High Glucose Variability Research Articles

Electronic dashboard-based remote glycemic management program reduces length of stay and readmission rate among hospitalized adults.

Aims/IntroductionCurrently, the impact of hospital‐wide glycemic control interventions on length of hospital stay (LOS) and readmission rates are largely unknown. We investigated the impact of a 4‐year hospital‐wide remote glycemic management program on LOS and 30‐day readmission rates among hospitalized adults who received glucose monitoring.Materials and MethodsIn this retrospective study, hospitalized patients who received glucose monitoring were classified into groups 1 (high glucose variability), 2 (hypoglycemia), 3 (hyperglycemia) and 4 (relatively stable). The monthly percentage changes, and average monthly percentage changes of hyperglycemia, hypoglycemia and treat to target were determined using joinpoint regression analysis.ResultsA total of 106,528 hospitalized patients (mean age 60.9 ± 18.5 years, 57% men) were enrolled. We observed a significant reduction in the percentage of inpatients in poor glycemic control groups (groups 1, 2 and 3, all P < 0.001), and a reciprocal increase in the relatively stable group (group 4) from 2016 to 2019. We found a significant reduction in LOS by 11.4% (10.5–9.3 days, P = 0.002, after adjustment for age, sex, and admission department). The 30‐day readmission rate decreased from 29.9% to 29.3%, mainly among those in group 4 in 2019 (P < 0.001 after adjustment of sex, age, admission department and LOS).ConclusionsImproved glycemic control through a hospital‐wide electronic remote glycemic management system reduced LOS and 30‐day readmission rates. Findings observed in this study might be associated with the reduction in cost of avoidable hospitalizations.

Long-term effects of continuous subcutaneous insulin infusion in adults with type 1 diabetes mellitus patients: Results of a public healthcare system

AimTo evaluate the long-term clinical effect of continuous subcutaneous insulin infusion (CSII) in adult type 1 diabetes mellitus (T1DM) patients in a regional public healthcare system real-world scenario. MethodsAll adult T1DM patients on CSII for ≥10 years subjected to follow-up in the regional Castilla-La Mancha Public Health Service were included. The primary efficacy outcome was the variation in HbA1c during follow-up. Direct patient data were compiled through the web-based Spanish national registry on CSII therapy. ResultsA total of 69 T1DM adult patients were treated with insulin pumps for ≥10 years in our region. The mean age was 45.0±10.5 years, with a T1DM duration of 13.9±8.5 years. The mean duration of CSII therapy was 11.4±2.1 years. The main indications for treatment were high glucose variability (39%), problematic hypoglycemia (26%), and HbA1c >53mmol/mol (7%) on multiple daily injections (20%). Sensor-augmented pump therapy was used by 31% of the patients. Glycosylated hemoglobin did not change during follow-up (58±11mmol/mol vs. 58±11mmol/mol; 7.5±1.0 vs. 7.5±1.0; p=0.66). However, the percentage of patients with at least one episode of severe hypoglycemia during the last year and unnoticed hypoglycemia decreased from 36% to 7% (p=0.006) and from 38% to 32% (p<0.001), respectively. The proportion of subjects with ≥1 episode of diabetic ketoacidosis in the last year decreased from 30% to 6% (p=0.045). ConclusionsThe reduction of severe hypoglycemia without deterioration of glycemic control can be sustained over long-term CSII therapy.

Critical illness myopathy precedes hyperglycaemia and high glucose variability

Critical Illness Myopathy (CIM) is a serious ICU complication, and dysglycaemia is widely regarded as a risk factor. Although glucose variability (GV) has been independently linked to ICU mortality, an association with CIM has not been investigated. This study examines the relationship between CIM and GV. Retrospective investigation including ICU patients with SOFA ≥8, mechanical ventilation, and CIM diagnostics. Glucose readings were collected every 6h throughout the first week of treatment, when CIM is thought to develop. GV was measured using standard deviation (SD), coefficient of variability (CV), mean absolute glucose (MAG), mean amplitude of glycaemic excursions (MAGE), and mean of daily difference (MODD). 74 patients were included, and 50 (67.6%) developed CIM. Time on glycaemic target (70-179mg/dL), caloric and insulin intakes, mean, maximum and minimum blood glucose values were similar for all patients until the 5th day, after which CIM patients exhibited higher mean and maximum glucose levels. Significantly higher GV in CIM patients were observed on day 5 (SD, CV, MAG, MAGE), day 6 (MODD), and day 7 (SD, CV, MAG). CIM patients developed transient increases in GV and hyperglycaemia only late in the first week, suggesting that myopathy precedes dysglycaemia.

