Variability in Glycated Hemoglobin and Risk of Poor Outcomes Among People With Type 2 Diabetes in a Large Primary Care Cohort Study

Prevalence and determinants of poor glycemic control among diabetic chronic kidney disease patients on maintenance hemodialysis in Tanzania

BACKGROUND

Poor glycemic control in diabetic chronic kidney disease (CKD) patients on maintenance hemodialysis is of great challenge, resulting in increased risk of morbidity and mortality. This study aimed to determine the prevalence and determinants of poor glycemic control among diabetic CKD patients on maintenance hemodialysis.

METHODOLOGY

A cross-sectional study was conducted in 12 dialysis centers located in four regions of Tanzania from March to June 2023. The study population was diabetic CKD patients above 18 years on maintenance hemodialysis for three months or more. A consecutive sampling technique was used for patient recruitment, and a semi-structured questionnaire was used to collect data. The primary outcome was poor glycemic control were considered when glycated hemoglobin (HbA1c) levels were <  6% or > 8%. Statistical Package for Social Sciences (SPSS) version 23 was used for data analysis. Univariate and multivariable regression models were used to evaluate the determinants of poor glycemic control. A p-value < 0.05 was considered statistically significant.

RESULTS

Out of 233 enrolled patients, the overall prevalence of poor glycemic control was 55.4%, whereby 27.0% had HbA1c < 6% and 28.33% had HbA1c > 8%. A high risk of HbA1c > 8% was observed among patients who were on antidiabetic medication (2.16 (95% CI: 1.06-4.41) p =  0.035) and those attending dialysis sessions less than 3 times a week (1.59 (95% CI: 1.02-2.48) p =  0.040). The lower risk of HbA1c < 6% was observed in patients dialyzed using glucose-containing dialysates than those dialyzed with glucose-free dialysate (0.57 (95% CI 0.36-0.87) p =  0.020).

CONCLUSION

The high prevalence of poor glycemic control among diabetic CKD patients, as revealed by this study, has significant implications. Patients on antidiabetic medication and those with less than three dialysis sessions per week are at a high risk of HbA1c > 8%. Conversely, patients dialyzed using glucose-free dialysates are at a high risk of HbA1c < 6%. Glycemic control in diabetic chronic kidney disease (CKD) patients is a great challenge due to altered glucose homeostasis, gluconeogenesis, tubular glucose reabsorption and inaccuracy of glycemic regulation metrics [1]. Furthermore, changed renal pharmacokinetics of antihyperglycemic agents (AHA), uremic milieu, and dialysis therapy also contribute to this challenge [2]. Based on the severe risk of hyperglycemia and hypoglycemia in patients with diabetic end-stage renal disease (ESRD), glycemic control is of paramount importance.

Effects of the COVID-19 Lockdown on HbA1c Levels of Ethnic Minorities and Low-income Groups with Type 2 Diabetes in Israel

AIMS

To investigate the impact of low socioeconomic status (SES) and/or membership in ethnic minority has on HbA1c before and during the COVID-19 lockdown.

METHODS

A retrospective cohort study was conducted between March 2019 and March 2021, based on data from electronic medical records of 17,072 patients with type-2 diabetes, collected by Clalit (Israel's largest health maintenance organization). Low SES was compared to high and ethnic minorities (Arabs and ultra-Orthodox Jews) were compared to the general Israeli population of mostly Jewish, but not ultra-Orthodox, Israeli citizens. Quantile regressions were used to examine the impact of SES and ethnic minority membership on HbA1c levels in the 0.10, 0.25, 0.50, 0.75, 0.90 quantiles before and during the lockdown.

RESULTS

In the pre-lockdown period, patients with type-2 diabetes of low versus high SES, and Arabs versus the general population, had higher HbA1c. During the lockdown HbA1c levels of low versus high SES rose significantly in the 0.10 and 0.90 quantiles, and among Arabs HbA1c levels rose significantly across all quantiles, with a remarkable increment in the 0.90 quantile (from 0.316% in the pre-lockdown period to 0.730% in the lockdown period). Ultra-Orthodox Jewish diabetic patients had a marginally higher mean HbA1C level regardless of the period. Quantile regressions did not reveal a significant difference between the ultra-Orthodox Jewish and the general population.

CONCLUSION

The lockdown exacerbated disparities in glycemic control between low and high SES individuals and between Arab minority and the general population.

Association between variation in hemoglobin A1c levels and diabetes therapy-related quality of life in patients with diabetes

AIMS/INTRODUCTION

We aimed to investigate the association between glycemic variability and quality of life (QOL) in patients with diabetes, which has not been studied previously.

MATERIALS AND METHODS

Patients who were undergoing treatment at the Kyoto Prefectural University of Medicine Hospital and Kameoka City Hospital participated in the KAMOGAWA-DM study, and completed the diabetes therapy-related (DTR)-QOL questionnaire from January 2016 to July 2020 were included in this study. We used linear regression analyses to compare the association between DTR-QOL scores and glycemic variability.

RESULTS

We included a total of 635 patients in this analysis. The hemoglobin A1c (HbA1c) levels of these patients were measured at least four times during the 9-month period, before and after answering the questionnaire. Results showed that HbA1c variability, HbA1c mean and duration of diabetes were negatively associated with the total DTR-QOL score. Conversely, the body mass index and total DTR-QOL score were positively associated with HbA1c variability.

CONCLUSIONS

A small variation in HbA1c level was associated with higher total DTR-QOL scores and the scores for each factor. Reducing blood glucose variability is significant when we treat diabetes.

Prospective cohort studies underscore the association of abnormal glycemic measures with all-cause and cause-specific mortalities

The role of fasting plasma glucose (FPG), glycated hemoglobin (HbA1c), and triglyceride-glucose index (TyG index) in predicting all-cause and cause-specific mortalities remains elusive. This study included 384,420 adults from the Shanghai cohort and the UK Biobank (UKB) cohort. After multivariable adjustment in the Cox models, FPG ≥7.0 mmol/L or HbA1c ≥ 6.5% increased the risk of all-cause mortality, FPG ≥5.6 mmol/L or HbA1c ≥ 6.5% increased CVD-related mortality, and higher or lower TyG index increased all-cause and CVD-related mortalities in the Shanghai cohort; FPG ≥5.6 mmol/L, HbA1c ≥ 5.7%, TyG index <8.31 or ≥9.08 increased the risks of all-cause, CVD-related, and cancer-related mortalities in the UKB cohort. FPG or HbA1c increased the discrimination of the conventional risk model in predicting all-cause and CVD-related mortalities in both cohorts. Thus, increased levels of FPG and HbA1c and U-shaped TyG index increase the risks of all-cause especially CVD-related mortalities.

Management of Type 2 Diabetes Mellitus: Synopsis of the Department of Veterans Affairs and Department of Defense Clinical Practice Guideline

The US Department of Veterans Affairs (VA) and the US Department of Defense (DoD) approved a joint clinical practice guideline for the management of type 2 diabetes. This was the product of a multidisciplinary guideline development committee composed of clinicians from both the VA and the DoD and was overseen by the VA/DoD Evidence Based Practice Work Group. The development process conformed to the standards for trustworthy guidelines as established by the National Academy of Medicine. The guideline development committee developed 12 key questions to guide an evidence synthesis. An independent third party identified relevant randomized controlled trials and systematic reviews that were published from January 2016 through April 2022. This evidence synthesis served as the basis for drafting recommendations. Twenty-six recommendations were generated and rated by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) system. Two algorithms were developed to guide clinical decision-making. This synopsis summarizes key aspects of the VA/DoD Clinical Practice Guideline for diabetes in 5 areas: prediabetes, screening for co-occurring conditions, diabetes self-management education and support, glycemic treatment goals, and pharmacotherapy. The guideline is designed to help clinicians and patients make informed treatment decisions to optimize health outcomes and quality of life and to align with patient-centered goals of care.

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.

