Comparison of Glucose Control by Added Liraglutide to Only Insulin Infusion in Diabetic Patient Undergoing Cardiac Surgery: A Preliminary Randomized?Controlled Trial

Background: Liraglutide, glucagon-like peptide-1 (GLP-1) receptor agonist, has been investigated for safety and effectiveness for blood glucose (BG) control in a surgical setting. However, there are only a few studies specific to cardiac surgery patients. Aims: To primarily compare perioperative 1) BG and 2) glycemic variability (GV) between added liraglutide and only insulin infusion in diabetes mellitus (DM) patients undergoing cardiac surgery. Setting and Design: A randomized control trial was conducted in DM patients undergoing cardiac surgery with cardiopulmonary bypass (CPB). Inclusion criteria were age 20� years and DM Type 2. Material and Methods: The recruited patients were randomly assigned to Group 1 (added liraglutide with insulin infusion) and Group 2 (insulin infusion). Insulin infusion was based on institutional protocol. Point of care testing (POCT) glucose was used for the adjustment of insulin and BG analysis. Continuous glucose monitor (CGM) was for GV analysis (using Standard deviation: SD). Statistics: t?test, Chi?square or Fisher?exact test, or Mann朩hitney U test. Results: Finally, 60 patients were in our study (Group 1 = 32 vs Group 2 = 28). Perioperative mean BG levels of Group 1 were significantly lower than Group 2 with a mean difference of 15.9 mg/dL. Nine patients (18.7% vs 10.7%, P = 0.384) had BG of 60� with mean BGs (109.1 vs 147.9, P = 0.001) in the morning. Thirteen patients (9.4% vs 35.7%, P = 0.025) had BG >180 mg/dL at the 1st operative hour. SDs were increasing, but lower SD of Group 1 were observed at the postoperative period. Mean of SDs at postoperative day 2 were 23.65 vs 32.79 mg/dL, P = 0.018. Conclusions: Liraglutide added with insulin infusion can attenuate perioperative BG and is beneficial in the aspect of lowering GV together with BG at the postoperative period in DM patients. Liraglutide can be applied in cardiac surgery but a rearrangement of time and dosage should be further investigated.

Maintenance of plasma glucose variability after an acute session of aerobic exercise despite changes in insulin and glucagon-like peptide-1 levels in type 2 diabetes

ABSTRACT Objective: The present study aimed to evaluate glucose variability and hormonal responses during and after an aerobic exercise session performed after breakfast in type 2 diabetes patients treated with metformin. Materials and methods: In this quasi-experimental study individuals underwent clinical and laboratory evaluations and maximal exercise test. After two weeks an aerobic exercise session (30 minutes at 60%-70% of the peak heart rate) was performed. At rest, during and after the exercise session, glucose variability (mean amplitude glucose excursions, glucose coefficient of variation, and glucose standard deviation) and levels of plasma glucose, insulin, glucagon, and glucagon-like-peptide-1 were evaluated. Results: Thirteen patients were enrolled in the study. Plasma glucose increased at 15 minutes during the exercise session (244.6 ± 61.9 mg/dL), and decreased at 60 min after exercise (195.6 ± 50.0 mg/dL). Glucose variability did not show any difference before and after exercise. Insulin levels at 15 min [27.1 µU/mL (14.2-42.1)] and 30 min [26.3 µU/mL (14.6-37.4)] during the exercise were higher than those at fasting [11.2 µU/mL (6.7-14.9)] but decreased 60 minutes after exercise (90 minutes) [16.6 µU/mL (8.7-31.7)]. Glucagon levels did not show any difference. GLP-1 levels increased at 30 min [7.9 pmol/L (7.1-9.2)] during exercise and decreased 60 min after exercise (90 minutes) [7.7 pmol/L (6.8-8.5)]. Conclusion: Subjects with type 2 diabetes presented expected changes in insulin, glucagon and GLP-1 levels after breakfast and a single aerobic exercise session, not accompanied by glycemic variability changes.

