Impact of visit-to-visit glycemic variability on the risks of macrovascular and microvascular events and all-cause mortality in type 2 diabetes: the ADVANCE trial

Clinical implications and pharmacological considerations of glycemic variability in patients with type 2 diabetes mellitus

Glycemic variability (GV), independently of glycemic control, has emerged as a prognostic marker in patients with type 2 diabetes mellitus (DM). In this study, we assessed the prognostic value of long-term GV for predicting major adverse cardiovascular events (MACE) in our local population. We also assessed its prognostic value for diabetic microvascular complications (DMC) and its relationships with antidiabetic medications. This was a retrospective cohort study that recruited 680 patients with type 2 DM across 2015-2017. MACE were defined as: the composite of; total death, myocardial infarction (MI), stroke, hospitalization due to heart failure, and revascularization. GV was calculated for two glycemic control markers: glycated hemoglobin (G-Hb) and fasting blood sugar (FBS); via three metrics- standard deviation (SD), coefficient of variation (CV), and variability independent from the mean (VIM). Cox proportional hazard models and Kruskal-Wallis tests were used in the statistical analysis. 105 events classified as MACE were identified in 86 patients and 104 DMC in 98 patients in an average follow-up period of 78.43 months. Long-term GV was found to be an independent predictor of MACE, particularly for FBS-CV but not a predictor of DMC. FBS-CV ≥ 17.51% as compared with < 17.51% was a significant and independent predictor of MACE, with HR 1.589 (95% CI; 1.022, 2.472) (P = 0.040). DMC were predicted mainly by the duration of type 2 DM, and by the glycemic control; similarly represented by G-Hb and FBS. Patients on metformin, and dipeptidyl peptidase (DPP) 4 inhibitors, had the lowest GV, as compared with patients whose treatments included insulin/sulphonylureas (P < 0.001). In our population, long-term GV predicted MACE: with FBS-CV superior to the "gold standard" glycemic control marker G-Hb. Further, GV may be explained, partially at least, by the choice of antidiabetic medications: this finding might contribute to the cardiovascular protection attributed to one class rather than another.

A comparative study of the relationship between time in range assessed by self-monitoring of blood glucose and continuous glucose monitoring with microalbuminuria outcome, HOMA-IR and HOMA-β test

AIMS

To compare the time in range (TIR) obtained from self-monitoring of blood glucose (SMBG) with that obtained from continuous glucose monitoring (CGM), and explore the relationship of TIR with microalbuminuria outcome, HOMA-IR and HOMA-β test.

METHODS

We recruited 400 patients with type 2 diabetes to carry out blood glucose monitoring by both SMBG and CGM for 3 consecutive days. TIR, TAR, TBR and other blood glucose variation indices were calculated respectively through the glucose data achieved from SMBG and CGM. The HOMA-IR and HOMA-β test was evaluated by an oral glucose tolerance test. Urinary microalbumin-to-creatinine ratio completed in the laboratory.

RESULTS

The median (25 %, 75 % quartile) of TIRCGM and TIRSMBG were 74.94(44.90, 88.04) and 70.83(46.88, 87.50) respectively, and there was no significant difference, p = 0.489; For every 1 % increase in TIRCGM, the risk of microalbuminuria decreased by 1.6 % (95%CI:0.973, 0.995, p = 0.006) and for every 1 % increase in TIRSMBG, the risk of microalbuminuria decreased by 1.3 % (95%CI:0.975, 0.999, p = 0.033). Stepwise multiple linear regression analysis showed an independent positive correlation between TIR (including TIRCGM and TIRSBMG) and LnDI30 and LnDI120 levels (p = 0.000).

CONCLUSIONS

The TIR calculated by SMBG was highly consistent with that reported by CGM and was significantly associated with the risk of microalbuminuria and the HOMA-β. Higher TIR quartiles were associated with lower incidence of microalbuminuria as well as higher lever of HOMA-β. For patients with limited CGM application, SMBG-derived TIR may be an alternative to CGM-derived TIR, to assess blood glucose control.

Risk prediction of diabetic retinopathy based on visit-to-visit fasting blood glucose indices

Objective

The long-term glucose monitoring is essential to the risk assessment of diabetic retinopathy (DR), the aim of this study was to investigate the predictive ability of visit-to-visit fasting blood glucose (FBG) indices on the risk of DR.

Methods

This was a community-based, cohort study conducted from 2013 to 2021. DR was diagnosed by digital fundus photography. The FPG indices included FBG, var. Associations of each FBG indices and DR were estimated using multinomial logistic regression models adjusting for confounders, and discrimination was determined by area under the curve (AUC). Predictive utility of different models was compared by changes in AUC, integrated discrimination improvement (IDI), and net reclassification index (NRI).

Results

This study analyzed 5054 participants, the mean age was 46.26 ± 11.44 years, and 2620 (51.84%) were women. After adjustment for confounders, the adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for FBG, SD, CV, VIM, ARV, M-FBG, and cumulative FBG load were 1.62 (1.52-1.73), 2.74 (2.38-3.16), 1.78 (1.62-1.95), 1.11 (0.95-1.29), 1.72 (1.56-1.91), 2.15 (1.96-2.36), and 2.57 (2.31-2.85), respectively. The AUC of the model with separate cumulative FBG load and classical risk factors was 0.9135 (95%CI 0.8890-0.9380), and no substantive improvement in discrimination was achieved with the addition of other FBG indices once cumulative FBG load was in the model.

Conclusions

Cumulative FBG load is adequate for capturing the glucose-related DR risk, and the predictive utility of cumulative FBG load is not significantly improved by adding or replacing other FBG indices in the assessment of DR risk.

Potential Benefits of Continuous Glucose Monitoring for Predicting Vascular Outcomes in Type 2 Diabetes: A Rapid Review of Primary Research

(1) Background: Chronic hyperglycaemia is a cause of vascular damage and other adverse clinical outcomes in type 2 diabetes mellitus (T2DM). Emerging evidence suggests a significant and independent role for glycaemic variability (GV) in contributing to those outcomes. Continuous glucose monitoring (CGM) provides valuable insights into GV. Unlike in type 1 diabetes mellitus, the use of CGM-derived GV indices has not been widely adopted in the management of T2DM due to the limited evidence of their effectiveness in predicting clinical outcomes. This study aimed to explore the associations between GV metrics and short- or long-term vascular and clinical complications in T2DM. (2) Methods: A rapid literature review was conducted using the Cochrane Library, MEDLINE, and Scopus databases to seek high-level evidence. Lower-quality studies such as cross-sectional studies were excluded, but their content was reviewed. (3) Results: Six studies (five prospective cohort studies and one clinical trial) reported associations between GV indices (coefficient of variation (CV), standard deviation (SD), Mean Amplitude of Glycaemic Excursions (MAGE), Time in Range (TIR), Time Above Range (TAR), and Time Below Range (TBR)), and clinical complications. However, since most evidence came from moderate to low-quality studies, the results should be interpreted with caution. (4) Conclusions: Limited but significant evidence suggests that GV indices may predict clinical compilations in T2DM both in the short term and long term. There is a need for longitudinal studies in larger and more diverse populations, longer follow-ups, and the use of numerous CGM-derived GV indices while collecting information about all microvascular and macrovascular complications.

Glycemic Variability as a Predictor of Graft Failure Following Infrainguinal Bypass for Peripheral Arterial Disease: A Retrospective Cohort Study

BACKGROUND

Glycemic variability (GV), measured as the change in visit-to-visit glycated hemoglobin (HbA1c), increases the risk of multiple adverse outcomes. However, the impact of GV on graft patency following infrainguinal bypass (IIB) is unknown. A retrospective cohort study was undertaken to assess the impact of GV on graft patency.

METHODS

A 3-year single-center retrospective case notes analysis of all people undergoing IIB between 2017 and 2019. Rutherford stage, graft conduit, level of bypass, procedure details, baseline demographics, comorbidities, and GV were assessed. Time to reintervention, ipsilateral amputation, or death was recorded to determine primary patency (PP).

RESULTS

One hundred six IIB outcomes were analyzed: mean (± standard deviation) age 68.0 (9.2) years; 69 (65.1%) male, 37 (33.9%), 75 (70.8%) had diabetes mellitus; and 46 (43.4%) underwent elective procedures. GV > 9.1% was associated with significantly lower median PP than GV < 9.1%, 198 (97-753.5) vs. 713 (166.5-1,044.5) days (P = 0.045). On univariate analysis, GV > 9.1% vs. < 9.1% was significantly associated with PP (hazard ratio [HR] 1.85 [confidence interval {CI} 1.091-3.136], P = 0.022). Bypass level was also a univariate predictor, with below knee bypasses (HR 2.31 [CI 1.164-4.564], P = 0.017), and tibial (HR 2.00 [CI 1.022-3.090], P < 0.043) having lower PP than above knee bypasses. On multivariate adjustment, GV > 9.1% and level of bypass remained independent predictors of PP, HR 1.96 (95% CI: 1.12-3.42, P = 0.018) and HR 2.54 (95% CI: 1.24-5.22, P = 0.011), respectively.

CONCLUSIONS

GV is an independent predictor of PP following infrainguinal bypass, thus optimizing GV should be a therapeutic target.

Relationship Between Glycosylated Hemoglobin Variability and the Severity of Coronary Artery Disease in Patients With Type 2 Diabetes Mellitus

Background: Glycosylated hemoglobin (HbA1c) variability is a risk factor for cardiovascular complications in patients with Type 2 diabetes mellitus (T2DM), but its relationship with the severity of coronary artery disease (CAD) is unclear. Methods: Patients with T2DM who underwent coronary angiography due to angina were enrolled. HbA1c variability was expressed as coefficient of variation (CV), standard deviation (SD), variability independent of mean (VIM), and time in range (TIR). The severity of CAD was expressed by the number of involved vessels and Gensini score. Multivariate regression models were constructed to test the relationship between HbA1c variability, number of involved vessels, and the Gensini score, followed by linear regression analysis. Results: A total of 147 patients were included. In multivariate analysis, VIM-HbA1c (OR = 2.604; IQR: 1.15, 5.90; r = 0.026) and HbA1cTIR (OR = 0.13; IQR: 0.04, 0.41; r < 0.001) were independent risk factors for the number of involved vessels. After adjustment, HbA1cTIR (OR = 0.01; IQR: 0.002, 0.04; r < 0.001), SD-HbA1c (OR = 4.12, IQR: 1.64, 10.35; r = 0.001), CV-HbA1c (OR = 1.41, IQR: 1.04, 1.92; r = 0.007), and VIM-HbA1c (OR = 3.26; IQR: 1.43, 7.47; r = 0.003) were independent risk factors for the Gensini score. In the linear analysis, the Gensini score was negatively correlated with HbA1cTIR (β = -0.629; r < 0.001) and positively correlated with SD-HbA1c (β = 0.271; r = 0.001) and CV-HbA1c (β = 0.176; r = 0.033). After subgroup analysis, HbA1cTIR was a risk factor for the number of involved vessels. The Gensini score was negatively correlated with HbA1cTIR and positively correlated with SD-HbA1c at subgroups of subjects with a mean HbA1c ≤ 7%. Conclusions: Our analysis indicates that HbA1c variability, especially HbA1cTIR, plays a role for the severity of CAD in patients with T2DM. HbA1c variability may provide additional information and require management even at the glycemic target. Translational Aspects: Studies have shown that HbA1c variability is related to cardiovascular complications. Further, we explore the correlation between HbA1c variability and the severity of CAD. HbA1c variability is a risk factor for coronary stenosis in T2DM. It may be a potential indicator reflecting glycemic control for the prevention and treatment of cardiovascular complications.