Glycemic variability assessed using continuous glucose monitoring in individuals without diabetes and associations with cardiometabolic risk markers: A systematic review and meta-analysis

BACKGROUND & AIMS

Continuous glucose monitoring (CGM) provides data on short-term glycemic variability (GV). GV is associated with adverse outcomes in individuals with diabetes. Whether GV is associated with cardiometabolic risk in individuals without diabetes is unclear. We systematically reviewed the literature to assess whether GV is associated with cardiometabolic risk markers or outcomes in individuals without diabetes.

METHODS

Searches were performed in PubMed/Medline, Embase and Cochrane from inception through April 2022. Two researchers were involved in study selection, data extraction and quality assessment. Studies evaluating GV using CGM for ≥24 h were included. Studies in populations with acute and/or critical illness were excluded. Both narrative synthesis and meta-analyzes were performed, depending on outcome.

RESULTS

Seventy-one studies were included; the majority were cross-sectional. Multiple measures of GV are higher in individuals with compared to without prediabetes and GV appears to be inversely associated with beta cell function. In contrast, GV is not clearly associated with insulin sensitivity, fatty liver disease, adiposity, blood lipids, blood pressure or oxidative stress. However, GV may be positively associated with the degree of atherosclerosis and cardiovascular events in individuals with coronary disease.

CONCLUSION

GV is elevated in prediabetes, potentially related to beta cell dysfunction, but less clearly associated with obesity or traditional risk factors. GV is associated with coronary atherosclerosis development and may predict cardiovascular events and type 2 diabetes. Prospective studies are warranted, investigating the predictive power of GV in relation to incident disease. GV may be an important risk measure also in individuals without diabetes.

A matched cohort study evaluating the risks of infections in people with type 1 diabetes and their associations with glycated haemoglobin

AIMS

People with type 1 diabetes (T1D) have raised infection rates compared to those without, but how these risks vary by age, sex and ethnicity, or by glycated haemoglobin (HbA1c), remain uncertain.

METHODS

33,829 patients with T1D in Clinical Practice Research Datalink on 01/01/2015 were age-sex-ethnicity matched to two non-diabetes patients. Infections were collated from primary care and linked hospitalisation records during 2015-2019, and incidence rate ratios (IRRs) were estimated versus non-diabetes. For 26,096 people with T1D, with ≥3 HbA1c measurements in 2012-2014, mean and coefficient of variation were estimated, and compared across percentiles.

RESULTS

People with T1D had increased risk for infections presenting in primary care (IRR = 1.81, 95%CI 1.77-1.85) and hospitalisations (IRR = 3.37, 3.21-3.53) compared to non-diabetes, slightly attenuated after further adjustment. Younger ages and non-White ethnicities had greater relative risks, potentially explained by higher HbA1c mean and variability amongst people with T1D within these sub-groups. Both mean HbA1c and greater variability were strongly associated with infection risks, but the greatest associations were at the highest mean levels (hospitalisations IRR = 4.09, 3.64-4.59) for >97 versus ≤53 mmol/mol.

CONCLUSIONS

Infections are a significant health burden in T1D. Improved glycaemic control may reduce infection risks, while prompter infection treatments may reduce hospital admissions.

Key indices of glycaemic variability for application in diabetes clinical practice

Near normal glycaemic control in diabetes consists to target daily glucose fluctuations and quarterly HbA1c oscillations in addition to overall glucose exposure. Consequently, the prerequisite is to define simple, and mathematically undisputable key metrics for the short- and long-term variability in glucose homeostasis. As the standard deviations (SD) of either glucose or HbA1c are dependent on their means, the coefficient of variation (CV = SD/mean) should be applied instead as it that avoids the correlation between the SD and mean values. A CV glucose of 36% is the most appropriate threshold between those with stable versus labile glucose homeostasis. However, when near normal mean glucose concentrations are achieved a lower CV threshold of <27 % is necessary for reducing the risk for hypoglycaemia to a minimal rate. For the long-term variability in glucose homeostasis, a CVHbA1c < 5 % seems to be a relevant recommendation for preventing adverse clinical outcomes.

Attachment in close relationships and glycemic outcomes in children with type 1 diabetes

BACKGROUND

Our aim was to determine whether child attachment to parents, parent attachment style, and morning cortisol levels were related to diabetes outcomes measured by average glycated hemoglobin (HbA1c), HbA1c variability over 4 years and time in range (TIR) in children with type 1 diabetes (T1D).

RESEARCH DESIGN AND METHODS

101 children with T1D and one of their parents were assessed at baseline for child attachment (Child Attachment Interview; CAI) and parent attachment (Relationship Structures Questionnaire; ECR-RS). Serum samples were collected for cortisol measurements before the interviews. HbA1c levels were measured during a 4-year follow-up period at regular 3-monthly visits, and data for TIR were exported from blood glucose measuring devices. Multivariate linear regression models were constructed to identify independent predictors of glycemic outcomes.

RESULTS

More girls than boys exhibited secure attachment to their mothers. The results of the regression models showed that securely attached girls (CAI) had higher average HbA1c than did insecurely attached girls (B = -0.64, p = 0.03). In boys, the more insecure the parent's attachment style, the worse the child's glycemic outcome: the higher the average Hb1Ac (B = 0.51, p = 0.005), the higher the HbA1c variability (B = 0.017, p = 0.011), and the lower the TIR (B = -8.543, p = 0.002).

CONCLUSIONS

Attachment in close relationships is associated with glycemic outcomes in children with T1D, and we observed significant differences between sexes. A sex- and attachment-specific approach is recommended when treating children with less favorable glycemic outcomes. Special attention and tailored support should be offered to securely attached girls in transferring responsibility for diabetes care and at least to male children of insecurely attached parents to prevent suboptimal glycemic control. Further studies in larger samples and more daily cortisol measurements may help us better understand the links between stress response, attachment and T1D.

Reducing Hemoglobin A1C Levels in Type II Diabetes: A Retrospective Analysis of the Renew Procedure

INTRODUCTION

Periodontal disease and type 2 diabetes are interrelated, with inflammation playing a significant role in the progression of both conditions. Previous research has demonstrated the potential of various treatments, such as diet, exercise, and periodontal therapies, to improve glycemic control in diabetic patients.

METHOD

This study proposed a novel surgical approach, the Renew Procedure, as a potential solution to enhance glycemic control in type 2 diabetic patients with periodontal issues. The procedure involves the removal of all teeth, the elimination of oral and maxillofacial infections, the placement of dental implants, and the provision of implant-supported and implant-retained removable dentures.

RESULTS

Preliminary findings indicated a significant reduction in HbA1c levels post-surgery, suggesting that this approach may improve overall oral health, reduce inflammation, and consequently lower HbA1c levels.

CONCLUSION

Further research is necessary to confirm the efficacy of the proposed solution, but these initial results highlight the importance of addressing oral health through comprehensive strategies for diabetic and periodontitis patients.

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.

Long-term Visit-to-Visit Variability in Hemoglobin A1c and Kidney-Related Outcomes in Persons With Diabetes

RATIONALE & OBJECTIVE

To characterize associations between long-term visit-to-visit variability of hemoglobin A1c (HbA1c) and risk of adverse kidney outcomes in patients with diabetes.

STUDY DESIGN

Observational study.

SETTING & PARTICIPANTS

93,598 adults with diabetes undergoing routine care in Stockholm, Sweden.

EXPOSURES AND PREDICTORS

Categories of baseline and time-varying HbA1c variability score (HVS, the percentage of total HbA1c measures that vary by>0.5% [5.5mmol/mol] during a 3-year window): 0-20%, 21%-40%, 41%-60%, 61%-80%, and 81%-100%, with 0-20% as the reference group.

OUTCOME

Chronic kidney disease (CKD) progression (composite of>50% estimated glomerular filtration rate [eGFR] decline and kidney failure), acute kidney disease (AKI by clinical diagnosis or transient creatinine elevations according to KDIGO criteria), and worsening of albuminuria.

ANALYTICAL APPROACH

Multivariable Cox proportional hazards regression.