A novel classification of glucose profile in pregnancy based on continuous glucose monitoring data.

To investigate the glucose profile of women with and without gestational diabetes mellitus (GDM) by simultaneously analyzing several factors of continuous glucose monitoring (CGM) data. CGM was conducted for 2 weeks in the second trimester of pregnant women whose random blood glucose level was ≥100 mg/dl. A 75-g oral glucose tolerance test was performed around day 7, and the index of hyperglycemia, relative hypoglycemia, and indices of glucose variability were extracted from CGM data. Unsupervised hierarchical clustering was performed to categorize glucose profiles of the participants. CGM data were obtained from 29 women. Glucose profiles were categorized into three clusters: low glucose levels with less glucose variability group (L group, n = 7); moderate glucose levels with moderate-to-high glucose variability group (M group, n = 18); and high glucose levels with high glucose variability group (H group, n = 4). The waveforms of the glucose profiles were very different among the three groups. Women with GDM tended to be more frequent in the H group than in the M and L groups (75.0%, 16.7%, and 14.3%, respectively; p = 0.053). Maternal age was significantly higher and the proportion of multiparous women was significantly larger in the H group compared to L group (p = 0.002 and 0.015, respectively). A comprehensive analysis of CGM data could help us extract a subgroup of women with characteristics of GDM.

Characteristics of Continuous Glucose Monitoring Metrics in Persons with Type 1 and Type 2 Diabetes Treated with Multiple Daily Insulin Injections

Although guidelines advocate similar CGM targets for insulin-treated persons with type 1 and type 2 diabetes, it is unclear how these persons differ with respect to hypoglycaemia, glucose variability and other CGM metrics in clinical practice. Methods; We used data from two multicenter randomized controlled trials (GOLD and MDI-Liraglutide) where 161 persons with type 1 diabetes and 124 persons with type 2 diabetes treated with multiple daily injections were included and monitored with masked CGM. Persons from both cohorts had similar mean glucose levels, 10.9 mmol/l (196 mg/dL) in persons with type 1 diabetes and 10.8 mmol/l (194 mg/dL) in persons with type 2 diabetes. Time in hypoglycemia (<3.9 mmol/l (70 mg/dL) was 5.1% and 1.0 % for persons with type 1 and type 2 diabetes, respectively (p<0.001). Corresponding estimates for the standard deviations of mean glucose levels were 4.4 mmol/l (79 mg/dL) vs 3.0 (54 mg/dL) (p<0.001), for CV 41% vs 28% (p<0.001) and for time in range 38.2% vs 45.3%, respectively (p=0.004). Mean C-peptide levels were 0.05 nmol/l and 0.67 nmol/l (p<0.001) for persons with type 1 and type 2 diabetes, respectively. Persons with type 1 diabetes compared to persons with type 2 diabetes treated with multiple daily injections spend considerably more time in hypoglycemia, have higher glucose variability, and less "Time in range". This needs to be taken into account in daily clinical care and in recommended targets for CGM metrics.

Daytime Glycemic Variability and Frailty in Older Patients with Diabetes: a Pilot Study Using Continuous Glucose Monitoring.

We investigated the relationship between glucose variability and frailty. Forty-eight type 2 diabetic patients aged ≥ 65 years were enrolled. The FRAIL scale was used for frailty assessment, and participants were classified into ‘healthy & pre-frail’ (n = 24) and ‘frail’ (n = 24) groups. A continuous glucose monitoring (CGM) system was used for a mean of 6.9 days and standardized CGM metrics were analyzed: mean glucose, glucose management indicator (GMI), coefficient of variation, and time in range, time above range (TAR), and time below range. The demographics did not differ between groups. However, among the CGM metrics, mean glucose, GMI, and TAR in the postprandial periods were higher in the frail group (all P < 0.05). After multivariate adjustments, the post-lunch TAR (OR = 1.12, P = 0.019) affected the prevalence of frailty. Higher glucose variability with marked daytime postprandial hyperglycemia is significantly associated with frailty in older patients with diabetes.

