Standard Deviation HbA1c Research Articles

The association of glycaemic risk factors and diabetes duration with risk of heart failure in people with type 2 diabetes: A systematic review and meta-analysis.

To conduct a systematic review in order to better understand the association of glycaemic risk factors and diabetes duration with risk of heart failure (HF) in individuals with type 2 diabetes (T2D). We identified longitudinal studies investigating the association of glycaemic factors (glycated haemoglobin [HbA1c], HbA1c variability, and hypoglycaemia) and diabetes duration with HF in individuals with T2D. Hazard ratios and odds ratios were extracted and meta-analysed using a random-effects model where appropriate. Risk of bias assessment was carried out using a modified Newcastle-Ottawa Scale. Egger's test along with the trim-and-fill method were used to assess and account for publication bias. Forty studies representing 4 102 589 people met the inclusion criteria. The risk of developing HF significantly increased by 15% for each percentage point increase in HbA1c, by 2% for each additional year of diabetes duration, and by 43% for having a history of severe hypoglycaemia. Additionally, variability in HbA1c levels was associated with a 20%-26% increased risk of HF for each unit increase in the metrics of variability (HbA1c standard deviation, coefficient of variation, and average successive variability). All included studies scored high in the risk of bias assessment. Egger's test suggested publication bias, with trim-and-fill analyses revealing a significant 14% increased risk of HF per percentage point increase in HbA1c. Glycaemic risk factors and diabetes duration significantly contribute to the heightened risk of HF among individuals with T2D. A reduction in risk of HF is anticipated with better management of glycaemic risk factors.

HbA1c variability associated with dementia risk in people with type 2 diabetes.

Although poor glycemic control is associated with dementia, it is unknown if variability in glycemic control, even in those with optimal glycosylated hemoglobin A1c (HbA1c) levels, increases dementia risk. Among 171,964 people with type 2 diabetes, we evaluated the hazard of dementia association with long-term HbA1c variability using five operationalizations, including standard deviation (SD), adjusting for demographics and comorbidities. The mean baseline age was 61 years (48% women). Greater HbA1c SD was associated with greater dementia hazard (adjusted hazard ratio=1.15 [95% confidence interval: 1.12, 1.17]). In stratified analyses, higher HbA1c SD quintiles were associated with greater dementia hazard among those with a mean HbA1c<6% (P=0.0004) or 6% to 8% (P<0.0001) but not among those with mean HbA1c ≥ 8% (P=0.42). Greater HbA1c variability is associated with greater dementia risk, even among those with HbA1c concentrations at ideal clinical targets. These findings add to the importance and clinical impact of recommendations to minimize glycemic variability. We observed a cohort of 171,964 people with type 2 diabetes (mean age 61 years). This cohort was based in Northern California between 1996 and 2018. We examined the association between glycosylated hemoglobin A1c (HbA1c) variability and dementia risk. Greater HbA1c variability was associated with greater dementia hazard. This was most evident among those with normal-low mean HbA1c concentrations.

Associations Between HbA1c and Glucose Time in Range Using Continuous Glucose Monitoring in Type 1 Diabetes: Cross-Sectional Population-Based Study.

Continuous glucose monitoring (CGM) introduces novel indicators of glycemic control. This cross-sectional study, based on the Swedish National Diabetes Register, examines 27,980 adults with type 1 diabetes. It explores the relationships between HbA1c (glycated hemoglobin) and various CGM-derived metrics, including TIR (time in range, representing the percentage of time within the range of 4-10mmol/l for 2weeks), TAR (time above range), TBR (time below range), mean glucose, standard deviation (SD), and coefficient of variation (CV). Pearson correlation coefficients and linear regression models were utilized for estimation. The analysis included 46% women, 30% on insulin pump, 7% with previous coronary heart disease and 64% with retinopathy. Mean ± SD values were age 48 ± 18years, diabetes duration 25 ± 16years, HbA1c 58.8 ± 12.8mmol/mol, TIR 58.8 ± 19.0%, TAR 36.3 ± 20.0%, TBR 4.7 ± 5.4%, mean sensor glucose 9.2 ± 2.0mmol/l, SD 3.3 ± 1.0mmol/l, and CV 36 ± 7%. The overall association between HbA1c and TIR was -0.71 (Pearson's r), with R2 0.51 in crude linear regression and 0.57 in an adjusted model. R2values between HbA1c and CGM mean glucose were 0.605 (unadjusted) 0.619 (adjusted) and TAR (unadjusted 0.554 and fully adjusted 0.568, respectively), while fully adjusted R2values were 0.458, 0.175 and 0.101 between HbA1c and CGM SD, CGM CV and TBR, respectively. This descriptive study demonstrates that the degree of association between HbA1c and new and readily available CGM-derived metrics, i.e., time in range (TIR), time above range (TAR), and CGM mean glucose, is robust in assessing the management of individuals with type 1 diabetes in clinical settings. Metrics from CGM that pertain to variability and hypoglycemia exhibit only weak correlations with HbA1c.