RESULTS

Compared with persons showing low HbA1c variability (HVS 0-20%), any increase in variability was associated with a higher risk of adverse kidney outcomes beyond mean HbA1c. For example, for patients with a baseline HbA1c variability of 81%-100%, the adjusted HR was 1.6 (95% CI, 1.47-1.74) for CKD progression, 1.23 [1.16-1.3] for AKI, and 1.28 [1.21-1.36] for worsening of albuminuria. The results were consistent across subgroups (diabetes subtypes, baseline eGFR, or albuminuria categories), in time-varying analyses and in sensitivity analyses including time-weighted average HbA1c or alternative metrics of variability.

LIMITATIONS

Observational study, limitations of claims data, lack of information on diet, body mass index, medication changes, and diabetes duration.

CONCLUSIONS

Higher long-term visit-to-visit HbA1c variability is consistently associated with the risks of CKD progression, AKI, and worsening of albuminuria.

PLAIN-LANGUAGE SUMMARY

The evidence for current guideline recommendations derives from clinical trials that focus on a single HbA1c as the definitive measure of efficacy of an intervention. However, long-term visit-to-visit fluctuations of HbA1c may provide additional value in the prediction of future kidney complications. We evaluated the long-term fluctuations in glycemic control in almost 100,000 persons with diabetes undergoing routine care in Stockholm, Sweden. We observed that higher long-term HbA1c fluctuation is consistently associated with the risks of chronic kidney disease progression, worsening of albuminuria and acute kidney injury. This finding supports a role for long-term glycemic variability in the development of kidney complications and illustrates the potential usefulness of this metric for risk stratification at the bedside beyond a single HbA1c test.

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.

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.

Association of hemoglobin A1c stability with mortality and diabetes complications in older adults with diabetes

INTRODUCTION

Hemoglobin A1c (A1c) treatment goals in older adults should be individualized to balance risks and benefits. It is unclear if A1c stability over time within unique target ranges also affects adverse outcomes.

RESEARCH DESIGN AND METHODS

We conducted a retrospective observational cohort study from 2004 to 2016 of veterans with diabetes and at least four A1c tests during a 3-year baseline. We generated four distinct categories based on the percentage of time that baseline A1c levels were within patient-specific target ranges: ≥60% time in range (TIR), ≥60% time below range (TBR), ≥60% time above range (TAR), and a mixed group with all times <60%. We assessed associations of these categories with mortality, macrovascular, and microvascular complications.

RESULTS

We studied 397 634 patients (mean age 76.9 years, SD 5.7) with an average of 5.5 years of follow-up. In comparison to ≥60% A1c TIR, mortality was increased with ≥60% TBR, ≥60% TAR, and the mixed group, with HRs of 1.12 (95% CI 1.11 to 1.14), 1.10 (95% CI 1.08 to 1.12), and 1.06 (95% CI 1.04 to 1.07), respectively. Macrovascular complications were increased with ≥60% TBR and ≥60% TAR, with estimates of 1.04 (95% CI 1.01 to 1.06) and 1.06 (95% CI 1.03 to 1.09). Microvascular complications were lower with ≥60% TBR (HR 0.97, 95% CI 0.95 to 1.00) and higher with ≥60% TAR (HR 1.11, 95% CI 1.08 to 1.14). Results were similar with higher TIR thresholds, shorter follow-up, and competing risk of mortality.

CONCLUSIONS

In older adults with diabetes, mortality and macrovascular complications are associated with increased time above and below individualized A1c target ranges. Higher A1c TIR may identify patients with lower risk of adverse outcomes.

Long-term HbA1c variability and macro-/micro-vascular complications in type 2 diabetes mellitus: a meta-analysis update

AIMS

The aim of the present study was to evaluate, by means of a meta-analysis approach, whether new available data, appeared on qualified literature, can support the effectiveness of an association of HbA1c variability with the risk of macro- and/or micro-vascular complications in type 2 diabetes mellitus (T2DM).

METHODS

The meta-analysis was conducted according to PRISMA Statement guidelines and considered published studies on T2DM, presenting HbA1c variability as standard deviation (SD) or its derived coefficient of variation (CV). Literature search was performed on PubMed in the time range 2015-July 2022, with no restrictions of language.

RESULTS

Twenty-three selected studies fulfilled the aims of the present investigation. Overall, the analysis of the risk as hazard ratios (HR) indicated a significant association between the HbA1c variability, expressed either as SD or CV, and the complications, except for neuropathy. Macro-vascular complications were all significantly associated with HbA1c variability, with HR 1.40 (95%CI 1.31-1.50, p < 0.0001) for stroke, 1.30 (95%CI 1.25-1.36, p < 0.0001) for transient ischaemic attack/coronary heart disease/myocardial infarction, and 1.32 (95%CI 1.13-1.56, p = 0.0007) for peripheral arterial disease. Micro-vascular complications yielded HR 1.29 (95%CI 1.22-1.36, p < 0.0001) for nephropathy, 1.03 (95%CI 0.99-1.08, p = 0.14) for neuropathy, and 1.15 (95%CI 1.08-1.24, p < 0.0001) for retinopathy. For all-cause mortality, HR was 1.33 (95%CI 1.27-1.39, p < 0.0001), and for cardiovascular mortality 1.25 (95%CI 1.17-1.34, p < 0.0001).

CONCLUSIONS

Our meta-analysis on HbA1c variability performed on the most recent published data since 2015 indicates positive association between HbA1c variability and macro-/micro-vascular complications, as well as mortality events, in T2DM, suggesting that this long-term glycaemic parameter merits further attention as a predictive, independent risk factor for T2DM population.

Improving Health and Diabetes Self-Management in Immigrants with Type 2 Diabetes Through a Co-Created Diabetes Self-Management Education and Support Intervention

To examine the impact of a co-created culturally sensitive diabetes self-management education and support (DSMES) intervention on the physical and mental health of immigrants with type 2 diabetes (T2D). Pre- and post-test among people with T2D whose primary language was Urdu, Arabic or Turkish (n = 97). Participants were offered a six-week intervention based on a person-centred approach using research-based dialogue tools to facilitate learning and reflection, which was developed in co-creation with immigrants and healthcare professionals. Data were collected at baseline, post-intervention and after 6 months and analysed using paired t-tests, Wilcoxon signed-rank tests, chi-square tests and regression models when appropriate. Several clinical outcomes were improved post-intervention, including HbA1c (P < 0.001), body fat percentage (P = 0.002), self-rated general health (P = 0.05), well-being (P = 0.004) and several self-management behaviours, e.g., physical activity (P < 0.001). Most outcomes remained improved after 6 months, but the effect on HbA1c was no longer statistically significant. Some outcomes were improved only at 6 months, including waist circumference (P < 0.001) and diabetes-related emotional distress (P < 0.001). Fatigue did not change. Attendance at more programme sessions was associated with better outcomes. The DSMES intervention developed in a co-creation process was highly effective in improving the health of immigrants with T2D.

Development and validation of a novel nomogram to predict diabetic kidney disease in patients with type 2 diabetic mellitus and proteinuric kidney disease

PURPOSE

Differentiating between diabetic kidney disease (DKD) and non-diabetic kidney disease (NDKD) in patients with Type 2 diabetes mellitus (T2DM) is important due to implications on treatment and prognosis. Clinical methods to accurately distinguish DKD from NDKD are lacking. We aimed to develop and validate a novel nomogram to predict DKD in patients with T2DM and proteinuric kidney disease to guide decision for kidney biopsy.

METHODS

A hundred and two patients with Type 2 Diabetes Mellitus (T2DM) who underwent kidney biopsy from 1st January 2007 to 31st December 2016 were analysed. Univariate and multivariate analyses were performed to identify predictive variables and construct a nomogram. The discriminative ability of the nomogram was assessed by calculating the area under the receiver operating characteristic curve (AUROC), while calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test and calibration plot. Internal validation of the nomogram was assessed using bootstrap resampling.

RESULTS

Duration of T2DM, HbA1c, absence of hematuria, presence of diabetic retinopathy and absence of positive systemic biomarkers were found to be independent predictors of DKD in multivariate analysis and were represented as a nomogram. The nomogram showed excellent discrimination, with a bootstrap-corrected C statistic of 0.886 (95% CI 0.815-0.956). Both the calibration curve and the Hosmer-Lemeshow goodness-of-fit test (p = 0.242) showed high degree of agreement between the prediction and actual outcome, with the bootstrap bias-corrected curve similarly indicating excellent calibration.

