Glycemic variability in diagnosis of gestational diabetes as predictor of pharmacological treatment.

INTRODUCTION: To establish whether glycemic variability (GV) parameters used when gestational diabetes mellitus (GDM) has been diagnosed could help predict the probability that a patient will need pharmacological treatment, and to analyze the link of these parameters to the development of maternal-fetal complications. MATERIALS AND METHODS: A prospective study of 87 women with GDM who underwent retrospective continuous glucose monitoring (CGM) for six days between weeks 26 and 32 of gestation, following diagnosis. The mean glycemia levels and GV variables were analyzed together with their link to maternal-fetal complications, and the need for pharmacological treatment. ROC (receiver operating characteristic) curves were developed to determine validity to detect the need for pharmacological treatment. RESULTS: Patients with higher mean glycemia (p < 0.001) and continuous overlapping of net glycemic action in a period of n-hours (CONGAn) (p = 0.001) required pharmacological treatment. The ROC curves showed cut-off points of 98.81 mg/dL for mean glycemia, and 86.70 mg/dL for CONGAn, with 83.3% sensitivity and 67.8% specificity for both parameters. No relation between the GV parameters and development of maternal-fetal complications was observed. CONCLUSIONS: The use of CGM, once GDM is diagnosed, enables us to identify those patients who would benefit from closer monitoring during gestation, and facilitate a speedier take-up of pharmacological treatment. However, prospective studies involving a higher number of patients are needed, as well as a cost assessment for recommending the use of CGM following GDM diagnosis.

Faster-acting insulin aspart reduces glycaemic variability in sensor-augmented pump treated type 1 diabetes patients.

AIM: To evaluate the effect of faster aspart over glycaemic variability in type 1 diabetes (T1D) patients treated with sensor-augmented pump (SAP) in a real-world scenario. METHODS: Observational study with SAP-treated adult T1D patients treated with faster aspart for three months. The primary endpoint was the mean amplitude of glucose excursions (MAGE). RESULTS: Fifty patients were treated with faster aspart. Eleven patients (23%) withdrew during the follow-up mainly due to worsening of diabetes control (9 patients). Mean age was 41.2 yrs. (range 21-59) and T1D duration 22.4±10.0 yrs. Mean SAP treatment duration was 3.6±3.1 yrs. We detected a reduction of -7.0 (95% CI -1.1, -12.9; p=0.021) in MAGE at the end of the study. Other glycemic variability indices were also improved: standard deviation of mean interstitial glucose (-3mg/dl; 95% CI, -1, -5; p=0.01), CONGA4 (-2.2; 95% CI -0.3, -4.2; p=0.029), CONGA6 (-2.6; 95% CI -0.6, -4.6; p=0.011), GRADE (-0.5; 95% CI -0.1, -0.9; p=0.022), HBGI (-0.7; 95% CI -0.2, -1.3; p=0.013), J-index (-2.9; 95% CI -0.7, -5.0; p=0.011) and MODD (-5.7; 95% CI -1.7, -9.7; p=0.006). A slight reduction in mean glucose management indicator was also detected (-0.14%; 95% CI, -0.02, -0.27; -1.4mmol/mol; 95% CI -0.1, -3.3; p=0.03). CONCLUSIONS: In SAP-treated T1D patients, faster aspart insulin was associated with reduced glycaemic variability, but also a high percentage of dropouts due to worsened glycaemic control. NCT04233203.

Beyond hyperglycemia: glycaemic variability as a prognostic factor after acute ischemic stroke.

INTRODUCTION: Glycaemic variability (GV) refers to variations in blood glucose levels, and may affect stroke outcomes. This study aims to assess the effect of GV on acute ischaemic stroke progression. METHODS: We performed an exploratory analysis of the multicentre, prospective, observational GLIAS-II study. Capillary glucose levels were measured every 4 hours during the first 48 hours after stroke, and GV was defined as the standard deviation of the mean glucose values. The primary outcomes were mortality and death or dependency at 3 months. Secondary outcomes were in-hospital complications, stroke recurrence, and the impact of the route of insulin administration on GV. RESULTS: A total of 213 patients were included. Higher GV values were observed in patients who died (n = 16; 7.8%; 30.9 mg/dL vs 23.3 mg/dL; p = 0.05). In a logistic regression analysis adjusted for age and comorbidity, both GV (OR = 1.03; 95% CI, 1.003-1.06; p = 0.03) and stroke severity (OR = 1.12; 95% CI, 1.04-1.2; p = 0.004) were independently associated with mortality at 3 months. No association was found between GV and the other outcomes. Patients receiving subcutaneous insulin showed higher GV than those treated with intravenous insulin (38.95 mg/dL vs 21.34 mg/dL; p < 0.001). CONCLUSIONS: High GV values during the first 48 hours after ischaemic stroke were independently associated with mortality. Subcutaneous insulin may be associated with higher VG levels than intravenous administration.