Glycemic variability and dementia risk in a diverse cohort of older adults with type 2 diabetes

AbstractBackgroundType 2 diabetes is associated with a two‐fold increase in dementia risk. Although glycemic variability is becoming increasingly recognised as contributing to end‐organ damage, less is known about its contribution to dementia risk. We aimed to study the association between HbA1c variability and dementia risk in a large, diverse sample of people in Northern California.MethodOver 209,000 members of a fully integrated health care delivery system with type 2 diabetes aged ≥ 50 years were followed from 1996 to 2018 to obtain repeated measures of HbA1c, dementia diagnoses, and comorbidities. Variability was measured using standard deviation (SD), coefficient of variation, and average real variability. Cox proportional hazards models estimated the association between HbA1c variability in the first 3 years of cohort entry and incident dementia at least 2 years after the end of the exposure period adjusting for age (as timescale) and baseline health conditions.ResultThere were a total of 209,703 people in the cohort (mean baseline age 61.0 years (SD = 9.2), 47.5% women) (Table1). Approximately 49.6% of the sample were non‐Latino White. The mean number of HbA1c values available for each participant was 5.8 (SD = 2.3). The mean HbA1c for each participant in the first 3 years was 7.4% (SD = 1.33). Greater HbA1c variability was associated with greater hazard of dementia when measured using SD (aHR = 1.12 [95%CI: 1.10, 1.14]), coefficient of variation (aHR = 2.17 [95%CI: 1.85, 2.55]) (Figure1), or average real variability (aHR = 1.06 [95%CI: 1.06, 1.07]). When stratified by mean HbA1c, we found that ‐ relative to the lowest quintile of variation ‐ increasing variability of SD of HbA1c was associated with greater hazard of dementia in HbA1c categories of &lt;6% (p = 0.0004) and 6 ‐8% (p&lt;0.0001) but not in those with a mean HbA1c ≥8% (p = 0.42).ConclusionGreater HbA1c variability is associated with greater dementia hazard in those with good glycemic control. The absence of association in less well controlled (HbA1c ≥8%) patients may stem from greater variability including lower risk periods of optimal glycemic control. These results support current clinical recommendations to minimize glycemic variability and extend known benefits to include lowering of dementia risk.

Correlates of disordered eating and insulin restriction behavior and its association with psychological health in Taiwanese youths with diabetes mellitus

BackgroundAdolescents and young adults (AYAs) with diabetes mellitus (DM) are prone to eating disorders that may worsen metabolic control. This study investigated the clinical and behavioral correlates of disordered eating and insulin restriction (DE/IR) behavior and its association with psychological health among AYAs with DM.MethodsWe enrolled patients with DM aged 10–30 years receiving insulin treatment in a tertiary medical center from 2019 to 2021. After obtaining informed consent, we assessed various visit-to-visit HbA1c measures indicating glycemic control, DE/IR behavior using the modified SCOFF questionnaire, weight-control practices (e.g., self-medication, induced vomiting, and over-exercising), and anxious and depressive symptoms using the Hospital Anxiety and Depression Scale. Correlation and hierarchical regression analyses were applied to understand the clinical and behavioral correlates of DE/IR behavior and its association with anxiety and depression.ResultsAmong the 110 patients with type 1 and type 2 DM recruited, we found 17.6% restricting insulin use and 6.3% self-medicating for weight control (higher in type 2 DM than type 1 DM). Hierarchical regression analyses showed HbA1c standard deviation (odds ratio = 2.18, [95% confidence interval 1.07–4.42]), body image (1.83, [1.05–3.20]), and dieting (4.74, [1.70–13.23]) associated with DE/IR behavior. Moreover, DE/IR behavior was further associated with anxiety (1.17 [1.08–1.27]) and depression (1.12 [1.03–1.22]).ConclusionDE/IR behavior is not uncommon among AYAs with DM, particularly those with type 2 DM, and may be associated with anxiety and depressive symptoms. In addition, HbA1c variability is correlated with DE/IR behavior, and the clinical implications need further exploration.