Relationship Between Type 2 Diabetes and White Matter Hyperintensity: A Systematic Review.

White matter (WM) disease is recognized as an important cause of cognitive decline and dementia. White matter lesions (WMLs) appear as white matter hyperintensities (WMH) on T2-weighted magnetic resonance imaging (MRI) scans of the brain. Previous studies have shown that type 2 diabetes (T2DM) is associated with WMH. In this review, we reviewed the literature on the relationship between T2DM and WMH in PubMed and Cochrane over the past five years and explored the possible links among the presence of T2DM, the course or complications of diabetes, and WMH. We found that: (1) Both from a macro- and micro-scopic point of view, most studies support the relationship of a larger WMH and a decrease in the integrity of WMH in T2DM; (2) From the relationship between brain structural changes and cognition in T2DM, the poor performance in memory, attention, and executive function tests associated with abnormal brain structure is consistent; (3) Diabetic microangiopathy or peripheral neuropathy may be associated with WMH, suggesting that the brain may be a target organ for T2DM microangiopathy; (4) Laboratory markers such as insulin resistance and fasting insulin levels were significantly associated with WMH. High HbA1c and high glucose variability were associated with WMH but not glycemic control.

Randomized Study Comparing Vildagliptin vs Glibenclamide on Glucose Variability and Endothelial Function in Patients with Type 2 Diabetes Mellitus and Hypertension.

BackgroundGlucose variability (GV) is considered an important factor for cardiovascular disease (CVD) in patients with type 2 diabetes mellitus (T2DM). High GV causes endothelial dysfunction and increased oxidative stress. Dipeptidyl peptidase-4 (DPP-4) inhibitors may improve endothelial function and decrease GV. The aim of this study was to investigate the effects of vildagliptin, a DPP-4 inhibitor, compared with glibenclamide in GV and endothelial function in patients with T2DM and arterial hypertension.MethodsThis is a prospective, randomized, open and drug-controlled study. Fifty patients older than 35 years with T2DM and hypertension without CVD were randomized to receive vildagliptin (n=25) or glibenclamide (n=25), both in added-on metformin. Laboratory tests and analysis of endothelial function were performed before and 12 weeks after treatment. Endothelial function, defined by reactive hyperemia index (RHI), was analyzed by peripheral artery tonometry (endo-PAT2000). GV was evaluated by capillary glucose with intermittent monitoring device, six measurements per day, for three days, before and after treatment. The median of standard deviation (SD) of mean blood glucose (MBG) was used to evaluate GV.ResultsGV decreased in the vildagliptin group (35.2 to 30.7, P=0.037) but did not change with glibenclamide (37.6 to 37.5, P=0.765). Glycated hemoglobin was similar in both groups. MBG decreased only in glibenclamide group, without difference with vildagliptin group (P=0.374). There were no changes in the RHI in both groups and there was no correlation between GV and RHI (P=0.658).ConclusionVildagliptin reduces GV; however, the action on endothelial function was not demonstrated. In addition, there was no correlation between GV and endothelial function.

Effects of Cardiovascular Risk Factor Variability on Health Outcomes.

Innumerable studies have suggested “the lower, the better” for cardiovascular risk factors, such as body weight, lipid profile, blood pressure, and blood glucose, in terms of health outcomes. However, excessively low levels of these parameters cause health problems, as seen in cachexia, hypoglycemia, and hypotension. Body weight fluctuation is related to mortality, diabetes, obesity, cardiovascular disease, and cancer, although contradictory findings have been reported. High lipid variability is associated with increased mortality and elevated risks of cardiovascular disease, diabetes, end-stage renal disease, and dementia. High blood pressure variability is associated with increased mortality, myocardial infarction, hospitalization, and dementia, which may be caused by hypotension. Furthermore, high glucose variability, which can be measured by continuous glucose monitoring systems or self-monitoring of blood glucose levels, is associated with increased mortality, microvascular and macrovascular complications of diabetes, and hypoglycemic events, leading to hospitalization. Variability in metabolic parameters could be affected by medications, such as statins, antihypertensives, and hypoglycemic agents, and changes in lifestyle patterns. However, other mechanisms modify the relationships between biological variability and various health outcomes. In this study, we review recent evidence regarding the role of variability in metabolic parameters and discuss the clinical implications of these findings.

