Nomograma predictivo de hiperglucemia. Aplicación en población trabajadora

Resumo

Background: The growing number of people with undiagnosed diabetes and no previous family history approaches the use of predictive models for prevention and early detection of risk. Objectives: to identify graphically, using a nomograph, the variables that can influence a person has blood glucose basal level ≥ 100 mg/dl as a risk factor for diabetes. Patients and methods: We analyse in 6.345 workers of both sexes (56.8% female, 43.2% male), mean age 41 years, the relationship between independent variables and the basal levels of blood glucose ≥ 100 mg/dl or <100 mg/dl. A regression model is done to design a nomogram that relates these variables. Results: scores ranging from 0-11 (better / worse prognosis) classified in four risk groups: low (0-2), medium (3-8) or high (> 9). The probability of having a glycemic levels ≥ 100 mg/dl is assigned to each group. The nomograph predicts the probability of evolution to high blood glucose levels and potential diabetes type 2: 35.1% for the high risk group, 1.6% for the low risk group and 5.2 %-13.6% for the media risk groups. Conclusions: this result could provide early preventive actions from the companies, being useful in Public Health.