Factors associated with glycemic variability in children with type 1 diabetes mellitus based on flash glucose monitoring system / 中南大学学报(医学版)

OBJECTIVES@#Patients with classical type 1 diabetes mellitus (T1DM) require lifelong dependence on exogenous insulin therapy due to pancreatic beta-cell destruction and absolute insulin deficiency. T1DM accounts for about 90% of children with diabetes in China, with a rapid increase in incidence and a younger-age trend. Epidemiological studies have shown that the overall glycated haemoglobin (HbA1c) and compliance rate are low in Chinese children with T1DM. Optimal glucose control is the key for diabetes treatment, and maintaining blood glucose within the target range can prevent or delay chronic vascular complications in patients with T1DM. Therefore, this study aims to investigate the glycemic control of children with T1DM from Hunan and Henan Province with flash glucose monitoring system (FGMS), and to explore factors associated with glycemic variability.@*METHODS@#A total of 215 children with T1DM under 14 years old were enrolled continuously in 16 hospitals from August 2017 to August 2020. All subjects wore a FGMS device to collect glucose data. Correlation of HbA1c, duration of diabetes, or glucose scan rates with glycemic variability was analyzed. Glucose variability was compared according to the duration of diabetes, HbA1c, glucose scan rates and insulin schema.@*RESULTS@#HbA1c and duration of diabetes were positively correlated with mean blood glucose, standard deviation of glucose, mean amplitude of glucose excursions (MAGE), and coefficient of variation (CV) of glucose (all P<0.01). The glucose scan rates during FGMS wearing was significantly positively correlated with time in range (TIR) (P=0.001) and negatively correlated with MAGE and mean duration of hypoglycemia (all P<0.01). Children with duration ≤1 year had lower time below range (TBR) and MAGE when compared with those with duration >1 year (all P<0.05). TIR and TBR in patients with HbA1c ≤7.5% were higher (TIR: 65% vs 45%, TBR: 5% vs 4%, P<0.05), MAGE was lower (7.0 mmol/L vs 9.4 mmol/L, P<0.001) than those in HbA1c >7.5% group. Compared to the multiple daily insulin injections group, TIR was higher (60% vs 52%, P=0.006), MAGE was lower (P=0.006) in the continuous subcutaneous insulin infusion group. HbA1c was lower in the high scan rates (≥14 times/d) group (7.4% vs 8.0%, P=0.046), TIR was significantly higher (58% vs 47%, P<0.001), and MAGE was lower (P<0.001) than those in the low scan rate (<14 times/d) group.@*CONCLUSIONS@#The overall glycemic control of T1DM patients under 14 years old in Hunan and Henan Province is under a high risk of hypoglycemia and great glycemic variability. Shorter duration of diabetes, targeted HbA1c, higher glucose scan rates, and CSII are associated with less glycemic variability.

The Effect of DPP4 Inhibitor on Glycemic Variability in Patients with Type 2 Diabetes treated with twice-daily Premixed Human Insulin / Journal of the ASEAN Federation of Endocrine Societies

Objective@#To evaluate the effect of adding DPP4 inhibitor (DPP4-i) on glycemic variability (GV) in patients with type 2 diabetes mellitus (T2DM) treated with premixed human insulin (MHI).@*Methodology@#We conducted a prospective study in patients with T2DM on twice-daily MHI with or without metformin therapy. Blinded continuous glucose monitoring was performed at baseline and following 6 weeks of Vildagliptin therapy.@*Results@#Twelve patients with mean (SD) age of 55.8 (13.1) years and duration of disease of 14.0 (6.6) years were recruited. The addition of Vildagliptin significantly reduced GV indices (mmol/L): SD from 2.73 (IQR 2.12-3.66) to 2.11 (1.76-2.55), p=0.015; mean amplitude of glycemic excursions (MAGE) 6.94(2.61) to 5.72 (1.87), p=0.018 and CV 34.05 (8.76) to 28.19 (5.36), p=0.010. In addition, % time in range (3.9-10 mmol/l) improved from 61.17 (20.50) to 79.67 (15.33)%, p=0.001; % time above range reduced from 32.92 (23.99) to 18.50 (15.62)%, p=0.016; with reduction in AUC for hyperglycemia from 1.24 (1.31) to 0.47 (0.71) mmol/day, p=0.015. Hypoglycemic events were infrequent and the reduction in time below range and AUC for hypoglycemia did not reach statistical significance.@*Conclusion@#The addition of DPP4-I to commonly prescribed twice-daily MHI in patients with T2DM improves GV and warrants further exploration.