Más allá de la hiperglucemia: la variabilidad glucémica como factor pronóstico en el infarto cerebral agudo / Beyond hyperglycemia: glycaemic variability as a prognostic factor after acute ischemic stroke

Introducción: La variabilidad glucémica (VG) hace referencia a las oscilaciones en los niveles de glucosa en sangre y podría influir en el pronóstico del ictus. Objetivo: Analizar el efecto de la VG en la evolución del infarto cerebral agudo (IC).MétodosAnálisis exploratorio del estudio GLIAS-II (multicéntrico, prospectivo y observacional). Se midieron los niveles de glucemia capilar cada cuatro horas durante las primeras 48 horas y la VG se definió como la desviación estándar de los valores medios. Variables principales: mortalidad y muerte o dependencia a los tres meses. Variables secundarias: porcentaje de complicaciones intrahospitalarias y de recurrencia de ictus, e influencia de la vía de administración de insulina sobre la VG.ResultadosSe incluyeron 213 pacientes. Los pacientes que fallecieron (N = 16;7,8%) presentaron mayores valores de VG (30,9 mg/dL vs. 23,3 mg/dL; p = 0,05). En el análisis de regresión logística ajustado por edad y comorbilidad, tanto la VG (OR = 1,03; IC del 95%: 1,003-1,06: p = 0,03) como la gravedad del IC (OR = 1,12; IC del 95%: 1,04-1,2; p = 0,004) se asociaron de forma independiente con la mortalidad a los tres meses. No se encontró asociación entre la VG y las demás variables de estudio. Los pacientes que recibieron tratamiento con insulina subcutánea mostraron una mayor VG que los tratados con insulina intravenosa (38,9 mg/dL vs. 21,3 mg/dL; p < 0,001).ConclusionesValores elevados de VG durante las primeras 48 horas tras el IC se asociaron de forma independiente con la mortalidad. La administración subcutánea de insulina podría condicionar una mayor VG que la vía intravenosa. (AU)

Introduction: Glycaemic variability (GV) refers to variations in blood glucose levels, and may affect stroke outcomes. This study aims to assess the effect of GV on acute ischaemic stroke progression.MethodsWe performed an exploratory analysis of the multicentre, prospective, observational GLIAS-II study. Capillary glucose levels were measured every 4 hours during the first 48 hours after stroke, and GV was defined as the standard deviation of the mean glucose values. The primary outcomes were mortality and death or dependency at 3 months. Secondary outcomes were in-hospital complications, stroke recurrence, and the impact of the route of insulin administration on GV.ResultsA total of 213 patients were included. Higher GV values were observed in patients who died (n = 16; 7.8%; 30.9 mg/dL vs 23.3 mg/dL; p = 0.05). In a logistic regression analysis adjusted for age and comorbidity, both GV (OR = 1.03; 95% CI, 1.003-1.06; p = 0.03) and stroke severity (OR = 1.12; 95% CI, 1.04-1.2; p = 0.004) were independently associated with mortality at 3 months. No association was found between GV and the other outcomes. Patients receiving subcutaneous insulin showed higher GV than those treated with intravenous insulin (38.95 mg/dL vs 21.34 mg/dL; p < 0.001).ConclusionsHigh GV values during the first 48 hours after ischaemic stroke were independently associated with mortality. Subcutaneous insulin may be associated with higher VG levels than intravenous administration. (AU)

Impacto de la actividad física en la variabilidad glucémica en personas con diabetes mellitus tipo 2 / Impact of physical activity on glycemic variability in people with diabetes mellitus type 2