What is the best predictor of mortality in patients with type 2 diabetes and chronic kidney disease: mean, variability of HbA1c or HbA1c-Hemoglobin ratio?

AIM

Limitations in the measurement of glycated hemoglobin (HbA1c) in patients with type 2 diabetes (T2D) and chronic kidney disease (CKD) result in uncertainty about the best predictor of mortality among these patients. Our study aimed to determine the association between the mean and average real variability (ARV) of HbA1c, as well as HbA1c-hemoglobin (HH) ratio with mortality among patients with T2D and CKD.

MATERIALS AND METHODS

We identified 16,868 T2D patients with stage 3 or above CKD from outpatient visits during 2003-2018. We ascertained all-cause and cardiovascular mortality through linkage to Taiwan's National Death Registry. Mortality rates were estimated using the Poisson distribution, and we conducted Cox proportional hazards regressions to assess relative risks of mortality corresponding to the mean HbA1c, ARV of HbA1c and HH ratio.

RESULTS

Compared to patients with a mean HbA1c of 7.0-7.9%, a mean HbA1c < 7.0% was persistently associated with highest risk of all-cause but not cardiovascular mortality after adjusting for confounders. On the contrary, patients with HbA1c-ARV in the second to fourth quartiles and HH ratios in the higher quartiles showed increased risk of all-cause and cardiovascular mortality compared to those in the first quartiles.

CONCLUSIONS

HbA1c-ARV was more effective than mean HbA1c or HH ratio in predicting mortality in T2D patients with CKD. Apart from optimal glucose control, multidisciplinary care focusing on glycemic variability is essential for reducing mortality in these patients.

Glycemic Risk Index in a Cohort of Patients with Type 1 Diabetes Mellitus Stratified by the Coefficient of Variation: A Real-Life Study

Objective: To analyze the Glycemic Risk Index (GRI) and assess their possible differences according to coefficient of variation (CV) in a cohort of real-life type 1 diabetes mellitus (DM) patient users of intermittently scanned continuous glucose monitoring (isCGM). Patients and Methods: In total, 447 adult users of isCGM with an adherence ≥70% were included in a cross-sectional study. GRI was calculated with its hypoglycemia (CHypo) and hyperglycemia (CHyper) components. Multivariate linear regression analysis was performed to evaluate the factors associated with GRI. Results: Mean age was 44.6 years (standard deviation [SD] 13.7), 57.7% being male; age of DM onset was 24.5 years (SD 14.3) and time of evolution was 20.6 years (SD 12.3). In patients with CV >36% (52.8%) versus CV ≤36% (47.2%), differences were observed in relation to GRI (18.8% [SD 1.9]; P < 0.001), CHypo (2.9% [SD 0.3]; P < 0.001), CHyper (6.3% [SD 1.4]; P < 0.001), and all classical glucometric parameters except time above range level 1. The variables that were independently associated with GRI in patient with CV >36% were time in range (TIR) (β = -1.49; confidence interval [CI:] 95% -1.63 to -1.37; P < 0.001), glucose management indicator (GMI) (β = -7.22; CI: 95% -9.53 to -4.91; P < 0.001), and CV (β = 0.85; CI: 95% 0.69 to 1.02; P < 0.001). However, in patients with CV ≤36%, the variables were age (β = 0.15; CI: 95% 0.03 to 0.28; P = 0.019), age of onset (β = -0.15; CI: 95% -0.28 to -0.02; P = 0.023), TIR (β = -1.35; CI: 95% -1.46 to -1.23; P < 0.001), GMI (β = -6.67; CI: 95% -9.18 to -4.15; P < 0.001), and CV (β = 0.33; CI: 95% 0.11 to 0.56; P = 0.004). Conclusions: In this study, the factors independently associated with metabolic control according to GRI are modified by glycemic variability.

Research progress on the association between glycemic variability index derived from CGM and cardiovascular disease complications

Currently, glycated hemoglobin A1c (HbA1c) has been widely used to assess the glycemic control of patients with diabetes. However, HbA1c has certain limitations in describing both short-term and long-term glycemic control. To more accurately evaluate the glycemic control of diabetes patients, the continuous glucose monitoring (CGM) technology has emerged. CGM technology can provide robust data on short-term glycemic control and introduce new monitoring parameters such as time in range, time above range, and time below range as indicators of glycemic fluctuation. These indicators are used to describe the changes in glycemic control after interventions in clinical research or treatment modifications in diabetes patient care. Recent studies both domestically and internationally have shown that these indicators are not only associated with microvascular complications of diabetes mellitus but also closely related to cardiovascular disease complications and prognosis. Therefore, this article aims to comprehensively review the association between CGM-based glycemic parameters and cardiovascular disease complications by analyzing a large number of domestic and international literature. The purpose is to provide scientific evidence and guidance for the standardized application of these indicators in clinical practice, in order to better evaluate the glycemic control of diabetes patients and prevent the occurrence of cardiovascular disease complications. This research will contribute to improving the quality of life for diabetes patients and provide important references for clinical decision-making.

Glycated Hemoglobin Variability Is Associated With Adverse Outcomes in Patients With Heart Failure Irrespective of Diabetic Status

BACKGROUND

The effect of glycated hemoglobin (HbA1c) variability on adverse outcomes in patients with heart failure (HF) is unclear. We aim to investigate the predictive value of HbA1c variability on the risks of all-cause death and HF rehospitalization in patients with HF irrespective of their diabetic status.

METHODS AND RESULTS

Using a previously validated territory-wide clinical data registry, HbA1c variability was assessed by average successive variability (ASV) or SD of all HbA1c measurements after HF diagnosis. Multivariable Cox proportional hazards models were used to estimate the adjusted hazard ratio (HR) and its corresponding 95% CI. A total of 65 950 patients with HF were included in the study. Over a median follow-up of 6.7 (interquartile range, 4.0-10.6) years, 34 508 patients died and 52 446 required HF rehospitalization. Every unit increment of variability in HbA1c was significantly associated with higher HF rehospitalization (HR ASV, 1.20 [95% CI, 1.18-1.23]) and all-cause death (HR ASV, 1.50 [95% CI, 1.47-1.53]). Diabetes significantly modified the association between HbA1c variability and outcomes (Pinteraction<0.001). HbA1c variability in patients with HF without diabetes conferred a higher risk of rehospitalization (HR ASV, 1.92 [95% CI, 1.70-2.17] versus HR ASV, 1.19 [95% CI, 1.17-1.21]), and all-cause death (HR ASV, 3.90 [95% CI, 3.31-4.61] versus HR ASV, 1.47 [95% CI, 1.43-1.50] compared with patients with diabetes).

CONCLUSIONS

HbA1c variability is significantly associated with greater risk of rehospitalization and all-cause death in patients with HF, irrespective of their diabetic status. These observations were more pronounced in patients with HF without diabetes.

Effects of long-term HbA1c variability on serious infection risks in patients with type 2 diabetes and the influence of age, sex and ethnicity: A cohort study of primary care data

AIMS

Long-term HbA1c (glycated haemoglobin) variability is associated with micro- and macrovascular complications in Type 2 diabetes (T2D). We explored prospective associations between HbA1c variability and serious infections, and how these vary by HbA1c level, age, sex and ethnicity.

METHODS

411,963 T2D patients in England, aged 18-90, alive on 01/01/2015 in the Clinical Practice Research Datalink with ≥ 4 HbA1c measurements during 2011-14. Poisson regression estimated incidence rate ratios (IRRs) for infections requiring hospitalisation during 2015-19 by HbA1c variability score (HVS) and average level, adjusting for confounders, and stratified by age, sex, ethnicity and average level. Attributable risk fractions (AF) were calculated using reference categories for variability (HVS < 20) and average level (42-48 mmol/mol).

RESULTS

An increased infection risk (IRR > 1.2) was seen with even modest variability (HVS ≥ 20, 73 % of T2D patients), but only at higher average levels (≥64 mmol/mol, 27 % patients). Estimated AFs were markedly greater for variability than average level (17.1 % vs. 4.1 %). Associations with variability were greater among older patients, and those with lower HbA1c levels, but not observed among Black ethnicities.

CONCLUSIONS

HbA1c variability between T2D patients' primary care visits appears to be associated with more serious infections than average level overall. Well-designed trials could test whether these associations are causal.

Prevalence of nonalcoholic fatty liver disease and liver cirrhosis in Chinese adults with type 2 diabetes mellitus

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) and liver cirrhosis are significant clinical concerns, especially among individuals with type 2 diabetes mellitus (T2DM). However, in China, there is a paucity of reliable evidence detailing the characteristics of NAFLD and liver cirrhosis in T2DM. Furthermore, the relationship between blood glucose levels and NAFLD prevalence remains unclear.

METHODS

Data from the Shanghai Suburban Adult Cohort and Biobank were analyzed, including 6621 participants with T2DM. NAFLD was diagnosed by ultrasonography and liver cirrhosis was performed according to the health information systems. Logistic regression and restricted cubic spline analysis were used to explore the potential risk factors for NAFLD and liver cirrhosis.

RESULTS

The prevalence of NAFLD was 59.36%, and liver cirrhosis was 1.43% among T2DM patients. In these patients, factors like age, being female, marital status, and obesity significantly increased the risk of NAFLD. Specifically, obesity had a strong positive association with NAFLD (odds ratio [OR] = 4.70, 95% confidence interval [CI]: 4.13-5.34). The higher glycated hemoglobin (HbA1c) quartile was associated with a heightened NAFLD risk compared to the lowest quartile (all p < .001). The HbA1c-NAFLD relationship displayed a linear that mimicked an inverted L-shaped pattern. A significant positive association existed between HbA1c levels and NAFLD for HbA1c <8.00% (OR = 1.59, 95% CI: 1.44-1.75), but this was not observed for HbA1c >8.00% (OR = 1.03, 95% CI: 0.92-1.15).