CONCLUSIONS

A novel nomogram incorporating 5 clinical parameters is useful in predicting DKD in type 2 diabetes mellitus patients with proteinuric kidney disease.

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.

Fasting Glucose Variability and the Risk of Dementia in Individuals with Diabetes: A Nationwide Cohort Study

BACKGROUND

We investigated whether fasting glucose (FG) variability could predict the risk of dementia.

METHODS

This cohort study analyzed data from Koreans with diabetes after at least three health examinations by the Korean National Health Insurance Corporation between 2005 and 2010, which included at least one examination between 2009 and 2010. A total of 769,554 individuals were included, excluding those aged <40 years and those with dementia. FG variability was measured using the variability independent of the mean (FG-VIM). The incidence of dementia was defined by the International Classification of Diseases 10th Revision codes and prescription of anti-dementia medication and was subdivided into Alzheimer's disease (AD) and vascular dementia (VD).

RESULTS

During the 6.9-year follow-up, 54,837, 41,032, and 6,892 cases of all-cause dementia, AD, and VD, respectively, were identified. Cox proportional regression analyses showed that as the FG-VIM quartile increased, the risk of dementia serially increased after adjustment for metabolic factors, income status, and diabetes-related characteristics, including the mean FG. Participants in FG-VIM quartile 4 showed a 18%, 19%, and 17% higher risk for all-cause dementia, AD, and VD, respectively, than those in quartile 1; this particularly included non-obese patients with a longer duration of diabetes, high FG levels, dyslipidemia, and those taking glucose-lowering medications. Conversely, the baseline FG status and dementia showed a U-shaped association.

CONCLUSION

Increased FG variability over 5 years can predict the risk of dementia in individuals with diabetes in Korea. This finding was more pronounced in patients with less favorable metabolic profiles.

Long-term glycemic variability and risk of adverse health outcomes in patients with diabetes: A systematic review and meta-analysis of cohort studies

AIMS

To quantify associations of different metrics of long-term glycemic variability (GV) with multiple adverse diabetes-related outcomes.

METHODS

We searched PubMed and Embase from database inception to 23 August 2021. GV was based on measurements of HbA1c or fasting plasma glucose (FPG) and calculated by standard deviation (SD), coefficient of variance (CV) or other metrics. Outcomes included mortality, cardiovascular disease (CVD), renal disease, peripheral neuropathy, retinopathy, dementia and cancer. Random-effects meta-analyses were adopted to pool the relative risks (RRs).

RESULTS

Seventy-five articles with 2,051,701 participants were included. When comparing top with bottom quartiles, HbA1c variabilities were associated with all-cause mortality (RR_CV = 1.63, 95 % CI 1.37-1.92; RR_SD = 1.87, 1.55-2.26), CVD (RR_CV = 1.38, 1.07-1.78; RR_SD = 1.34, 1.12-1.59), renal disease (RR_CV = 1.43, 1.18-1.74; RR_SD = 1.44, 1.24-1.67), and peripheral neuropathy (RR_CV = 1.84, 1.40-2.43; RR_SD = 1.98, 1.51-2.61), but not retinopathy. FPG variabilities were associated with all-cause mortality (RR_CV = 1.59, 1.43-1.78; RR_SD = 1.67, 1.26-2.20), renal disease (RR_CV = 1.77, 1.32-2.38), and retinopathy (RR_CV = 1.92, 1.10-3.35), but not CVD and peripheral neuropathy. Associations of GV with Alzheimer's disease (RR_HbA1c-CV = 1.38, 1.13-1.70; RR_FPG-CV = 1.32, 1.07-1.63) and cancer (RR_HbA1c-SD = 2.19, 1.52-3.17; RR_FPG-CV = 3.64, 2.21-5.98) were each found significant in one study.

CONCLUSIONS

Long-term GV was associated with multiple adverse diabetes-related outcomes, while the strength of associations varied. The findings support the use of long-term GV for diabetes management in clinical practice.

The Impact of Dementia on Diabetes Control: An Evaluation of HbA1c Trajectories and Care Outcomes in Linked Primary and Specialist Care Data

OBJECTIVES

Diabetes self-care may become increasingly challenging as cognition declines. We sought to characterize glycated hemoglobin A1c (HbA1c) trajectories, markers of diabetes-related management, health care utilization, and mortality in people with preexisting type 2 diabetes (T2D) with and without dementia and based on the extent of cognitive impairment at the time of dementia diagnosis.

DESIGN

Retrospective matched cohort study.

SETTING AND PARTICIPANTS

Using a linkage between a primary care (Lambeth DataNet) and a secondary mental healthcare database, up to 5 individuals aged ≥65 y with preexisting T2D without dementia were matched to each individual with dementia based on age, sex, and general practice.

METHODS

Comparisons were made for HbA1c trajectories (linear mixed effects models), markers of diabetes-related management and severity at dementia diagnosis (logistic regression), mortality (Cox regression), and health care utilization (multilevel mixed effects binomial regression).

RESULTS

In 725 incident dementia and 3154 matched comparators, HbA1c trajectories differed by dementia status; HbA1c increased over time for mild dementia and non-dementia, but the increase was greater in the mild dementia group; for those with moderate-severe dementia, HbA1c decreased over time. Despite individuals with dementia having increased health care utilization around the time of dementia diagnosis, they were less likely to have had routine diabetes-related management. Patients with dementia had a higher prevalence of macrovascular complications and diabetes foot morbidity at dementia diagnosis and a higher mortality risk than those without dementia; these relationships were most marked in those with moderate-severe dementia.

CONCLUSIONS AND IMPLICATIONS

Our study has highlighted important differences in the monitoring, management, and control of diabetes in people with dementia. The effects of frailty and the extent of cognitive impairment on the ability to self-manage diabetes and on glycemic control may need to be considered in treatment guidelines and by primary care.

Long-Term Effectiveness of the TIME Intervention to Improve Diabetes Outcomes in Low-Income Settings: a 2-Year Follow-Up

BACKGROUND

We previously found that a 6-month multidimensional diabetes program, TIME (Telehealth-Supported, Integrated Community Health Workers, Medication-Access) resulted in improved clinical outcomes.

OBJECTIVE

To follow TIME participant clinical outcomes for 24 months PARTICIPANTS: Low-income Latino(a)s with type 2 diabetes DESIGN AND INTERVENTION: We collected post-intervention clinical data for five cohorts (n = 101, mean n = 20/cohort) who participated in TIME programs from 2018 to 2020 in Houston, Texas.

MAIN MEASURES

We gathered HbA1c (primary outcome), weight, body mass index (BMI), and blood pressure data at baseline, 6 months (intervention end), and semiannually thereafter until 24 months after baseline to assess sustainability. We also evaluated participant loss to follow-up until 24 months.

KEY RESULTS

Participants decreased HbA1c levels during the intervention (p < 0.0001) and maintained these improvements at each timepoint from baseline to 24 months (p range: < 0.0001 to 0.015). Participants reduced blood pressure levels during TIME and maintained these changes at each timepoint from baseline until 18 months (systolic p range < 0.0001 to 0.0005, diastolic p range: < 0.0001 to 0.008) but not at 24 months (systolic: p = 0.065; diastolic: p = 0.85). There were no significant weight changes during TIME or post-intervention: weight (p range = 0.07 to 0.77), BMI (p range = 0.11 to 0.71). Attrition rates (loss to follow-up during the post-intervention period) were 5.9% (6 months), 24.8% (12 months), 35.6% (18 months), and 41.8% (24 months).

CONCLUSIONS

It is possible for vulnerable populations to maintain long-term glycemic and blood pressure improvements using a multiple dimensional intervention. Attrition rates rose over time but show promise given the majority of post-intervention timepoints occurred during the COVID-19 pandemic when low-income populations were most susceptible to suboptimal healthcare access. Future studies are needed to evaluate longitudinal outcomes of diabetes interventions conducted by local clinics rather than research teams.

