RESUMO

Objective: To define the mathematical relationship between fructosamine levels and average glucose values. Subjects and methods: The study comprised laboratory data of 1,227 patients with type 1 or 2 diabetes mellitus. Fructosamine levels measured at the end of a 3-week period were compared against the average blood glucose levels of the previous 3 weeks. Average glucose levels were determined by the weighted average of the daily fasting capillary glucose results performed during the study period, and the plasma glucose measured in the same sample collected for fructosamine measurement. Results: In total, 9,450 glucose measurements were performed. Linear regression analysis between fructosamine levels and average glucose levels showed that for each 1.0 µmol/L increase in fructosamine level there was a 0.5 mg/dL increase in average glucose level, as estimated by the equation Mean glucose level = (0.5157 × Fructosamine) - 20. The coefficient of determination (r2 = 0.353492, p < 0.006881) allowed the calculation of the estimated average glucose based on fructosamine level. Conclusion: Our study demonstrated a linear correlation between fructosamine level and mean blood glucose level, suggesting that fructosamine levels can be a proxy for the average glucose level in assessing the metabolic control of patients with diabetes.

Assuntos

RESUMO

ABSTRACT Objective: To define the mathematical relationship between fructosamine levels and average glucose values. Subjects and methods: The study comprised laboratory data of 1,227 patients with type 1 or 2 diabetes mellitus. Fructosamine levels measured at the end of a 3-week period were compared against the average blood glucose levels of the previous 3 weeks. Average glucose levels were determined by the weighted average of the daily fasting capillary glucose results performed during the study period, and the plasma glucose measured in the same sample collected for fructosamine measurement. Results: In total, 9,450 glucose measurements were performed. Linear regression analysis between fructosamine levels and average glucose levels showed that for each 1.0 µmol/L increase in fructosamine level there was a 0.5 mg/dL increase in average glucose level, as estimated by the equation Mean glucose level = (0.5157 x Fructosamine) - 20. The coefficient of determination (r2 = 0.353492, p < 0.006881) allowed the calculation of the estimated average glucose based on fructosamine level. Conclusion: Our study demonstrated a linear correlation between fructosamine level and mean blood glucose level, suggesting that fructosamine levels can be a proxy for the average glucose level in assessing the metabolic control of patients with diabetes.

RESUMO

Objetivo: comparar o comportamento glicêmico dos pacientes em pós-operatório de cirurgia cardíaca valvar e de revascularização do miocárdio, submetidos ao mesmo protocolo de controle glicêmico, e avaliar a incidência de hipoglicemia e mortalidade intra-hospitalar dessa população. Método: estudo de coorte, retrospectivo, quantitativo, que avaliou 354 prontuários de cirurgias realizadas em 2016. Resultados: pacientes revascularizados apresentaram maiores médias glicêmicas (149,14±36,03), maior uso de insulina e coeficiente de variação (23,30%). Entretanto, a incidência de hipoglicemia foi maior entre valvares (35,32%), mais acometidos por lesão renal aguda (6,58%), terapia de substituição renal (11,97%) e mortalidade hospitalar (6,58%). Conclusão: evidenciou-se uma população heterogênea com desfechos clínicos que caracterizaram os valvares como mais criticos, devido a maior número de portadores de fibrilaçao atrial, maior tempo de CEC, e maior uso de vasoaminas e corticosteroides. Logo, é necessário conhecer as particularidades de cada população, para gerenciar protocolos específicos de controle glicêmico para diferentes perfis epidemiológicos.

Objective: to compare the glycemic behavior of patients in the postoperative period of valve heart surgery and myocardial revascularization, submitted to the same glycemic control protocol and to assess the incidence of hypoglycemia and mortality and in-hospital mortality in this population. Method: cohort, retrospective, quantitative study that evaluated 354 medical records of surgeries performed in 2016. Results: revascularized patients had higher blood glucose means (149,14±36.03), greater use of insulin and higher coefficient of variation (23.30%). However, the incidence of hypoglycemia was higher (35.32%) valve patients, more affected by acute kidney injury (6.58%), renal replacement therapy (11.97%) and hospital mortality (6.58%). Conclusion: a heterogeneous population with clinical outcomes that characterized the valves as more critical, due to a greater number of patients with atrial fibrillation, longer CEC time, and greater use of vasoamines and corticosteroids. It is necessary to know the particularities of each population, in order to manage specific glycemic control protocols for different epidemiological profiles.

Objetivo: comparar el comportamiento glucémico de pacientes en postoperatorio de cirugía valvular y revascularización miocárdica, sometidos al mismo protocolo de control glicémico y evaluar la incidencia de hipoglucemia y mortalidad hospitalaria en esta población. Método: estudio de cohorte, retrospectivo, cuantitativo que evaluó 354 historias clínicas, entre agosto y octubre de 2020, de cirugías realizadas en 2016. Resultados: pacientes revascularizados presentaron mayores medias de glucemia (149,14±36,03), mayor uso de insulina y mayor coeficiente de variación (23,30%). Aunque, la incidencia de hipoglucemia fue mayor (35,32%) entre las válvulas, que se vieron más afectadas por daño renal agudo (6,58%), terapia de reemplazo renal (11,97%) y mortalidad hospitalaria (6,58%). Conclusión: el estudio mostró una población heterogénea con resultados clínicos que caracterizaron a las válvulas como más críticas, debido a un mayor número de pacientes con fibrilación auricular, mayor tiempo de CEC y mayor uso de vasoaminas y corticoides. Por tanto, es necesario conocer las particularidades de cada población, para gestionar el control glucémico con protocolos específicos para diferentes perfiles epidemiológicos.