CONCLUSION

Systematic screening for NAFLD is essential in T2DM patients, especially with poor glucose control and obesity in female.

Assessing the temporal within-day glycemic variability during hospitalization in patients with type 2 diabetes patients using continuous glucose monitoring: a retrospective observational study

AIMS

Frequent and extensive within-day glycemic variability (GV) in blood glucose levels may increase the risk of hypoglycemia and long-term mortality in hospitalized patients with diabetes. We aimed to assess the amplitude and frequency of within-day GV in inpatients with type 2 diabetes and to explore the factors influencing within-day GV.

METHODS

We conducted a single-center, retrospective observational study by analyzing hospital records and 10-day real-time continuous glucose monitoring data. Within-day GV was assessed using the coefficient of variation (%CV). The primary outcome was the amplitude and frequency of within-day GV. The frequency of within-day GV was assessed by the consecutive days (CD) of maintaining within the target %CV range after first reaching it (CD after first reaching the target) and the maximum consecutive days of maintaining within the target %CV range (Max-CD). The target %CV range was less than 24.4%. We evaluated the factors influencing within-day GV using COX regression and Poisson regression models.

RESULTS

A total of 1050 cases were analyzed, of whom 86.57% reduced the amplitude of within-day GV before the sixth day of hospitalization. Of the 1050 hospitalized patients, 66.57% stayed within the target %CV range for less than two days after first reaching the target and 69.71% experienced a Max-CD of fewer than four days. Reducing the average postprandial glucose excursion (hazard ratio [HR]: 0.81, 95% confidence interval [CI]: 0.77-0.85; incidence rate ratios [IRR]: 0.72, 95% CI: 0.69-0.74) and the use of α-glucosidase inhibitors (IRR: 1.1, 95% CI: 1.01-1.18) and glucagon-like peptide-1 agonist (IRR: 1.30, 95% CI: 1.02-1.65) contributed to reducing the amplitude and decreasing the frequency of within-day GV. However, the use of insulin (HR: 0.64, 95% CI: 0.55-0.75; IRR: 0.86, 95% CI: 0.79-0.93) and glinide (HR: 0.47, 95% CI: 0.31-0.73; IRR: 0.84, 95% CI: 0.73-0.97) may lead to an increased frequency of within-day GV.

CONCLUSIONS

An increasing frequency of within-day GV was observed during the hospitalization in patients with type 2 diabetes, despite the effective reduction in the amplitude of within-day GV. Using medications designed to lower postprandial blood glucose could contribute to minimize the risk of frequent within-day GV.

Effect of Intensive Lifestyle Intervention on Cardiovascular Risk Factors: Analysis From the Perspective of Long-Term Variability

BACKGROUND

An association between variability of cardiovascular risk factors and cardiovascular events has been reported. We examined whether intensive lifestyle intervention (ILI) for weight loss decreased variability of cardiovascular risk factors with a view to additional cardiometabolic benefits.

METHODS AND RESULTS

This study was a post hoc secondary analysis of the Look AHEAD (Action for Health in Diabetes) study. Cardiovascular risk factors were measured at 1-year intervals for 4 years in 4249 adults with overweight or obesity and type 2 diabetes who were randomly assigned to ILI or diabetes support and education. Long-term variability was defined as the SD of cardiovascular risk factors during 4-year follow-up. At multiple linear regression analysis, compared with the diabetes support and education group, the ILI group was associated with reduced variability of fasting blood glucose (β=-1.49 [95% CI, -2.39 to -0.59]), total cholesterol (β=-1.12 [95% CI, -1.75 to -0.48]), and low-density lipoprotein cholesterol (β=-1.04 [95% CI, -1.59 to -0.49]), as well as increased variability of systolic blood pressure (β=0.27 [95% CI, 0.00-0.54]). No significant effect of ILI was found on the variability of diastolic blood pressure (β=-0.08 [95% CI, -0.22 to 0.05]).

CONCLUSIONS

Among adults with overweight or obesity and type 2 diabetes, ILI may reduce long-term variability of fasting blood glucose, total cholesterol, and low-density lipoprotein cholesterol. Our results support that ILI should be recommended to individuals with diabetes as part of management of long-term glycemic and blood lipid control.

Effect of delay in treatment intensification in people with type 2 diabetes and suboptimal glycaemia after basal insulin initiation: A real-world observational study

AIM

Despite global recommendations for type 2 diabetes mellitus treatment to maintain optimal glycaemic targets, a significant proportion of people remain in suboptimal glycaemic control. Our objective was to investigate the impact of intensification delay after basal insulin (BI) initiation on long-term complications in people with suboptimal glycaemia.

MATERIALS AND METHODS

We conducted a retrospective cohort study in individuals with type 2 diabetes mellitus initiated on BI. Those with suboptimal glycaemia (glycated haemoglobin ≥7% or ≥53 mmol/mol) within 12 months of BI initiation were divided into early (treatment intensified within 5 years), or late (≥5 years) intensification groups. We estimated the age-stratified risks of micro- and macrovascular complications among these groups compared with those with optimal glycaemia (glycated haemoglobin <7%).

RESULTS

Of the 13 916 people with suboptimal glycaemia, 52.5% (n = 7304) did not receive any treatment intensification. In those aged <65 years, compared with the optimal glycaemia group late intensification was associated with a 56% higher risk of macrovascular complications (adjusted hazard ratio 1.56; 95% confidence intervals 1.08, 2.26). In elderly people (≥65 years), late intensification was associated with a higher risk of cardiovascular-related death (1.62; 1.03, 2.54) and a lower risk of microvascular complications (0.26; 0.08, 0.83).

CONCLUSIONS

Those who had late intensification were at an increased risk of cardiovascular death if they were ≥65 years and an increased risk of macrovascular complications if they were <65 years. These findings highlight the critical need for earlier intensification of treatment and adopting personalized treatment strategies to improve patient outcomes.

Glycemic variability leads to higher levels of auto-oxidized oxysterol species in patients with type 1 diabetes mellitus

PURPOSE

Hyperglycemia and glycemic variability (GV) are associated with oxidative stress in patients with diabetes mellitus (DM). Oxysterol species, produced by the non-enzymatic oxidation of cholesterol, are potential biomarkers of oxidative stress. This study examined the relationship between auto-oxidized oxysterols and GV in patients with type 1 DM.

METHODS

Thirty patients with type 1 DM using a continuous subcutaneous insulin infusion pump therapy and a healthy control group (n = 30) were included in this prospective study. A Continuous Glucose Monitoring System device was applied for 72 h. Blood samples were taken for oxysterols produced by non-enzymatic oxidation [7-ketocholesterol (7-KC) and cholestane-3β, 5α, 6β-triol (Chol-Triol)] levels at 72 h. Short-term glycemic variability parameters, mean amplitude of glycemic excursions (MAGE), the standard deviation of glucose measurements (Glucose-SD), and mean of daily differences (MODD) were calculated with continuous glucose monitoring data. HbA1c was used to evaluate glycemic control and HbA1c-SD (the SD of HbA1c over the past year) for long-term glycemic variability.

RESULTS

7-KC and Chol-triol levels were significantly higher in the study group than in the control group. Strong positive correlations were found between 7-KC with MAGE(24-48 h) and Glucose-SD(24-48 h). 7-KC was positively correlated with MAGE(0-72 h) and Glucose-SD(0-72 h). No significant correlation was found between HbA1c and HbA1c -SD with oxysterol levels. The regression models showed that SD(24-48 h) and MAGE(24-48 h) predicted 7-KC levels while HbA1c did not.

CONCLUSIONS

Glycemic variability leads to higher levels of auto-oxidized oxysterol species in patients with type 1 DM independent of long-term glycemic control.

The effect of sodium-glucose cotransporter 2 inhibitors as an adjunct to insulin in patients with type 1 diabetes assessed by continuous glucose monitoring: A systematic review and meta-analysis

AIMS

Patients undergoing insulin-based therapy for type 1 diabetes often experience poor glycemic control characterized by significant fluctuations. This study was undertaken to analyze the effect of sodium-glucose cotransporter 2 inhibitors (SGLT2Is), as an adjunct to insulin, on time in range (TIR) and glycemic variability in patients with type 1 diabetes, using continuous glucose monitoring (CGM). In addition, we examined which type of SGLT2I yielded a superior effect compared to others.

METHODS

We conducted a comprehensive search of PubMed, EMBASE, the Cochrane Library, Web of Science, and clinical trial registry websites, retrieving all eligible randomized clinical trials (RCTs) published up until February 2023. We analyzed the mean TIR, mean amplitude of glucose excursions (MAGE), mean daily glucose (MDG), diabetic ketoacidosis (DKA), standard deviation (SD), total insulin dose, and severe hypoglycemia to evaluate the efficacy and safety of SGLT2Is. A random-effects model was also employed.

RESULTS

This study encompassed 15 RCTs. The meta-analysis revealed that the use of SGLT2Is as an adjuvant therapy to insulin led to a significant increase in TIR (MD = 10.78, 95%CI = 9.33-12.23, I2 = 42 %, P < 0.00001) and a decrease in SD (MD = -0.38, 95%CI = -0.50 to -0.26, I2 = 0 %, P < 0.00001), MAGE (MD = -0.92, 95%CI = -1.17 to -0.67, I2 = 19 %, P < 0.00001), MDG(MD = -1.01, 95%CI = -1.32 to -0.70, I2 = 48 %, P < 0.00001), and total insulin dose (MD = -5.81, 95%CI = -7.81 to -3.82, I2 = 32 %, P < 0.00001). No significant increase was observed in the rate of severe hypoglycemia (RR = 1.04, 95 % CI = 0.76-1.43, P = 0.80). However, SGLT2I therapy was associated with increased DKA occurrence (RR = 2.79, 95 % CI = 1.42-5.48; P = 0.003, I2 = 16 %). In addition, the subgroup analyses based on the type of SGLT2Is revealed that dapagliflozin might exhibit greater efficacy compared to other SGLT2Is across most outcomes.

CONCLUSIONS

SGLT2Is exhibited a positive effect on improving blood glucose level fluctuations. Subgroup analysis showed that dapagliflozin appeared to have more advantages. However, giving due consideration to preventing adverse effects, particularly DKA, is paramount.

REGISTRATION

Prospero CRD42023408276.

Gut Microbiota Composition and Functionality Are Associated With REM Sleep Duration and Continuous Glucose Levels

CONTEXT

Sleep disruption is associated with worse glucose metabolic control and altered gut microbiota in animal models.

OBJECTIVE

We aimed to evaluate the possible links among rapid eye movement (REM) sleep duration, continuous glucose levels, and gut microbiota composition.