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.

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.

Long-Term Glycemic Variability and Risk of Cardiovascular Events in Type 2 Diabetes: A Meta-Analysis

Long-term glycemic fluctuation has been associated with cardiovascular risk in patients with type 2 diabetes mellitus (T2DM). However, the findings are inconsistent. We performed a meta-analysis to summarize the association between parameters of long-term glycemic variability and risk of cardiovascular events in T2DM patients. Medline, Embase, and Web of Science databases were searched for longitudinal follow-up studies comparing the incidence of cardiovascular events in T2DM patients with higher or lower long-term glycemic variability. A random-effect model incorporating the potential heterogeneity among the included studies was used to pool the results. Twelve follow-up studies with 146 653 T2DM patients were included. The mean follow-up duration was 4.9 years. Pooled results showed that compared to those with the lowest glycemic variability, patients with the highest glycemic variability had significantly increased risk of cardiovascular events, as evidenced by the standard deviation of glycated hemoglobin [HbA1c-SD: relative risk (RR)=1.44, 95% confidence interval (CI): 1.23 to 1.69, p<0.001; I²=70%], HbA1c coefficient of variation (HbA1c-CV: RR=1.46, 95% CI: 1.19 to 1.79. p<0.001; I²=83%), standard deviation of fasting plasma glucose (FPG-SD: RR=1.33, 95% CI: 1.07 to 1.65, p=0.009; I²=0%), and FPG coefficient of variation (FPG-CV: RR=1.29, 95% CI: 1.01 to 1.64, p=0.04; I²=47%). In conclusion, increased long-term glycemic variability may be an independent risk factor for cardiovascular events in T2DM patients.

Association between Variability of Metabolic Risk Factors and Cardiometabolic Outcomes

Despite strenuous efforts to reduce cardiovascular disease (CVD) risk by improving cardiometabolic risk factors, such as glucose and cholesterol levels, and blood pressure, there is still residual risk even in patients reaching treatment targets. Recently, researchers have begun to focus on the variability of metabolic variables to remove residual risks. Several clinical trials and cohort studies have reported a relationship between the variability of metabolic parameters and CVDs. Herein, we review the literature regarding the effect of metabolic factor variability and CVD risk, and describe possible mechanisms and potential treatment perspectives for reducing cardiometabolic risk factor variability.

Machine learning based study of longitudinal HbA1c trends and their association with all-cause mortality: Analyses from a National Diabetes Registry

OBJECTIVE

The association of long-term HbA1c variability with mortality has been previously suggested. However, the significance of HbA1c variability and trends in different age and HbA1c categories is unclear.

RESEARCH DESIGN AND METHODS

Data on patients with diabetes listed in the Israeli National Diabetes Registry during years 2012-2016 (observation period) were collected. Patients with >4 HbA1c measurements, type 1 diabetes, eGFR < 30mg/ml/min, persistent HbA1c < 6% or malignancy were excluded. Utilizing machine learning methods, patients were classified into clusters according to their HbA1c trend (increasing, stable, decreasing). Mortality risk during 2017-2019 was calculated in subgroups defined by age (35-54, 55-69, 70-89 years) and last HbA1c (≤7% and >7%) at end of observation period. Models were adjusted for demographic, clinical and laboratory measurements including HbA1c, standard deviation (SD) of HbA1c and HbA1c trend.

RESULTS

This historical cohort study included 293,314 patients. Increased HbA1c variability (high SD) during the observation period was an independent predictor of mortality in patients aged more than 55 years (p < 0.01). The HbA1c trend was another independent predictor of mortality. Patients with a decreasing versus stable HbA1c trend had a greater mortality risk; this association persisted in all age groups in patients with HbA1c > 7% at the end of the observation period (p = 0.02 in age 35-54; p < 0.01 in aged >55). Patients with an increasing versus stable HbA1c trend had a greater mortality risk only in the elderly group (>70), yet in both HbA1c categories (p < 0.01).

CONCLUSIONS

HbA1c variability and trend are important determinants of mortality risk and should be considered when adjusting glycaemic targets.

Association of visit-to-visit glycemic variability with risk of cardiovascular diseases in high-risk Japanese patients with type 2 diabetes: A subanalysis of the EMPATHY trial

AIMS/INTRODUCTION

Long-term glycemic variability is important for predicting diabetic complications, but evaluation in a Japanese population is lacking. The aim of this study was to explore the relationship between visit-to-visit glycemic variability (VVV) and cardiovascular diseases (CV) in Japanese patients with type 2 diabetes, using the prospective cohort of the EMPATHY trial.

MATERIALS AND METHODS

Among 4532 participants with at least three HbA1c measurements, VVV was defined using the coefficient of variation (CV-HbA1c). The outcomes were the composite cardiovascular endpoints, including cardiac, cerebral, renal, and vascular events. The odds ratios (ORs) for the development of outcomes were estimated by using logistic regression models.

RESULTS

During a median follow-up of 38 months, 190 subjects developed CV events. The risk of developing CV events increased significantly with increasing quintile of CV-HbA1c, after multivariable adjustment including the mean-HbA1c (OR for the fifth vs first quintile, 1.73; 95%CI, 1.03-2.91; P for trend test = 0.003). There was a stronger association between CV-HbA1c and CV events in patients with a mean-HbA1c of <7% compared with those with a mean-HbA1c of ≥7% (OR per 1 standard deviation, 1.51; 95%CI, 1.23-1.85 and 1.13; 95%CI, 0.98-1.29, respectively; P for interaction = 0.02).

CONCLUSIONS

Increases of VVV were associated with the risk of CV events in Japanese patients with type 2 diabetes independent of the mean-HbA1c. The long-term variability of HbA1c as well as the mean HbA1c might be an important glycemic indicator in the management of patients with type 2 diabetes, especially in those with a mean-HbA1c of <7%.

The Association Between Mean Glycated Haemoglobin or Glycaemic Variability and the Development of Retinopathy in People with Diabetes: A Retrospective Observational Cohort Study

INTRODUCTION

To determine the association between mean glycated haemoglobin (HbA_1c) or glycaemic variability and the development of diabetic retinopathy (DR) in people with diabetes.

METHODS

An observational cohort study with people registered with a DR eye screening service between October 2012 and October 2017. Those who had no DR at the start of the study were followed for a maximum of 5 years. HbA_1c measures were used to calculate HbA_1c variability and mean HbA_1c to assess any relationship between these and the risk of developing new onset DR.

RESULTS

A total of 2511 individuals were followed up for up to 5 years. Of these, 542 (21.6%) developed DR. After adjustment, HbA_1c variability was not significantly associated with the development of DR (p = 0.3435). However, the mean HbA_1c was (p < 0.0001). Those with type 1 diabetes had an odds of 1.63 (95% CI 1.11-2.40) of a retinopathy diagnosis compared to those with type 2 diabetes.

CONCLUSIONS

We have shown that mean HbA_1c is associated with an increased risk of developing diabetic retinopathy. However, after adjustment for sex, age, diabetes type and the mean, the HbA_1c variability no longer remained significant. Our data suggest that optimizing long-term glycaemic control remains paramount.

Glycaemic variabilities: Key questions in pursuit of clarity

After years of intensive investigation, the definition of glycaemic variability remains unclear and the term variability in glucose homoeostasis might be more appropriate covering both short and long-term glycaemic variability. For the latter, we remain in the search of an accurate definition and related targets. Recent work leads us to consider that the within-subject variability of HbA1c calculated from consecutive determinations of HbA1c at regular time-intervals could be the most relevant index for assessing the long-term variability with a threshold value of 5% (%CV = SD of HbA1c/mean HbA1c) to separate stability from lability of HbA1c. Presently, no one can deny that short- and long-term glucose variability should be maintained within their lower ranges to limit the incidence of hypoglycaemia. Usually, therapeutic strategies aimed at reducing post-meal glucose excursions, i.e. the major contributor to daily glucose fluctuations, exert a beneficial effect on the short-term glucose variability. This explains the effectiveness of adjunct therapies with either GLP- receptor agonists or SGLT inhibitors in type 2 diabetes. In type 1 diabetes, the application of a CGM device alone reduces the short-term glycaemic variability. In contrast, sophisticated insulin delivery does not necessarily lead to such reductions despite marked downward shifts of 24-hour glycaemic profiles. Such contrasting observations raise the question as to whether the prolonged wear of CGM devices is or not the major causative factor for improvement in glucose variability among intensively insulin-treated persons with type 1 diabetes.