Uno de los principales roles de la prescripción de actividad física para personas con diabetes tipo 2 es reducir la hiperglucemia. El efecto beneficioso que otorga el entrenamiento físico sobre el nivel glucémico es considerado como la suma de los efectos de cada sesión de ejercicio. Una mejor comprensión de las respuestas agudas al ejercicio, a través de la variabilidad glucémica a corto plazo, podría explicar las diferencias en los resultados de distintos protocolos de entrenamiento. El objetivo del estudio fue analizar la información científica de distintos protocolos de ejercicio y su asociación con la variabilidad glucémica a corto plazo en los pacientes diabéticos tipo 2. Se realizó una revisión sistemática de estudios publicados en idioma inglés y español; los buscadores científicos utilizados fueron: PubMed, Cochrane, ScienceDirect y Medline. Solo se incluyeron estudios realizados en adultos (mayores de 18 años). Se identificaron 36 estudios, los cuales se analizaron y completaron utilizando la plataforma Covidence®, incluyendo para el análisis final 10 artículos y sumando un total de 296 pacientes. Los 10 artículos incluidos fueron divididos acorde al tipo de protocolo de intervención utilizado: grupo 1, ejercicio agudo, y grupo 2, entrenamiento. Se encontraron diferencias significativas sobre la variabilidad glucémica en el 71,4% de los artículos del grupo 1 y en el 100% de los artículos incluidos en el grupo 2. Se demuestran efectos positivos del ejercicio agudo y del entrenamiento físico sobre la variabilidad glucémica a corto plazo, siendo más contundentes los hallazgos en los protocolos de intervención que con base en entrenamiento físico (AU)

One of the main roles of the prescription of physical activity for people with type 2 diabetes is to reduce hyperglycemia. The beneficial effect of physical training on glycemic levels is considered as the sum of the effects of each exercise session. A better understanding of acute responses to exercise, through short-term glycemic variability, could explain the differences in the results of distinct training protocols. The objective of this study was to analyze the scientific information on different exercise protocols and their association with short-term glycemic variability in patients with type 2 diabetes. A systematic review of studies published in English and Spanish was carried out. The databases used were PubMed, Cochrane, ScienceDirect, and Medline. Only studies conducted in adults (older than 18 years) were included. A total of 36 studies were identified, which were analyzed and completed using the Covidence® platform. The final analysis included 10 articles with 296 patients. The 10 included articles were divided according to the type of intervention protocol used: group 1, acute exercise, and group 2, training. Significant differences were found in glycemic variability in 71.4% of the articles in group 1 and in 100% of the articles included in group 2. Positive effects of acute exercise and physical training on short-term glycemic variability were demonstrated. The findings were more pronounced in the intervention protocols than in physical training (AU)

Efecto de la variabilidad glucémica intrahospitalaria en la mortalidad de los pacientes con diabetes / Effect of in-hospital glycemic variability on mortality in patients with diabetes

Introducción El objectivo fue evaluar la importancia de glucemia media (GM) y variabilidad glucémica (VG) durante la hospitalización sobre la mortalidad tras el alta.Material y métodosEstudio de cohortes retrospectivo longitudinal analítico. Se incluyeron pacientes dados de alta del Servicio de Medicina Interna con algún diagnóstico relacionado con la diabetes. El pronóstico evaluado fue la mortalidad. Se recogieron durante el ingreso variables clínicas, analíticas y relacionadas con el control glucémico hospitalario (GM, VG e hipoglucemias). La VG se midió con el coeficiente de variación (CV).Se calcularon las tasas de mortalidad por cada 1000 pacientes-año y se compararon con curvas de Kaplan-Meier. La determinación de los factores predictivos de mortalidad se realizó mediante regresión de Cox.ResultadosSe incluyeron 276 pacientes con edad media 77,6 (DE 10,2) años. La duración mediana del seguimiento extrahospitalario fue de 2,7 años.En análisis multivariante, una GM > 140 (HR=1,72; IC 95% 1,14-2,61; p=0,01) y un CV > 0,29 (HR=1,52; IC 95% 1,12-2,06; p=0,006), no así la presencia de hipoglucemias, se asociaron a incremento del riesgo de mortalidad de forma aditiva e independiente. Tener una GM > 140 simultáneamente con un CV > 0,29 incrementó las tasas de mortalidad (123 vs. 317 por 1.000 pacientes-año; p <0,001) y el riesgo ajustado de mortalidad (HR=2,70; IC 95% 1,71-4,27; p<0,001) respecto a tener una GM ≤ 140mg/dl.ConclusiónLa presencia simultánea de GM y VG elevadas constituye una potente herramienta de estratificación del riesgo de mortalidad tras el alta hospitalaria. (AU)

