. These motifs results from independent experimental studies carried out on small data sets. Testing with multiple data sets showed that each of the motifs at best describes only a subset of the solution space, and these motifs therefore lack generalization ability. This study focuses on seeking a motif with higher generalization ability so that it can predict binders in all A(g7) data sets with high accuracy. A binding score matrix representing peptide binding motif to A(g7) was derived using genetic algorithm (GA). The evolved score matrix significantly outperformed previously reported

Carotid artery intimal medial thickness, brachial artery flow-mediated vasodilation and cardiovascular risk factors in diabetic and non-diabetic indigenous Australians

Background: Indigenous Australians are at high risk for cardiovascular disease and type 2 diabetes. Carotid artery intimal medial thickness (CIMT) and brachial artery flow-mediated vasodilation (FMD) are ultrasound imaging based surrogate markers of cardiovascular risk. This study examines the relative contributions of traditional cardiovascular risk factors on CIMT and FMD in adult Indigenous Australians with and without type 2 diabetes mellitus. Method: One hundred and nineteen Indigenous Australians were recruited. Physical and biochemical markers of cardiovascular risk, together with CIMT and FMD were meausred for all subjects. Results: Fifty-three Indigenous Australians subjects (45%) had type 2 diabetes mellitus. There was a significantly greater mean CIMT in diabetic versus non-diabetic subjects (p = 0.049). In the non-diabetic group with non-parametric analyses, there were significant correlations between CIMT and: age (r = 0.64, p < 0.001), systolic blood pressure (r = 0.47, p < 0.001) and non-smokers (r = -0.30, p = 0.018). In the diabetic group, non-parametric analysis showed correlations between CIMT, age (r = 0.36, p = 0.009) and duration of diabetes (r = 0.30, p = 0.035) only. Adjusting forage, sex, smoking and history of cardiovascular disease, Hb(A1c) became the sole significant correlate of CIMT (r = 0.35,p = 0.01) in the diabetic group. In non-parametric analysis, age was the sole significant correlate of FMD (r = -0.31,p = 0.013), and only in non-diabetic subjects. Linear regression analysis showed significant associations between CIMT and age (t = 4.6,p < 0.001), systolic blood pressure (t = 2.6, p = 0.010) and Hb(A1c) (t = 2.6, p = 0.012), smoking (t = 2.1, p = 0.04) and fasting LDL-cholesterol (t = 2.1, p = 0.04). There were no significant associations between FMD and examined cardiovascular risk factors with linear regression analysis Conclusions: CIMT appears to be a useful surrogate marker of cardiovascular risk in this sample of Indigenous Australian subjects, correlating better than FMD with established cardiovascular risk factors. A lifestyle intervention programme may alleviate the burden of cardiovascular disease in Indigenous Australians by reducing central obesity, lowering blood pressure, correcting dyslipidaemia and improving glycaemic control. CIMT may prove to be a useful tool to assess efficacy of such an intervention programme. (c) 2004 Elsevier Ireland Ltd. All rights reserved.

Strength and endurance training lead to different post exercise glucose profiles in diabetic participants using a continuous subcutaneous glucose monitoring system

Background Although both strength training (ST) and endurance training (ET) seem to be beneficial in type 2 diabetes mellitus (T2D), little is known about post-exercise glucose profiles. The objective of the study was to report changes in blood glucose (BG) values after a 4-month ET and ST programme now that a device for continuous glucose monitoring has become available. Materials and methods Fifteen participants, comprising four men age 56.5 +/- 0.9 years and 11 women age 57.4 +/- 0.9 years with T2D, were monitored with the MiniMed (Northridge, CA, USA) continuous glucose monitoring system (CGMS) for 48 h before and after 4 months of ET or ST. The ST consisted of three sets at the beginning, increasing to six sets per week at the end of the training period, including all major muscle groups and ET performed with an intensity of maximal oxygen uptake of 60% and a volume beginning at 15 min and advancing to a maximum of 30 min three times a week. Results A total of 17 549 single BG measurements pretraining (619.7 +/- 39.8) and post-training (550.3 +/- 30.1) were recorded, correlating to an average of 585 +/- 25.3 potential measurements per participant at the beginning and at the end of the study. The change in BG-value between the beginning (132 mg dL(-1)) and the end (118 mg dL(-1)) for all participants was significant (P = 0.028). The improvement in BG-value for the ST programme was significant (P = 0.02) but for the ET no significant change was measured (P = 0.48). Glycaemic control improved in the ST group and the mean BG was reduced by 15.6% (Cl 3-25%). Conclusion In conclusion, the CGMS may be a useful tool in monitoring improvements in glycaemic control after different exercise programmes. Additionally, the CGMS may help to identify asymptomatic hypoglycaemia or hyperglycaemia after training programmes.