Association of sleep quality and glycemic control in type 2 diabetes mellitus

Abstract Background: Sleep is a modifiable risk factor for many chronic diseases, including type 2 diabetes mellitus. Poor quality of sleep leads to poor management of diabetes, adversely affecting sleep. The vicious cycle can be curtailed by good quality of sleep. Our study observed the association of glycemic control (glycosylated hemoglobin [HbA1C]) with sleep quality. Materials and Methods: A cross-sectional, observational study was conducted in the Diabetic Clinic of MGM Hospital, Kamothe, Navi Mumbai, India. Type 2 diabetes patients in the age group of 30–60 years were assessed for sleep quality using the Pittsburgh Sleep Quality Index questionnaire, and their HbA1C was measured by high-performance liquid chromatography. Results: A total of 101 type 2 diabetes patients aged 30–60 were assessed. A total of 25% were good sleepers, and 75% were poor sleepers. The mean ± standard deviation of HbA1C in good sleepers was 7.14 ± 1.30, and in poor sleepers was 8.9 ± 2.44. The correlation between sleep quality and glycemic control gave an r value of 0.36, and the P value was 0.002, which shows a highly significant correlation between poor sleep and glycemic control. Conclusion: The study shows poor sleep quality leads to poor glycemic control in type 2 diabetic patients with higher HbA1c levels. Creating awareness among diabetic patients about the good quality and duration of sleep for better management of diabetes is essential.

HbA1c variability is associated with adverse outcomes in heart failure patients with and without diabetes

Abstract Funding Acknowledgements Type of funding sources: None. Background Glycemic control is an important clinical issue in the management of patients with heart failure (HF). Variability of Glycated hemoglobin A1c (HbA1c) has been proven to be a predictor of cardiovascular events. However, previous studies mainly focused on general population and patients with coronary artery disease, while less is known about the effect of long-term HbA1c variability on clinical outcomes in HF patients. Purpose To evaluate the association of HbA1c variability and the risk of all-cause mortality and rehospitalization in patients with HF irrespective of their diabetic status. Methods By using the data from the well-validated Clinical Data Analysis Reporting System (CDARS), HF patients from 2003-2020 who had more than 3 times HbA1c measurements after the diagnosis of HF were included (N=65950, mean age was 66.5±12.0 years and 39409 (52.9%) were male). Average successive variability (ASV) ( average absolute difference between successive values), standard deviation (SD) of HbA1c were calculated. Hazard ratio (HR) of all-cause mortality and HF rehospitalization were estimated using competing risk regression with Cox proportional-hazard model. Results During a median follow-up of 7.2 years, 52446 (79.5%) patients developed HF rehospitalization and 34508 (52.3%) died. After adjusting for confounders, each unit change of HbA1c ASV or SD was significantly associated with higher risk of all-cause mortality, as well as higher risk of HF-rehospitalization (Figure 1). Among the study population, 48673 (73.8%) was diabetic while the remaining 17277 (26.2%) were non-diabetic. Interestingly, HbA1c variability had a stronger impact to non-diabetic compared to diabetic patients (P for interaction &amp;lt;0.001) in predicting all-cause mortality and HF rehospitalization (Table 1). Conclusion In patients with HF, a greater HbA1c variability was associated with an increased risk of HF rehospitalization and all-cause mortality. Such effect was stronger in non-diabetic compared with diabetic. HbA1c variability, irrespective of baseline diabetic status, should be evaluated in HF patients for better risk-stratification.

