Going beyond HbA1c to understand the benefits of advanced diabetes therapies

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

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

Time in range and complications of diabetes: a cross-sectional analysis of patients with Type 1 diabetes

BACKGROUND/ OBJECTIVE

To evaluate the association of CGM parameters and HbA1c with diabetes complications in patients with Type 1 Diabetes (T1D).

METHODS

Patients with T1D using the CGM system Freestyle Libre were included in this analysis. The association of CGM-metrics and HbA1c with diabetes complications (any complication, microvascular complications, or macrovascular complications) was assessed using logistic regression unadjusted and adjusted for age, sex, and diabetes duration (model 1), and further adjusted for hypertension and dyslipidemia (model 2).

RESULTS

One hundred and sixty-one patients with T1D were included. The mean (± SD) age was 37.4 ± 13.4 years old and the median T1D duration was 17.7 ± 10.6 years. Time in range (TIR) was associated with any complication and microvascular complications in the unadjusted model and in the adjusted models. TIR was associated with retinopathy in the unadjusted model as well as in model 1, and was associated with macrovascular complications only in the unadjusted model. HbA1c was associated with any complications, microvascular complications, and retinopathy in the unadjusted model but not in the adjusted models. HbA1c was associated with macrovascular complications in the unadjusted model and in the adjusted model 1.

CONCLUSIONS

In this cross-sectional analysis of patients with T1D using intermittent scanned CGM, TIR, and HbA1c were associated with complications of diabetes. TIR may be a better predictor than HbA1c of any complication and microvascular complications, while HbA1c may be a better predictor of macrovascular complications.

Psychometric analysis of the cross-cultural Spanish version of the diabetes management questionnaire

Evaluation of the degree of adherence to self-care among Spanish type 1 diabetes (T1DM) pediatric population lacks of a validated tool.

PURPOSE

To cross-culturally adapt and determine the psychometric properties of the Spanish version of the Diabetes Management Questionnaire to assess the degree of adherence to self-care among children with T1DM.

METHODS

Translation, back-translation, and patient suggestions, were considered to obtain the Spanish version (DMQ-Sp). A cross-sectional study was conducted with 323 children (aged 8-18 years) with T1DM and their parents to determine internal reliability, structural validity, and external validity. Responsiveness to change was analyzed through a prospective longitudinal study involving 102 newly diagnosed T1DM patients. Psychometrics were evaluated for the entire sample and stratified by age (8-12 and 13-18 years).

RESULTS

A total of 323 children with T1DM [49.8% female; age 13.3 ± 2.8 years; 155 aged 8-12; glycated hemoglobin (HbA1c) value 7.7 ± 1.0%] answered the Spanish final version. The internal consistency Cronbach's alpha was 0.76 and intraclass correlation coefficient 0.84. Test-retest reliability was r = 0.84 (p < 0.001). Fit index of structural validity was >0.7. External validity correlated inversely with HbA1c (r = -0.39; p < 0.001). The DMQ-Sp score increased significantly after 6 months of receiving the full therapeutic education program (TEP) (baseline 57.07 ± 10.81 vs. 6 months 78.80 ± 10.31; p < 0.001).

CONCLUSION

The DMQ-Sp is reliable, valid, and sensitive to change in a large sample of children (aged 8-18 years) with T1DM and their parents.

PRACTICE IMPLICATIONS

DMQ-Sp can be a useful tool for diabetes teams to identify adherence to different tasks and to evaluate TEPs.

