Estimativa dos níveis glicêmicos a partir do pH salivar: desenvolvimento de um kit diagnóstico - SAUAIA, Bismarck Ascar (2016)
Estimation of blood glucose levels using invasive methods currently is a routine in emergency and ambulatory attendance of public health services, as well as in residential glucose monitoring, in order to prevent glucose levels variation, which may evolve to ophthalmic, renal, vascular and neurological complications. In order to develop a low-cost, socially accessible and non-invasive method to establish blood glucose levels, it was created a linear conversion mathematical model from salivary hidrogenionic potential (pH) values to blood glucose level. After signing the informed consent form and filling out the survey questionnaire to gather personal, clinical and family history data, it was collected a drop of blood from the tip of the right index finger, which was submitted to the glucometer for blood glucose level determination and after that, it was also collected 2 mL of saliva in a 5ml glass Beacker to salivary pH definition with a digital pH meter. Data collection was performed between May and November, 2014, with a sample of 333 cappilary blood glucose (CG) and salivary ph tests from non - diabetic adult volunteers, in fasting state from 2 to 4 hours after last meal, who were randomly selected from medicine and physiotherapy clinics of UNICEUMA. After entering data in EPINFO 2000 program, results were analyzed with Pearson’s correlation coefficient (r) in Bioestat 5.3 Software and presented a value of – 0,7522, showing the existence of a correlation between capillary blood glucose and salivary pH. Then, we defined that variables were related in a mathematical form of a straight line. Thus, we found the coefficient of determination between capillary blood glucose and salivary pH using simple linear regression test: R2 = 0,5658. Regarding alpha level = 0.05, we established a mathematical model: y = a + bx, where a = 9.3286 and b = - 0.0278. So, after calculating blood glucose level from pH (pH = F (Glycemia); we have: CG = (9.3286 - pH)/ 0.0278. The results demonstrated the relation among CG values (mg/dl), corresponding salivary ph and the diagnosis respectively: CG < 70  pH > 7,94 with (Variation (Δ) = 7,784 to 8,096) = Hypoglycemic Risk; CG between 70 and 100  pH 7,94 to 6,69 = Security Gap or normality; CG > 100  pH < 6,69 with (Δ = 6,536 to 6,848) = Hyperglycemic Risk. The proposed mathematical model may allow the definition of a diagnostic kit to estimate blood glucose levels from salivary pH through a non-invasive, low-cost, socially accessible and less traumatic method either in healthy patients or at risk for developing diabetes.