Sexual dysfunctions in young women with type 1 diabetes and high glucose variability: findings from the METRO study.

Sexual dysfunctions in young women with type 1 diabetes and high glucose variability: findings from the METRO study.

MON-LB111 Evaluation of Mixed Meal Test on the Diagnosis of Hyperinsulinemic Hypoglycemia After Bariatric Surgery

Background and aims: The physiopathology of hyperinsulinemic hypoglycemia (HH) after gastric bypass (GB) is not well understood, although it is a common adverse event after this procedure. The fast absorption of glucose after a meal, the high glucose variability, the increase in glucagon peptide 1 secretion or the hyperplasia of beta cell have been postulated as possible hypothesis. Mixed Meal Tolerance test (MMT) is used in clinical practice during HH investigation, but there is no consensus for HH diagnosis after bariatric surgery. In this scenario, we evaluated the MMT for the diagnosis of HH after GB. Material and Methods: This is an observational cross sectional descriptive study of adult (> 18 years) patients submitted to a MMT after GB from July 2016 to October 2019. 51 patients were divided in two groups: Group 1, with a history of predominantly neuroglycopenic symptoms (n = 24) and Group 2 (control) without symptoms of postprandial hypoglycemia (n= 27). The patients had no diagnosis of diabetes and weren’t using any hypoglycemic drugs. All subjects performed the MMT composed by a typical Brazilian breakfast with the following composition: 494 Kcal with 63.4% carb, 27.5% fat and 9.1% protein, in the morning after 8h fasting and blood samples (glucose, insulin, C peptide) were collected before the meal and every 30 minutes for 5 h after it. A positive test was considered if patient presents Whipple’s Triad: HH (plasma glucose was ≤ 55mg/dL with insulinemia ≥ 3 µU/mL, C peptide ≥ 0.6 ng/mL) and hypoglycemic symptoms. Statistical analysis were done using SPSS 13.0 version. Results:​ From 51 patients, 46 were female, mean age was 46.8 ± 9.2 years. 15 of the 24 patients with predominantly neuroglycopenic symptoms (Group 1) developed laboratory HH, but only 9 (37.5%) presented the Whipple’s Triad. Only one subject of the control group presented HH. All patients with neuroglycopenic symptoms during the test presented HH. From those with HH, 43% presented hypoglycemia at 90’, 50% at 120’ and 6.2% at 150’ during MMT. There were no difference between the two groups when compared the amount of weight loss neither the period of follow up after GB. Conclusion: Since all patients with neuroglycopenic symptoms during the test presented HH it might be a useful tool to exclude HH in patients with hypoglycemic symptoms after GB. This study suggests that the BMT doesn’t need to be 5h, since all of hypoglycemic episodes occur until 150’.

Effects of glucose variability on hematopoietic stem/progenitor cells in patients with type 1 diabetes.

Diabetes reduces the levels of hematopoietic stem/progenitor cells (HSPCs), which can contribute to organ and tissue homeostasis. Among patients with diabetes, lower HSPC levels predict the development or worsening of micro- and macro-angiopathy. High glucose variability is also associated with diabetic complications and we have previously shown that acute hypoglycaemia can stimulate stem/progenitor cells. Thus, we evaluated the relationship between glucose variability or time in hypoglycaemia and HSPCs in patients with type 1 diabetes (T1D). Patients with T1D were compared to healthy subjects. HSPCs (CD34+, CD133+, CD34+CD133+, CD34 + CD45dim) were quantified by flow cytometry. Using flash glucose monitoring system for 90days, we calculated several measures of glucose variability and time in hypoglycaemia. Forty-four patients with T1D and 44 healthy subjects were enrolled. Compared to healthy controls, T1D patients had significantly lower levels of HSPCs and duration of diabetes was inversely correlated with HSPC levels. Significant direct correlations were found between HSPC levels and the coefficient of variation of glucose levels or time in hypoglycaemia, which were stronger in patients with short-term than in those with long-standing diabetes. This study confirms the pauperization of HSPCs in T1D patients and demonstrates a potential HSPC-stimulatory effect of hypoglycaemia, which mitigates with long-lasting diabetes. These data are consistent with a model whereby disease chronicity progressively blunts the release of HSPCs in response to adrenergic triggers, like hypoglycaemic events.