Introduction The aim of this study was to evaluate the impact of mean blood glucose (MBG) and glycaemic variability (GV) during hospitalisation on mortality after discharge.Material and methodsWe conducted a retrospective longitudinal analytical cohort study that included patients discharged form a department of internal medicine with a diabetes-related diagnosis The evaluated prognosis was mortality. During hospitalisation, the patients’ clinical, laboratory and glycaemic control-related variables were recorded (MBG, GV and hypoglycaemia). The GV was measured with the coefficient of variation (CV).We calculated the mortality rates for every 1000 patient-years and compared them with Kaplan-Meier curves. We determined the predictors of mortality by performing a Cox regression.ResultsThe study included 276 patients with a mean age of 77.6 (SD, 10.2) years. The median outpatient follow-up duration was 2.7 years.In the multivariate analysis, an MBG >140mg/dl (HR, 1.72; 95% CI 1.14–2.61; p=.01) and a CV >0.29 (HR, 1.52; 95% CI 1.12–2.06; p=.006) but not the presence of hypoglycaemia were additively and independently associated with an increased risk of mortality. An MBG >140mg/dl with a CV >0.29 increased the mortality rates (123 vs. 317 per 1000 patient-year; p <.001) and the adjusted mortality risk (HR, 2.70; 95% CI 1.71–4.27; p<.001) compared with having an MBG ≤140mg/dl.ConclusionThe simultaneous presence of a high MBG level and CV constitutes a powerful tool for stratifying mortality risk after hospital discharge. (AU)

Effect of in-hospital glycemic variability on mortality in patients with diabetes.

INTRODUCTION: The aim of this study was to evaluate the impact of mean blood glucose (MBG) and glycaemic variability (GV) during hospitalisation on mortality after discharge. MATERIAL AND METHODS: We conducted a retrospective longitudinal analytical cohort study that included patients discharged form a department of internal medicine with a diabetes-related diagnosis. The evaluated prognosis was mortality. During hospitalisation, the patients' clinical, laboratory and glycaemic control-related variables were recorded (MBG, GV and hypoglycaemia). The GV was measured with the coefficient of variation (CV). We calculated the mortality rates for every 1000 patient-years and compared them with Kaplan-Meier curves. We determined the predictors of mortality by performing a Cox regression. RESULTS: The study included 276 patients with a mean age of 77.6 (SD, 10.2) years. The median outpatient follow-up duration was 2.7 years. In the multivariate analysis, an MBG > 140 mg/dL (HR = 1.72; 95% CI 1.14-2.61; p = .01) and a CV > 0.29 (HR = 1.52; 95% CI 1.12-2.06; p = .006), but not the presence of hypoglycaemia, were additively and independently associated with an increased risk of mortality. An MG > 140 mg/dL with a CV > 0.29 increased the mortality rates (123 vs. 317 per 1000 patient-year; p < .001) and the adjusted mortality risk (HR = 2.70; 95% CI 1.71-4.27; p < .001) compared with having an MBG ≤ 140 mg/dL. CONCLUSION: The simultaneous presence of a high MBG level and CV constitutes a powerful tool for stratifying mortality risk after hospital discharge.

[Impact of physical activity on glycemic variability in people with diabetes mellitus type 2]. / Impacto de la actividad física en la variabilidad glucémica en personas con diabetes mellitus tipo 2.

