CGMS and Glycemic Variability, Relevance in Clinical Research to Evaluate Interventions in T2D, a Literature Review

The effect of adding protein to a carbohydrate meal on postprandial glucose and insulin responses: a systematic review and meta-analysis of acute controlled feeding trials

BACKGROUND

protein influences acute postprandial-glucose and -insulin responses but the effects of dose, protein-type and health-status are unknown.

OBJECTIVE

to determine the acute effect of adding protein to carbohydrate on postprandial responses and identify effect modifiers.

METHODS

we searched MEDLINE, EMBASE and Cochrane databases through 30 July 2023 for acute, crossover trials comparing acute postprandial-responses elicited by carbohydrate-containing test-meals with vs without added protein in adults without-diabetes or with type-2 (T2DM) or type-1 (T1DM) diabetes. Group data were pooled separately using generic inverse-variance with random-effects models and expressed as ratio-of-means with [95% CIs]. Risk-of-bias and certainty-of-evidence (GRADE) were assessed.

RESULTS

in 154 trial-comparisons of animal-, dairy- and plant-proteins (without-diabetes, n=22,67,32; T2DM, n=14,16,3), each gram-protein/gram-carbohydrate (g/g) reduced glucose-area-under-the-curve (AUC) less in T2DM than in those without-diabetes (-10% vs -50%, P<0.05) but increased insulin-AUC similarly (+76 vs +56%, respectively). In subjects without-diabetes, each g/g of dairy- and plant-proteins reduced glucose-AUC by 52 and 55% and increased insulin-AUC by 64 and 45% (all P<0.05). Animal-proteins significantly reduced glucose-AUC by 31% and increased insulin-AUC by 37% (pooled effects), but without a significant dose-response. In T2DM animal-protein reduced glucose-AUC by 13% and increased insulin-AUC by 105%, with no significant dose-response. Dairy-protein reduced glucose-AUC by 18% (no dose-response), but each g/g increased insulin-AUC by 34% (P<0.05). In T1DM protein increased glucose-AUC by 40% (P<0.05, n=5). Data-source (reported vs calculated) and study-methodology-quality significantly modified some outcomes and contributed to high between-study heterogeneity.

CONCLUSIONS

in people without-diabetes, adding dairy- or plant-protein to a carbohydrate-containing meal elicits physiologically significant reductions in glucose-AUC and increases insulin-AUC. Animal-protein may slightly reduce glucose-AUC and may increase insulin-AUC. In T2DM, protein may not have such large and consistent effects. Further research is needed to determine if the effects of protein differ by health status and protein-source.

REGISTRATION

PROSPERO CRD42022322090.

FUNDING

General Mills.

The impact of slowly digestible and resistant starch on glucose homeostasis and insulin resistance

PURPOSE OF REVIEW

This review will summarize recent studies assessing the effect of slowly digestible starch (SDS) and resistant starch (RS) on glucose metabolism in healthy, prediabetic or type 2 diabetic adults.

RECENT FINDINGS

Currently, a particular interest in starch and its digestibility has arisen, with data showing a positive effect of SDS and RS on the glucose homeostasis of healthy, at-risk, prediabetic and type 2 diabetic patients but research is ongoing.

SUMMARY

Carbohydrates (CHO) and especially starch play a major role in the prevention and management of metabolic diseases such as type 2 diabetes (T2D). This largely depends on the quality and the digestibility (rate and extent) of the ingested starchy products, beyond their quantity. SDS have been poorly studied but display a beneficial effect on reducing glucose excursions in healthy and insulin-resistant subjects and a relevant potential to improve glucose control in type 2 diabetic individuals. As for RS, the results appear to be encouraging but remain heterogeneous, depending the nature of the RS and its role on microbiota modulation. Further studies are needed to confirm the present results and investigate the potential complementary beneficial effects of SDS and RS on long-term glucose homeostasis to prevent cardiometabolic diseases.

Increased glycemic variability results in abnormal differentiation of T cell subpopulation in type 2 diabetes patients

AIMS

We aimed to investigate the association between glycemic variability (GV) and the abnormal differentiation of T-cell subpopulations in patients with type 2 diabetes mellitus (T2DM).

METHODS

In total, 108 hospitalized patients with T2DM were enrolled and divided into two subgroups (normal glycemic excursion (NGE) and high glycemic excursion (HGE)) according to their mean amplitude of glycemic excursion (MAGE) level. The MAGE was evaluated via continuous glucose monitoring for 72 h consecutively. Flow cytometry was used to determine the proportions of T cell subpopulations.

