Diastolic dysfunction is a manifestation of ventricular-vascular interaction in patients with type 2 diabetes mellitus

Vascular disease is accelerated in patients with Type 2 diabetes mellitus (T2DM). Since the systemic vasculature plays a pivotal role in myocardial loading, this study aimed to determine the effect of arterial characteristics on left ventricular (LV) morphology and function in patients with T2DM. Conventional echocardiography and tissue Doppler imaging were performed in 172 T2DM patients (95 men; aged 55±11y) with preserved ejection fraction (62±5%). Patients were stratified into groups based on LV geometric pattern (normal [n = 79], concentric remodeling [n = 33], concentric hypertrophy [n = 29], eccentric hypertrophy [n = 31]). Total arterial compliance (TAC) was recorded by simultaneous radial tonometry and aortic outflow pulsed wave Doppler. Arterial (brachial and carotid) structure and function were determined by standard ultrasound methods. There were no significant differences between the LV geometric groups in demographic or clinical parameters. The concentric hypertrophy group had significantly increased carotid artery diameter (6.0±0.7mm versus 6.5±0.7mm; p < 0.05) and stiffness (1912±1203 dynes/cm2mm versus 2976±2695 dynes/cm2mm×10−6; p < 0.05) compared to those with normal geometry. However, TAC did not differ between groups. LV diastolic function, as determined by the ratio of diastolic mitral inflow velocity to mitral annulus tissue velocity (E/E_), was significantly associated with carotid artery relative wall thickness and intima media thickness (p < 0.05). Moreover, E/E_ was independently predicted by carotid artery relative wall thickness (β = 22.9; p = 0.007). We conclude that structural characteristics of the carotid artery are associated with abnormal LV structure and function in patients with T2DM. The LV functional irregularities may be a downstream consequence of amplified pressure wave reflections effecting sub-optimal ventricular-vascular interaction.

Diagnosis of diabetes mellitus: case of different cutoff values: A data mining approach

Objective: An estimation of cut-off points for the diagnosis of diabetes mellitus (DM) based on individual risk factors. Methods: A subset of the 1991 Oman National Diabetes Survey is used, including all patients with a 2h post glucose load >= 200 mg/dl (278 subjects) and a control group of 286 subjects. All subjects previously diagnosed as diabetic and all subjects with missing data values were excluded. The data set was analyzed by use of the SPSS Clementine data mining system. Decision Tree Learners (C5 and CART) and a method for mining association rules (the GRI algorithm) are used. The fasting plasma glucose (FPG), age, sex, family history of diabetes and body mass index (BMI) are input risk factors (independent variables), while diabetes onset (the 2h post glucose load >= 200 mg/dl) is the output (dependent variable). All three techniques used were tested by use of crossvalidation (89.8%). Results: Rules produced for diabetes diagnosis are: A- GRI algorithm (1) FPG>=108.9 mg/dl, (2) FPG>=107.1 and age>39.5 years. B- CART decision trees: FPG >=110.7 mg/dl. C- The C5 decision tree learner: (1) FPG>=95.5 and 54, (2) FPG>=106 and 25.2 kg/m2. (3) FPG>=106 and =133 mg/dl. The three techniques produced rules which cover a significant number of cases (82%), with confidence between 74 and 100%. Conclusion: Our approach supports the suggestion that the present cut-off value of fasting plasma glucose (126 mg/dl) for the diagnosis of diabetes mellitus needs revision, and the individual risk factors such as age and BMI should be considered in defining the new cut-off value.