Continuous glucose monitoring in diabetic long distance runners

Marathon running is growing in popularity, and many diabetic patients are participating in various marathon races all over the world each year. This study aimed to investigate the prevalence and extent of glycemic excursions (hypo- and hyperglycemic) during a marathon run in patients with well-controlled diabetes mellitus using a continuous glucose monitoring system (CGMS). Five subjects with type 1 and one patient with type 2 diabetes mellitus were monitored with the Medtronic MiniMed CGMS during the 2002 Vienna City Marathon (n = 3) or the Fernwarme run (n = 3) long distance runs of 42.19/15.8 km. All six patients finished their course. The CGSM system was well tolerated in all patients over an average duration of 34 +/- 4.0 hours and it did not limit the patients' activities. The mean running time for the Vienna city marathon was 257 +/- 8 min (247 to 274 min) and for the Fernwarme run 134 +/- 118 min (113 to 150 min). A total of 1470 blood glucose measurements (mean 245 readings per subject) were performed. During and after the marathons frequent hypo and hyperglycemic episodes with and without clinical symptoms were measured. Our data confirm that the CGMS may help to identify asymptomatic hypoglycemia or hyperglycemia during and after a long distance run. The system may also be helpful to improve our understanding about the individual changes of glucose during and after a marathon and may protect hypoglycemic or hyperglycemic periods in future races.

Diabetic heart disease

Diabetes mellitus is responsible for a spectrum of cardiovascular disease. The best known complications arise from endothelial dysfunction, oxidation, inflammation, and vascular remodelling and contribute to atherogenesis. However, the effects on the heart also relate to concurrent hypertensive heart disease, as well as direct effects of diabetes on the myocardium. Diabetic heart disease, defined as myocardial disease in patients with diabetes that cannot be ascribed to hypertension, coronary artery disease, or other known cardiac disease, is reviewed.

Relationship between myocardial perfusion and dysfunction in diabetic cardiomyopathy: A study of quantitative contrast echocardiography and strain rate imaging

Objective: To use quantitative myocardial contrast echocardiography (MCE) and strain rate imaging (SRI) to assess the role of microvascular disease in subclinical diabetic cardiomyopathy. Methods: Stress MCE and SRI were performed in 48 patients (22 with type II diabetes mellitus (DM) and 26 controls), all with normal left ventricular systolic function and no obstructive coronary disease by quantitative coronary angiography. Real-time MCE was acquired in three apical views at rest and after combined dipyridamole-exercise stress. Myocardial blood flow (MBF) was quantified in the 10 mid- and apical cardiac segments at rest and after stress. Resting peak systolic strain rate (SR) and peak systolic strain (epsilon) were calculated in the same 10 myocardial segments. Results: The DM and control groups were matched for age, sex and other risk factors, including hypertension. The DM group had higher body mass index and left ventricular mass index. Quantitative SRI analysis was possible in all patients and quantitative MCE in 46 (96%). The mean e, SR and MBF reserve were all significantly lower in the DM group than in controls, with diabetes the only independent predictor of each parameter. No correlation was seen between MBF and SR (r = -0.01, p = 0.54) or between MBF and epsilon ( r = -0.20, p = 0.20). Conclusions: Quantitative MCE shows that patients with diabetes but no evidence of obstructive coronary artery disease have impaired MBF reserve, but abnormal transmural flow and subclinical longitudinal myocardial dysfunction are not related.