Association of Glucose Variability and ICU Delirium of Patients after Liver Transplantation

To study the association of glucose variability and ICU delirium of patients after liver transplantation. This was a retrospective, single-center cohort study. Patients who admitted to ICU after liver transplantation during Aug. 2016 to Dec. 2018 were enrolled. They were divided into two groups accoding to whether they had delirium in ICU. Multivariate logistic regression analysis model was used to analyze the relationship between glucose variability and ICU delirium, and Cochran-Armitage trend test was used to analyze the linear relationship between blood glucose variability levels and the incidence of delirium. A total of 242 patients were enrolled, among them, 36 patients had delirium. The occurrence rate of delirium was 14.9% (36/242). Results indicated that glucose variability was an independently risk factor of ICU delirium for liver transplant patients ( P=0.045), and delirium was more common in patients with higher glucose variability (fourth quartile vs. first quartile, odds ratio =5.283, 95% confidence interval: 1.092～25.550, P=0.038). Results of Cochran-Armitage trend test indicated that there was a linear relationship between blood glucose variability level and ICU delirium rate, with the increase of glucose variability level, the risk of ICU delirium was increased too ( P<0.001). Glucose variability was an independently risk factor of ICU delirium in liver transplantation patients.

Clinically Accurate Prediction of Glucose Levels in Patients with Type 1 Diabetes.

Background and Aims: Accurate prediction of glucose levels in patients with type 1 diabetes mellitus (T1DM) is critical both for their glycemic control and for the development of closed-loop systems. Methods: In this study, we utilized real-life, retrospective, continuous glucose monitoring data from 141 T1DM patients (9,083 connection days, 1,592,506 glucose measurements) and in silico data generated by the UVA/Padova T1DM simulator to evaluate different computational methods for glucose prediction. We evaluated the performance of the models using both measures of numerical accuracy, measured by the root mean square error, and clinical accuracy, measured by the percentage of time in each of the Clarke error grid (CEG) zones, and compared the predictions done by autoregressive (AR) models, tree-based methods, artificial neural networks, and a novel model that we devised and optimized for this task. Results: Our novel model, constructed on real-life data, achieved clinical accuracy of 99.3% and 95.8% in predicting the glucose level 30 and 60 min ahead, respectively, and reduced the percentage of glucose predictions in zones C-E of the CEG by 60.6% and 38.4% in these prediction horizons, compared with a standard AR model. The model was superior to all other models across all age groups and achieved higher clinical accuracy in subgroups of patients with high glucose variability and greater time spent in hypoglycemia. Compared with real-life data, when evaluated on in silico data, the model had a higher clinical and numerical accuracy. Conclusions: A model that optimizes for CEG zones may significantly improve clinical accuracy and clinical outcomes of treatment decisions in T1DM patients. Results obtained from simulated data may overestimate the performance of models on real-life data.

Abstract P349: Association of Lower Fasting Glucose and Visit-to-visit Glucose Variability With Cognitive Performance: The Multi-ethnic Study of Atherosclerosis