Time-in-range: a promising glycemic control metric for bariatric surgery

As a complication of obesity, type 2 diabetes (T2D) is a chronic disease that is difficult to manage. However, bariatric surgery makes it possible to alleviate T2D. While the existing generic index glycosylated hemoglobin (HbA1c) is a powerful tool for examining overall blood glucose levels, it still has some limitations as a daily measure of blood glucose levels and as a judge of the effectiveness of bariatric surgery. Using the time-in-range (TIR) measurement and its derivatives is a better way to evaluate short-term blood glucose fluctuations and can be used as a supplement to HbA1c. In this article, we discuss the utility and limitations of HbA1c and other indicators used during surgery. In addition, we mentioned TIR as a novel metric that can act as an accurate predictor of the risk of T2D complications and an index of preoperative risk assessment in bariatric surgery. In contrast to previous indicators, TIR has the advantage that it cannot be affected by caloric restriction to better reflect the patient's glucose level and the level of pancreatic islet function. On this basis, TIR is a promising indicator for both the diagnosis of diabetes and the preoperative and postoperative prediction and evaluation.

Assessment of Glycemic Control in Patients With Diabetes in Northern Sudan Using Calculated HbA1c

BACKGROUND

Diabetes mellitus (DM) significantly burdens health services worldwide. As a simple and cost-effective method, the mathematical calculation of HbA1c is coming to be of value in areas with scarce resources. This study aimed to use calculated HbA1c to ascertain the prevalence of uncontrolled DM and correlate it with the risk factors for DM.

METHODS

In the River Nile State of northern Sudan, a cross-sectional study was conducted in five leading cities from May to August 2021. Patients diagnosed and recorded as having type 2 or type 1 DM were included in this study. Enzymatic methods were used to assess fasting blood glucose (FBG). We used the mean of three FBG readings for three months to calculate HbA1c using the equation {HbA1c = (FBG mg/dl) x 0.03+2.6}, which was used to compute the estimated mediocre blood sugar over the course of three months.

RESULTS

A total of 2047 diabetic patients from northern Sudan were studied for their DM control. Nearly two-thirds (65.2%) had uncontrolled DM. Of the patients studied, uncontrolled DM was significantly positively associated with older age, history of ischemic heart disease, and being a housewife. Multivariate regression analysis showed significant correlations between uncontrolled DM, an inactive lifestyle, and obesity.

CONCLUSION

The prevalence of uncontrolled DM among known patients with diabetic in northern Sudan is high (65.2%). The inactive lifestyles of housewives and freelance workers, having type 1 DM, and being hypertensive and obese are risk factors significantly associated with uncontrolled DM and its related complications.

Association of Time in Range with Endothelial Injury in Patients with Type 2 Diabetes Treated with Exenatide

INTRODUCTION

We aimed to investigate whether treatment with exenatide could increase time in range (TIR) and decrease glycemic variability, and to evaluate the association between TIR and endothelial injury in patients with type 2 diabetes mellitus (T2DM).

METHODS

Two-hundred patients with T2DM treated with exenatide for 16 weeks were included in this study. Seven-point fingerstick blood glucose was used to evaluate derived TIR and glycemic variability. The serum levels of soluble endothelial cell protein C receptor (sEPCR) and von Willebrand factor (vWF) were measured. Ninety-three patients having the data of endothelial injury markers were categorized as derived TIR > 70% or ≤ 70% after the treatment and the association between TIR and endothelial injury were evaluated.

RESULTS

Treatment with exenatide for 16 weeks resulted in a significant reduction in fasting blood glucose, postprandial 2 h blood glucose, and glycated hemoglobin A1c (HbA1c) levels in patients with T2DM. Compared with baseline, derived TIR value was significantly increased [85.7 (57.1, 100.0) % vs. 42.9 (14.9, 71.4) %, P < 0.001], and the parameters of glycemic variability were remarkably decreased after the treatment. After the treatment, serum sEPCR level was significantly decreased from baseline in patients with TIR > 70% [74.5 (32.8, 122.5) ng/mL vs. 96.9 (48.5, 150.9) ng/mL, P = 0.006] but not in those with TIR ≤ 70%; serum vWF level was remarkably decreased in patients with TIR > 70% [from 1166.2 (848.1, 1335.5) mIU/mL to 907.4 (674.3, 1335.1) mIU/mL, P = 0.001] while this effect was modest in those with TIR ≤ 70%.