Relationship between short and long-term glycemic variability and oxidative stress in type 1 diabetes mellitus under daily life insulin treatment

ABSTRACT Objectives: The purpose of this study was to investigate the heterogeneity of the association between glycemic variability and oxidative stress markers in T1DM patients under daily life insulin treatment. Subjects and methods: We studied, in a cross-sectional analysis, 76 T1DM patients without clinical chronic diabetes complications and 22 healthy individuals. Were evaluated the short-term glycemic variability (STGV), long-term glycemic variability (LTGV), oxidative stress markers [8-isoprostaglandin-F2α (Ur-8-iso-PGF2α), nitric oxide (NO), thiobarbituric acid reactive substances (TBARS) and erythrocytes reduced/oxidized glutathione (GSH/GSSG)] and biochemical dosages (glycaemia, HbA1c, lipidogram, albuminuria). Results: Plasmatic NO was positively associated with LTGV (last year average of HbA1c) (8.7 ± 1.6% or 71 ± 18 mmol) (rS: 0.278; p: 0.042). Plasmatic TBARS, erythrocytes GSH/GSSH and Ur-8-iso-PGF-2α didn't show correlation with glycemic variability. GSH/GSSG was inversely correlated with LDL-cholesterol (rS: - 0.417; p: 0.047) and triglycerides (rS: −0.521; p: 0.013). Albuminuria was positive correlated with age (rS: 0.340; p: 0.002), plasmatic NO (rS: 0.267; p 0.049) and TBARS (rS: 0.327; p: 0.015). Conclusion: In daily life insulin treatment, young T1DM patients have higher plasmatic NO than healthy subjects. However, the correlation between glycemic variability and oxidative stress markers is heterogeneous. Lipid profile and albuminuria are associated with different oxidative stress markers. These data collaborate to explain the controversial results in this issue.

Continuous Blood Glucose Monitoring to Determine the Glycemic Variability in Patients Having SARS CoV-2 Infection with ARDS and Its Bearing on the Severity of the Disease

Aims and Objectives:A study to determine the effect of glycemic variability measured by continuous blood glucose monitoring as assessed by standard deviation of each SARS CoV -2 patient's mean glucose level and to correlate with the severity of the disease.Study Design:Cross-sectional observational study of 13 patients with SARS CoV-2 infection with Acute Respiratory Distress Syndrome (ARDS) with and without diabetes.Place and Duration of Study:Department of Medicine, Dhiraj Hospital, Smt. Bhikhiben Kanjibhai Shah MedicalCollege and Research Institute; between June 2020 to July 2020.Results:13 patients of SARS CoV-2 with ARDS were enrolled in the study. The median age of the enrolled patients was 55±12 years. Out of the 13 patients, 5 patients belonged to mild and severe category of ARDS each respectively and 3 patients belonged to the moderate category of ARDS. There was a gradual rise in inflammatory markers such as serum LDH, Ferritin, CRP from mild to severe ARDS and D-dimer level was more than double in severe category as compared to the mild ARDS. Normal glycemic variability in adults is 0-3 SD, and we found that there was a significant co-relation of glycemic variability with severity of the disease evidenced by the mean standard deviation of severe ARDS patients as 27.44 SD; whereas 19.26 SD and 9.7 SD for moderate and mild ARDS patients respectively. Hypoglycemia was documented in 10 patients. The maximum stay in the hospital was that of the patients with high glycemic variability that is 22 ± 2 daysConclusion:This preliminary study relates glycemic variability with severity of ARDS in patients of severe SARS CoV-2. Frequent episode of hypoglycemia is not uncommon and should be monitored

Different amounts of moderate to vigorous physical activity and change in glycemic variability in adolescents with type 1 diabetes: is there dose-response relationship?