Effects of initiating insulin pump therapy in the real world: A nationwide, register-based study of adults with type 1 diabetes

AimsWe aimed to estimate effects of insulin pump therapy (IPT) on HbA1c level, HbA1c variability, and risk of hospitalised diabetic ketoacidosis (DKA) and severe hypoglycaemia (SH), compared with multiple daily insulin injections (MDI). MethodsWe identified a cohort of all adults with type 1 diabetes in Denmark using national registry data and assigned each individual to either IPT (treatment) or MDI (control) from 2010 to 2020. We estimated average treatment effects on the treated (ATT) and treatment effects among population subgroups using treatment-staggered difference-in-differences. ResultsThe cohort consisted of 26,687 individuals with a collective 243,601 person-years of observation; 38,823 (16 %) were IPT person-years. We identified an ATT for HbA1c of −0.33 % (95 % CI −0.39 to −0.27; −3.6 mmol/mol [95 % CI −4.2 to −2.9]). ATTs were larger among women and individuals who were older, had highest baseline HbA1c, and used continuous glucose monitoring. ATT for HbA1c variability (−0.016 % [−0.028 to −0.0041); −0.17 mmol/mol [95 % CI −0.30 to −0.045]) corresponded to a 6.5 % decrease in the standard deviation of HbA1c. ATTs for DKA and SH corresponded to 0.52 additional and 0.11 fewer hospitalisations per 1,000 person-years, respectively. ConclusionsIPT significantly reduced HbA1c level and variability, compared with MDI. However, it also marginally increased the risk of hospitalised DKA.

PSUN200 Effect of carbohydrate counting education in children and adolescents with type I diabetes

Abstract Background The achievement and maintenance of normoglycemia is one of the most important goals to prevent both short and long-term complications in type 1 diabetes mellitus (T1DM). As carbohydrate acts as the primary macronutrient affecting postprandial glycemic response, carbohydrate counting is crucial in adjusting prandial insulin doses to preserve postprandial blood glucose within normal limits. The purpose of this study is to evaluate the effect of carbohydrate counting education in children and adolescents with T1DM. Method: A retrospective chart review of 128 diagnosed T1DM patients who underwent carbohydrate counting education was conducted. All subjects were diagnosed with T1DM before December 2019, and were educated carbohydrate counting before December 2020 in pediatric endocrinology, Severance Children's Hospital, Seoul, Korea. We analyzed the data including clinical characteristics, education on carbohydrate counting, and glycated hemoglobin A1c (HbA1c) levels. Results In 128 T1DM subjects educated, 48 (38%) were male. Their mean age at diagnosis was 8.6 ± 4.0 (years) and mean age at the time of education was 22.6 ± 7.8 (years). Overall, HbA1c levels at 3, 6, and 12 months after education showed a significant decrease compared to the baseline. The mean ±SD(standard deviation) HbA1c level, which was 8.8 ±1.9 (%) at the baseline, decreased to 8.3 ±1.7 at 3 months, 8.3 ±1.7 at 6 months, and 8.3 ±1.7 at 12 months after education. In multivariate linear regression analyses, only the value of baseline HbA1c (P&amp;lt;0.001) as an indicator of DM management was significantly correlated with decrease in HbA1c. Conclusions In our study, carbohydrate counting education seems effective in glycemic control in patients with type 1 diabetes mellitus, but the decrease in HbA1c seems not enough. The effect of education differs according to the degree of glycemic management. For patients with poor management, providing proper education of carbohydrate counting can make improvement in glycemic control. For well-managed patients, more advanced approach beyond traditional education appears to be required. With proper education, better blood glucose control can be expected to reduce complications and improve quality of life in T1DM patients. Presentation: Sunday, June 12, 2022 12:30 p.m. - 2:30 p.m.

Mean HbA1c and HbA1c variability are associated with differing diabetes-related complications in patients with type 2 diabetes mellitus