CONCLUSIONS

Treatment with exenatide increases TIR and decreases glycemic variability in patients with T2DM. Moreover, the amelioration of endothelial injury is more pronounced in patients with TIR > 70% after the treatment.

TRIAL REGISTRATION

ChiCTR-IPR-15006558 (registered, 27 May 2015).

Telehealth Technologies and Their Benefits to People With Diabetes

This article reviews the current diabetes technology landscape and how recent advancements are being used to help overcome barriers in the management of diabetes. The authors offer case examples of how digital tools and platforms can facilitate diabetes care via telehealth and remote patient monitoring for individuals in special populations. They also provide tips to ensure success in implementing diabetes technology to provide the best possible care for people with diabetes in outpatient settings.

Negative association of time in range and urinary albumin excretion rate in patients with type 2 diabetes mellitus: a retrospective study of inpatients

Background:

Time in range (TIR) refers to the time an individual spends within their target glucose range, which now has been popularized as an important metric to classify glycemic management and also recognized as an important outcome of current diabetes therapies. This study aimed to investigate the association between TIR and the severity of the urinary albumin excretion rate (UAER) in patients with type 2 diabetes mellitus (T2DM).

Methods:

We retrospectively analyzed the data of 1014 inpatients with T2DM at the Department of Endocrinology and Metabolism of Peking University International Hospital, China. TIR was defined as the percentage of blood glucose within the target range of 3.90–10.00 mmol/L. Urine samples for assessment of UAER were collected for 3 consecutive days from the start of hospitalization.

Results:

The TIR values for patients with normal urine levels of albumin, microalbuminuria, and macroalbuminuria were 70% ± 20%, 50% ± 20%, and 30% ± 20%, respectively (all P < 0.001). The patients were stratified according to quartiles of TIR as follows: quartile (Q) 1, <55%; Q2, 55%–72%; Q3, 73%–83%; and Q4, >83%. The incidences of microalbuminuria in Q1, Q2, Q3, and Q4 were 41.1%, 21.6%, 7.1%, and 5.5% (all P < 0.001), respectively. The respective incidences of macroalbuminuria were 24.2%, 1.1%, 1.4%, and 0% (all P < 0.001). In multinomial logistic regression analyses, TIR was significantly correlated with microalbuminuria (odds ratio [OR] 0.58, 95% confidence interval [CI]: 0.52–0.65, P < 0.001) and macroalbuminuria (OR 0.26, 95% CI: 0.18–0.38, P < 0.001) after adjusting for age, sex, body mass index, diabetes duration, systolic blood pressure, and levels of triglycerides, glycosylated hemoglobin A1c, and creatinine.

Conclusion:

The proportion of blood glucose in TIR is closely related to the severity of UAER in patients with T2DM.

Association of sleep quality with glycemic variability assessed by flash glucose monitoring in patients with type 2 diabetes

BACKGROUND

Deterioration of sleep quality has been reported to contribute to the incidence of diabetes and may be responsible for glycemic status in diabetes. The present study explored the relationship between sleep quality and glycemic variability in patients with type 2 diabetes (T2D).

METHODS

We recruited 111 patients with T2D for this cross-sectional study. Each patient underwent flash glucose monitoring for 14 days to obtain glycemic variability parameters, such as standard deviation of glucose (SD), coefficient of variation of glucose (CV), mean amplitude of glycemic excursions (MAGE), mean of daily differences (MODD), and time in glucose range of 3.9-10 mmol/L (TIR_3.9-10). After 14 days of flash glucose monitoring, each patient received a questionnaire on the Pittsburgh Sleep Quality Index (PSQI) to evaluate subjective sleep quality. HbA1c was also collected to assess average glucose.