RESULTS

The T helper (Th) 1 cell/Th2 cell ratio was significantly higher, and the proportion of regulatory T cells (Tregs) was significantly lower in the NGE group than in the HGE group (all P < 0.05). After fully adjusting for confounders, the MAGE was positively associated with the Th1 cell/Th2 cell ratio (β = 0.370; P = 0.009) and negatively associated with the proportion of Tregs (β = -0.554; P = 0.001).

CONCLUSION

The MAGE was an independent risk factor for abnormally high Th1 cell/Th2 cell ratio and proportion of Tregs. Abnormal differentiation of T cell subpopulations induced by GV may impair β-cell function, aggravate insulin resistance, and contribute to the development of diabetic complications.

Retrospective Observational Study on Assessing Sitagliptin and Dapagliflozin as a Fixed-Dose Combination in the Indian Population With Type 2 Diabetes Mellitus: The SIDAXA Study

Introduction Type 2 diabetes mellitus (T2DM), a prevalent chronic metabolic disorder, necessitates multifaceted treatment approaches. Emerging studies highlight the cardiovascular advantages of sodium-glucose transport protein 2 (SGLT2) and dipeptidyl peptidase 4 (DPP-4) inhibitors in T2DM. This investigation delves into the synergistic effects of the fixed-dose combination (FDC) of sitagliptin and dapagliflozin, offering insights into its safety and efficacy for the Indian population. Methods This real-world, retrospective, observational study spanned 328 cases across 111 Indian centres, evaluating the safety, efficacy, and clinical utilization of the sitagliptin and dapagliflozin FDC in T2DM patients after obtaining ethical approval. Assessments at baseline, week four, and week 12 encompassed hemoglobin A1C (HbA1C), fasting plasma glucose (FPG), postprandial blood glucose (PPBG), low-density lipoprotein cholesterol (LDL-C), systolic blood pressure (SBP), diastolic blood pressure (DBP), and weight change. The statistical analysis was done using Statistical Package for Social Sciences (SPSS) version 29.0.1.0(171) (IBM Corp., Armonk, NY, USA) with a significance level p<0.05. Results Study participants [mean age: 51.14±5.55 years, 77.74% (n=255) males, 22.26% (n=73) females] exhibited prevalent risk factors like sedentary lifestyle (n=167, 50.91%) and smoking (n=147, 44.82%). Comorbidities included hypertension (n=235, 71.65%) and dyslipidaemia (n=139, 42.38%). Metformin (n=282, 85.98%) and sulfonylurea (n=134, 40.85%) were commonly prescribed concomitant oral antidiabetic agents (OADs). FDC administration significantly reduced HbA1c by 1.05 ± 0.83% (p < 0.0001) at week 12. FPG and PPBG showed significant reductions of 22.98 ± 22.23 mg/dL (p < 0.0001), 165.50 ± 37.02 mg/dL and 40.94 ± 36.04 mg/dL (p < 0.0001) at four weeks respectively. By week 12, significant reductions were noted in SBP (14.61±13.98mmHg reduction, p-value <0.0001), DBP (7.80±8.45mmHg reduction, p-value <0.0001), and LDL-C levels (18.14±23.95 mg/dL reduction, p-value <0.0001). In patients with established cardiovascular disease, there was reduction in HbA1c levels by 1.02 ± 0.63% after 12 weeks, with FPG decreasing by 54.52 ± 32.67 mg/dL and PPBG decreasing by 88.73 ± 44.90 mg/dL. Treatment-emergent adverse events included headache, changes in micturition, genital mycotic infection, and nausea and diarrhoea which were mild, transient, and necessitated no treatment discontinuation. Conclusion The FDC of sitagliptin and dapagliflozin significantly improved glycaemic control and lipid profiles in T2DM patients, particularly those with coronary artery disease. It demonstrated a favourable safety profile in the Indian population, signifying its potential as an effective and well-tolerated therapeutic option in patients with established cardiovascular disease.

Dietary composition and time in range in population with type 2 diabetes mellitus-exploring the association using continuous glucose monitoring device

AIM

To understand the association between macronutrient composition of a diet with Time in Range (TIR), Time above Range (TAR) and Time below Range (TBR) derived using a Continuous Glucose Monitoring (CGM) device for 14 days.

METHODOLOGY

An exploratory analysis on the baseline data of 50 Type 2 Diabetes Mellitus participants with age 25-55 years, HbA1c upto 8% and on Metformin only) enrolled for an interventional clinical trial was performed.