Background: Diabetes is a well-known risk factor for dementia. Despite emerging evidence that higher glucose variability is associated with cognitive decline and hypoglycemia is associated with increased risk for dementia, few studies have investigated the relationship of lower fasting glucose and glucose variability with cognitive performance in the general population. Hypothesis: Diabetic and lower levels of fasting glucose and higher visit-to-visit glucose variability over 10 years are associated with worse cognitive performance. Methods: Participants in the Multi-Ethnic Study of Atherosclerosis (N = 4,591; mean age 69.7 ± 9.4 years) completed a cognitive assessment at Exam 5 including the Cognitive Abilities Screening Instrument (CASI), Digit Symbol Coding (DSC), and Digit Span (DS, Forward and Backward combined) tests measuring global cognitive performance, executive function/processing speed, and working memory, respectively. We defined fasting glucose categories as low (&lt;80 mg/dL), normal (80-99 mg/dL), impaired (100-125 mg/dL), and diabetic (≥126 mg/dL). Participants with diabetes were included in the diabetic category. We examined the relationship of Exam 1 and Exam 5 fasting glucose categories and visit-to-visit glucose variability (coefficient of variation across Exams 1-5) to scores on the CASI (0-100), DSC (0-133), and DS (0-28). We report regression coefficients ( β [95% confidence limits]) from regression models adjusted for age, sex, race/ethnicity, education, income, cardiovascular risk factors, and APOE genotype. Results: Relative to normal glucose, participants with diabetic fasting glucose performed significantly worse on the CASI (Exam 1 β = -0.75 [-1.36, -0.15]; Exam 5 β = -0.30 [-0.83, 0.23]), DSC (Exam 1 β = -2.97 [-4.20, -1.74]; Exam 5 β = -1.26 [-2.34, -0.18]), and DS (Exam 1 β = -0.39 [-0.72, -0.07]; Exam 5 β = -0.29 [-0.58, -0.003]). In contrast, participants with low Exam 1 fasting glucose performed significantly better on the DSC (Exam 1 β = 1.55 [0.45, 2.65]) and similarly on the CASI and DS compared to those with normal fasting glucose. Adjusting for glucose lowering medication attenuated associations with the DSC and DS but not the CASI. Accounting for heterogeneity in the low glucose category by hypoglycemia (&lt;70 mg/dL) did not significantly alter results. Higher visit-to-visit glucose variability from Exam 1 to Exam 5 was associated with worse performance on the CASI ( β = -0.36 [-0.60, -0.12]) and DSC ( β = -1.14 [-1.63, -0.65]). Associations were consistent across race and sex. Conclusions: Results support the hypothesis that hyperglycemia and higher glucose variability are associated with worse cognitive performance. Despite previous suggestion of a link between hypoglycemia and incident dementia, lower antecedent fasting glucose may be associated with better executive function/processing speed in this population-based sample.

Long-term effects of continuous subcutaneous insulin infusion in adults with type 1 diabetes mellitus patients: Results of a public healthcare system

AimTo evaluate the long-term clinical effect of continuous subcutaneous insulin infusion (CSII) in adult type 1 diabetes mellitus (T1DM) patients in a regional public healthcare system real-world scenario. MethodsAll adult T1DM patients on CSII for ≥10 years subjected to follow-up in the regional Castilla-La Mancha Public Health Service were included. The primary efficacy outcome was the variation in HbA1c during follow-up. Direct patient data were compiled through the web-based Spanish national registry on CSII therapy. ResultsA total of 69 T1DM adult patients were treated with insulin pumps for ≥10 years in our region. The mean age was 45.0±10.5 years, with a T1DM duration of 13.9±8.5 years. The mean duration of CSII therapy was 11.4±2.1 years. The main indications for treatment were high glucose variability (39%), problematic hypoglycemia (26%), and HbA1c >53mmol/mol (7%) on multiple daily injections (20%). Sensor-augmented pump therapy was used by 31% of the patients. Glycosylated hemoglobin did not change during follow-up (58±11mmol/mol vs. 58±11mmol/mol; 7.5±1.0 vs. 7.5±1.0; p=0.66). However, the percentage of patients with at least one episode of severe hypoglycemia during the last year and unnoticed hypoglycemia decreased from 36% to 7% (p=0.006) and from 38% to 32% (p<0.001), respectively. The proportion of subjects with ≥1 episode of diabetic ketoacidosis in the last year decreased from 30% to 6% (p=0.045). ConclusionsThe reduction of severe hypoglycemia without deterioration of glycemic control can be sustained over long-term CSII therapy.