RESULTS

HbA1c was comparable among the subgroups of PSQI score tertiles. Across ascending tertiles of PSQI scores, SD, CV and MAGE were increased, while TIR_3.9-10 was decreased (p for trend  <  0.05), but not MODD (p for trend  =  0.090). Moreover, PSQI scores were positively correlated with SD, CV, MODD and MAGE (r =  0.322, 0.361, 0.308 and 0.354, respectively, p  <  0.001) and were inversely correlated with TIR_3.9-10 (r  =  - 0.386, p  <  0.001). After adjusting for other relevant data by multivariate linear regression analyses, PSQI scores were independently responsible for SD (β  =  0.251, t  =  2.112, p  =  0.041), CV (β  =  0.286, t  =  2.207, p  =  0.033), MAGE (β  =  0.323, t  =  2.489, p  =  0.018), and TIR_3.9-10 (β  =  - 0.401, t  =  - 3.930, p  <  0.001) but not for MODD (β  =  0.188, t  =  1.374, p  =  0.177).

CONCLUSIONS

Increased glycemic variability assessed by flash glucose monitoring was closely associated with poor subjective sleep quality evaluated by the PSQI in patients with T2D.

Relationships between HbA1c and continuous glucose monitoring metrics of glycaemic control and glucose variability in a large cohort of children and adolescents with type 1 diabetes

AIMS

To evaluate the relationships between HbA1c and Continuous Glucose Monitoring (CGM) metrics in children/adolescents with Type 1 Diabetes (T1D).

METHODS

HbA1c and real-life CGM data of the 12 weeks preceding its measurement were retrospectively collected from 654 children/adolescents with T1D. The relationships between HbA1c and CGM metrics were assessed by Spearman correlation coefficient. Participants were categorized into groups based on HbA1c and CGM metrics values. ANOVA was run across HbA1c and CGM metrics groups in the entire study population and in subjects stratified by CGM type, insulin therapy, age and puberty.

RESULTS

HbA1c was positively correlated with mean glucose, SD, %TAR > 180 mg/dL, %TAR > 250 mg/dL, HBGI and negatively with %TIR, %TBR and %time < 54 mg/dL. HbA1c-based groups were significantly associated with these metrics, but for each group their value widely ranged with a substantial overlap between them. HbA1c and HbA1c-based groups were not associated with %CV and LBGI, as well as %CV and LBGI-based groups had not significantly different HbA1c. Comparable results were found analysing subjects according to age, type of CGM, insulin therapy and puberty.

CONCLUSIONS

The relationships between HbA1c and CGM metrics described in this cohort of paediatric subjects with T1D support the importance of the evaluation of these metrics, in particular %CV and LBGI, independently of HbA1c value.

A new approach for investigating the relative contribution of basal glucose and postprandial glucose to HbA1C

To develop an accurate method for evaluating the relative contributions of basal glucose (BG) and postprandial glucose (PPG) to glycated haemoglobin (HbA1c) in subjects with hyperglycaemia using a Continuous Glucose Monitoring System (CGMS®). The subjects were divided into the normal glucose tolerance (NGT), impaired glucose tolerance (IGT), newly-diagnosed type 2 diabetes (NDDM), and drug-treated type 2 diabetes (T2DM) groups. We evaluated the relative contributions of BG and PPG to HbA1c in patients with hyperglycaemia according to three different baseline values. Subjects (n = 490) were grouped as follows: 92 NGT, 36 IGT, 131 NDDM, and 231 T2DM. The relative contributions of PPG to HbA1c were calculated using baseline values of 6.1 mmol/L, 5.6 mmol/L, and the 24-h glucose curve of the NGT group. The relative contribution of PPG to HbA1c decreased progressively from the IGT group to the T2DM group. Compared with the 24-h glucose curve as the baseline, the relative contribution of PPG was overestimated in 9.04% and 1.76% of the subjects when 6.1 mmol/L and 5.6 mmol/L were used as baselines, respectively (P < 0.01), in T2DM patients. The 24-h glucose curve of NGT is more suitable for studying the relative contributions of BG and PPG to HbA1c and it is more precise, as it considers physiological fluctuations in NGT after meals. However, 5.6 mmol/L can be used when the 24-h glucose curve for NGT is unavailable; using 6.1 mmol/L as a baseline value may overestimate the contribution to the HbA1c. There is no unified standard for assessing the contributions of basal glucose (BG) and postprandial glucose (PPG) to HbA1c. The 24-h glucose curve of NGT is more suitable for studying the relative contributions of BG and PPG to HbA1c, as it considers physiological fluctuations in NGT after meals. However, 5.6 mmol/L can be used when the 24-h glucose curve for NGT is unavailable; using 6.1 mmol/L as a baseline value may overestimate the contribution to the HbA1c.