RESULTS

Participants consuming adequate carbohydrates (CHO) of 55 to 60% of total calories had better Average Blood Glucose of 142.0 ± 24.0 mg/dL with a significance of p = 0.03 and Glucose Management Indicator (GMI) of 6.6 ± 0.7% significant at p = 0.01, than those with high CHO intake >60% of the total calories, with Average Blood Glucose - 155.0 ± 13.4 mg/dL and GMI - 7.06 ± 0.4%. Similarly, TIR - 68.2 ± 5.1% and TAR - 23.0 ± 10.8% was significantly better (p = 0.00) among those consuming adequate protein (12-15%) as compared to low protein (≤ 10%) with TIR- 61.0 ± 5.1% & TAR- 32.9 ± 10.3%. A correlation (r = -0.482 & p = 0.00) and simple linear regression analysis (R² = 0.33, F = 7.72, p = 0.000) revealed that when CHO intake increases the TIR decreases whereas TAR increases (r = 0.380 & p = 0.006). We did not find any significant relation between fat intake and TIR, TAR or TBR.

CONCLUSION

Our results suggest that lowering CHO, while increasing protein in the diet may help improve TIR. Further in-depth studies are needed to confirm these findings.

Enhancement of Ambulatory Glucose Profile for Decision Assistance and Treatment Adjustments

The ambulatory glucose profile (AGP) lacks sufficient statistical metrics and insightful graphs; indeed, it is missing important information on the temporal patterns of glucose variations. The AGP graph is difficult to interpret due to the overlapping metrics and fluctuations in glucose levels over 14 days. The objective of this proposed work is to overcome these challenges, specifically the lack of insightful information and difficulty in interpreting AGP graphs, to create a platform for decision assistance. The present work proposes 20 findings built from decision rules that were developed from a combination of AGP metrics and additional statistical metrics, which have the potential to identify patterns and insightful information on hyperglycemia and hypoglycemia. The "CGM Trace" webpage was developed, in which insightful metrics and graphical representations can be used to make inferences regarding the glucose data of any user. However, doctors (endocrinologists) can access the "Findings" tab for a summarized presentation of their patients' glycemic control. The findings were implemented for 67 patients' data, in which the data of 15 patients were collected from a clinical study and the data of 52 patients were gathered from a public dataset. The findings were validated by means of MANOVA (multivariate analysis of variance), wherein a p value of < 0.05 was obtained, depicting a strong significant correlation between the findings and the metrics. The proposed work from "CGM Trace" offers a deeper understanding of the CGM data, enhancing AGP reports for doctors to make treatment adjustments based on insightful information and hidden patterns for better diabetic management.

Acute Glycemic Variability and Early Outcomes After Cardiac Surgery: A Meta-Analysis

The influence of acute glycemic variability (GV) on early outcomes of patients after cardiac surgery remains not fully determined. We performed a systematic review and meta-analysis to evaluate the association between acute GV and in-hospital outcomes of patients after cardiac surgery. Relevant observational studies were obtained by search of electronic databases including Medline, Embase, Cochrane Library, and Web of Science. A randomized-effects model was selected to pool the data by incorporating the influence of potential heterogeneity. Nine cohort studies involving 16 411 patients after cardiac surgery were included in this meta-analysis. Pooled results showed that a high acute GV was associated with an increased risk of major adverse events (MAE) during hospitalization for patients after cardiac surgery [odds ratio [OR]: 1.29, 95% CI: 1.15 to 1.45, p<0.001, I22=38%]. Sensitivity analysis limited to studies of on-pump surgery and GV evaluated by coefficient of variation of blood glucose showed similar results. Subgroup analysis suggested that a high acute GV was related to an increased incidence of MAE in patients after coronary artery bypass graft, but not for those after isolated valvular surgery (p=0.04), and the association was weakened after adjustment of glycosylated hemoglobin (p=0.01). Moreover, a high acute GV was also related to an increased risk of in-hospital mortality (OR: 1.55, 95% CI: 1.15 to 2.09, p=0.004; I22=0%). A high acute GV may be associated with poor in-hospital outcomes in patients after cardiac surgery.

A Consensus Statement for Continuous Glucose Monitoring Metrics for Inpatient Clinical Trials

Diabetes Technology Society organized an expert consensus panel to develop metrics for research in the use of continuous glucose monitors (CGMs) in a hospital setting. The experts met virtually in small groups both before and after an April 13, 2023 virtual meeting of the entire panel. The goal of the panel was to develop consensus definitions in anticipation of greater use of CGMs in hospital settings in the future. Establishment of consensus definitions of inpatient analytical metrics will be easier to compare outcomes between studies. Panelists defined terms related to 10 dimensions of measurements related to the use of CGMs including (1) hospital hypoglycemia, (2) hospital hyperglycemia, (3) hospital time in range, (4) hospital glycemic variability, (5) hospital glycemia risk index, (6) accuracy of CGM devices and reference methods for CGMs in the hospital, (7) meaningful time blocks for hospital glycemic goals, (8) hospital CGM data sufficiency, (9) using CGM data for insulin dosing, and (10) miscellaneous factors. The panelists voted on 51 proposed recommendations. Based on the panel vote, 51 recommendations were classified as either strong (43) or mild (8). Additional research is needed on CGM performance in the hospital. This consensus report is intended to support that type of research intended to improve outcomes for hospitalized people with diabetes.