One of the main roles of the prescription of physical activity for people with type 2 diabetes is to reduce hyperglycemia. The beneficial effect of physical training on glycemic levels is considered as the sum of the effects of each exercise session. A better understanding of acute responses to exercise, through short-term glycemic variability, could explain the differences in the results of distinct training protocols. The objective of this study was to analyze the scientific information on different exercise protocols and their association with short-term glycemic variability in patients with type 2 diabetes. A systematic review of studies published in English and Spanish was carried out. The databases used were PubMed, Cochrane, ScienceDirect, and Medline. Only studies conducted in adults (older than 18 years) were included. A total of 36 studies were identified, which were analyzed and completed using the Covidence® platform. The final analysis included 10 articles with 296 patients. The 10 included articles were divided according to the type of intervention protocol used: group 1, acute exercise, and group 2, training. Significant differences were found in glycemic variability in 71.4% of the articles in group 1 and in 100% of the articles included in group 2. Positive effects of acute exercise and physical training on short-term glycemic variability were demonstrated. The findings were more pronounced in the intervention protocols than in physical training.

Beyond hyperglycemia: glycaemic variability as a prognostic factor after acute ischemic stroke. / Más allá de la hiperglucemia: la variabilidad glucémica como factor pronóstico en el infarto cerebral agudo.

INTRODUCTION: Glycaemic variability (GV) refers to variations in blood glucose levels, and may affect stroke outcomes. This study aims to assess the effect of GV on acute ischaemic stroke progression. METHODS: We performed an exploratory analysis of the multicentre, prospective, observational GLIAS-II study. Capillary glucose levels were measured every 4 hours during the first 48 hours after stroke, and GV was defined as the standard deviation of the mean glucose values. The primary outcomes were mortality and death or dependency at 3 months. Secondary outcomes were in-hospital complications, stroke recurrence, and the impact of the route of insulin administration on GV. RESULTS: A total of 213 patients were included. Higher GV values were observed in patients who died (n = 16; 7.8%; 30.9 mg/dL vs 23.3 mg/dL; p = 0.05). In a logistic regression analysis adjusted for age and comorbidity, both GV (OR = 1.03; 95% CI, 1.003-1.06; p = 0.03) and stroke severity (OR = 1.12; 95% CI, 1.04-1.2; p = 0.004) were independently associated with mortality at 3 months. No association was found between GV and the other outcomes. Patients receiving subcutaneous insulin showed higher GV than those treated with intravenous insulin (38.95 mg/dL vs 21.34 mg/dL; p < 0.001). CONCLUSIONS: High GV values during the first 48 hours after ischaemic stroke were independently associated with mortality. Subcutaneous insulin may be associated with higher VG levels than intravenous administration.

Effect of in-hospital glycemic variability on mortality in patients with diabetes. / Efecto de la variabilidad glucémica intrahospitalaria en la mortalidad de los pacientes con diabetes.

INTRODUCTION: The aim of this study was to evaluate the impact of mean blood glucose (MBG) and glycaemic variability (GV) during hospitalisation on mortality after discharge. MATERIAL AND METHODS: We conducted a retrospective longitudinal analytical cohort study that included patients discharged form a department of internal medicine with a diabetes-related diagnosis The evaluated prognosis was mortality. During hospitalisation, the patients' clinical, laboratory and glycaemic control-related variables were recorded (MBG, GV and hypoglycaemia). The GV was measured with the coefficient of variation (CV). We calculated the mortality rates for every 1000 patient-years and compared them with Kaplan-Meier curves. We determined the predictors of mortality by performing a Cox regression. RESULTS: The study included 276 patients with a mean age of 77.6 (SD, 10.2) years. The median outpatient follow-up duration was 2.7 years. In the multivariate analysis, an MBG >140mg/dl (HR, 1.72; 95% CI 1.14-2.61; p=.01) and a CV >0.29 (HR, 1.52; 95% CI 1.12-2.06; p=.006) but not the presence of hypoglycaemia were additively and independently associated with an increased risk of mortality. An MBG >140mg/dl with a CV >0.29 increased the mortality rates (123 vs. 317 per 1000 patient-year; p <.001) and the adjusted mortality risk (HR, 2.70; 95% CI 1.71-4.27; p<.001) compared with having an MBG ≤140mg/dl. CONCLUSION: The simultaneous presence of a high MBG level and CV constitutes a powerful tool for stratifying mortality risk after hospital discharge.

Relationship between glucose control, glycemic variability, and oxidative stress in children with type 1 diabetes.