Impact of blinded retrospective continuous glucose monitoring on clinical decision making and glycemic control in persons with type 2 diabetes on insulin therapy

BACKGROUND AND AIMS

Blinded retrospective continuous glucose monitoring (rCGM) provides detailed information about real-life glycaemic profile. In persons with type 2 diabetes without adequate glycaemic control, the structured introduction of rCGM may be beneficial to sustain improvements in diabetes management.

METHODS AND RESULTS

102 individuals with insulin-treated type 2 diabetes, age less than 66 years old and HbA1c >7.5%, were recruited. Participants performed a 7-day blinded rCGM (iPro2) every four months for one year. Biochemical, anthropometric, and rCGM data was collected. Participants' and healthcare professionals' perceptions were assessed. 90 participants completed the protocol. HbA1c was 9.1 ± 0.1% one year prior to enrolment and 9.4 ± 0.1% at enrolment (p < 0.01). With the rCGM-based intervention, a decrease in HbA1c was achieved at 4 months (8.4 ± 0.1%, p < 0.0001), and 12 months (8.1 ± 0.1%, p < 0.0001). A significant increase in time-in-range was observed (50.8 ± 2.4 at baseline vs 61.5 ± 2.2% at 12 months, for 70-180 mg/dL, p < 0.001), with no difference in exposure time to hypoglycaemia. After 12 months, there was an increase in self-reported diabetes treatment satisfaction (p < 0.05).

CONCLUSION

In persons with type 2 diabetes and poor metabolic control, specific data from blinded rCGM informed therapeutic changes and referral to targeted education consultations on nutrition and insulin administration technique. Therapeutic changes were made more frequently and targeted to changes in medication dose, timing, and/or type, as well as to lifestyle. Together, these brought significant improvements in clinical outcomes, effective shared decision-making, and satisfaction with treatment.

REGISTRATION NUMBER

NCT04141111.

Relationship of continuous glucose monitoring-related metrics with HbA1c and residual β-cell function in Japanese patients with type 1 diabetes

The targets for continuous glucose monitoring (CGM)-derived metrics were recently set; however, studies on CGM data over a long period with stable glycemic control are limited. We analyzed 194,279 CGM values obtained from 19 adult Japanese patients with type 1 diabetes. CGM data obtained during stable glycemic control over four months were analyzed. CGM-related metrics of different durations "within 120, 90, 60, 30, and 7 days" were calculated from baseline. Time in range (TIR; glucose 70-180 mg/dL), time above range (TAR; glucose ≥ 181 mg/dL), and average glucose levels, but not time below range (TBR; glucose ≤ 69 mg/dL), strongly correlated with glycated hemoglobin (HbA1c) values (P < 0.0001). TBR correlated with glucose coefficient of variation (CV) (P < 0.01). Fasting serum C-peptide levels negatively correlated with glucose CV (P < 0.01). HbA1c of approximately 7% corresponded to TIR of 74% and TAR of 20%. The shorter the CGM period, the weaker was the relationship between HbA1c and CGM-related metrics. TIR, TAR, and average glucose levels accurately reflected HbA1c values in Japanese patients with type 1 diabetes with stable glycemic control. Glucose CV and TBR complemented the limitation of HbA1c to detect glucose variability and hypoglycemia. Stable glycemic control with minimal hypoglycemia depended on residual β-cell function.