AimsTo study the different effects of mean HbA1c and HbA1c variability on diabetes-related complications in patients with type 2 diabetes mellitus. Methods1869 patients with type 2 diabetes were followed-up for a median of 9.5 years in a Diabetes Shared Care Program. Mean HbA1c (HbA1c-mean) and standard deviation of HbA1c (HbA1c-SD) were calculated during the first 5 years. The clinical outcomes included nephropathy (urine albumin-to-creatinine ratio [UACR] > 300 mg/g and doubling of serum creatinine), retinopathy (any and advanced), and mortality (due to all-causes, and cardiovascular disease [CVD]). ResultsHbA1c-mean was independently associated with UACR > 300 mg/g (Hazard ratio [HR] 1.308 [95% confidence interval {CI}, 1.194–1.433]), any retinopathy (HR 1.274 [1.171–1.385]), and advanced retinopathy (HR 1.237 [1.014–1.509]). HbA1c-SD was independently associated with UACR > 300 mg/g (HR 1.478 [1.189–1.837]), doubling of serum creatinine (HR 2.133 [1.470–3.095]), all-cause mortality (HR 1.880 [1.561–2.266]), and CVD mortality (HR 1.431 [1.069–1.915]). Receiver operating characteristic (ROC) curves showed HbA1c-mean was more associated with any retinopathy, whereas HbA1c-SD was more associated with doubling of serum creatinine, all-cause and CVD mortality. ConclusionBoth HbA1c-mean and HbA1c-SD predicted most diabetes-related complications in patients with type 2 diabetes. However, HbA1c-mean was more effective at predicting retinopathy, while HbA1c-SD was more effective at predicting deterioration of renal function and increased mortality.

The Scope of HbA1c Variability and Risk of Vascular Complications Among Patients with Type 2 Diabetes: A Systematic Review and Meta-Analysis of Prospective Studies.

Glycated hemoglobin (HbA1c) variability is emerging as an indicator of long-term glycemic control, which may play a significant role during vascular complications. We conducted a systematic review and meta-analysis to assess the association between the scope of HbA1c variability and vascular complications in patients with type 2 diabetes mellitus. PubMed and Embase were searched for studies that evaluated the association of HbA1c variability with vascular complications in patients with type 2 diabetes. Two reviewers independently completed data extraction. Random-effects meta-analysis was conducted with stratification according to the type of vascular complications. Nine studies were eligible for inclusion in our systematic review and meta-analysis. Six studies evaluated the impact of the standard deviation of HbA1c (HbA1c-SD) on cardiovascular events and showed an association of HbA1c-SD with cardiovascular events (HR: 1.25, 95% CI 1.18-1.32, 5 studies). Six studies evaluated renal disease associated with HbA1c-SD and showed that HbA1c-SD was correlated with an increased risk of renal disease (HR: 1.19, 95% CI 1.13-1.24). Two studies evaluated HbA1c-SD and the risk of retinopathy and showed that no significant association was found between retinopathy and HbA1c-SD (HR 1.08, 95% CI 0.92-125). For HbA1c-SD ranging from 0.6 to 0.8%, HbA1c-SD was associated with an increased risk of cardiovascular events (HR: 1.25, 95% CI 1.15-1.35) and renal disease (HR: 1.16, 95% CI 1.11-1.22). For individuals with index HbA1c variability greater than or equal to 0.6%, HbA1c variability was significantly associated with vascular complications in patients with type 2 diabetes mellitus.

The Effect of HbA1c Variability as a Risk Measure for Microangiopathy in Type 1 Diabetes Mellitus.

Background: To measure the relationship between variability in HbA1c and microalbuminuria (MA) and diabetic retinopathy (DR) in the long term. Methods: A prospective case-series study, was conducted on 366 Type 1 Diabetes Mellitus patients with normoalbuminuria and without diabetic retinopathy at inclusion. The cohort was followed for a period of 12 years. The Cox survival analysis was used for the multivariate statistical study. The effect of variability in microangiopathy (retinopathy and nephropathy) was evaluated by calculating the standard deviation of HbA1c (SD-HbA1c), the coefficient of variation of HbA1c (CV-HbA1c), average real variability (ARV-HbA1c) and variability irrespective of the mean (VIM-HbA1c) adjusted for the other known variables. Results: A total of 106 patients developed diabetic retinopathy (29%) and 73 microalbuminuria (19.9%). Overt diabetic nephropathy, by our definition, affected only five patients (1.36%). Statistical results show that the current age, mean HbA1c, SD-HbA1c and ARV-HbA1c are significant in the development of diabetic retinopathy. Microalbuminuria was significant for current age, mean HbA1c, CV-HbA1c and ARV-HbA1c. Conclusions: By measuring the variability in HbA1c, we can use SD-HbA1c and ARV-HbA1c as possible targets for judging which patients are at risk of developing DR and MA, and CV-HbA1c as the target for severe DR.

Decreasing prevalence of retinopathy in childhood-onset type 1 diabetes over the last decade: A comparison of two cohorts diagnosed 10 years apart.