INTRODUCTION: Few studies assessing the relationship between oxidative stress and glycemic variability in children with type 1 diabetes mellitus (T1DM) are available, and most of them reported no significant results. OBJECTIVE: To assess the relationship between glucose control, glycemic variability, and oxidative stress as measured by urinary excretion of 8-iso-prostanglandin F2-alpha (8-iso-PGF2α) in children with T1DM. MATERIALS AND METHODS: A cross-sectional study including 25 children with T1DM. Participants were evaluated during five days in two different situations: 1st phase during a summer camp, and 2nd phase in their everyday life at home. The following data were collected in each study phase:. - Six capillary blood glucose measurements per day. Mean blood glucose (MBG) levels and glucose variability parameters, including standard deviation, coefficient of variation, and mean amplitude of glycemic excursions (MAGE), were calculated. - Capillary HbA1c level. - 24-h urine sample to measure 8-iso-PGF2α. RESULTS: There were no statistically significant differences in urinary 8-iso-PGF2α levels (142±37 vs. 172±61pg/mg creatinine) and glucose control and glycemic variability parameters between both phases. In the 2nd phase, statistically significant correlations were found between urinary 8-iso-PGF2α and HbA1c levels (r=0.53), MBG (r=0.72), standard deviation (r=0.49), and MAGE (r=0.42). No significant correlations between glucose control, glycemic variability and urinary 8-iso-PGF2α excretion were found in the 1st phase. CONCLUSIONS: A significant correlation was found between glycemic variability and HbA1c level and urinary 8-iso-PGF2α excretion in a group of children with T1DM during their daily lives. Additional studies are needed to confirm this finding and to explore its long-term impact on health.

Comparison of 2 intravenous insulin protocols: Glycemia variability in critically ill patients. / Comparación de 2 protocolos de insulina intravenosa: variabilidad de la glucemia en pacientes críticos.

OBJECTIVE: Glycemic variability is an independent predictor of mortality in critically ill patients. The objective of this study was to compare two intravenous insulin protocols in critically ill patients regarding the glycemic variability. MATERIAL AND METHODS: This was a retrospective observational study performed by reviewing clinical records of patients from a Critical Care Unit for 4 consecutive months. First, a simpler Scale-Based Intravenous Insulin Protocol (SBIIP) was reviewed and later it was compared for the same months of the following year with a Sliding Scale-Based Intravenous Insulin Protocol (SSBIIP). All adult patients admitted to the unit during the referred months were included. Patients in whom the protocol was not adequately followed were excluded. A total of 557 patients were reviewed, of whom they had needed intravenous insulin 73 in the first group and 52 in the second group. Four and two patients were excluded in each group respectively. RESULTS: Glycemic variability for both day 1 (DS1) and total stay (DST) was lower in SSBIIP patients compared to SBIIP patients: SD1 34.88 vs 18.16 and SDT 36.45 vs 23.65 (P<.001). CONCLUSION: A glycemic management protocol in critically ill patients based on sliding scales decreases glycemic variability.

La variabilidad de la glucemia en pacientes críticamente enfermos: el manejo deberá ser personalizado / Glycemic variability in critically ill patients: the management should be customized / A variabilidade glicêmica em pacientes em estado crítico: o tratamento deve ser personalizado

Resumen: Introducción: Los tres dominios del control glucémico (hipoglucemia, hiperglucemia y variabilidad glucémica) componen un marco conceptual para la disminución de los riesgos asociados a él durante la enfermedad crítica. Aun así, el componente premórbido no suele ser tomado en cuenta en dichos dominios. Se ha demostrado que las metas de glucosa en sangre más liberales pueden beneficiar a aquellos pacientes con hiperglucemia crónica, contrariamente a lo que se ha demostrado en individuos con buen manejo glucémico premórbido. Material y métodos: Mediante el uso de las cifras de hemoglobina glucosilada (HbA1c) y la glucosa predicha de 90 días previos se desarrolló una fórmula de «variabilidad glucémica relativa¼ (VGR) en sujetos adultos críticamente enfermos. Luego, mediante los valores de glucosa capilar, se obtuvieron los eventos de hipoglucemia, la media de glucemia capilar, VGR y coeficiente de variación (CV) glucémica durante los primeros siete días de estancia. Se dividió a la población en HbA1c < 7% y ≥ 7%, así como en vivos y muertos, y se compararon las variables capturadas y calculadas entre estos. Resultados: Mediante el protocolo de control glucémico, las personas con HbA1c ≥ 7% mantuvieron una VGR negativa; es decir, cifras menores a lo habituado. En el grupo < 7%, permanecieron positivas; es decir, mayores a lo habitual. El primer grupo mostró una estancia hospitalaria mayor, nueve versus siete días (p < 0.05); aquellos pacientes con HbA1c < 7% fallecidos mostraron un CV mayor (p < 0.05) 27.49 (11.02-37.07) versus 12.49 (8.2-8.75). Dicha asociación no se encontró en el grupo ≥ 7%. Conclusión: La VGR negativa en relación con el control premórbido muestra efectos negativos en la evolución de los individuos con mal manejo glucémico previo. A su vez, un CV de mayor magnitud mostró su efecto negativo en la mortalidad de aquellos sujetos con buena regulación anterior. Se reitera que en relación con el control glucémico, efectivamente «una talla no se ajusta a todos¼.