METHODS

This observational, prospective, real-life, cross-sectional case-control study included 118 (60 with obesity), middle-aged (39.1-54.8 years) healthy volunteers recruited at a tertiary hospital. Glucose variability and REM sleep duration were assessed by 10-day continuous glucose monitoring (CGM) (Dexcom G6) and wrist actigraphy (Fitbit Charge 3), respectively. The coefficient of variation (CV), interquartile range (IQR), and SD of glucose variability was assessed and the percentage of time in range (% TIR), at 126-139 mg/dL (TIR2), and 140-199 mg/dL (TIR3) were calculated. Shotgun metagenomics sequencing was applied to study gut microbiota taxonomy and functionality.

RESULTS

Increased glycemic variability (SD, CV, and IQR) was observed among subjects with obesity in parallel to increased % TIR2 and % TIR3. REM sleep duration was independently associated with % TIR3 (β = -.339; P < .001) and glucose variability (SD, β = -.350; P < .001). Microbial taxa from the Christensenellaceae family (Firmicutes phylum) were positively associated with REM sleep and negatively with CGM levels, while bacteria from Enterobacteriacea family and bacterial functions involved in iron metabolism showed opposite associations.

CONCLUSION

Decreased REM sleep duration was independently associated with a worse glucose profile. The associations of species from Christensenellaceae and Enterobacteriaceae families with REM sleep duration and continuous glucose values suggest an integrated picture of metabolic health.

Glucose variability: a new risk factor for cardiovascular disease

AIMS AND DATA SYNTHESIS

Glucose variability (GV) is increasingly considered an additional index of glycemic control. Growing evidence indicates that GV is associated with diabetic vascular complications, thus being a relevant point to address in diabetes management. GV can be measured using various parameters, but to date, a gold standard has not been identified. This underscores the need for further studies in this field also to identify the optimal treatment.

CONCLUSIONS

We reviewed the definition of GV, the pathogenetic mechanisms of atherosclerosis, and its relationship with diabetic complications.

Particularities of Urinary Tract Infections in Diabetic Patients: A Concise Review

Diabetes mellitus is a chronic disease that, untreated or poorly controlled, can lead to serious complications, reducing life expectancy and quality. Diabetic patients are more likely to develop infections, including many common infections, but also pathognomonic ones such as emphysematous pyelonephritis, malignant otitis externa, mucormycosis and Fournier's gangrene. Considering the fact that diabetic patients experience more frequently urinary tract infections (UTIs) with a worse prognosis than non-diabetic people, we conducted a review study based on data in the literature, following the particularities of UTIs in this group of patients, the risk factors, the mechanisms involved and the challenges in their management. The findings highlight that UTI in diabetic patients have some particularities, including a more frequent evolution to bacteremia, increased hospitalizations, and elevated rates of recurrence and mortality than non-diabetic patients. The possible risk factors identified seem to be female gender, pregnancy, older age, UTI in the previous six months, poor glycemic control and duration of diabetes. The mechanisms involved are related to glucosuria and bladder dysfunction, factors related to bacterial strains and host response. The bacterial strains involved in UTIs in diabetic patients and their antibiotic susceptibility profile are, with some exceptions, similar to those in non-diabetic people; however, the antimicrobial agents should be carefully chosen and the duration of the treatment should be as those required for a complicated UTI. The data related to the risk of developing UTIs in patients treated with SGLT-2 inhibitors, a new class of oral hypoglycaemic agents with cardiovascular and renal benefits, are controversial; overall, it was evidenced that UTIs occurred at the initiation of the treatment, recurrent infection was uncommon and the majority of UTIs responded to treatment with standard antibiotics. Moreover, interruption or discontinuation of SGLT-2 inhibitor as a result of UTI was rare and SGLT-2 inhibitors did not increase the risk of severe infections such as urosepsis and pyelonephritis.

Development and validation of a clinical prediction model for detecting coronary heart disease in middle-aged and elderly people: a diagnostic study

OBJECTIVE

To develop and validate a multivariate prediction model to estimate the risk of coronary heart disease (CHD) in middle-aged and elderly people and to provide a feasible method for early screening and diagnosis in middle-aged and elderly CHD patients.

METHODS

This study was a single-center, retrospective, case-control study. Admission data of 932 consecutive patients with suspected CHD were retrospectively assessed from September 1, 2020 to December 31, 2021 in the Department of Integrative Cardiology at China-Japan Friendship Hospital. A total of 839 eligible patients were included in this study, and 588 patients were assigned to the derivation set and 251 as the validation set at a 7:3 ratio. Clinical characteristics of included patients were compared between derivation set and validation set by univariate analysis. The least absolute shrinkage and selection operator (Lasso) regression analysis method was performed to avoid collinearity and identify key potential predictors. Multivariate logistic regression analysis was used to construct a clinical prediction model with identified predictors for clinical practice. Bootstrap validation was used to test performance and eventually we obtained the actual model. And the Hosmer-Lemeshow test was carried out to evaluate the goodness-fit of the constructed model. The area under curve (AUC) of receiver operating characteristic (ROC), calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC) were plotted and utilized with validation set to comprehensively evaluate the predictive accuracy and clinical value of the model.

RESULTS

A total of eight indicators were identified as risk factors for the development of CHD in middle-aged and elderly people by univariate analysis. Of these candidate predictors, four key parameters were defined to be significantly related to CHD by Lasso regression analysis, including age (OR 1.034, 95% CI 1.002 ~ 1.067, P = 0.040), hemoglobin A1c (OR 1.380, 95% CI 1.078 ~ 1.768, P = 0.011), ankle-brachial index (OR 0.078, 95% CI 0.012 ~ 0.522, P = 0.009), and brachial artery flow-mediated vasodilatation (OR 0.848, 95% CI 0.726 ~ 0.990, P = 0.037). The Hosmer-Lemeshow test showed a good calibration performance of the clinical prediction model (derivation set, χ2 = 7.865, P = 0.447; validation set, χ2 = 11.132, P = 0.194). The ROCs of the nomogram in the derivation set and validation set were 0.722 and 0.783, respectively, suggesting excellent predictive power and suitable performance. The clinical prediction model presented a greater net benefit and clinical impact based on DCA and CIC analysis.

CONCLUSION

Overall, the development and validation of the multivariate model combined the laboratory and clinical parameters of patients with CHD, which could be beneficial to the individualized prediction of middle-aged and elderly people, and helped to facilitate clinical assessments and decisions during treatment and management of CHD.

Long-term glycemic variability predicts compromised development of heart failure with improved ejection fraction: a cohort study

Background

A substantial portion of heart failure (HF) patients adherent to guideline-directed medical therapies have experienced improved ejection fraction (EF), termed HFimpEF. Glycemic variability (GV) has emerged as a critical cardiometabolic factor. However, the relation between long-term GV and the incidence of HFimpEF is still unclear.

Methods

A total of 591 hospitalized HF patients with reduced EF (HFrEF, EF≤ 40%) admitted from January 2013 to December 2020 were consecutively enrolled. Repeat echocardiograms were performed at baseline and after around 12 months. The incidence of HFimpEF, defined as (1) an absolute EF improvement ≥10% and (2) a second EF > 40% and its association with long-term fasting plasma glucose (FPG) variability were analyzed.

Results

During a mean follow-up of 12.2 ± 0.6 months, 218 (42.0%) patients developed HFimpEF. Multivariate analysis showed FPG variability was independently associated with the incidence of HFimpEF after adjustment for baseline HbA1c, mean FPG during follow-up and other traditional risk factors (odds ratio [OR] for highest vs. lowest quartile of CV of FPG: 0.487 [95% CI 0.257~0.910]). Evaluation of GV by alternative measures yielded similar results. Subgroup analysis revealed that long-term GV was associated with HFimpEF irrespective of glycemic levels and diabetic conditions.

Conclusions

This study reveals that greater FPG variability is associated with compromised development of HFimpEF. A more stable control of glycemic levels might provide favorable effects on myocardial functional recovery in HF patients even without diabetes.

Visit to Visit Hemoglobin A1c Variation and Long-term Risk of Major Adverse Limb Events in Patients With Type 2 Diabetes

CONTEXT

Glycemic variation had been demonstrated to be associated with several complications of diabetes.

OBJECTIVE

Investigation of the association between visit to visit hemoglobin A1c (HbA1c) variation and the long-term risk of major adverse limb events (MALEs).

METHODS

Retrospective database study. Average real variability was used to represent glycemic variations with all the HbA1c measurements during the 4 following years after the initial diagnosis of type 2 diabetes. Participants were followed from the beginning of the fifth year until death or the end of the follow-up. The association between HbA1c variations and MALEs was evaluated after adjusting for mean HbA1c and baseline characteristics. Included were 56 872 patients at the referral center with a first diagnosis of type 2 diabetes, no lower extremity arterial disease, and at least 1 HbA1c measurement in each of the 4 following years were identified from a multicenter database. The main outcome measure was incidence of a MALE, which was defined as the composite of revascularization, foot ulcers, and lower limb amputations.

RESULTS

The average number of HbA1c measurements was 12.6. The mean follow-up time was 6.1 years. The cumulative incidence of MALEs was 9.25 per 1000 person-years. Visit to visit HbA1c variations were significantly associated with MALEs and lower limb amputation after multivariate adjustment. People in the highest quartile of variations had increased risks for MALEs (HR 1.25, 95% CI 1.10-1.41) and lower limb amputation (HR 3.05, 95% CI 1.97-4.74).

CONCLUSION

HbA1c variation was independently associated with a long-term risk of MALEs and lower limb amputations in patients with type 2 diabetes.

Visit-to-Visit Variability in Fasting Blood Glucose Predicts the New-Onset Heart Failure: Results From Two Large Chinese Cohorts

Previous studies have hypothesized an association between higher fasting blood glucose (FBG) and heart failure (HF). However, FBG values fluctuate continuously over time, the association between FBG variability and the risk of HF is uncertain. We investigated the relationship between visit-to-visit variability in FBG and the risk of new-onset HF. This cohort study used data from a prospective Kailuan cohort (recruited during 2006-2007) and a retrospective cohort of family medicine patients from Hong Kong (recruited during 2000-2003) were followed up until December 31st, 2016, and December 31st, 2019, respectively, for the outcome of incident HF. Four indexes of variability were used, including standard deviation (SD), coefficient of variation (CV), variability independent of the mean (VIM), and average real variability (ARV). Cox regression was used to identify HF. In total, 98,554 and 22,217 subjects without preexisting HF from the Kailuan and Hong Kong cohorts were analyzed, respectively, with 1218 cases of incident HF in the former and 4,041 in the latter. Subjects in the highest quartile of FBG-CV had the highest risk of incident HF in both cohorts (Kailuan: HR 1.245, 95% CI 1.055-1.470); Hong Kong: HR 1.362, 95%CI 1.145-1.620; compared with the lowest quartile). Similar results were observed when using FBG-ARV, FBG-VIM, and FBG-SD. Meta-analysis showed similar results (highest versus lowest quartile: HR 1.30, 95%CI 1.15-1.47, P < 0.0001). As observed from 2 large, geographically distinct Chinese cohorts, a higher FBG variability was independently associated with higher risk of incident HF.

