Usando la curva de tolerancia a la glucosa para calcular el porcentaje relativo de sensibilidad insulínica y el porcentaje relativo de función beta insular / A program to estimate insulin resistance based on data from the oral glucose tolerance test

RESUMEN

Background An instrument to help clinicians to evaluate the oral glucose tolerance test (OGTT) at-a-glance is lacking. Aim To generate a program written in HTML squeezing relevant information from the OGTT with glucose and insulin measurements. Material and Methods We reanalyzed a database comprising 90 subjects. All of them had both an OGTT and a pancreatic suppression test (PST) measuring insulin resistance directly. Thirty-seven of the 90 studied participants were insulin resistant (IR). Receiver operating characteristic (ROC) curves and Bayesian analyses delineated the diagnostic performances of four predictors of insulin resistance HOMA, QUICKI, ISI-OL (Matsuda-DeFronzo) and I0*G60. We validated a new biochemical predictor, the Percentual Relative Insulin Sensitivity (%RIS), and calculated the Percentual Relative Beta Cell Function (%RBCF). Results The best diagnostic performance of the five predictors were those of the I0*G60 and the %RIS. The poorest diagnostic performances were those of the HOMA and QUICKI. The ISI-OL's performance was in between. The %RIS of participants with and without IR was 44.4 ± 7.3 and 101.1 ± 8.8, respectively (p < 0.05). The figures for % RBCF were 55.8 ± 11.8 and 90.8 ± 11.6, respectively (p < 0.05). Mathematical modeling of the relationship between these predictors and the Steady State Plasma Glucose Value from the PST was performed. We developed a program with 10 inputs (glucose and insulin values) and several outputs I0*G60, HOMA, QUICKI, ISI-OL, Insulinogenic Index, Disposition Index, %RBCF, %RIS, and metabolic categorization of the OGTT (ADA 2003). Conclusions The OGTT data permitted us to write successfully an HTML program allowing the user to fully evaluate at-a-glance its metabolic information.