ABSTRACT Objective To identify the level of physical activity and glycemic variability of adolescents with type 1 diabetes mellitus and to compare glycemic variability on days with different amounts of moderate to vigorous physical activity (MVPA). Subjects and methods A sample of 34 subjects aged 10 to 15 years, 18 (52.94%) female; age: 13.04 ± 1.94; HbA1c: 9.76 ± 1.51. Physical activity was measured by wGT3X accelerometer. The glucose data were obtained using continuous glucose monitoring, and the following glycemic variability measures were calculated: standard deviation (SD), low blood glucose index (LBGI), high blood glucose index (HBGI), mean amplitude of glycemic excursions (MAGE), glycemic risk assessment in diabetes equation (GRADE) and coefficient of variation (CV). The most and least active days (the days with greater and lesser time dedicated to physical activities of moderate to vigorous intensity, respectively) were identified. In addition, based on the whole period of accelerometer use, daily means of time spent in MVPA were identified among participants, who were then divided into three groups: up to 100 minutes; from 101 to 200 minutes and above 201 minutes. Then, the measures of glycemic variability were compared among the most and least active days and among the groups too. Results The amount of MVPA was significantly different between the days evaluated (237.49 ± 93.29 vs. 125.21 ± 58.10 minutes), but glycemic variability measures did not present a significant difference. Conclusion Despite the significant differences in the amount of MVPA between the two days evaluated, the glycemic variability did not change significantly. Arch Endocrinol Metab. 2020;64(3):312-8

Glycemic patterns and factors associated with Post-Hemodialysis Hyperglycemia among end-stage Renal Disease patients undergoing, maintenance Hemodialysis / Journal of the ASEAN Federation of Endocrine Societies

Introduction@#Chronic and post-prandial hyperglycemia are independent risk factors for diabetic complications. Glycemic patterns among hemodialysis end-stage-renal-disease (ESRD) differ as glucose metabolism changes with declining kidney function with more pronounced glycemic fluctuations. The objectives of this study are to determine glycemic patterns on hemodialysis days, the magnitude of post-hemodialysis rebound hyperglycemia (PHH) and their associated factors.@*Methodology@#148 patients on hemodialysis were analysed, 91 patients had end-stage-diabetic-renal disease (DM-ESRD), and 57 patients had end-stage-non-diabetic renal disease (NDM-ESRD). Glycemic patterns and PHH data were obtained from 11-point and 7-point self-monitoring blood glucose (SMBG) profiles on hemodialysis and non-hemodialysis days. PHH and its associated factors were analysed with logistic regression.@*Results@#Mean blood glucose on hemodialysis days was 9.33 [SD 2.7] mmol/L in DM-ESRD patients compared to 6.07 [SD 0.85] mmol/L in those with NDM-ESRD (p<0.001). PHH occurred in 70% of patients and was more pronounced in DM-ESRD compared to NDM-ESRD patients (72.5% vs 27.5%; OR 4.5). Asymptomatic hypoglycemia was observed in 18% of patients. DM-ESRD, older age, previous IHD, obesity, high HbA1c, elevated highly-sensitive CRP and low albumin were associated with PHH.@*Conclusion@#DM-ESRD patients experienced significant PHH in our cohort. Other associated factors include older age, previous IHD, obesity, high HbA1c, elevated hs-CRP and low albumin.

Impact of glycemic variability on left ventricular function in patients with acute ST-segment elevation myocardial infarction and type 2 diabetes / 中国综合临床