Rapid-Acting Insulin Analogues Versus Regular Human Insulin: A Meta-Analysis of Effects on Glycemic Control in Patients with Diabetes

IntroductionThe aim of this meta-analysis was to investigate the impact of rapid-acting insulin analogues (RAIAs) and regular human insulin (RHI) on glycemic control, including long- and short-term glycemic variability as measured by glycated haemoglobin (HbA1c) and pre- and postprandial glucose (PPG).MethodsPubMed was searched for studies published between 1999 and 29 June 2016. Randomised controlled trials of patients with diabetes that assessed the effects of RAIAs or RHI on glycemic control, focusing on preprandial glucose, PPG and HbA1c, were included. Only studies that reported both means and standard deviations for those outcomes were analysed; from these data, weighted mean differences and 95% confidence intervals were generated to yield overall point estimates. The primary outcomes of the meta-analysis were the mean differences between RAIAs and RHI at the end of the study in PPG, preprandial glucose, and HbA1c.ResultsTwenty-seven studies (n = 7452) were included. The difference in PPG between RAIA- and RHI-treated patients was significant—in favour of RAIAs—in patients with type 1 diabetes (T1D) [− 22.2 mg/dL; 95% confidence interval (CI) − 27.4, − 17.0 mg/dL; P < 0.0001] but not in those with type 2 diabetes (T2D). For preprandial glucose, there was a non-significant trend favouring RHIs in T1D; no data were available for patients with T2D. In patients with T1D, the between-group difference in end-of-treatment (EOT) HbA1c favoured RAIAs (− 0.13%; 95% CI − 0.18, − 0.08%; P < 0.0001), but was not significant in patients with T2D. The main study limitations were the small number and heterogeneity of the included studies.ConclusionsThese results demonstrate that RAIAs are more effective at reducing PPG and improving HbA1c than RHIs in T1D. More data are required to assess the effect of these agents on glucose control in T2D.Plain Language SummaryIn patients with diabetes, the risk of complications is increased by poor control of blood glucose levels and high blood glucose variability. Complications may include cardiovascular disease, eye problems and amputation. Control and variability of blood glucose levels can be evaluated using a range of measures, including (i) glycated haemoglobin (HbA1c) level at the end of the treatment period; (ii) change in HbA1c level during the treatment period; (iii) fasting plasma glucose level; (iv) postprandial glucose (PPG) level; (v) change in blood glucose level after a meal. PPG levels following a meal are an important measure of overall metabolic control in diabetes, and reduction of glycemic variability (GV) can be achieved via reductions in PPG. Both rapid-acting insulin analogues (RAIAs; aspart, glulisine and lispro) and regular human insulin (RHI) are widely used in the management of diabetes. Using data from 27 randomised controlled trials involving more than 7000 patients, we investigated the impact of RAIAs and RHI on measures of glycemic control and variability in patients with type 1 diabetes (T1D) or type 2 diabetes (T2D). Our results show that, in patients with T1D, RAIAs are more effective than RHI at reducing PPG excursions and HbA1c. This indicates that glycemic control is better with RAIAs than with RHI. More data are required to assess the effects of RAIAs and RHI on glycemic control and variability in patients with T2D.Electronic Supplementary MaterialThe online version of this article (10.1007/s13300-019-00732-w) contains supplementary material, which is available to authorized users.

High Glucose Variability Increases 30-Day Readmission Rates in Patients with Type 2 Diabetes Hospitalized in Department of Surgery

Glucose variability is common among hospitalized patients with type 2 diabetes mellitus (DM). I investigated to assess the variability of glucose in patients with type 2 DM accounts for in-hospital readmission rates in department of Surgery. I retrospectively analyzed 206 patients with type 2 DM, who was admitted to our hospital for surgical interventions and re-admitted within 30 days after discharge. I also enrolled 610 age, sex and diabetic duration matched patients with type 2 DM, as control. Outcomes measure included average and standard deviation (SD) of blood glucose during admission, glycated hemoglobin (HbA1c), lipid profile, renal function, length of stay (LOS). Patients who had re-admission within 30 days after discharge had higher SD of blood glucose levels than control (84.7 ± 53.5 mg/dL vs. 46.2 ± 42.8 mg/dL, p < 0.001) but not average of blood glucose levels. Comparing to control group, the study group also had higher HbA1c (8.4 ± 1.3% vs. 7.7 ± 1.1%, p = 0.015) and LOS (8.5 ± 2.5 days vs 7.0 ± 1.5 days, p = 0.020). The independent predictors of 30-day readmission rates were SD of blood glucose during admission and HbA1c (hazard ratio: 1.680, 1.493; p value < 0.001, 0.008, respectively). Decreasing glucose variability during admission for surgery is important for patients with type 2 DM to decreasing re-admission rates and LOS. HBA1c may also identify patients at higher risk of postoperative complications and possibility of re-admission.