To ascertain whether the prevalence of retinopathy has declined over the last 2 decades in individuals with childhood-onset type 1 diabetes and whether this might be explained by changes in lifetime HbA1c. A multicentre, retrospective, observational study, comparing 128 subjects with diabetes onset in 2000-2003 assessed for retinopathy in 2016-2019, with a previous cohort of 115 individuals diagnosed in 1990-1993 and assessed for retinopathy in 2007-2009, was conducted. The two cohorts had both a similar diabetes duration and age at diagnosis. Retinal photographs were centrally graded. Lifetime HbA1c and its variability, estimated as the ratio between intrapersonal mean and standard deviation of HbA1c, were evaluated. The prevalence of any retinopathy in the new and old cohort was 24.2% and 43.5% (P < .003), respectively, and that of severe retinopathy was 1.7% and 9.6% (P=.018). Lifetime HbA1c was lower in the new cohort (7.8% ± 0.8% vs. 8.1% ± 0.8%; P=.002) during all periods following the first 5 years after diagnosis. Patients without retinopathy in the two cohorts had similar levels of HbA1c. Compared with patients without retinopathy, those with retinopathy had higher lifetime HbA1c and long-term HbA1c variability. However, on multiple regression analysis, only lifetime HbA1c was independently associated with retinopathy (P=.0018). The risk of developing retinopathy was nearly halved in children who developed type 1 diabetes in the new millennium compared with previous cohorts. These results confirm that maintaining the lowest possible levels of HbA1c throughout lifetime protects from diabetic retinopathy.

Relationship between glycemic intraday variations evaluated in continuous glucose monitoring and HbA1c variability in type 2 diabetes: pilot study

BackgroundHbA1c variability is independent of mean HbA1c, and associated with mortality due to vascular complications. However, the significance of HbA1c variability is unknown at present. In this study, we used flash glucose monitoring (FGM) and evaluated glycemic intraday variations, and then examined the association with HbA1c variability.MethodsWe conducted a retrospective pilot study of 26 patients treated at the Outpatient department for type 2 diabetes mellitus (T2DM), and evaluated the following items associated with blood glucose levels and their changes/variations using FGM. The primary endpoint was factor(s) associated with standard deviation (SD) HbA1c over a 6-month period. To adjust for the effect of varying numbers of HbA1c measurements, we used the adjusted SD of HbA1c.ResultsThere were significant correlations between mean HbA1c and each of glucose management indicator, maximum, percent time at glucose > 180 mg/day, mean of daily difference of blood glucose, and high blood glucose index. Adjusted SD HbA1c correlated significantly with percent time at glucose < 70 mg/dL and low blood glucose index. We estimated the regression coefficient of adjusted SD HbA1c using multivariate linear regression analysis, and noted that the presence of hypoglycemia affected Adjusted SD HbA1c (β = 0.130, SE = 0.044, P = 0.008). Hypoglycemia was noted in 17 patients, and adjusted SD HbA1c was significantly higher (p = 0.001) in the hypoglycemic group (0.22 ± 0.12%), compared with the non-hypoglycemic group (0.08 ± 0.05%). The cut-off value of adjusted SD HbA1c was 0.109% in the hypoglycemic group.ConclusionsThe results showed that HbA1c variability is associated with hypoglycemia. For patients with high HbA1c variability, we recommend evaluation for the presence of hypoglycemia and reconsideration of their treatment regimen including their glucose-lowering medications.Trial registrationThe study protocol and opt-out method of informed consent were approved by the ethics committees of the University of Occupational and Environmental Health (Trial registration: H27-186, Registered 25 Dec 2015)

Long-term safety and effectiveness of linagliptin as add-on therapy in Japanese patients with type 2 diabetes: final results of a 3-year post-marketing surveillance