Objective To assess the impact of glycemic variability on left ventricular function in patients with acute ST-segment elevation myocardial infarction (STEMI) and type 2 diabetes.Methods Three hundred and three patients with type 2 diabetes and first STEMI between May 2014 and December 2016 in Beijing Anzhen Hospital,Capital Medical University were seclected continuously.All participants' continuous glucose monitoring system (CGMS) parameters,echocardiogram and biochemical characteristics were measured at baseline.According to the level of mean amplitude of glycemic excursion (MAGE) which is the gold indicator to present glycemic variability patients were classified into low MAGE group (n=182) and high MAGE group (n =117).Impact of glycemic variability on left ventricular function in patients with acute ST-segment elevation myocardial infarction and type 2 diabetes were analysed.Results (1) Cardiac function evaluation:The level of left ventricular ejection fraction (LVEF) were significantly lower in high MAGE group than in low MAGE group ((43.8± 7.2) vs.(52.3± 8.5) ％,t =4.912,P＜ 0.001).There were significant differences between the two groups in Killip classification (x2 =49.931,P＜ 0.001).(2) Pearson correlation analysis shows that LVEF negatively correlated with the levels of MAGE(r=-0.367,P＜0.001),postprandial glucose excursion (PPGE) (r=-0.274,P=0.003),Hemoglobin A1c(HbA1c) (r=-0.238,P =0.010),serum highsensitive C-reactive protein (hs-CRP) via logarithmic transformation (r =-0.245,P =0.008) and fasting plasma glucose (FPG) (r =-0.229,P =0.021).Killip classification positively correlated with the levels of MAGE (r =0.301,P ＜ 0.001),PPGE (r =0.228,P =0.022),hs-CRP via logarithmic transformation (r =0.234,P =0.019),H bA 1 c (r =0.195,P =0.041) and FPG (r =0.193,P =0.045).(3) Multiple stepwise regression analysis and multivariate Logistic regression analysis indicated that the level of MAGE was independent risk factor of LVEF (t =-2.279,P =0.005,95％ CI(-3.160 -0.219)) and the level of MAGE was an independent risk factor of Killip classification (Waldx2 =5.673,OR=1.665,95％CI(1.095-2.534),P=0.017).Conclusion Glycemic variability is associated with the presence and severity of left ventricular function in patients with STEMI and type 2 diabetes.

Predictive value of glycosylated serum protein combined with glycemic variability on secondary persistent inflammatory immunosuppressed catabolic syndrome prediction in elderly septic patients / 中华危重病急救医学

Objective To investigate the predictive value of glycosylated serum protein (GSP) combined with glycemic variability (GV) in persistent inflammation immunosuppressive catabolic syndrome (PICS) in elderly septic patients. Methods A retrospective study was conducted. The septic patients aged≥60 years old with 28 days hospitalized duration admitted to geriatric intensive care unit (ICU) of Guangzhou General Hospital of Guangzhou Military Command from January 2014 to December 2017 were enrolled. The patients were divided into two groups according to whether PICS occurred within 14 days after ICU admission according to the PICS diagnostic criteria. General patients' data including gender, age, underlying disease, site of infection, the length of ICU stay were collected, acute physiology and chronic health evaluation Ⅱ (APACHE Ⅱ), GSP at 1 day after hospitalization and lymphocyte count (LYM), C-reactive protein (CRP), albumin (ALB), prealbumin (PA) levels at 1 day and 14 days were recorded. The levels of blood glucose on the 1st day and 14th day were observed, the GV was calculated. Data were cross-validated using the random forest method. Receiver operating characteristic (ROC) curve was plotted to evaluate the predictive value of glycemic parameters for PICS. Results A total of 315 elderly septic patients were included. Patients with malignant tumors, severe autoimmune diseases, and immunosuppressive therapy or dead within 28 days of hospitalization were excluded. A total of 132 patients were enrolled in the analysis, including 45 in the PICS group and 87 in the non-PICS group. The length of ICU stay in the PICS group was significantly longer than that in the non-PICS group [days: 35.0 (22.0, 49.5) vs. 8.0 (5.0, 23.0), P < 0.01]. No significant difference in the baseline data of gender, age, underlying disease, infection site or APACHE Ⅱ score between the two groups was found. ① Parameters for PICS diagnosis: with the prolongation of ICU stay, LYM and PA in the non-PICS group were increased and those in the PICS group were decreased, and CRP and ALB levels were decreased in both groups. LYM, ALB and PA levels in the PICS group were significantly lower than those in the non-PICS group at 14 days after ICU admission [LYM (×109/L): 0.6 (0.5, 0.7) vs. 1.1 (0.9, 1.6), ALB (g/L): 25.4±2.7 vs. 29.9±4.3, PA (g/L): 0.08 (0.05, 0.14) vs. 0.11 (0.10, 0.21), all P < 0.01], and CRP level was significantly higher than that in the non-PICS group (mg/L: 87.5±56.3 vs. 49.2±49.1, P < 0.01). ② Glycemic parameters: the GSP level of the PICS group at 1 day after ICU admission was significantly lower than that of the non-PICS group (mmol/L: 2.3±0.6 vs. 2.7±0.6, P < 0.01), but there was no statistically significant difference in the level of blood glucose or GV at 1 day and 14 days after ICU admission as compared with the non-PICS group [blood glucose (mmol/L): 10.0±3.3 vs. 9.4±3.3 at 1 day, 10.8±3.6 vs. 10.4±3.5 at 14 days; GV: (24.2±1.4)% vs. (23.7±1.2)% at 1 day, (24.8±7.8)% vs. (24.7±7.7)% at 14 days, all P > 0.05]. ③ ROC curve analysis: 1-day GSP as well as 1-day and 14-day GV had certain predictive value for PICS secondary to sepsis in the elderly. The predictive value of 1-day GSP combined with 14-day GV was the highest, its area under ROC curve (AUC) was 0.637, with a sensitivity of 95.8% and a specificity of 25.0%, while the positive likelihood ratio was 1.278, the negative likelihood ratio was 0.167, the positive predictive value was 71.9%, and the negative predictive value was 75.0%. Conclusion GSP combined with GV could effectively predict secondary PICS in elderly septic patients.