Abstract: Introduction: The three domains of glycemic control (hypoglycemia, hyperglycemia and glycemic variability) comprise a conceptual framework for reducing the risk associated with it during critical illness. However, the premorbid component is usually not taken into account. It has been shown that those patients with chronic hyperglycemia could benefit from more liberal glycemic goals, contrary to what has been shown in patients with good premorbid glycemic control. Material and methods: By using the glycosylated hemoglobin (HbA1c) and predicted glucose of the previous 90 days, a formula of «relative glycemic variability¼ (RGV) in critically ill adult patients was developed. Then, using the capillary glucose values, events of hypoglycemia were obtained, as well as mean capillary glucose, RGV and coefficient of variation (CV) during the first seven days of stay. The population was divided into HbA1c < 7% and ≥ 7%, as well as in alive and deceased; the variables between them captured and calculated were compared. Results: Using the glycemic control protocol, HbA1c ≥ 7% patients maintained a negative RGV, that is, lower values than usual; the group < 7% kept a positive RV, higher than usual. The first group showed a prolonged hospital stay, nine versus seven days (p < 0.05), and those deceased and with HbA1c < 7% showed a higher CV (p < 0.05), 27.49 (11.02-37.07) versus 12.49 (8.2-8.75); such association was not observed in the group of patients ≥ 7%. Conclusion: Negative RGV in relation to premorbid control shows negative effects on the evolution of patients with poor previous glycemic control; at the same time, a greater CV showed its negative effect in patients with good previous control. It is reasserted that, in relation to glycemic control, «one size does not fit all¼.

Resumo: Introdução: Os três domínios do controle glicêmico (hipoglicemia, hiperglicemia e variabilidade glicêmica) compreendem uma estrutura conceitual para reduzir os riscos associados com tais controles durante a doença crítica. No entanto, o componente pré-mórbido geralmente não acostuma ser tomado em conta neste âmbito. Demonstrou-se que em pacientes com hiperglicemia crônica as metas da glicemia no sangue mais flexíveis podem beneficiar essa população, ao contrário do que tem sido demonstrado em pacientes com um adequado controle glicêmico pré-mórbido. Material e metodos: Utilizando as cifras da hemoglobina glicosilada (HbA1c) e a glicemia prevista de 90 dias prévios, desenvolveu-se uma fórmula da «Variabilidade Glicêmica Relativa¼ (VGR) nos pacientes adultos em estado crítico. Posteriormente, por meio de valores da glicemia capilar foram obtidos os episódios de hipoglicemia, glicemia capilar média, VGR e coeficiente de variabilidade glicêmica (CV) durante os primeiros 7 dias de estadia hospitalar. A população foi dividida em HbA1c < 7% e ≥7%, assim como nos vivos e mortos, comparando as variáveis ​​capturadas e calculadas entre elas. Resultados: Utilizando o protocolo de controle glicêmico, os pacientes HbA1c ≥7 mantiveram uma VGR negativa, isto é, cifras menores que a habitual e no grupo < 7% positivas que é maior do que o habitual. O primeiro grupo mostrou uma estadia hospitalar maior a 9 vs 7 dias (p < 0.05) e os pacientes com HbA1c < 7% falecidos mostraram um CV maior (p < 0.05) 27.49 (11.02-37.07) vs 12.49 (8.2-8.75), tal associação não foi encontrada no grupo ≥7%. Conclusão: A VGR negativa em relação ao controle pré-mórbido mostra efeitos negativos na evolução dos pacientes com um inadecuado controle glicêmico, um CV de maior magnitude mostrou o seu efeito negativo na mortalidade em pacientes com um adequado controle prévio. Reitera-se que, em relação ao controle glicêmico, efetivamente «uma medida não serve para todos¼.