Individualizing Time-in-Range Goals in Management of Diabetes Mellitus and Role of Insulin: Clinical Insights From a Multinational Panel

Diabetes mellitus is a global health concern associated with significant morbidity and mortality. Inadequate control of diabetes leads to chronic complications and higher mortality rates, which emphasizes the importance of achieving glycemic targets. Although glycated hemoglobin (HbA_1c) is the gold standard for measuring glycemic control, it has several limitations. Therefore, in recent years, along with the emergence of continuous glucose monitoring (CGM) technology, glycemic control modalities have moved beyond HbA_1c. They encompass modern glucometrics, such as glycemic variability (GV) and time-in-range (TIR). The key advantage of these newer metrics over HbA_1c is that they allow personalized diabetes management with person-centric glycemic control. Basal insulin analogues, especially second-generation basal insulins with properties such as longer duration of action and low risk of hypoglycemia, have demonstrated clinical benefits by reducing GV and improving TIR. Therefore, for more effective and accurate diabetes management, the development of an integrated approach with second-generation basal insulin and glucometrics involving GV and TIR is the need of the hour. With this objective, a multinational group of endocrinologists and diabetologists reviewed the existing recommendations on TIR, provided their clinical insights into the individualization of TIR targets, and elucidated on the role of the second-generation basal insulin analogues in addressing TIR.

A Systematic Review of Collective Evidences Investigating the Effect of Diabetes Monitoring Systems and Their Application in Health Care

INTRODUCTION

Diabetes monitoring systems (DMS) are a possible approach for regular control of glucose levels in patients with Type 1 or 2 diabetes in order to improve therapeutic outcomes or to identify and modify inappropriate patient behaviors in a timely manner. Despite the significant number of studies observing the DMS, no collective evidence is available about the effect of all devices.

GOAL

To review and consolidate evidences from multiple systematic reviews on the diabetes monitoring systems and the outcomes achieved.

MATERIALS AND METHODS

Internet-based search in PubMed, EMBASE, and Cochrane was performed to identify all studies relevant to the research question. The data regarding type of intervention, type of diabetes mellitus, type of study, change in clinical parameter(s), or another relevant outcome were extracted and summarized.

RESULTS

Thirty-three out of 1,495 initially identified studies, involving more than 44,100 patients with Type 1, Type 2, or gestational diabetes for real-time or retrospective Continuous Glucose Monitoring (CGMS), Sensor Augmented Pump Therapy (SAPT), Self-monitoring Blood Glucose (SMBG), Continuous subcutaneous insulin infusion (CSII), Flash Glucose Monitoring (FGM), Closed-loop systems and telemonitoring, were included. Most of the studies observed small nominal effectiveness of DMS. In total 11 systematic reviews and 15 meta-analyses, with most focusing on patients with Type 1 diabetes (10 and 6, respectively), reported a reduction in glycated hemoglobin (HbA1c) levels from 0.17 to 0.70% after use of DMS.

CONCLUSION

Current systematic review of already published systematic reviews and meta-analyses suggests that no statistically significant difference exists between the values of HbA1c as a result of application of any type of DMS. The changes in HbA1c values, number and frequency of hypoglycemic episodes, and time in glucose range are the most valuable for assessing the appropriateness and effectiveness of DMS. Future more comprehensive studies assessing the effectiveness, cost-effectiveness, and comparative effectiveness of DMS are needed to stratify them for the most suitable diabetes patients' subgroups.