Effect of peritoneal dialysis on glycemic variability in patients with diabetes and its clinical implications / 中华临床营养杂志

Objective To compare glycemic profile between diabetic patients receiving peritoneal dialysis and diabetic patients with normal kidney function, and to investigate the impact of peritoneal dialysis on glycemic control through continuous glucose monitor system ( CGMS). Methods 19 diabetic patients with end-stage renal disease receiving regular peritoneal dialysis (DMPD group) and 8 patients with non-diabetic ne-phropathy receiving regular peritoneal dialysis ( PD group) were randomly selected and matched with 20 diabetic patients with normal kidney function (DM group) based on age, gender and 72 hours mean glucose. CGMS were applied on all patients for 72 hours. Glycemic variability parameters were compared among the three groups. Results Peritoneal transport function was positively correlated with mean glucose, glucose standard deviation and mean amplitude of glycemic excursion. Compared with PD group, multiple variation parameters, such as intraday glycemic standard deviation (P<0. 001), covariant efficiency (P=0. 009) and mean of daily difference (P=0. 043), were significantly lower in DMPD group. Though both DMPD and DM group exhibited profile as trough in wee hours and post-prandial hyperglycemia, DMPD had higher glycemic level in wee hours (P<0. 001). Conclusion Diabetic patients with end-stage renal disease receiving regular peritoneal dialysis have smaller glucose variability than diabetic patients with normal renal function.

Glycemic variability in hemodialysis patients: implications, characteristics and interventions / 中华临床营养杂志

Glycemic variability is an important indicator for glycemic control and an independent risk factor for cardiovascular events and overall mortality in type 2 diabetes.Hemodialysis patients have greater challenge controling glycemic variability because patients of end-stage renal disease generally have more "brittle" glycemic hemostasis and dialysis itself may cause extra disturbance.In this article,we present an overview on the characteristics,cause,potential damage,and intervention of glycemic variability in hemodialysis patients.

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.

Effects of Vildagliptin or Pioglitazone on Glycemic Variability and Oxidative Stress in Patients with Type 2 Diabetes Inadequately Controlled with Metformin Monotherapy: A 16-Week, Randomised, Open Label, Pilot Study

BACKGROUND: Glycemic variability is associated with the development of diabetic complications through the activation of oxidative stress. This study aimed to evaluate the effects of a dipeptidyl peptidase 4 inhibitor, vildagliptin, or a thiazolidinedione, pioglitazone, on glycemic variability and oxidative stress in patients with type 2 diabetes. METHODS: In this open label, randomised, active-controlled, pilot trial, individuals who were inadequately controlled with metformin monotherapy were assigned to either vildagliptin (50 mg twice daily, n=17) or pioglitazone (15 mg once daily, n=14) treatment groups for 16 weeks. Glycemic variability was assessed by calculating the mean amplitude of glycemic excursions (MAGE), which was obtained from continuous glucose monitoring. Urinary 8-iso prostaglandin F₂α, serum oxidised low density lipoprotein, and high-sensitivity C-reactive protein were used as markers of oxidative stress or inflammation. RESULTS: Both vildagliptin and pioglitazone significantly reduced glycated hemoglobin and mean plasma glucose levels during the 16-week treatment. Vildagliptin also significantly reduced the MAGE (from 93.8±38.0 to 70.8±19.2 mg/dL, P=0.046), and mean standard deviation of 24 hours glucose (from 38±17.3 to 27.7±6.9, P=0.026); however, pioglitazone did not, although the magnitude of decline was similar in both groups. Markers of oxidative stress or inflammation including urinary 8-iso prostaglandin F₂α did not change after treatment in both groups. CONCLUSION: In this 16-week treatment trial, vildagliptin, but not pioglitazone, reduced glycemic variability in individuals with type 2 diabetes who was inadequately controlled with metformin monotherapy, although a reduction of oxidative stress markers was not observed.