Prognostic importance of glycaemic variability on hospital mortality in patients hospitalised in Internal Medicine Departments.

INTRODUCTION: The objective was to assess the prognostic importance of various glycaemic control measures on hospital mortality. MATERIAL AND METHODS: Retrospective, analytical cohort study that included patients hospitalised in internal medicine departments with a diagnosis related to diabetes mellitus (DM), excluding acute decompensations. The clinical endpoint was hospital mortality. We recorded clinical, analytical and glycaemic control-related variables (scheduled insulin administration, plasma glycaemia at admission, HbA1c, mean glycaemia (MG) and in-hospital glycaemic variability and hypoglycaemia). The measurement of hospital mortality predictors was performed using univariate and multivariate logistic regression. RESULTS: A total of 384 patients (50.3% men) were included. The mean age was 78.5 (SD, 10.3) years. The DM-related diagnoses were type 2 diabetes (83.6%) and stress hyperglycaemia (6.8%). Thirty-one (8.1%) patients died while in hospital. In the multivariate analysis, the best model for predicting mortality (R(2)=0.326; P<.0001) consisted, in order of importance, of age (χ(2)=8.19; OR=1.094; 95% CI 1.020-1.174; P=.004), Charlson index (χ(2)=7.28; OR=1.48; 95% CI 1.11-1.99; P=.007), initial glycaemia (χ(2)=6.05; OR=1.007; 95% CI 1.001-1.014; P=.014), HbA1c (χ(2)=5.76; OR=0.59; 95% CI 0.33-1; P=.016), glycaemic variability (χ(2)=4.41; OR=1.031; 95% CI 1-1.062; P=.036), need for corticosteroid treatment (χ(2)=4.03; OR=3.1; 95% CI 1-9.64; P=.045), administration of scheduled insulin (χ(2)=3.98; OR=0.26; 95% CI 0.066-1; P=.046) and systolic blood pressure (χ(2)=2.92; OR=0.985; 95% CI 0.97-1.003; P=.088). CONCLUSION: An increase in initial glycaemia and in-hospital glycaemic variability predict the risk of mortality for hospitalised patients with DM.

[Glycemic variability and oxidative stress in children, with type 1 diabetes attending a summer camp]. / Variabilidad glucémica y estrés oxidativo en niños con diabetes tipo 1 asistentes a un campamento.

OBJECTIVE: To assess glycemic variability, oxidative stress and their relationship in children and adolescents with type 1 diabetes (T1DM) attending a summer camp. PATIENTS AND METHOD: Cross-sectional study that included 54 children and adolescents with T1DM aged 7-16, attending a 7 day summer camp. Sociodemographic information, clinical data, and blood glucose values measured using an Accu-Chek Nano® glucose meter were recorded. Glucose variability markers (standard deviation [SD], low blood glucose index [LBGI], high blood glucose index [HBGI], mean amplitude of glycemic excursions [MAGE] and mean of daily differences [MODD]) were calculated. Oxidative stress was assessed by the measurement of 8-iso-prostaglandin F2 alpha (PGF2α) in a 24-hour urine sample collected at the end of the camp in 14 children. RESULTS: The Median SD, MAGE and MODD indexes were in the high range (61, 131 and 58 mg/dl, respectively), LBGI in the moderate range (3.3), and HBGI in the low range (4.5). The mean HbA1c was 7.6% and the median urinary excretion rate of 8-iso-PGF2α was 864.39 pg/mg creatinine. The Spearman correlation coefficients between markers of glycemic variability (SD, HBGI, MAGE, MODD) were significant. Non-significant correlations were found between markers of glycemic variability and urinary 8-iso-PGF2α. CONCLUSIONS: High glycemic variability was observed in children and adolescents attending a summer camp. However, no correlations were found between markers of glycemic variability and oxidative stress measured by urinary 8-iso-PGF2α. Further studies are needed to address the relationship between oxidative stress and glycemic variability in children with T1DM.