Effect of Liraglutide on Times in Glycaemic Ranges as Assessed by CGM for Type 2 Diabetes Patients Treated With Multiple Daily Insulin Injections

IntroductionThe effects of the GLP-1 analogue liraglutide on time in hypoglycaemia, time in hyperglycaemia, and time in range for type 2 diabetes patients initially treated with multiple daily insulin injections (MDI) were investigated. Variables associated with hypoglycaemia in the current population were also identified.MethodsAnalyses were based on data from a previously performed double-blind, placebo-controlled trial in which 124 MDI-treated patients with type 2 diabetes were randomized to liraglutide or placebo. Masked continuous glucose monitoring (CGM) was performed at baseline and week 24 in 99 participants.ResultsThe mean time in hypoglycaemia was similar for participants receiving liraglutide and those receiving placebo after 24 weeks of treatment. Mean time in target was greater in the liraglutide group than in the placebo group: 430 versus 244 min/24 h (p < 0.001) and 960 versus 695 min/24 h (p < 0.001) for the two glycaemic ranges considered, 4–7 mmol/l and 4–10 mmol/l, respectively. Mean time in hyperglycaemia was lower in the liraglutide group: 457 versus 723 min/24 h (p = 0.001) and 134 versus 264 min/24 h (p = 0.023) for the two cutoffs considered, > 10 mmol/l and > 14 mmol/l, respectively. Lower mean glucose level, lower C-peptide, and higher glucose variability were associated with an increased risk of hypoglycaemia in both treatment groups. Higher proinsulin level was associated with a lower risk of hypoglycaemia in the liraglutide group.ConclusionFor type 2 diabetes patients initially treated with MDI, introducing liraglutide had a beneficial effect on glucose profiles estimated by masked CGM. Mean glucose level, glycaemic variability, C-peptide, and proinsulin level influenced the risk of hypoglycaemia in this population.Trial RegistrationClinicalTrials.gov, number (EudraCT nr: 2012-001941-42).FundingNovo Nordisk funded this study. The Diabetes Research Unit, NU-Hospital Group funded the journal’s Rapid Service Fee.Electronic Supplementary MaterialThe online version of this article (10.1007/s13300-019-00692-1) contains supplementary material, which is available to authorized users.

Increased Glucose Variability Is Associated With Major Adverse Events After Coronary Artery Bypass

Elevated preoperative hemoglobin A1c (HbA1c) is a predictor of poor outcomes after coronary artery bypass grafting (CABG), but the role of postoperative glucose variability (GV) is unknown. We hypothesized that short-term postoperative GV is associated with major adverse events (MAEs) after isolated CABG. This retrospective study evaluated 2215 patients who underwent isolated CABG from January 2012 to March 2018 at 2 medical centers. Postoperative GV in the first 12 hours and 24 hours was measured by the SD, coefficient of variation, and mean amplitude of glycemic excursions. The primary outcome (MAEs) was the composite of postoperative cardiac arrest, pneumonia, renal failure, stroke, sepsis, reoperation, and 30-day mortality. Multivariate logistic regression assessed the independent association of GV with MAE. A total of 2215 patients met the study criteria, and an MAE developed in 260 patients (11.7%). High 12-hour and 24-hour postoperative GV were associated with elevated HbA1c, insulin-dependent diabetes, renal failure, and nonelective operation. Multivariate logistic regression analysis showed MAEs were associated with increased mean postoperative glucose in the first 12 hours (odds ratio [OR], 1.013; 95% confidence interval [CI], 1.008-1.018; P < .001), the first 24 hours (OR, 1.017; 95% CI, 1.010-1.024; P < .001), and 24-hour postoperative GV (OR, 1.22; 95% CI, 1.09-1.37; P < .001). MAEs were not associated with preoperative HbA1c or 12-hour postoperative GV. Increased 24-hour but not 12-hour postoperative GV after CABG is a predictor of poor outcomes. Preoperative HbA1c is not associated with MAEs after adjusting for postoperative mean glucose and GV.