A study of factors influencing long-term glycemic variability in patients with type 2 diabetes: a structural equation modeling approach

Aim

The present study aims to utilize structural equation modeling (SEM) to investigate the factors impacting long-term glycemic variability among patients afflicted with type 2 diabetes.

Method

The present investigation is a retrospective cohort study that involved the collection of data on patients with type 2 diabetes mellitus who received care at a hospital located in Chengdu, Sichuan Province, over a period spanning from January 1, 2013, to October 30, 2022. Inclusion criteria required patients to have had at least three laboratory test results available. Pertinent patient-related information encompassing general demographic characteristics and biochemical indicators was gathered. Variability in the dataset was defined by standard deviation (SD) and coefficient of variation (CV), with glycosylated hemoglobin variation also considering variability score (HVS). Linear regression analysis was employed to establish the structural equation models for statistically significant influences on long-term glycemic variability. Structural equation modeling was employed to analyze effects and pathways.

Results

Diabetes outpatient special disease management, uric acid variability, mean triglyceride levels, mean total cholesterol levels, total cholesterol variability, LDL variability, baseline glycated hemoglobin, and recent glycated hemoglobin were identified as significant factors influencing long-term glycemic variability. The overall fit of the structural equation model was found to be satisfactory and it was able to capture the relationship between outpatient special disease management, biochemical indicators, and glycated hemoglobin variability. According to the total effect statistics, baseline glycated hemoglobin and total cholesterol levels exhibited the strongest impact on glycated hemoglobin variability.

Conclusion

The factors that have a significant impact on the variation of glycosylated hemoglobin include glycosylated hemoglobin itself, lipids, uric acid, and outpatient special disease management for diabetes. The identification and management of these associated factors can potentially mitigate long-term glycemic variability, thereby delaying the onset of complications and enhancing patients' quality of life.

Correlation Between Glycemic Variability and Diabetic Complications: A Narrative Review

Diabetes mellitus is a metabolic disorder with a complex etiology in which glycemic dynamics are disturbed and the body is unable to maintain the process of glucose homeostasis through the pancreas. Persistent symptoms of high blood glucose or low blood glucose may lead to diabetic complications, such as neuropathy, nephropathy, retinopathy, and cardiovascular diseases. Glycemic variability which can represent the presence of excessive glycemic excursions is an indicator for evaluating glucose homoeostasis. Limiting glycemic variability has gradually become an emerging therapeutic target in improve diabetes metabolism and prevent associated complications. This article reviews the progress of research on the various quantifiable parameters of glycemic variability and their relationships with vascular lesions and mechanisms.

Intensified glycemic control by HbA1c for patients with coronary heart disease and Type 2 diabetes: a review of findings and conclusions

The occurrence and development of coronary heart disease (CHD) are closely linked to fluctuations in blood glucose levels. While the efficacy of intensified treatment guided by HbA1c levels remains uncertain for individuals with diabetes and CHD, this review summarizes the findings and conclusions regarding HbA1c in the context of CHD. Our review showed a curvilinear correlation between regulated level of HbA1c and therapeutic effectiveness of intensified glycemic control among patients with type 2 diabetes and coronary heart disease. It is necessary to optimize the dynamic monitoring indicators of HbA1c, combine genetic profiles, haptoglobin phenotypes for example and select more suitable hypoglycemic drugs to establish more appropriate glucose-controlling guideline for patients with CHD at different stage of diabetes.

Hemoglobin A1c Variability Metrics Predict Coronary Artery Calcium and Cardiovascular Events in Type 1 Diabetes: The CACTI Study

CONTEXT

Interventions that decrease mean glucose have reduced rates of micro- and macrovascular complications in type 1 diabetes (T1D). However, the difference in cardiovascular risk between people with T1D and the general population endures, suggesting that factors beyond hemoglobin A1C (HbA1c) normalization drive cardiovascular outcomes.

OBJECTIVE

To determine whether various HbA1c metrics predict anatomic cardiovascular disease (CVD) risk factors and/or CVD events in people with T1D.

METHODS

We used linear regression to analyze the relationship of several HbA1c metrics to anatomic CVD risk factors and then used Cox regression to model their relationship to incident CVD events in the CACTI Study (ClinicalTrials.gov Identifier: NCT00005754).

RESULTS

In linear regression models adjusted for age, sex, and T1D duration, baseline Hba1c (b = 0.3998, P = 0.0236), mean HbA1c (b = 0.5385, P = 0.0109), and HbA1c SD (b = 1.1521, P = 0.0068) were each positively associated with square root transformed coronary artery calcium volume. Conversely, only mean HbA1c (b = 1.659, P = 0.0048) positively associated with pericardial adipose tissue volume. In survival models adjusted for age, sex, and T1D duration, baseline HbA1c [hazard ratio (HR): 1.471, 95% CI: 1.257-1.721], mean HbA1c (HR: 1.850, 95% CI: 1.511-2.264), time-varying HbA1c (HR: 1.500, 95% CI: 1.236-1.821), and HbA1c SD (HR: 1.665, 95% CI: 1.022-2.711) each independently predicted CVD events over 14.3 ± 5.2 person-years of follow-up.

CONCLUSIONS/INTERPRETATION

We found that various HbA1c metrics positively correlated with CAC volume and independently predicted incident CVD events in the CACTI T1D cohort. These associations with CVD events persisted for baseline HbA1c, mean HbA1c, and time-varying HbA1c even after adjustment for numerous CVD risk factors.

Higher glucose fluctuation is associated with a higher risk of cardiovascular disease: Insights from pooled results among patients with diabetes

BACKGROUND

The relationship between glucose fluctuation and the risk of cardiovascular disease (CVD) in patients with diabetes remains elusive. Glycated hemoglobin (HbA1c) variability is a key parameter of glucose fluctuation.

METHODS

PubMed, Cochrane Library, Web of Science, and Embase were searched up to 1 July 2022. Studies reporting associations of HbA1c variability (HbA1c-SD), coefficient of variation of HbA1c (HbA1c-CV), and HbA1c variability score [HVS] with the risk of CVD among patients with diabetes were included. We used three different insights (a high-low value meta-analysis, a study-specific meta-analysis, and a non-linear dose-response meta-analysis) to explore the relationship between HbA1c variability and CVD risk. A subgroup analysis was also performed to screen the potential confounding factors.

RESULTS

A total of 14 studies with 254 017 patients with diabetes were eligible. The highest HbA1c variability was significantly associated with increased risks of CVD (HbA1c-SD, risk ratio [RR] 1.45; HbA1c-CV, RR 1.74; HVS, RR 2.46; all p < .001) compared to the lowest HbA1c variability. The RRs of CVD for per HbA1c variability were significantly >1 (all p < .001). The subgroup analysis for per HbA1c-SD found a significant exposure-covariate interaction in the types of diabetes (p = .003 for interaction). The dose-response analysis showed a positive association between HbA1c-CV and CVD risk (P for nonlinearity <.001).

CONCLUSIONS

Our study suggests that the higher glucose fluctuation is significantly associated with the higher CVD risk in diabetes patients based on HbA1c variability. The CVD risk associated with per HbA1c-SD might be higher among patients type 1 diabetes than patients with type 2 diabetes.

Increased Two-Hour Post-Load Plasma Glucose Fluctuation Corresponds with Worse Clinical Prognoses among Acute Ischemic Stroke Patients without a History of Diabetes Mellitus

INTRODUCTION

This study aimed to evaluate the relationship between 2-h post-load minus fasting plasma glucose (2hPG-FPG) and 1-year clinical outcomes, such as death, stroke recurrence, and modified Rankin Scale (mRS) ≥2-3 among acute ischemic stroke (AIS) patients without diabetes mellitus (DM) history.

METHODS

1,214 AIS patients without DM history, obtained from ACROSS-China, were divided into 4 quartiles, based on 2hPG-FPG measurements obtained 14 days post-admission. Four models were constructed using multivariate Cox and logistic regression analyses, based on the inclusion of age, gender, trial of ORG 10172 in acute stroke treatment, NIH Stroke Scale scores (model 1), plus 10 other clinical parameters (model 2), plus newly diagnosed DM (NDDM) post-admission (model 3), plus 2hPG and FPG (model 4). Associations found from those 4 models between 2hPG-FPG and 1-year clinical outcomes were confirmed via stratification, multiplicative interaction, sensitivity, and restricted cubic spline analyses.

RESULTS

The highest quartile of 2hPG-FPG, after adjusting for variables, such as stroke severity (model 2), was independently associated with death, stroke recurrence, and mRS ≥2-3 (odds ratio [OR] = 3.95, 2.96, 4.15, and 4.83, respectively, all p < 0.0001). Increased 2hPG-FPG remained independently associated with mRS ≥2-3 in models 3-4, as well as increased mRS ≥2 under stratification analyses among both non-NDDM and NDDM patients.

CONCLUSION

2hPG-FPG is a relatively specific indicator of poorer 1-year clinical prognoses among AIS patients, independent of NDDM, 2hPG, and FPG post-hospital admission. Therefore, the oral glucose tolerance test could be a useful approach for detecting a higher likelihood for developing poorer prognoses among patients without DM history.

Hyperglycemia and Glycemic Variability Associated with Glucocorticoids in Women without Pre-Existing Diabetes Undergoing Neoadjuvant or Adjuvant Taxane Chemotherapy for Early-Stage Breast Cancer

Glucocorticoids, which are administered with chemotherapy, cause hyperglycemia. Glycemic variability among breast cancer patients without diabetes is not well known. A retrospective cohort study was conducted involving early-stage breast cancer patients without diabetes who received dexamethasone prior to neoadjuvant or adjuvant taxane chemotherapy between August 2017-December 2019. Random blood glucose levels were analyzed, and steroid-induced hyperglycemia (SIH) was defined as a random glucose level of >140 mg/dL. A multivariate proportional hazards model was used to identify the risk factors of SIH. Out of 100 patients, the median age was 53 years (IQR: 45-63.5). A total of 45% of patients were non-Hispanic White, 28% Hispanic, 19% Asian, and 5% African American. The incidence of SIH was 67%, and glycemic fluctuations were highest in those with glucose levels of >200 mg/dL. Non-Hispanic White patients represented a significant predictor for time to SIH, with a hazard ratio of 2.5 (95% CI: 1.04, 5.95, p = 0.039). SIH was transient in over 90% of the patients, and only seven patients remained hyperglycemic after glucocorticoid and chemotherapy completion. Pretaxane dexamethasone-induced hyperglycemia was observed in 67% of the patients, with the greatest glycemic lability in those patients with blood glucose levels of >200 mg/dL. The non-Hispanic White patients had a higher risk of developing SIH.