ABSTRACT Background We investigated the long-term safety and effectiveness of linagliptin in Japanese type 2 diabetes (T2D) patients starting linagliptin add-on therapy in routine clinical practice. Research design and methods This 3-year prospective, observational, post-marketing surveillance (PMS) was conducted in Japanese patients starting linagliptin add-on therapy. The primary outcome was the incidence of adverse drug reactions (ADRs). The secondary outcome was the change from baseline in HbA1c. Results The safety analysis set comprised of 3,372 patients. Mean ± standard deviation (SD) age was 66.5 ± 12.4 years. Most patients (63.2%) received linagliptin in combination with another antidiabetic drug, most commonly a sulfonylurea (38.6%). The incidence of ADRs was 11.39%; the most common ADRs according to MedDRA preferred terms were diabetes mellitus (1.25%), hypertension (0.83%), and hypoglycemia (0.80%). In the effectiveness analysis set (n = 3,029), mean ± SD HbA1c was 7.76 ± 1.37% at baseline and 7.26 ± 1.19% at last observation; mean change from baseline to last observation was – 0.49 ± 1.33%; sustained reductions in HbA1c were observed. These results were consistent across patient subgroups. Conclusions In this PMS, linagliptin add-on therapy for Japanese T2D patients had a safety profile consistent with its known profile and HbA1c reductions over 3 years were observed. ClinicalTrials.gov NCT01904383

Glycated hemoglobin variability and microvascular complications in patients with type1 diabetes mellitus.

Glycated hemoglobin (HbA1c) has proven to be indicative in the development of microvascular complications. In this study, the contribution of HbA1c variability to microvascular complications was evaluated. Twenty-one cases with type 1 diabetes mellitus (T1DM) who developed microvascular complications and 39 cases without complications, that were similar in terms of gender, age of diagnosis, insulin treatment, insulin doses (U/kg), and mean HbA1c levels were included. Mean age of T1DM diagnosis was 5.87±3.93 years in the complication group and 4.63±3.33 years in the control group. Nephropathy was detected in 17 cases, neuropathy in 8 cases, and retinopathy in 1 case. Nephropathy occurred at a mean age of 11.52±4.12 years and neuropathy at 14.13±5.68 years. The mean HbA1c during follow-up was similar in the group with complications and the control group (8.60±0.63 vs. 8.84±1.32). Adjusted HbA1c-standard deviation (SD) and HbA1c-variation coefficient (CV) values were 1.30±0.65 and 14.36±6.23 in the group with complications (p=0.014), and 0.91±0.37 and 10.59±4.01 in the control group (p=0.013). In the Receiver Operating Characteristic (ROC)-analysis for microvascular complications, the limit value HbA1c-CV was 11.99 (sensitivity: 61.9%, specificity: 71.9%). This value for HbA1c-SD was 0.9699 (sensitivity: 71.43%, specificity: 66.67%). This study has shown that long-term fluctuations in HbA1c are associated with the development of microvascular complications in type 1 diabetes.

Association between alterations of corneal sub-basal nerve plexus analyzed with in vivo confocal microscopy and long-term glycemic variability.

The effect of long-term glycemic variability upon corneal sub-basal nerve plexus (CSNP) morphology analyzed by in vivo confocal microscopy (IVCM) has been poorly investigated in the setting of type 1 diabetes mellitus (T1DM). Our purpose was to analyze the association between morphometric parameters of CSNP and new markers of glycemic variability in a population of patients with T1DM. Forty patients with T1DM underwent: assessment of diabetic neuropathy (DN); analysis of subcutaneous advanced glycated end-products; IVCM scans of CSNP. The fully automated software ACCMetrics was employed to analyze IVCM images and calculate seven corneal nerve parameters. Data of diabetes duration, mean and standard deviation (SD) of either last-year and all-time glycated hemoglobin (HbA1C) were retrieved. Diabetes duration and all-time SD of HbA1C were independently associated with CNFD (R = -0.26, p = 0.01; R = -0.27, p = 0.047 respectively), CNFL (R = -0.12; p = 0.01; R = -0.17, p = 0.01 respectively) and CNFrD (R = -0.001, p = 0.009; R = -0.002, p = 0.007 respectively). The analysis of the association among IVCM parameters and specific subtypes of DN showed that altered cold sensitivity was independently associated with CNFD (B = -0.24, p = 0.01), CNFL (B = -0.46, p = 0.01) and CNFrD (B = -28.65, p = 0.03). All-time SD of HbA1C and disease duration were found to be independent predictors of damage to CSNP in patients with T1DM.

Association between visit-to-visit HbA1c variability and the risk of cardiovascular disease in patients with type 2 diabetes.

