Isabela Banu

Cardiovascular Risk Prediction Is Improved by Adding Asymptomatic Coronary Status to Routine Risk Assessment in Type 2 Diabetic Patients

OBJECTIVE To evaluate if silent myocardial ischemia (SMI) and silent coronary artery disease (CAD) provide significant additional value to routine cardiovascular risk assessment in type 2 diabetic patients. RESEARCH DESIGN AND METHODS We followed up to a first cardiovascular event 688 subjects (322 men, aged 59 ± 8 years) out of 731 consecutive asymptomatic type 2 diabetic patients with ≥1 additional risk factor who had been prospectively screened between 1992 and 2006 for SMI by stress myocardial scintigraphy and for silent CAD by coronary angiography. RESULTS SMI was found in 207 (30.1%) patients and CAD in 76 of those with SMI. Of the patients, 98 had a first cardiovascular event during a 5.4 ± 3.5 (range: 0.1–19.2) year follow-up period. Cox regression analysis considering parameters predicting events but not SMI and CAD (“routine assessment”) showed in univariate analyses that macroproteinuria (hazard ratio [HR] 3.33 [95% CI 1.74–6.35]; P < 0.001), current multifactorial care (0.27 [0.15–0.47]; P < 0.001), and peripheral/carotid occlusive arterial disease (PCOAD; 4.33 [2.15–8.71]; P < 0.001) independently predicted cardiovascular events. When added into the model, SMI (HR 1.76 [1.00–3.12]; P = 0.05) and CAD (2.28 [1.24–4.57]; P < 0.01) were also independently associated with events. SMI added to the prediction of an event in the following 5 years above and beyond routine assessment risk prediction (c statistic with or without SMI 0.788 [0.720–0.855] and 0.705 [0.616–0.794], respectively). CONCLUSIONS Although screening for SMI and silent CAD should not be systematic, these complications are predictive of cardiovascular events in type 2 diabetic patients in addition to routine risk predictors, especially represented by PCOAD, macroproteinuria, and nonintensive management.

Comparison of field methods to estimate fat mass in children

Background: Reliable field methods to measure fat mass (FM) in children may contribute to primary prevention of childhood obesity. Aim: The objective was to compare the accuracy of existing field methods (skinfold thickness (SF), leg-to-leg bioelectrical impedance analysis (BIA), anthropometrics for FM measurement in prepubertal European children. Subjects and methods: Reference FM was measured in 55 French children (30 boys, 25 girls; mean age 8.7 years) using a three-compartment model: body volume (BV) was assessed by air displacement plethysmography (ADP) and total body water (TBW) was assessed by deuterium dilution. Agreement between field methods and the reference method was assessed using Bland–Altman analyses. Since field methods for FM measurement are reported to be population-dependent, adjustment to the study population was performed using stepwise multiple linear regressions modelling. Results: Even after adjustment, field methods exhibited a high correlation (R2 = 0.71–0.84) but a moderate agreement (±3.32 to ±4.47 kg for fat mass) with the reference model. Methods based on BIA or SF performed slightly better than those based on anthropometry. Conclusions: Field methods for FM measurement may be recommended for epidemiological applications, but not for individual follow-up. New field equipment is required to improve accuracy of FM measurement in children and make individual follow-up possible.

What would be the outcome if the American Diabetes Association recommendations of 2010 had been followed in our pratice in 1998–2006?

Diabet. Med. 28, 567–574 (2011)

Evidence for a Specific Diabetic Cardiomyopathy: An Observational Retrospective Echocardiographic Study in 656 Asymptomatic Type 2 Diabetic Patients