Effectiveness of Telemedicine in Diabetes Management: A Retrospective Study in an Urban Medically Underserved Population Area (UMUPA)

This paper examines the efficacy of telemedicine (TM) technology compared to traditional face-to-face (F2F) visits as an alternative healthcare delivery service for managing diabetes in populations residing in urban medically underserved areas (UMUPAs). Retrospective electronic patient health records (ePHR) with type 2 diabetes mellitus (T2DM) were examined from 1 January 2019 to 30 June 2021. Multiple linear regression models indicated that T2DM patients with uncontrolled diabetes utilizing TM were similar to traditional visits in lowering hemoglobin (HbA1c) levels. The healthcare service type significantly predicted HbA1c % values, as the regression coefficient for TM (vs. F2F) showed a significant negative association (B = −0.339, p < 0.001), suggesting that patients using TM were likely to have 0.34 lower HbA1c % values on average when compared with F2F visits. The regression coefficient for female (vs. male) gender showed a positive association (B = 0.190, p < 0.034), with HbA1c % levels showing that female patients had 0.19 higher HbA1c levels than males. Age (B = −0.026, p < 0.001) was a significant predictor of HbA1c % levels, with 0.026 lower HbA1c % levels for each year’s increase in age. Black adults (B = 0.888, p < 0.001), on average, were more likely to have 0.888 higher HbA1c % levels when compared with White adults.

Diabetic Peripheral Neuropathy Associated with Foot Ulcer: One of a Kind

Significance: Diabetic peripheral neuropathy (DPN) associated with a diabetic foot ulcer (DFU) is likely to be complicated with critical factors such as biofilm infection and compromised skin barrier function of the diabetic skin. Repaired skin with a history of biofilm infection is known to be compromised in barrier function. Loss of barrier function is also observed in the oxidative stress affected diabetic and aged skin. Recent Advances: Loss of barrier function makes the skin prone to biofilm infection and cellulitis, which contributes to chronic inflammation and vasculopathy. Hyperglycemia favors biofilm formation as glucose lowering led to reduction in biofilm development. While vasculopathy limits oxygen supply, the O2 cost of inflammation is high increasing hypoxia severity. Critical Issues: The host nervous system can be inhabited by bacteria. Because electrical impulses are a part of microbial physiology, polymicrobial colonization of the host's neural circuit is likely to influence transmission of action potential. The identification of perineural apatite in diabetic patients with peripheral neuropathy suggests bacterial involvement. DPN starts in both feet at the same time. Future Directions: Pair-matched studies of DPN in the foot affected with DFU (i.e., DFU-DPN) compared with DPN in the without ulcer, and intact skin barrier function, are likely to provide critical insight that would help inform effective care strategies. This review characterizes DFU-DPN from a translational science point of view presenting a new paradigm that recognizes the current literature in the context of factors that are unique to DFU-DPN.

Efficacy and safety of intensive versus conventional glucose targets in people with type 2 diabetes: a systematic review and meta-analysis

OBJECTIVE

The aim of study is to re-evaluate the risk-benefits of intensive glycemic control in the context of multi-factorial intervention in adults with T2D.

METHODS

We searched Ovid MEDLINE, Embase, Cochrane, and CINHAL for randomized control trials comparing standard glucose targets to intensive glucose targets with pre-specified HbA_1clevels. Subgroup analysis was also performed to account for the inclusion of glucose only versus multi-factorial intervention trials. Results are reported as risk ratio (RR) and 95% confidence interval (CI).

RESULTS

Fifty-seven publications including 19 trials were included. Compared to conventional glycemic control, intensive glycemic control decreased the risk of non-fatal myocardial infarction (0.8, 0.7-0.91), macroalbuminuria (0.72, 0.5--0.87), microalbuminuria (0.67, 0.52-0.85), major amputation (0.6, 0.38-0.96), retinopathy (0.75 ,0.63-0.9), and nephropathy (0.78, 0.63-0.97). The risk of hypoglycemia increased with intensive glycemic control than conventional treatment (2.04, 1.34-3.1). No reduction in all-cause or cardiovascular mortality was observed. However, in the context of multifactorial intervention, intensive glucose control was associated with a significant reduction in all-cause mortality (0.74, 0.57-0.95).

CONCLUSION

Targeting HbA_1c levels should be individualized based on the clinical status, balancing risks and benefits and potential risk for developing these complications among people with T2D.

Protection of diabetes in aortic abdominal aneurysm: Are antidiabetics the real effectors?

Aortic aneurysms, including abdominal aortic aneurysms (AAAs), is the second most prevalent aortic disease and represents an important cause of death worldwide. AAA is a permanent dilation of the aorta on its infrarenal portion, pathologically associated with oxidative stress, proteolysis, vascular smooth muscle cell loss, immune-inflammation, and extracellular matrix remodeling and degradation. Most epidemiological studies have shown a potential protective role of diabetes mellitus (DM) on the prevalence and incidence of AAA. The effect of DM on AAA might be explained mainly by two factors: hyperglycemia [or other DM-related factors such as insulin resistance (IR)] and/or by the effect of prescribed DM drugs, which may have a direct or indirect effect on the formation and progression of AAAs. However, recent studies further support that the protective role of DM in AAA may be attributable to antidiabetic therapies (i.e.: metformin or SGLT-2 inhibitors). This review summarizes current literature on the relationship between DM and the incidence, progression, and rupture of AAAs, and discusses the potential cellular and molecular pathways that may be involved in its vascular effects. Besides, we provide a summary of current antidiabetic therapies which use could be beneficial for AAA.

In-hospital glycemic variability and all-cause mortality among patients hospitalized for acute heart failure

BACKGROUND

High glycemic variability (GV) is a poor prognostic marker in cardiovascular diseases. We aimed to investigate the association of GV with all-cause mortality in patients with acute heart failure (HF).

METHODS

The Korean Acute Heart Failure registry enrolled patients hospitalized for acute HF from 2011 to 2014. Blood glucose levels were measured at the time of admission, during hospitalization, and at discharge. We included those who had 3 or more blood glucose measurements in this study. Patients were divided into two groups based on the coefficient of variation (CoV) as an indicator of GV. Among survivors of the index hospitalization, we investigated all-cause mortality at 1 year after discharge.

RESULTS

The study analyzed 2,617 patients (median age, 72 years; median left-ventricular ejection fraction, 36%; 53% male). During the median follow-up period of 11 months, 583 patients died. Kaplan-Meier curve analysis revealed that high GV (CoV > 21%) was associated with lower cumulative survival (log-rank P < 0.001). Multivariate Cox proportional analysis showed that high GV was associated with an increased risk of 1-year (HR 1.56, 95% CI 1.26-1.92) mortality. High GV significantly increased the risk of 1-year mortality in non-diabetic patients (HR 1.93, 95% CI 1.47-2.54) but not in diabetic patients (HR 1.19, 95% CI 0.86-1.65, P for interaction = 0.021).

CONCLUSIONS

High in-hospital GV before discharge was associated with all-cause mortality within 1 year, especially in non-diabetic patients with acute HF.

Comparison of gliclazide vs linagliptin on hypoglycemia and cardiovascular events in type 2 diabetes mellitus: A systematic review

BACKGROUND

Cardiovascular outcome trials have demonstrated cardiovascular safety of glimepiride (a sulfonylureas) against dipeptidyl peptidase-4 inhibitor linagliptin. Gliclazide (another newer sulfonylureas) has shown similar glycemic efficacy and 50% decreased risk of hypoglycemia compared to glimepiride.

AIM

Considering the absence of cardiovascular outcome trials for gliclazide, we decided to conduct a systematic review of the literature to assess the car-diovascular (CV) safety by assessing the risk for major adverse CV events and hypoglycemia risk of gliclazide vs linagliptin in patients with type 2 diabetes (T2D).

METHODS

This systematic review followed the current Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to analyze all the clinical studies published from 2008 that compared the two drugs in patients with T2D with no risk of CV disease (CVD). We included only evidence designated high quality by the Oxford Center for Evidence-based Medicine-Levels of Evidence.

RESULTS

Eight clinical studies were included in the narrative descriptive analysis (gliclazide: 5 and linagliptin: 3). The CV safety of gliclazide in the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation trial and of linagliptin in the Cardiovascular and Renal Microvascular Outcome Study With Linagliptin (CARMELINA) and CARdiovascular Outcome study of LINAgliptin vs glimepiride in patients with T2D (CAROLINA) trials were excluded from the comparative analysis as these trials demonstrated CV and hypoglycemia benefits in patients at high risk of CVD. However, since these are landmark trials, they were discussed in brief to show the CV benefits and low hypoglycemia risk of gliclazide and linagliptin. We did not find any study comparing gliclazide with linagliptin. Hence, direct comparison of their major adverse CV events and hypoglycemia risk could not be carried out. However, the literature meeting the inclusion criteria showed that both drugs were effective in achieving the desired glycemic control and had low major adverse CV events and hypoglycemia risk in adult patients with no history of CVD.

CONCLUSION

Gliclazide can be considered an effective and safe glucose-lowering drug in T2D patients with no established CVD but at high risk of CVD due to their T2D status. Future randomized controlled trials comparing gliclazide with linagliptin or dipeptidyl peptidase-4 inhibitors can confirm these findings.

The Clinical Impact of Switching Basal Insulin to Insulin Degludec in Patients With Diabetes in Saudi Arabia: A Retrospective One-Group Pretest-Posttest Design Study

BACKGROUND

Diabetes is a health problem that has an enormous and intolerable public health burden on the individual, family, and community. Diabetes affects nearly one-fifth of adults in Saudi Arabia and is expected to double by 2030.

AIM OF THE STUDY

The study aims to evaluate the impact of switching patients from conventional basal insulin analogues to insulin degludec during a 90-day follow-up period.

METHODS

This was a retrospective observational pretest-posttest cohort study conducted at King Abdulaziz University Hospital between June 2019 and August 2020. Adult patients with diabetes who switched their basal insulin to insulin degludec were included and evaluated for its impact on insulin doses, hemoglobin A1c (HbA1c), hypoglycemic events, and/or body weight changes during a 90-day follow-up period.