Three-year trajectories of metabolic risk factors predict subsequent long-term mortality in patients with type 2 diabetes

AIM

This study aims to evaluate the associations between 3-year trajectories of metabolic risk factors and subsequent mortality in patients with type 2 diabetes.

METHODS

A total of 6400 persons aged ≥ 30 years with type 2 diabetes and ≥ 3 years of follow-up period were included. The cluster analysis determined the patterns of 3-year trajectories, and Cox proportional hazards models evaluated the associations between patterns and mortality.

RESULTS

Three trajectory subgroups of metabolic risk factors, namely, cluster 1, normal; cluster 2, high-stable or reducing with high level at baseline; and cluster 3, fluctuation: elevated and decreasing, were generated. The clusters 2 and 3 of body mass index (BMI), fasting plasma glucose (FPG), HbA1c, and triglyceride (TG) trajectories were associated with increased risks of all-cause mortality compared with cluster 1 (hazard ratio = 1.27, 95% confidence interval = 1.06-1.51 and 1.45, 1.19-1.78 for BMI; 1.41, 1.22-1.62 and 1.81, 1.38-2.38 for FPG; 1.42, 1.23-1.64 and 1.47, 1.23-1.75 for HbA1c; 1.34, 1.10-1.63 and 2.40, 1.30-4.37 for TG, respectively). For the systolic blood pressure trajectory, only cluster 3 was associated with an increased mortality risk relative to cluster 1 (1.76, 1.13-2.77).

CONCLUSIONS

Long-term metabolic risk factor trajectories may be associated with subsequent mortality.

Increased Hemoglobin A1c Time in Range Reduces Adverse Health Outcomes in Older Adults With Diabetes

OBJECTIVE

Short- and long-term glycemic variability are risk factors for diabetes complications. However, there are no validated A1C target ranges or measures of A1C stability in older adults. We evaluated the association of a patient-specific A1C variability measure, A1C time in range (A1C TIR), on major adverse outcomes.

RESEARCH DESIGN AND METHODS

We conducted a retrospective observational study using administrative data from the Department of Veterans Affairs and Medicare from 2004 to 2016. Patients were ≥65 years old, had diabetes, and had at least four A1C tests during a 3-year baseline period. A1C TIR was the percentage of days during the baseline in which A1C was in an individualized target range (6.0-7.0% up to 8.0-9.0%) on the basis of clinical characteristics and predicted life expectancy. Increasing A1C TIR was divided into categories of 20% increments and linked to mortality and cardiovascular disease (CVD) (i.e., myocardial infarction, stroke).

RESULTS

The study included 402,043 veterans (mean [SD] age 76.9 [5.7] years, 98.8% male). During an average of 5.5 years of follow-up, A1C TIR had a graded relationship with mortality and CVD. Cox proportional hazards models showed that lower A1C TIR was associated with increased mortality (A1C TIR 0 to <20%: hazard ratio [HR] 1.22 [95% CI 1.20-1.25]) and CVD (A1C TIR 0 to <20%: HR 1.14 [95% CI 1.11-1.19]) compared with A1C TIR 80-100%. Competing risk models and shorter follow-up (e.g., 24 months) showed similar results.

CONCLUSIONS

In older adults with diabetes, maintaining A1C levels within individualized target ranges is associated with lower risk of mortality and CVD.

Visit-to-visit variability of clinical risk markers in relation to long-term complications in type 1 diabetes

BACKGROUND

Clinical characteristics such as HbA_1c , systolic blood pressure (SBP), albuminuria and estimated glomerular filtration rate (eGFR) are important when treating type 1 diabetes. We investigated the variability in these measures as risk markers for micro- and macrovascular complications.

METHODS

This prospective study included 1062 individuals with type 1 diabetes. Visit-to-visit variability of HbA_1c , SBP, albuminuria and eGFR was calculated as the SD of the residuals in individual linear regression models using all available measures in a specified period of 3 years (VV). Endpoints included were as follows: cardiovascular events (CVE) defined as myocardial infarction, non-fatal stroke, or coronary or peripheral arterial intervention; end-stage kidney disease (ESKD) defined as eGFR <15 ml/min/1.73 m² , chronic dialysis or kidney transplantation; eGFR decline ≥30%; and mortality. Adjustment included age, sex, cholesterol, HbA_1c , SBP, body mass index, smoking, albuminuria, eGFR, and mean, intercept, slope of respective exposure variables and regression models.

RESULTS

SBP VV was significantly associated with CVE (adjusted hazard ratio per 50% increase, (CI 95%); p: 1.21 [1.05-1.39]; p = 0.008), ESKD (1.51 [1.16-1.96]; p = 0.002) and mortality (1.25 [1.09-1.44]; p = 0.002). HbA_1c VV was significantly associated with mortality (1.51 [1.30-1.75]; p < 0.001); albuminuria VV with eGFR decline (1.14 [1.08-1.20]; p = 0.024) and ESKD (1.14 [1.02-1.27]; p < 0.001), but neither CVE nor mortality. Adjusted eGFR VV was not associated with endpoints.

CONCLUSION

In type 1 diabetes, higher variability of basic clinical risk markers adds important risk stratification information for the development of micro- and macrovascular complications.

Population segmentation of type 2 diabetes mellitus patients and its clinical applications - a scoping review

BACKGROUND

Population segmentation permits the division of a heterogeneous population into relatively homogenous subgroups. This scoping review aims to summarize the clinical applications of data driven and expert driven population segmentation among Type 2 diabetes mellitus (T2DM) patients.

METHODS

The literature search was conducted in Medline®, Embase®, Scopus® and PsycInfo®. Articles which utilized expert-based or data-driven population segmentation methodologies for evaluation of outcomes among T2DM patients were included. Population segmentation variables were grouped into five domains (socio-demographic, diabetes related, non-diabetes medical related, psychiatric / psychological and health system related variables). A framework for PopulAtion Segmentation Study design for T2DM patients (PASS-T2DM) was proposed.

RESULTS

Of 155,124 articles screened, 148 articles were included. Expert driven population segmentation approach was most commonly used, of which judgemental splitting was the main strategy employed (n = 111, 75.0%). Cluster based analyses (n = 37, 25.0%) was the main data driven population segmentation strategies utilized. Socio-demographic (n = 66, 44.6%), diabetes related (n = 54, 36.5%) and non-diabetes medical related (n = 18, 12.2%) were the most used domains. Specifically, patients' race, age, Hba1c related parameters and depression / anxiety related variables were most frequently used. Health grouping/profiling (n = 71, 48%), assessment of diabetes related complications (n = 57, 38.5%) and non-diabetes metabolic derangements (n = 42, 28.4%) were the most frequent population segmentation objectives of the studies.

CONCLUSIONS

Population segmentation has a wide range of clinical applications for evaluating clinical outcomes among T2DM patients. More studies are required to identify the optimal set of population segmentation framework for T2DM patients.

New Insights into the Role of Visit-to-Visit Glycemic Variability and Blood Pressure Variability in Cardiovascular Disease Risk

PURPOSE OF REVIEW

There is evidence from epidemiologic studies that variability in cardiovascular risk factors influences risk of cardiovascular disease. We review new studies and novel findings in the relationship between visit-to-visit glycemic variability and blood pressure variability and risk of adverse outcomes.