Aim. Our aim was to assess the prevalence of subclinical diabetic cardiomyopathy, occurring among diabetic patients without hypertension or coronary artery disease (CAD). Methods. 656 asymptomatic patients with type 2 diabetes for 14 ± 8 years (359 men, 59.7 ± 8.7 years old, HbA1c 8.7 ± 2.1%) and at least one cardiovascular risk factor had a cardiac echography at rest, a stress cardiac scintigraphy to screen for silent myocardial ischemia (SMI), and, in case of SMI, a coronary angiography to screen for silent CAD. Results. SMI was diagnosed in 206 patients, and 71 of them had CAD. In the 157 patients without hypertension or CAD, left ventricular hypertrophy (LVH: 24.1%) was the most frequent abnormality, followed by left ventricular dilation (8.6%), hypokinesia (5.3%), and systolic dysfunction (3.8%). SMI was independently associated with hypokinesia (odds ratio 14.7 [2.7–81.7], p < 0.01) and systolic dysfunction (OR 114.6 [1.7–7907], p < 0.01), while HbA1c (OR 1.9 [1.1–3.2], p < 0.05) and body mass index (OR 1.6 [1.1–2.4], p < 0.05) were associated with systolic dysfunction. LVH was more prevalent among hypertensive patients and hypokinesia in the patients with CAD. Conclusion. In asymptomatic type 2 diabetic patients, diabetic cardiomyopathy is highly prevalent and is predominantly characterized by LVH. SMI, obesity, and poor glycemic control contribute to structural and functional LV abnormalities.

Haemoglobin glycation may partly explain the discordance between HbA1c measurement and oral glucose tolerance test to diagnose dysglycaemia in overweight/obese subjects

AIM This study assessed whether the poor correlation between HbA1c and oral glucose tolerance test (OGTT) for dysglycaemia diagnosis may be explained by haemoglobin glycation (HbG). METHODS A total of 1033 consecutive overweight or obese patients with no known diabetes underwent OGTT and measurement of HbA1c to diagnose diabetes and dysglycaemia (American Diabetes Association criteria). For each OGTT result category, low, medium and high HbG was defined according to the mean HbA1c/fructosamine ratio and mean fructosamine. High HbG was defined as values greater than mean values in each OGTT category for both HbA1c/fructosamine ratio and fructosamine levels, and low HbG was defined as lower values of both. The remaining patients were considered medium HbG. RESULTS Based on OGTT and HbA1c values, 267 (25.8%) and 443 (42.8%) patients had intermediate hyperglycaemia, and 66 (6.4%) and 95 (9.2%) patients had diabetes, respectively. The results were discordant for intermediate hyperglycaemia or diabetes diagnosis in 41.7% and for diabetes diagnosis in 10.0% of the patients. The proportion of patients with HbA1c≥6.5%, but without OGTT-diagnosed diabetes, was 0%, 3.8% and 32.8% in the low-HbG, medium-HbG and high-HbG groups, respectively. In contrast, the proportion of patients with HbA1c<5.7%, but with an abnormal OGTT, was 30.4%, 11.1% and 0%, respectively. The AUROC of HbA1c to detect OGTT-diagnosed diabetes was better in the medium-HbG group [0.874 (0.816-0.931)] than in those with low or high HbG [0.628 (0.489-0.768); P<0.01]. Only age was independently associated with high-HbG status [10-year OR: 1.3 (1.1-1.5); P<0.0001]. CONCLUSION Haemoglobin glycation may explain many of the discordant results between HbA1c and OGTT when used for dysglycaemia diagnosis.

Are Obese Individuals with no Feature of Metabolic Syndrome but Increased Waist Circumference Really Healthy? A Cross Sectional Study