Influencing Factors of Glycemic Variability in 217 Cases of Hospitalized Patients with Type 2 Diabetes / 中国医科大学学报

Objective To explore the influencing factors of glycemic variability in 217 cases of hospitalized patients with type 2 diabetes. Meth-ods A total of 217 cases of hospitalized patients with type 2 diabetes,whom received continuous glucose monitoring from January 2013 to Janu-ary 2016,were enrolled for the study. The evaluation variables of glycemic variability included mean amplitude of glycemic excursion(MAGE) and standard deviation of blood glucose(SDBG). Results The difference of glycemic variability was compared by gender,age,diabetic duration, HbA1c,BMI. The values of MAGE and SDBG in females were higher than those in males(P<0.05). There was no significant difference between various age groups and various diabetic duration. The level of glycemic variability increased gradually with the extension of HbA 1c(P<0.05). The level of glycemic variability increased gradually with the extension of body mass index(BMI)(P<0.05). Logistic regression analysis showed that gender(OR=0.67,P=0.02),HbA1c(OR=0.8,P=0.02),diastolic blood pressure(OR=0.9,P=0.03),triglycerides(OR=4.6,P=0.007),cholesterol(OR=0.6,P=0.007). HDL-C(OR=0.09,P=0.006)were significant influencing factors of glycemic variability in hospital-ized patients with type 2 diabetes. Conclusion Gender,HbA1c,BMI,and blood fat are significant influencing factors of glycemic variability while age and duration are not related to the glycemic variability in hospitalized patients with type 2 diabetes.

1,5-Anhydro-D-Glucitol Could Reflect Hypoglycemia Risk in Patients with Type 2 Diabetes Receiving Insulin Therapy

BACKGROUND: The identification of a marker for hypoglycemia could help patients achieve strict glucose control with a lower risk of hypoglycemia. 1,5-Anhydro-D-glucitol (1,5-AG) reflects postprandial hyperglycemia in patients with well-controlled diabetes, which contributes to glycemic variability. Because glycemic variability is related to hypoglycemia, we aimed to evaluate the value of 1,5-AG as a marker of hypoglycemia. METHODS: We enrolled 18 adults with type 2 diabetes mellitus (T2DM) receiving insulin therapy and assessed the occurrence of hypoglycemia within a 3-month period. We measured 1,5-AG level, performed a survey to score the severity of hypoglycemia, and applied a continuous glucose monitoring system (CGMS). RESULTS: 1,5-AG was significantly lower in the high hypoglycemia-score group compared to the low-score group. Additionally, the duration of insulin treatment was significantly longer in the high-score group. Subsequent analyses were adjusted by the duration of insulin treatment and mean blood glucose, which was closely associated with both 1,5-AG level and hypoglycemia risk. In adjusted correlation analyses, 1,5-AG was negatively correlated with hypoglycemia score, area under the curve at 80 mg/dL, and low blood glucose index during CGMS (P=0.068, P=0.033, and P=0.060, respectively). CONCLUSION: 1,5-AG level was negatively associated with hypoglycemia score determined by recall and with documented hypoglycemia after adjusting for mean glucose and duration of insulin treatment. As a result, this level could be a marker of the risk of hypoglycemia in patients with well-controlled T2DM receiving insulin therapy.

Glycemic Variability: How Do We Measure It and Why Is It Important?