RECENT FINDINGS

Visit-to-visit glycemic variability is consistently linked to macrovascular disease. This relationship has been observed in both clinical trials and retrospective studies of electronic health records. Long-term blood pressure variability also predicts cardiovascular outcomes, and the association appears stronger in those with lower levels of systolic and diastolic function. As epidemiologic evidence increases in support of a role for metabolic risk factor variability in cardiovascular risk, there is a corresponding rise in interest in applying this information toward improving risk factor prediction and treatment. Future investigation of underlying mechanisms for these associations as well as implications for therapy is also warranted. The potential additive contribution of variability of multiple parameters also merits additional scrutiny. As our technology for capturing risk factor variability continues to improve, this will only enhance our understanding of its links with vascular disease and how to best utilize this information to reduce cardiovascular outcomes.

Body mass index trajectories during mid to late life and risks of mortality and cardiovascular outcomes: Results from four prospective cohorts

BACKGROUND

Our understanding of the weight-outcome association mainly comes from single-time body mass index (BMI) measurement. However, data on long-term trajectories of within-person changes in BMI on diverse study outcomes are sparse. Therefore, this study is to determine the associations of individual BMI trajectories and cardiovascular outcomes.

METHODS

The present analysis was based on data from 4 large prospective cohorts and restricted to participants aged ≥45 years with at least two BMI measurements. Hazard ratios (HR) and 95% confidence intervals(95%CI) for each outcome according to different BMI trajectories were calculated in Cox regression models.

FINDINGS

The final sample comprised 29,311 individuals (mean age 58.31 years, and 77.31% were white), with a median 4 BMI measurements used in this study. During a median follow-up of 21.16 years, there were a total of 10,192 major adverse cardiovascular events (MACE) and 11,589 deaths. A U-shaped relation was seen with all study outcomes. Compared with maintaining stable weight, the multivariate adjusted HR for MACE were 1.53 (95%CI 1.40-1.66), 1.26 (95%CI 1.16-1.37) and 1.08 (95%CI 1.02-1.15) respectively for rapid, moderate and slow weight loss; 1.01 (95%CI 0.95-1.07), 1.13 (95%CI 1.05-1.21) and 1.29 (95%CI 1.20-1.40) respectively for slow, moderate and rapid weight gain. Identical patterns of association were observed for all other outcomes. The development of BMI differed markedly between the outcome-free individuals and those who went on to experience adverse events, generally beginning to diverge 10 years before the occurrence of the events.

INTERPRETATION

Our findings may signal an underlying high-risk population and inspire future studies on weight management.

FUNDING

National Natural Science Foundation of China, Guangdong Natural Science Foundation.

Flash CGM Is Associated With Reduced Diabetes Events and Hospitalizations in Insulin-Treated Type 2 Diabetes

Purpose

Suboptimal glycemic control among individuals with diabetes is a leading cause of hospitalizations and emergency department utilization. Use of flash continuous glucose monitoring (flash CGM) improves glycemic control in type 1 and type 2 diabetes, which may result in lower risk for acute and chronic complications that require emergency services and/or hospitalizations.

Methods

In this retrospective, real-world study, we analyzed IBM MarketScan Commercial Claims and Medicare Supplemental databases to assess the impact of flash CGM on diabetes-related events and hospitalizations in a cohort of 2463 individuals with type 2 diabetes who were on short- or rapid-acting insulin therapy. Outcomes were changes in acute diabetes-related events (ADE) and all-cause inpatient hospitalizations (ACH), occurring during the first 6 months after acquiring the flash CGM system compared with event rates during the 6 months prior to system acquisition. ICD-10 codes were used to identify ADE for hypoglycemia, hypoglycemic coma, hyperglycemia, diabetic ketoacidosis, and hyperosmolarity.

Results

ADE rates decreased from 0.180 to 0.072 events/patient-year (hazard ratio [HR]: 0.39 [0.30, 0.51]; P < 0.001) and ACH rates decreased from 0.420 to 0.283 events/patient-year (HR: 0.68 [0.59 0.78]; P < 0.001). ADE reduction occurred regardless of age or gender.

Conclusions

Acquisition of the flash CGM system was associated with reductions in ADE and ACH. These findings provide support for the use of flash CGM in type 2 diabetes patients treated with short- or rapid-acting insulin therapy to improve clinical outcomes and potentially reduce costs.

A Telehealth-supported, Integrated care with CHWs, and MEdication-access (TIME) Program for Diabetes Improves HbA1c: a Randomized Clinical Trial

BACKGROUND

Many individuals with diabetes live in low- or middle-income settings. Glycemic control is challenging, particularly in resource-limited areas that face numerous healthcare barriers.

OBJECTIVE

To compare HbA1c outcomes for individuals randomized to TIME, a Telehealth-supported, Integrated care with CHWs (Community Health Workers), and MEdication-access program (intervention) versus usual care (wait-list control).

DESIGN

Randomized clinical trial.

PARTICIPANTS

Low-income Latino(a) adults with type 2 diabetes.

INTERVENTIONS

TIME consisted of (1) CHW-participant telehealth communication via mobile health (mHealth) for 12 months, (2) CHW-led monthly group visits for 6 months, and (3) weekly CHW-physician diabetes training and support via telehealth (video conferencing).

MAIN MEASURES

Investigators compared TIME versus control participant baseline to month 6 changes of HbA1c (primary outcome), blood pressure, body mass index (BMI), weight, and adherence to seven American Diabetes Association (ADA) standards of care. CHW assistance in identifying barriers to healthcare in the intervention group were measured at the end of mHealth communication (12 months).

KEY RESULTS

A total of 89 individuals participated. TIME individuals compared to control participants had significant HbA1c decreases (9.02 to 7.59% (- 1.43%) vs. 8.71 to 8.26% (- 0.45%), respectively, p = 0.002), blood pressure changes (systolic: - 6.89 mmHg vs. 0.03 mmHg, p = 0.023; diastolic: - 3.36 mmHg vs. 0.2 mmHg, respectively, p = 0.046), and ADA guideline adherence (p < 0.001) from baseline to month 6. At month 6, more TIME than control participants achieved > 0.50% HbA1c reductions (88.57% vs. 43.75%, p < 0.001). BMI and weight changes were not significant between groups. Many (54.6%) TIME participants experienced > 1 barrier to care, of whom 91.7% had medication issues. CHWs identified the majority (87.5%) of barriers.

CONCLUSIONS

TIME participants resulted in improved outcomes including HbA1c. CHWs are uniquely positioned to identify barriers to care particularly related to medications that may have gone unrecognized otherwise. Larger trials are needed to determine the scalability and sustainability of the intervention.

CLINICAL TRIAL

NCT03394456, accessed at https://clinicaltrials.gov/ct2/show/NCT03394456.

Glucose variability and diabetes complications: Risk factor or biomarker? Can we disentangle the "Gordian Knot"?

« Variability in glucose homoeostasis » is a better description than « glycaemic variability » as it encompasses two categories of dysglycaemic disorders: i) the short-term daily glucose fluctuations and ii) long-term weekly, monthly or quarterly changes in either HbA1c, fasting or postprandial plasma glucose. Presently, the relationship between the "variability in glucose homoeostasis" and diabetes complications has never been fully clarified because studies are either observational or limited to retrospective analysis of trials not primarily designed to address this issue. Despite the absence of definitive evidence from randomized controlled trials (RCTs), it is most likely that acute and long-term glucose homoeostasis "cycling", akin to weight and blood pressure "cycling" in obese and hypertensive individuals, are additional risk factors for diabetes complications in the presence of sustained ambient hyperglycaemia. As hypoglycaemic events are strongly associated with short- and long-term glucose variability, two relevant messages can be formulated. Firstly, due consideration should be given to avoid within-day glucose fluctuations in excess of 36% (coefficient of variation) at least for minimizing the inconvenience and dangers associated with hypoglycaemia. Secondly, it seems appropriate to consider that variability in glucose homoeostasis is not only associated with cardiovascular events but is also a causative risk factor via hypoglycaemic episodes as intermediary step. Untangling the" Gordian Knot", to provide confirmation about the impact of variability in glucose homoeostasis and diabetes complications remains a daunting prospect.

Association between hemoglobin A1c variability and hypoglycemia-related hospitalizations in veterans with diabetes mellitus

INTRODUCTION

To study the impact of hemoglobin A1c (A1c) variability on the risk of hypoglycemia-related hospitalization (HRH) in veterans with diabetes mellitus.