AIM Patients displaying the metabolically healthy but obese phenotype have an intermediate cardiometabolic prognosis compared to normal weight healthy and metabolically unhealthy obese subjects. We aimed to evaluate the proportion of patients with a definite metabolically healthy obese phenotype and better characterize them. METHODS Definite metabolically healthy obese phenotype was defined as having none of the International Diabetes Federation metabolic syndrome criteria, excluding waist circumference. We recruited 1 159 obese patients (body mass index 38.4±6.3 kg/m(2)) including 943 women, without known diabetes. Patients were characterized for cardiometabolic disorders. RESULTS As the 202 (17.4%) metabolically healthy obese individuals were younger and had lower body mass indexes than the 957 metabolically unhealthy obese patients, they were matched for gender, age and body mass index with 404 metabolically unhealthy obese patients. In addition to the features of metabolic syndrome, when compared to unhealthy subjects, definite metabolically healthy obese patients were less frequently found with either homeostasis model assessment of insulin resistance index>3 (23.6 vs. 38.9%, p<0.001), or abnormal oral glucose tolerance test (13.9 vs. 33.9%, p<0.001), or HbA1c value≥5.7% (43.9 vs. 54.2%, p<0.05) or pulse pressure≥60 mmHg (11.7 vs. 64.9%, p<0.001). However, there were no significant differences in the prevalence of microalbuminuria (11.1 vs. 12.3%), cardiac autonomic dysfunction (45.5 vs. 35.3%) and fatty liver index ≥ 60 (5.6 vs. 10.2%). CONCLUSION Our data do not support the characterization of metabolically healthy obesity, even definite, as really healthy, as many patients with this phenotype have abnormal cardiovascular markers and glucose or liver abnormalities. HbA1c measurement seems to be more sensitive than OGTT to detect dysglycemia in this population.

0334: Coronary artery calcium score as a predictor of myocardial ischemia in asymptomatic diabetic patients

Background and aims High coronary artery calcium (CAC) scores were shown to predict a higher likelihood of inducible myocardial ischemia and to be associated with a poor cardio-vascular prognosis. However the predictive value for coronary stenoses (CS) has not been tested in asymptomatic diabetic patients. This study aimed to evaluate the predictive value of a high CAC score for silent myocardial ischemia (SMI) and CS in high risk asymptomatic diabetic patients. Materials and methods CAC score was measured by computed tomography in 150 diabetic patients without cardiac history or symptom, with a normal resting ECG and ≥1 additional risk factors. SMI was assessed using stress myocardial scintigraphy and/or stress echocardiography, and CS using coronary angiography in those with an abnormal SMI test. Results CAC score was ≥100 Agatston units in 35.3% of the patients. SMI was detected in 27 patients (18.0%). A coronary angiography was performed in 17 of SMI patients and detected significant CS in six of them. CAC score was associated with coronary status (no SMI: median value 14 (range 0-2900); SMI without CS: 101 (23-3230) and SMI with CS: 800 (76-2978); (p Conclusion These data suggest that in asymptomatic high risk diabetic patients CAC score is associated with cardiac ischemic status, with a 3.4-fold increased risk of SMI when the score is ≥100. The negative predictive value of CAC score for SMI is an interesting finding. The predictive value for CS remains to be determined in a larger sample of patients with CS.

096: Diabetic cardiomyopathy: data from a series of 656 asymptomatic diabetic patients with known cardiac ischemic status

Background The aim of the study was to assess the prevalence of subclinical cardiomyopathy among patients with type 2 diabetes without hypertension or coronary artery disease (CAD). Materials and methods: 656 patients with type 2 diabetes for 14±8 yrs (359 men, 59.7±8.7 years, HbA1c 8.7±2.1%), without cardiac symptom and at least one cardiovascular risk factor (hypertension 74%; dyslipidemia 70%; smoking habits 22%; peripheral occlusive arterial disease 10%, nephropathy 39%) had a contributive cardiac echography at rest; underwent a stress cardiac scintigraphy to screen for silent myocardial ischemia (SMI), and in case of SMI, a coronary angiography to screen for silent CAD. Results SMI was diagnosed in 206 patients, and 71 of them had silent CAD. In the patients without hypertension or CAD (n=157), left ventricular hypertrophy (LVH: 24.1%) was the most frequent abnormality, followed by left ventricular dilation (8.6%), hypokinesia (5.3%), abnormal type 1 relaxation (4.8%) and systolic dysfunction (3.8%). No parameter was associated with LVH neither with LV dilation nor with abnormal relaxation. In multivariate analysis, the parameters associated with hypokinesia were SMI (Odds ratio 14.7 [2.7-81.7] p Conclusion In asymptomatic type 2 diabetic patients, diabetic cardiomyopathy is highly prevalent and is characterized by LVH. SMI, obesity and poor glycemic control contribute to systolic dysfunction and/or hypokinesia. Hypertension is associated with more LVH, and CAD with more hypokinesia.