RESULTS

Out of 718 patients, 107 patients were included in the study, with 60.7% being females and their mean (± SD) age was 62.2 ± 14.6 years. There was a significant decrease in the mean baseline of HbA1c from 9.2% to 8.7% after 90 days of follow-up (P<0.001). A statistically significant reduction was noted in the total insulin requirements from a baseline of 71.70 (± 42.4) units to 46.5 (± 29) units, P=0.001, after switching to insulin degludec. However, there were no statistically significant differences in the body weight from the baseline mean (± SD) of 80.5 kg (± 19.4) to 79.9 kg (± 19.9), P=0.68, after switching to insulin degludec. Lastly, there were no statistically significant differences in the reported hypoglycemic episodes from a baseline of 48.7% vs 37.3% after 90 days of follow-up (P = 0.166).

CONCLUSION

Switching to the novel insulin degludec conferred better blood glucose control and dose reduction. There was no increase in the frequency of hypoglycemic episodes or body weight.

Needle-free injection of basal insulin improves fasting glucose variability as assessed by continuous glucose monitoring in T2DM: a prospective randomized multicenter open-label crossover study

BACKGROUND

Fasting glucose variability (FGV) extensively promotes the onset and development of diabetic complications. This study aimed to evaluate the FGV in type 2 diabetes mellitus (T2DM) patients administered basal insulin using a needle-free insulin injector (NFII).

RESEARCH DESIGN AND METHODS

This was a prospective randomized multicenter open-label crossover study. We randomly assigned 48 T2DM patients to receive basal insulin by NFII or conventional insulin pen (CIP) for 7-14 days and were then crossed over after washout. We conducted continuous glucose monitoring to investigate the FGV, our primary outcome was a composite parameter of the FGV with a fasting blood glucose target between 4.4 and 6.1 mmol/L.

RESULTS

The coefficient of variation for sensor glucose at 6 a.m. with CIP was 11.67 (8.70,14.81)% vs. 9.48 (6.48,12.24)% with NFII (p = 0.003), and the coefficient of variation for mean sensor glucose at 5-6 a.m. with CIP was 12.70 (9.17,16.56)% vs. 9.23 (7.01,11.98)% with NFII (p < 0.001). The overall basal insulin dosage with CIP injection was 18.00 (16.00, 20.00) IU vs. 16.00 (12.00, 19.00) IU during NFII (p < 0.003).

CONCLUSION

Compared with CIP, the use of the NFII to inject basal insulin improved FGV in T2DM.

CLINICAL TRIAL REGISTRATION

https://www.chictr.org.cn Identifier is ChiCTR2000034674.

Association of visit-to-visit HbA1c variability with cardiovascular diseases in type 2 diabetes within or outside the target range of HbA1c

Background

Although a growing attention has been recently paid to the role of HbA1c variability in the risk of diabetic complications, the impact of HbA1c variability on cardiovascular diseases (CVD) in type 2 diabetes is still debated. The aim of the study is to investigate the association of HbA1c variability with CVD in individuals within or outside the target range of HbA1c.

Methods

Using data from Action in Diabetes and Vascular disease: preterAx and diamicroN-MR Controlled Evaluation (ADVANCE), we enrolled 855 patients with type 2 diabetes in China. The primary outcomes included major macrovascular events and major microvascular events. Visit-to-visit HbA1c variability was expressed as the coefficient of variation (CV) of five measurements of HbA1c taken 3-24 months after treatment. Cox proportional hazard models were used to estimate adjusted hazard ratios (aHR).

Results

Among 855 patients in the intensive glucose treatment group, 563 and 292 patients were assigned to the group of "within the target range of HbA1c" (WTH) (updated mean HbA1c ≤ 7.0%) and "outside the target range of HbA1c" (OTH) (updated mean HbA1c > 7.0%), respectively. HbA1c variability was positively associated with the risk of major microvascular events in all patients and both the subgroups during a median follow-up period of 4.8 years. Particularly, the risk related to HbA1c variability was higher in patients in WTH group for the new or worsening nephropathy [aHR: 3.35; 95% confidence interval (CI): 1.05-10.74; P = 0.042].

Conclusions

This retrospective cohort study confirmed the positive correlation between HbA1c variability and major microvascular events, especially in subjects in WTH or OTH.

Association between visit-to-visit fasting glycemic variability and depression: a retrospective cohort study in a representative Korean population without diabetes

Glycemic variability (GV) is a risk factor for depression in patients with diabetes. However, whether it is also a predictor of incident depression in people without diabetes remains unclear. We aimed to investigate the association between visit-to-visit variability in fasting serum glucose (FSG) levels and the incidence of depression among Koreans without diabetes. This retrospective cohort study included data of people without diabetes who did not have depression at baseline and had at least three FSG measurements (n = 264,480) extracted from the 2002-2007 Korean National Health Insurance Service-National Health Screening Cohort. GV was calculated as the average successive variability of FSG. Among 264,480 participants, 198,267 were observed during 2008-2013 and their hazard ratios (HR) of incident depression were calculated. Participants with the highest GV showed a higher risk of depression in fully adjusted models than those with the lowest GV (HR, 1.09; 95% CI, 1.02-1.16). The risk of incident depression heightened with increasing GV (p for trend < 0.001). Greater visit-to-visit GV may be associated with the risk of developing depression in people without diabetes. Conversely, maintaining steady FSG levels may reduce the risk of incident depression in people without diabetes.

Glucagon-Like Peptide 1 Receptor Agonists Have the Potential to Revolutionize the Attainment of Target A1C Levels in Type 2 Diabetes-So Why Is Their Uptake So Low?

A target A1C of <7% is the recommended goal for most people with type 2 diabetes. However, many are not achieving this target with their current treatment. Glucagon-like peptide 1 (GLP-1) receptor agonists are highly efficacious in achieving glycemic control and could aid primary care providers (PCPs) in getting patients to their A1C target. However, despite their potential, use of GLP-1 receptor agonists in the primary care setting is limited. This review provides guidance for PCPs on how to help patients achieve their glycemic target and overcome perceived barriers of GLP-1 receptor agonist use, with the overall goal of improving PCP confidence in prescribing these agents.

Long-term Outcomes Among Young Adults With Type 2 Diabetes Based on Durability of Glycemic Control: Results From the TODAY Cohort Study

OBJECTIVE

To examine the effect of different patterns of durable glycemic control on the development of comorbidities among youth with type 2 diabetes (T2D) and to assess the impact of fasting glucose (FG) variability on the clinical course of T2D.

RESEARCH DESIGN AND METHODS

From the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) study, 457 participants (mean age, 14 years) with mean diabetes duration <2 years at entry and a minimum study follow-up of 10 years were included in these analyses. HbA1c, FG concentrations, and β-cell function estimates from oral glucose tolerance tests were measured longitudinally. Prevalence of comorbidities by glycemic control status after 10 years in the TODAY study was assessed.

RESULTS

Higher baseline HbA1c concentration, lower β-cell function, and maternal history of diabetes were strongly associated with loss of glycemic control in youth with T2D. Higher cumulative HbA1c concentration over 4 years and greater FG variability over a year within 3 years of diagnosis were related to higher prevalence of dyslipidemia, nephropathy, and retinopathy progression over the subsequent 10 years. A coefficient of variability in FG ≥8.3% predicted future loss of glycemic control and development of comorbidities.

CONCLUSIONS

Higher baseline HbA1c concentration and FG variability during year 1 accurately predicted youth with T2D who will experience metabolic decompensation and comorbidities. These values may be useful tools for clinicians when considering early intensification of therapy.

Joint effect of blood pressure and glycemic variation on the risk of cardiovascular morbidity and mortality in persons with type 2 diabetes

OBJECTIVE

Few studies have explored the association of visit-to-visit variation in blood pressure (BP) and glycemic factors with cardiovascular disease (CVD) morbidity and mortality. This study aimed to examine the independent and joint effect of visit-to-visit BP and glycemic variation on CVD morbidity and mortality in persons with T2DM.

METHODS

The present study consisted of two retrospective cohort studies. The Taiwan Diabetes Study was based on a database of the National Diabetes Care Management Program (DCMP) and linked with cardiovascular morbidity incidence. The Taichung Diabetes Study was based on the DCMP database of a medical center, which can be linked with the National Death Registry dataset. The outcomes were analyzed by using Cox's proportional hazard models.

RESULTS

A total of 13,280 and 10,894 persons with T2DM in Taiwan and Taichung Diabetes Study, respectively, were included. SBP-CV, FPG-CV, and HbA1c-CV were significant predictors of stroke, CVD event or death, all-cause mortality, and expanded CVD mortality, whereas DBP-CV was a significant predictor of all-cause mortality and expanded and non-expanded CVD mortality. The joint effect of SBP, FPG, and HbA1c predicted the incidence of stroke and CVD event or death with increased risks of 16 %-35 %. In addition, the joint effect of SBP, DBP, FPG, and HbA1c was associated with all-cause and expanded CVD mortality with increased risks of 29 %-81 %.

CONCLUSIONS

The joint effect of BP and glucose variation improved the prediction of cardiovascular morbidity and mortality. Moreover, simultaneous measurement of visit-to-visit BP and glycemic variation may stratify persons with cardiovascular risks and may be regarded as important therapeutic goals in the care of T2DM.

Changes in HbA1c and weight in people with Type 2 Diabetes after continuous glucose monitoring based Diabefly-Pro digital therapeutics program: Analysis of real-world data (Preprint)

BACKGROUND

Digital therapeutic platforms facilitate health care through patient-centered strategies based on multidisciplinary teams and shared decision-making. Such platforms can be used for developing a dynamic model of diabetes care delivery, which can help in improving glycemic control by promoting long-term behavior changes in people with diabetes.

OBJECTIVE

This study aims to evaluate the real-world effectiveness of the Fitterfly Diabetes CGM digital therapeutics program for improving glycemic control in people with type 2 diabetes mellitus (T2DM) after the completion of 90 days in the program.

METHODS

We analyzed deidentified data of 109 participants in the Fitterfly Diabetes CGM program. This program was delivered through the Fitterfly mobile app coupled with continuous glucose monitoring (CGM) technology. This program consists of 3 phases: the first phase is observation, wherein the patient's CGM readings are observed for 7 days (week 1); the second phase is the intervention; and the third phase aims at sustaining the lifestyle modification introduced during the second phase. The primary outcome of our study was the change in the participants' hemoglobin A_1c (HbA_1c) levels after program completion. We also evaluated the changes in participant weight and BMI after the program, changes in the CGM metrics in the initial 2 weeks of the program, and the effects of participant engagement in the program on improving their clinical outcomes.