RESEARCH DESIGN AND METHODS

342 059 veterans with diabetes aged 65 years or older were identified for a retrospective cohort study. All participants had a 3-year baseline period from January 1, 2005 to December 31, 2016, during which they had at least four A1c tests. A1c variability measures included coefficient of variation (A1c CV), A1c SD, and adjusted A1c SD. HRH was identified during a 2-year follow-up period from Medicare and the Veterans Health Administration through validated algorithms of International Classification of Diseases (ICD)-9 and ICD-10 codes. Logistic regression modeling was used to evaluate the relationship between A1c variability and HRH risk while controlling for relevant clinical covariates.

RESULTS

2871 patients had one or more HRH in the 2-year follow-up period. HRH risk increased with greater A1c variability, and this was consistent across A1c CV, A1c SD, and adjusted A1c SD. Average A1c levels were also independently associated with HRH, with levels <7.0% (53 mmol/mol) having lower risk and >9% (75 mmol/mol) with greater risk. The relationships between A1c variability remained significant after controlling for average A1c levels and prior HRH during the baseline period.

CONCLUSION

Increasing A1c variability and elevated A1c levels are associated with a greater risk of HRH in older adults with diabetes. Clinicians should consider A1c variability when assessing patients for risk of severe hypoglycemia.

Impact of flash glucose monitoring on glucose control and hospitalization in type 1 diabetes: A nationwide cohort study

BACKGROUND

We evaluated the impact of flash continuous glucose monitoring (FCGM) on glycemic control and healthcare burden in a large real-world cohort of patients with type 1 diabetes (T1D) initiating FCGM technology.

METHODS

In this retrospective cohort study, we included adults (age ≥18 years) with T1D from a large Health Maintenance Organization in Israel, who initiated FCGM during 2018. Primary outcomes included change in HbA1c ≥3 months following FCGM commencement and change in rate of internal-medicine hospitalization. Additional outcomes included changes in glucose test strip purchases, diabetes related outpatient health care visits and hospitalization for diabetic ketoacidosis (DKA) and/or severe hypoglycemia.

RESULTS

The study included 3490 patients, followed for a median of 14 (inter-quartile range 11-15) months after FCGM commencement. Among 2682 patients with an HbA1c measured both at baseline and ≥3 months after FCGM initiation, average HbA1c declined from 8.1% ± 1.46% to 7.9% ± 1.31% (P < .001) at first measurement and was maintained during follow up. Specifically, in those with HbA1c ≥8%, a mean decline of 0.5% (P < .001) was observed. A clinically significant HbA1c reduction of ≥0.5% was experienced by 25.5% of the patients. The rate of internal medicine hospitalization, visits to primary care, or visits to endocrine/diabetes specialists in the period following FCGM commencement vs the 6 months prior was significantly reduced (P < .001). Hospitalization for DKA and/or hypoglycemia declined as well (P = .004).

CONCLUSIONS

FCGM was associated with significant and durable improvement in glycemic control as well as reduced consumption of healthcare services.

Effect of Variability in Blood Pressure, Glucose and Cholesterol Concentrations, and Body Weight on Emergency Hospitalization and 30-Day Mortality in the General Population

Background

Variability in blood pressure, glucose concentration, cholesterol concentration, or body weight is associated with a wide range of health outcomes. We hypothesized that high variability in metabolic parameters is associated with an increased risk of emergency hospitalization and mortality.

Methods and Results

Using a nationally representative database from the Korean National Health Insurance System, 8 049 228 individuals who underwent 3 or more health examinations during 2005 to 2010 were followed up until the end of 2016. Variability in fasting blood glucose and total cholesterol concentrations, systolic blood pressure, and body weight was measured using the variability independent of the mean (VIM). High variability was defined as the highest quartile of variability. Subjects were classified according to the number of high variability parameters. The end points of the study were emergency hospitalization and 30‐day mortality. There were 733 387 emergency hospitalizations (9.1%) during a median follow‐up of 5.6±1.2 years. For each metabolic parameter, an incrementally higher risk of emergency hospitalization was observed for higher VIM quartile groups than for the lowest quartile group. Compared with the group with low variability for all 4 parameters, the group with high variability for all 4 parameters had a significantly higher risk for emergency hospitalization (hazard ratio [HR], 1.58; 95% CI, 1.54–1.61) and 30‐day mortality (HR, 2.44; 95% CI, 1.62–3.69), after adjusting for possible confounding factors.

Conclusions

High variability in metabolic parameters was associated with increased risk of emergency hospitalization and short‐term mortality.

Long-term variability of glycemic markers and risk of all-cause mortality in type 2 diabetes: the Look AHEAD study

INTRODUCTION

Glycemic variability may predict poor outcomes in type 2 diabetes. We evaluated the associations of long-term variability in glycosylated hemoglobin (HbA_1C) and fasting plasma glucose (FPG) with cardiovascular disease (CVD) and death among individuals with type 2 diabetes.

RESEARCH DESIGN AND METHODS

We conducted a secondary, prospective cohort analysis of the Look AHEAD (Action for Health in Diabetes) data, including 3560 participants who attended four visits (baseline, 12 months, 24 months, and 36 months) at the outset. Variability of HbA_1C and FPG was assessed using four indices across measurements from four study visits. Participants without CVD during the first 36 months were followed for incident outcomes including a CVD composite (myocardial infarction, stroke, hospitalization for angina, and CVD-related deaths), heart failure (HF), and deaths.

RESULTS

Over a median follow-up of 6.8 years, there were 164 deaths from any cause, 33 CVD-related deaths, 91 HF events, and 340 participants experienced the CVD composite. Adjusted HRs comparing the highest to lowest quartile of SD of HbA_1C were 2.10 (95% CI 1.26 to 3.51), 3.43 (95% CI 0.95 to 12.38), 1.01 (95% CI 0.69 to 1.46), and 1.71 (95% CI 0.69 to 4.24) for all-cause mortality, CVD mortality, CVD composite and HF, respectively. The equivalent HRs for highest versus lowest quartile of SD of FPG were 1.66 (95% CI 0.96 to 2.85), 2.20 (95% CI 0.67 to 7.25), 0.94 (95% CI 0.65 to 1.35), and 2.05 (95% CI 0.80 to 5.31), respectively.

CONCLUSIONS

A greater variability in HbA_1C was associated with elevated risk of mortality. Our findings underscore the need to achieve normal and consistent glycemic control to improve clinical outcomes among individuals with type 2 diabetes.

Preadmission Diabetes-Specific Risk Factors for Mortality in Hospitalized Patients With Diabetes and Coronavirus Disease 2019

OBJECTIVE

To examine whether HbA1c, outpatient diabetes treatment regimen, demographics, and clinical characteristics are associated with mortality in hospitalized patients with diabetes and coronavirus disease 2019 (COVID-19).

RESEARCH DESIGN AND METHODS

This was a retrospective cohort analysis of patients with diabetes hospitalized with confirmed COVID-19 infection from 11 March to 7 May 2020 at a large academic medical center in New York City. Multivariate modeling was used to assess the independent association of HbA1c levels and outpatient diabetes treatment regimen with mortality, in addition to independent effects of demographic and clinical characteristics.

RESULTS

We included 1,126 hospitalized patients with diabetes and COVID-19 for analysis, among whom mean age was 68 years, 50% were male, 75% were Black, mean BMI was 30 kg/m2, 98% had type 2 diabetes, mean HbA1c was 7.5%, and 33.1% died. HbA1c levels were not associated with mortality in unadjusted or adjusted analyses, but an outpatient regimen with any insulin treatment was strongly predictive. Additionally, age, sex, and BMI interacted such that in all age categories, mortality was higher with increasing BMI in males compared with females.

CONCLUSIONS

In this large U.S. cohort of hospitalized patients with diabetes and COVID-19, insulin treatment, as a possible proxy for diabetes duration, and obesity rather than long-term glycemic control were predictive of mortality. Further investigation of underlying mechanisms of mortality and inpatient glycemic control is needed.