To investigate the association between visit-to-visit HbA1c variability and the risk of cardiovascular disease in patients with type 2 diabetes. We performed a retrospective cohort study of 29 260 patients with at least four HbA1c measurements obtained within 2 years of their first diagnosis of type 2 diabetes. Different HbA1c variability markers were calculated, including the standard deviation (SD), coefficient of variation (CV) and adjusted SD. Cox proportional hazards regression models were used to estimate the association of these HbA1c variability markers with incident cardiovascular disease. During a mean follow-up of 4.18 years, a total of 3746 incident cardiovascular disease cases were diagnosed. Multivariate-adjusted hazard ratios for cardiovascular disease across the first, second, third and fourth quartiles of HbA1c SD values were 1.00, 1.30 (95% confidence interval [CI] 1.18-1.42), 1.40 (95% CI 1.26-1.55) and 1.59 (95% CI 1.41-1.77) (P for trend <.001), respectively. When we utilized HbA1c CV and adjusted HbA1c SD values as exposures, similar positive associations were observed. HbA1c variability was also associated with the risk of first and recurrent severe hypoglycaemic events. A mediating effect of severe hypoglycaemia was observed between HbA1c variability and incident cardiovascular disease. Large visit-to-visit HbA1c variability is associated with an increased risk of cardiovascular disease in patients with type 2 diabetes. Severe hypoglycaemia may mediate the association between HbA1c variability and incident cardiovascular disease.

Comparison of Turbidimetric Inhibition Immunoassay, High-Performance Liquid Chromatography, and Capillary Electrophoresis Methods for Glycated Hemoglobin Determination.

The purpose of this study was to compare the performances of and evaluate the agreement among glycated hemoglobin values analyzed by using National Glycohemoglobin Standardization Program-certified and International Federation of Clinical Chemistry-standardized analyzers. Armed Forces Institute of Pathology, Department of Chemical Pathology from March 2019 to May 2019. Glycated hemoglobin (HbA1c) was measured in the blood specimens from 100 patients on an ADVIA 1800 by a turbidimetric inhibitory immunoassay (TINIA), Sebia instrument by electrophoresis, and Bio-Rad Variant II Turbo system by high-performance liquid chromatography (HPLC). Quantitative variables were calculated as the mean ± standard deviation (SD). Precision and method comparisons were carried out according to Clinical and Laboratory Standards Institute recommendations. The results obtained from each analyzer were compared by correlation analysis. Method comparison was done by linear regression and Bland-Altman plots using the SPSS software version 24. The mean ± SD HbA1c values from TINIA, electrophoresis, and HPLC were 7.188% ± 1.89%, 7.164% ± 1.866%, and 7.160% ± 1.85%, respectively. The between-run coefficients of variation for TINIA, electrophoresis, and HPLC were 0.64%, 0.61%, and 0.60%, respectively. All 3 showed good correlation (TINIA, R2 = .994, P = .00; electrophoresis, R2 = .992, P = 0.00; and HPLC, R2 = .994, P = 0.00). The good clinical agreements of HbA1c and strong correlations between analyzers indicate that these analyzers can be used interchangeably.

Effect of mean HbA1c on the association of HbA1c variability and all-cause mortality in patients with type 2 diabetes.

To evaluate the effect of mean HbA1c on the correlation between HbA1c variability and all-cause mortality, and the risks associated with different levels of HbA1c and glycaemic control status in patients with type 2 diabetes. Patients with type 2 diabetes and at least three HbA1c measurements within 12-24 months were included. HbA1c variability score, coefficient of variation (CV) and standard deviation (SD) were used to evaluate variability. A variability score of 50 was set as a cutoff to define low and high variability. A total of 4216 patients were included, of whom 1196 died during the observation period (11.1 ± 3.2 years). All-cause mortality increased with HbA1c variability score and the quartiles of HbA1c CV and SD. The strength of this association was attenuated after adjustment for mean HbA1c, and the risks associated with HbA1c variability and glycaemic control status were similar. The highest associated risk was observed with an HbA1c variability score of >50 and mean HbA1c of ≥7.5%. Mortality risk was significantly higher with a mean HbA1c of ≤6.0% and >8.5% and of ≤6.0% and >8.0% for low and high HbA1c variability, respectively. Mean HbA1c contributed to the correlation between HbA1c variability and all-cause mortality. The risks associated with HbA1c variability and glycaemic control status were similar. The relationship between mean HbA1c and mortality presented a J-shaped distribution for both low and high HbA1c variability.