RESULTS

At the end of the 90 days of the program, the mean HbA_1c levels, weight, and BMI of the participants were significantly reduced by 1.2% (SD 1.6%), 2.05 (SD 2.84) kg, and 0.74 (SD 1.02) kg/m² from baseline values of 8.4% (SD 1.7%), 74.45 (SD 14.96) kg, and 27.44 (SD 4.69) kg/m² in week 1, respectively (P<.001). The average blood glucose levels and time above range values showed a significant mean reduction by 16.44 (SD 32.05) mg/dL and 8.7% (SD 17.1%) in week 2 from week 1 baseline values of 152.90 (SD 51.63) mg/dL and 36.7% (SD 28.4%), respectively (P<.001 for both). Time in range values significantly improved by 7.1% (SD 16.7%) from a baseline value of 57.5% (SD 25%) in week 1 (P<.001). Of all the participants, 46.9% (50/109) showed HbA_1c reduction ≥1% and 38.5% (42/109) showed weight loss ≥4%. The average number of times the mobile app was opened by each participant during the program was 108.80 (SD 127.91) times.

CONCLUSIONS

Our study shows that participants in the Fitterfly Diabetes CGM program showed a significant improvement in their glycemic control and reduction in weight and BMI. They also showed a high level of engagement with the program. Weight reduction was significantly associated with higher participant engagement with the program. Thus, this digital therapeutic program can be considered as an effective tool for improving glycemic control in people with T2DM.

Age and sex-specific associations of visit-to-visit variability of glycated hemoglobin A1c with all-cause mortality in patients with diabetes

BACKGROUND

Visit-to-visit variability (VVV) of glycated hemoglobin (HbA1c) levels have been found to be associated with prognosis of diabetes. However, little is known about whether or to what extent sex and age may modify the effects of VVV.

METHODS

To investigate age- and sex-specific rates of mortality from all causes and relative hazards of mortality in association with VVV of HbA1c levels, 47,145 patients with diabetes and prescription of any antidiabetic agents >6 months were identified from outpatient visits of a tertiary medical center in northern Taiwan during 2003-2018. VVV of HbA1c was measured by quartiles of standard deviation (SD), coefficient of variation (CV), and average real variability (ARV), respectively. The study subjects were linked to Taiwan's National Death Registry to identify all-cause mortality. The person-year approach with the Poisson assumption was used to assess the all-cause mortality rates, and Cox proportional hazard regression model was used to evaluate the relative hazards of all-cause mortality concerning various levels of VVV of HbA1c.

RESULTS

The lowest all-cause mortality rate was found in either the first or second quartile of various measures for VVV of HbA1c, but the highest mortality rate was consistently observed in the fourth quartile of VVV, regardless of SD, CV, or ARV across ages and sexes. Increased hazards of overall all-cause mortality were noticed from the second to fourth quartile of VVV of HbA1c. In detailed age- and sex-stratified analyses, elevated risk of mortality was seen in the fourth quartile of those aged <50 years while in those aged >69 years, increased risk of mortality was noticed in the third and fourth quartiles of any VVV of HbA1c irrespective of sex. In those aged 50-69 years, incremental increased hazards of mortality were consistently observed in the second to fourth quartiles of VVV of HbA1c.

CONCLUSION

HbA1c variability whether it was SD, CV, or ARV could strongly predict the risks of all-cause mortality. The extent of the relationship between VVV of HbA1c and all-cause mortality in different age groups was comparable between both sexes. Given the importance of long-term glucose fluctuation, the inclusion of HbA1c variability calculated from the standardized method should be considered by clinical guideline policymakers as part of the biochemical panel in daily diabetes management.

Glycemic variability and all-cause mortality in a large prospective southern European cohort of patients with differences in glycemic status

Background

Few studies have analyzed the relationship between glucose variability (GV) and adverse health outcomes in patients with differences in glycemic status. The present study tests the hypothesis that GV predicts all-cause mortality regardless of glycemic status after simple adjustment (age and sex) and full adjustment (age, sex, cardiovascular disease, hypertension, use of aspirin, statins, GLP-1 receptor agonists, SGLT-2 inhibitors and DPP-4 inhibitors, baseline FPG and average HbA1c).

Methods

Prospective cohort study with 795 normoglycemic patients, 233 patients with prediabetes, and 4,102 patients with type 2 diabetes. GV was measured using the coefficient of variation of fasting plasma glucose (CV-FPG) over 12 years of follow-up. The outcome measure was all-cause mortality.

Results

A total of 1,223 patients (657 men, 566 women) died after a median of 9.8 years of follow-up, with an all-cause mortality rate of 23.35/1,000 person-years. In prediabetes or T2DM patients, the fourth quartile of CV-FPG exerted a significant effect on all-cause mortality after simple and full adjustment. A sensitivity analysis excluding participants who died during the first year of follow-up revealed the following results for the highest quartile in the fully adjusted model: overall, HR (95%CI) = 1.54 (1.26–1.89); dysglycemia (prediabetes and T2DM), HR = 1.41 (1.15–1.73); T2DM, HR = 1.36 (1.10–1.67).

Conclusion

We found CV-FPG to be useful for measurement of GV. It could also be used for the prognostic stratification of patients with dysglycemia.

Early and ongoing stable glycaemic control is associated with a reduction in major adverse cardiovascular events in people with type 2 diabetes: A primary care cohort study

AIM

To determine whether achieving early glycaemic control, and any subsequent glycaemic variability, was associated with any change in the risk of major adverse cardiovascular events (MACE).

MATERIALS AND METHODS

A retrospective cohort analysis from the Oxford-Royal College of General Practitioners Research and Surveillance Centre database-a large, English primary care network-was conducted. We followed newly diagnosed patients with type 2 diabetes, on or after 1 January 2005, aged 25 years or older at diagnosis, with HbA1c measurements at both diagnosis and after 1 year, plus five or more measurements of HbA1c thereafter. Three glycaemic bands were created: groups A (HbA1c < 58 mmol/mol [<7.5%]), B (HbA1c ≥ 58 to 75 mmol/mol [7.5%-9.0%]) and C (HbA1c ≥ 75 mmol/mol [≥9.0%]). Movement between bands was determined from diagnosis to 1 year. Additionally, for data after the first 12 months, a glycaemic variability score was calculated from the number of successive HbA1c readings differing by 0.5% or higher (≥5.5 mmol/mol). Risk of MACE from 1 year postdiagnosis was assessed using time-varying Cox proportional hazards models, which included the first-year transition and the glycaemic variability score.

RESULTS

From 26 180 patients, there were 2300 MACE. Compared with group A->A transition over 1 year, those with C->A transition had a reduced risk of MACE (HR 0.75; 95% CI 0.60-0.94; P = .014), whereas group C->C had HR 1.21 (0.81-1.81; P = .34). Compared with the lowest glycaemic variability score, the greatest variability increased the risk of MACE (HR 1.51; 1.11-2.06; P = .0096).

CONCLUSION

Early control of HbA1c improved cardiovascular outcomes in type 2 diabetes, although subsequent glycaemic variability had a negative effect on an individual's risk.

Associations of Moderate Low-Carbohydrate Diets With Mortality Among Patients With Type 2 Diabetes: A Prospective Cohort Study

CONTEXT

A statement of context for the abstract was added in Objective as follows: Lower-carbohydrate-diet (LCD) has been reported to have beneficial effects on cardiovascular risk factor profile in general population. However, whether adherence to an LCD could benefit long-term survival among individuals with diabetes is unclear.

OBJECTIVE

This work aimed to investigate the associations of different types of lower-carbohydrate diets with mortality among individuals with type 2 diabetes (T2D).

METHODS

This prospective study included 5677 patients with T2D. The overall, unhealthy, and healthy lower-carbohydrate-diet (LCD) scores were calculated based on the percentage of energy from total and subtypes of carbohydrate, protein, and fat. Deaths were determined via linkage to the National Death Index records until December 31, 2015. Cox proportional hazards models were used to estimate the hazard ratios (HRs) and 95% CIs of mortality.

RESULTS

During a median of 6.3 years of follow-up (39 401 person-years), 1432 deaths were documented. After multivariable adjustment including lifestyle factors, diabetes duration, and glycated hemoglobin A1c, patients in the third quartile of overall LCD score had the lowest risk of mortality (HR: 0.65; 95% CI, 0.50-0.85), compared with the first quartile. The multivariable-adjusted HRs (95% CIs) of mortality across quartiles of healthy lower-carbohydrate-diet score were 1.00 (reference), 0.78 (0.64-0.96), 0.73 (0.58-0.91), and 0.74 (0.58-0.95) (Ptrend = .01). Isocalorically replacing 2% of energy from carbohydrates with plant-based protein or polyunsaturated fatty acids was associated with 23% to approximately 37% lower total mortality. Similar results were observed when analyses were stratified by age, sex, race/ethnicity, smoking status, body mass index, physical activity, and diabetes duration.

CONCLUSION

Healthy LCD score was significantly associated with a lower risk of mortality in adults with T2D. Adherence to a well-balanced moderate lower-carbohydrate diet that emphasizes healthy carbohydrates, plant-based protein, and polyunsaturated fat may prevent premature death among patients with T2D.

Masticatory dysfunction in patients with diabetic neuropathy: A cross-sectional study

Introduction

Chewing well is essential for successful diet therapy and control of blood glucose level in patients with diabetes. In addition, long-term hyperglycemia is a risk factor for microvascular complications, which are the main cause of morbidity and mortality in these patients. Hence, it is plausible that masticatory disorder may be relevant to diabetic microvascular complications which is caused by long-term hyperglycemia. The aim of this study was to investigate whether masticatory disorders are relevant to diabetic microvascular complications.

Methods

This cross-sectional study included 172 patients with type 2 diabetes who underwent educational hospitalization in the Department of Endocrinology and Diabetic Medicine, Hiroshima University Hospital, from April 2016 to March 2020. Masticatory efficiency was determined quantitatively by using the GLUCO SENSOR GS-Ⅱ. Multivariable linear regression models were constructed to examine which factors were related to masticatory efficiency. Statistical significance was defined as a two-sided p value of < 0.05.

Results

According to the bivariable analysis, masticatory efficiency was significantly correlated with duration of diabetes (p = 0. 049), number of remaining teeth (p < 0.0001), the number of moving teeth (p = 0.007) and condition of diabetic neuropathy (p < 0.0001). Moreover, the number of remaining teeth (p < 0.0001) and diabetic neuropathy (p = 0.007) remained significantly correlated with masticatory efficiency in the multivariable analysis.

Conclusions

For the first time, we demonstrated that patients with type 2 diabetes who developed diabetic neuropathy had significantly reduced masticatory efficiency. Effective mastication is an important factor in successful diet therapy for diabetes. To prevent the progression of diabetic complications, especially in patients with diabetic neuropathy, it may be necessary to combine individualized therapies from dentists and nutritionists with consideration for the level of masticatory dysfunction.