Chronic hyperglycemia is the primary risk factor for the development of complications in diabetes mellitus (DM); however, it is believed that frequent or large glucose fluctuations may independently contribute to diabetes-related complications. Postprandial spikes in blood glucose, as well as hypoglycemic events, are blamed for increased cardiovascular events in DM. Glycemic variability (GV) includes both of these events; hence, minimizing GV can prevent future cardiovascular events. Correcting GV emerges as a target to be pursued in clinical practice to safely reduce the mean blood glucose and to determine its direct effects on vascular complications in diabetes. Modern diabetes management modalities, including glucagon-related peptide-1-based therapy, newer insulins, modern insulin pumps and bariatric surgery, significantly reduce GV. However, defining GV remains a challenge primarily due to the difficulty of measuring it and the lack of consensus regarding the optimal approach for its management. The purpose of this manuscript was not only to review the most recent evidence on GV but also to help readers better understand the available measurement options and how the various definitions relate differently to the development of diabetic complications.

Factors Associated with Glycemic Variability in Patients with Type 2 Diabetes: Focus on Oral Hypoglycemic Agents and Cardiovascular Risk Factors

BACKGROUND: The role of glycemic variability (GV) in development of cardiovascular diseases remains controversial, and factors that determine glucose fluctuation in patients with diabetes are unknown. We investigated relationships between GV indices, kinds of oral hypoglycemic agents (OHAs), and cardiovascular risk factors in patients with type 2 diabetes mellitus (T2DM). METHODS: We analyzed 209 patients with T2DM. The GV index (standard deviation [SD] and mean absolute glucose change [MAG]) were calculated from 7-point self-monitoring of blood glucose profiles. The patients were classified into four groups according to whether they take OHAs known as GV-lowering (A) and GV-increasing (B): 1 (A only), 2 (neither), 3 (both A and B), and 4 (B only). The 10-year risk for atherosclerotic cardiovascular disease (ASCVD) was calculated using the Pooled Cohort Equations. RESULTS: GV indices were significantly higher in patients taking sulfonylureas (SUs), but lower in those taking dipeptidyl peptidase-4 inhibitors. In hierarchical regression analysis, the use of SUs remained independent correlates of the SD (beta=0.209, P=0.009) and MAG (beta=0.214, P=0.011). In four OHA groups, GV indices increased progressively from group 1 to group 4. However, these did not differ according to quartiles of 10-year ASCVD risk. CONCLUSION: GV indices correlated significantly with the use of OHAs, particularly SU, and differed significantly according to combination of OHAs. However, cardiovascular risk factors and 10-year ASCVD risk were not related to GV indices. These findings suggest that GV is largely determined by properties of OHAs and not to cardiovascular complications in patients with T2DM.

1,5-Anhydroglucitol as a Useful Marker for Assessing Short-Term Glycemic Excursions in Type 1 Diabetes

BACKGROUND: Type 1 diabetes is associated with more severe glycemic variability and more frequent hypoglycemia than type 2 diabetes. Glycemic variability is associated with poor glycemic control and diabetic complications. In this study, we demonstrate the clinical usefulness of serum 1,5-anhydroglucitol (1,5-AG) for assessing changes in glycemic excursion in type 1 diabetes. METHODS: Seventeen patients with type 1 diabetes were enrolled in this study. A continuous glucose monitoring system (CGMS) was applied twice at a 2-week interval to evaluate changes in glycemic variability. The changes in serum glycemic assays, including 1,5-AG, glycated albumin and hemoglobin A1c (HbA1c), were also evaluated. RESULTS: Most subjects showed severe glycemic excursions, including hypoglycemia and hyperglycemia. The change in 1,5-AG level was significantly correlated with changes in the glycemic excursion indices of the standard deviation (SD), mean amplitude of glucose excursion (MAGE), lability index, mean postmeal maximum glucose, and area under the curve for glucose above 180 mg/dL (r=-0.576, -0.613, -0.600, -0.630, and -0.500, respectively; all P<0.05). Changes in glycated albumin were correlated with changes in SD and MAGE (r=0.495 and 0.517, respectively; all P<0.05). However, changes in HbA1c were not correlated with any changes in the CGMS variables. CONCLUSION: 1,5-AG may be a useful marker for the assessment of short-term changes in glycemic variability. Furthermore, 1,5-AG may have clinical implications for the evaluation and treatment of glycemic excursions in type 1 diabetes.