Fit-for-Purpose Biometric Monitoring Technologies: Leveraging the Laboratory Biomarker Experience

Biometric monitoring technologies (BioMeTs) are becoming increasingly common to aid data collection in clinical trials and practice. The state of BioMeTs, and associated digitally measured biomarkers, is highly reminiscent of the field of laboratory biomarkers 2 decades ago. In this review, we have summarized and leveraged historical perspectives, and lessons learned from laboratory biomarkers as they apply to BioMeTs. Both categories share common features, including goals and roles in biomedical research, definitions, and many elements of the biomarker qualification framework. They can also be classified based on the underlying technology, each with distinct features and performance characteristics, which require bench and human experimentation testing phases. In contrast to laboratory biomarkers, digitally measured biomarkers require prospective data collection for purposes of analytical validation in human subjects, lack well‐established and widely accepted performance characteristics, require human factor testing, and, for many applications, access to raw (sample‐level) data. Novel methods to handle large volumes of data, as well as security and data rights requirements add to the complexity of this emerging field. Our review highlights the need for a common framework with appropriate vocabulary and standardized approaches to evaluate digitally measured biomarkers, including defining performance characteristics and acceptance criteria. Additionally, the need for human factor testing drives early patient engagement during technology development. Finally, use of BioMeTs requires a relatively high degree of technology literacy among both study participants and healthcare professionals. Transparency of data generation and the need for novel analytical and statistical tools creates opportunities for precompetitive collaborations.

The variability of glycated hemoglobin is associated with renal function decline in patients with type 2 diabetes

Background

The effect of glucose control, especially variability of glycated hemoglobin (HbA1c), on estimated glomerular filtration rate (eGFR) decline in type 2 diabetes is still debatable.

Methods

We used tertiles of coefficient of variation (CV) to determine the variability of HbA1c (HbA1c_CV). Mixed model repeated measures (MMRM) were used to evaluate the annual eGFR decline rate.

Results

In 1383 type 2 diabetic patients, we found the greater the HbA1c_CV, the greater the eGFR decline (p = 0.01, -0.99 in low, -1.73 in mid, and -2.53 ml/min/1.73 m²/year in high HbA1c_CV). Regardless of eGFR (⩾60 or <60 ml/min/1.73 m²), the same result holds (p = 0.019 and p = 0.007, respectively). In subgroup analysis of baseline HbA1c (%) (HbA1c < 7, 7 ⩽ HbA1c < 9, and HbA1c ⩾ 9), tertiles of HbA1c_CV showed similar effects on annual decline of eGFR (p = 0.193, 0.300, 0.182, respectively), although a trend for a steeper decline in renal function in the highest HbA1c_CV tertile was observed for all HbA1c strata, and even for HbA1c < 7%. A similar behavior was observed in patients with macroalbuminuria or normoalbuminuria (p = 0.219, and 0.109, respectively), with a significant trend in those with microalbuminuria (p = 0.019). Even in patients with HbA1c < 7, high HbA1c_CV also predicts rapid eGFR decline. Before macroalbuminuria, minimizing HbA1c_CV also has renal benefit.

Conclusions

HbA1c variability is an independent risk factor for deterioration of renal function. Even with well-controlled HbA1c levels (<7%), patients with high HbA1c_CV still experienced faster eGFR decline. Early minimization of glycemic variability (before macroalbuminuira) can curb deterioration of renal function. Monitoring and lowering of HbA1c_CV is highly recommended for diabetic care.

The Correlation between Time in Range and Diabetic Microvascular Complications Utilizing Information Management Platform

BACKGROUND

In recent years, the time of blood glucose within the target range is a new research hotspot in blood glucose management. TIR is expected to be a novel indicator for evaluating the efficacy of glycemic control and predicting diabetic complications. However, its relationship with diabetic complications has not been fully elucidated.

OBJECTIVE

To explore the relationship between time in range (TIR) and glycosylated hemoglobin (HbA1C) through the information big data management platform. Possible association between TIR and diabetic microvascular complications (retinopathy, nephropathy, and neuropathy) was investigated, attempting to provide theoretical basis for the clinical application of TIR and to explore the TIR control scope suitable for diabetic patients.

