[Geometric coding and cluster analysis to assess metabolic control of patients with type 2 diabetes mellitus].

Objective: Determine the frequency of combinations of higher-than-normal metabolic control parameters, using geometric coding and hierarchical cluster analysis, in patients with type 2 diabetes (DM2)

Methodology: A descriptive cross-sectional study was conducted in Mexico to assess a group of 1 051 patients with DM2. The inclusion criteria were to have one or more of the following values: fasting glucose of 130 mg/dL, total cholesterol of 240 mg/dL, total triglycerides of 200 mg/dL, Body Mass Index of 27 kg/m(2), and systolic blood pressure higher than 130 mmHg or diastolic blood pressure higher than 85 mmHg. Through geometric coding, the frequencies of all combinations were obtained. Cluster analysis was used to determine similarities among the combinations.

Results: Using the proposed instrument, it was observed that the paired combinations with the highest number of subjects were hyperglycemia-hypertriglyceridemia (7.3%) and hyperglycemia-hypercholesterolemia (3.6%). The most frequent polycombinations were hyperglycemia-hypercholesterolemia-hypertriglyceridemia (13.2%) and hyperglycemia-hypertriglyceridemia-hypercholesterolemia-hypertension (10.5%).

Conclusions: Geometric coding and cluster analysis could become a suitable instrument for assessing the metabolic control of patients with DM2, as well as for identifying parameters that will help improve their monitoring and treatment.