METHODS

A total of 5,644 type 2 diabetic patients hospitalized in the Department of Endocrinology, the Second Affiliated Hospital of Nanchang University, were selected from April 2017 to June 2020. Fingertip capillary blood glucose monitoring (FCGM) was monitored for a total of 455,664 times, and patients who are nondiabetic, pregnant, or with diabetic ketosis were excluded. Patients with 7 blood glucose points monitored for at least three consecutive days were selected as subjects in the study. 1,895 males and 1,513 females with diabetes were included, with an average age of (59.74 ± 13.40) years old and an average course of disease of 8.28 ± 7.11 years. The proportion of time in range (TIR) (70∼180 mg/dl) within the target range and the correlation between TIR and HbA1C were analyzed, as well as the relationship between TIR and the risk of diabetic complications.

RESULTS

(1) The average of TIR and HbA1C was 49.65 ± 23.36% and 8.92 ± 2.49%, respectively, and was linearly correlated. With the decrease of TIR, HbA1C increased significantly, and the difference was statistically significant (P < 0.01, R ² = 0.458). The correlation coefficient of mean TIR with mean HbA1C was -0.626. (2) There were 836 patients diagnosed with diabetic nephropathy (DN). The difference of TIR value between DN and non-DN was significant (T = 2.250, P < 0.05). Risk assessment showed the lower the TIR was, the higher the risk of DN was. TIR less than 40% was a risk factor for DN (OR = 1.249, 95% CI: 0.915-1.375). (3) There were 1,296 patients diagnosed with diabetic peripheral neuropathy (DPN). The difference of TIR value between DPN and non-DPN was significant (T = 3.844, P < 0.01). TIR value less than 70% was a risk factor for DPN (OR = 1.030, 95% CI: 0.769-1.379). (4) There were 2,077 patients diagnosed with diabetic retinopathy (DR). The difference of TIR value between DPN and non-DPN was significant (T = 3.608, P < 0.01). TIR value less than 50% was a risk factor for DR (OR = 1.092, 95% CI: 0.898-1.264). Summary. TIR may serve as a reference index for short-term blood glucose control, strongly reflecting the clinical blood glucose regulation and predicting the risk of diabetic microvascular complications.

The impact of shift work on glycemic characteristics assessed by CGM and its association with metabolic indices in non-diabetic subjects

AIM

To explore the glycemic characteristics of non-diabetic shift workers and associations with metabolic indices.

METHODS

In this cross-sectional study, 450 non-diabetic males, including 238 shift workers, aged 23-58 years, were recruited after a screening oral glucose tolerance test. Blood samples and anthropometric data were collected. Hundred and fifty of them finished a continuous glucose monitoring for 3-7 days.

RESULTS

Compared to daytime workers, shift workers presented with larger WHR (p < 0.001), higher HOMA-IR (p < 0.001), higher hs-CRP level (p < 0.001) and worse lipid profiles. In glycemic characteristics, shift workers with normal glucose regulation had a similar mean blood glucose (MBG), daytime MBG, percentage of time of hyperglycemia, hypoglycemia, euglycemia, and fluctuation parameters, including standard deviation of blood glucose (SDBG), mean amplitude of glycemic excursions (MAGE) and mean of daily differences (p > 0.05, respectively), while they had a higher nighttime MBG (p = 0.026) and blood glucose (BG) at 3 a.m. (p = 0.015). For subjects with impaired glucose regulation, both groups had no difference in any clinical characteristics or glycemic parameters (p > 0.05, respectively). Further regression analysis revealed the association between MBG/SDBG/MAGE/nighttime MBG/BG at 3 a.m. and age/WHR/hs-CRP/TC.

CONCLUSION

For non-diabetic shift workers, the glycemic characteristic was the elevated nighttime glycemia, presented as higher nighttime MBG and BG at 3 a.m. And both metrics were closely associated with central obesity. Elevated nighttime glycemia was an early signal of glucose metabolism disorder in shift workers.