Glucose variability: a new risk factor for cardiovascular disease

AIMS AND DATA SYNTHESIS

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

CONCLUSIONS

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

Glycemic Variability and Prognosis of Patients with Intracerebral Hemorrhage: A Meta-Analysis

Glycemic disorder may affect the outcomes of patients with intracerebral hemorrhage (ICH). However, the association between glycemic variability (GV) and prognosis in these patients remains to be determined. We performed a meta-analysis to compressive the influence of GV on functional outcome and mortality in patients with ICH. Observational studies comparing the risks of poor functional outcome (defined as modified Rankin Scale>2) and all-cause mortality between ICH patients with higher versus lower acute GV were retrieved by systematic search of Medline, Web of Science, Embase, CNKI, and Wanfang databases. A random-effect model was used to pool the data after incorporating the between-study heterogeneity. Sensitivity analyses were performed to evaluate the stability of the findings. Eight cohort studies involving 3400 patients with ICH were included in the meta-analysis. The follow-up duration was within 3 months after admission. All of the included studies used standard deviation of blood glucose (SDBG) as the indicator of acute GV. Pooled results showed that ICH patients with higher SDBG were associated with a higher risk of poor functional outcome as compared to those with lower SDBG [risk ratio (RR): 1.84, 95% confidence interval (CI): 1.41 to 2.42, p<0.001, I2=0%]. In addition, patients with higher category of SDBG were also associated with a higher mortality risk (RR: 2.39, 95% CI: 1.79 to 3.19, p<0.001, I2=0%). In conclusion, high acute GV may be a predictor of poor functional outcome and mortality of patients with ICH.

Anagliptin twice-daily regimen improves glycaemic variability in subjects with type 2 diabetes: A double-blind, randomized controlled trial

AIM

To determine whether the twice-daily (BID) regimen is superior to the once-daily (QD) regimen for managing glycaemic variability by comparing the effects of anagliptin 100 mg BID versus sitagliptin 100 mg QD.

MATERIALS AND METHODS

A double-blinded, randomized, multicentre study was performed in 89 patients with type 2 diabetes treated with metformin alone (6.5% < HbA1c < 8.5%). Subjects were randomly assigned to anagliptin 100 mg BID or sitagliptin 100 mg QD in a 1:1 ratio for 12 weeks. Continuous glucose monitoring was used to measure the mean amplitude of glycaemic excursion (MAGE) and postprandial time in range (TIR) before and after dipeptidyl peptidase-4 (DPP-4) inhibitor treatment to compare glycaemic variability.

RESULTS

The decrease from baseline in MAGE at 12 weeks after DPP-4 inhibitor treatment was significantly greater in the anagliptin BID group than in the sitagliptin QD group (P < .05); -30.4 ± 25.6 mg/dl (P < .001) in the anagliptin group versus -9.5 ± 38.0 mg/dl (P = .215) in the sitagliptin group. The TIR after dinner increased by 33.0% ± 22.0% (P < .001) in the anagliptin group and by 14.6% ± 28.2% (P = .014) in the sitagliptin group, with a statistically significant difference (P = .009). No statistically significant differences were observed between the groups in the changes in HbA1c and fasting plasma glucose (FPG).

CONCLUSIONS

The anagliptin BID regimen for the treatment of type 2 diabetes was superior in blood glucose control after dinner to improve glycaemic variability, as indicated by MAGE and TIR, but was equivalent to the QD regimen in terms of HbA1c and FPG.

Insulin resistance is associated with an unfavorable outcome among non-diabetic patients with isolated moderate-to-severe traumatic brain injury – A propensity score-matched study

Background

Hyperglycemia is an independent risk factor for the poor prognosis in patients with traumatic brain injury (TBI), and stress-induced impaired insulin function is the major factor of hyperglycemia in non-diabetic patients with TBI. Several types of research suggested that insulin resistance (IR) is related to the poor prognosis of neurocritical ill patients; here we focused on the role of IR in non-diabetic patients after TBI.

Methods

We performed a prospective observational study with the approval of the Ethics Committee of our institute. IR was accessed via the update Homeostasis Model Assessment (HOMA2) of IR, a computer-calculated index by glucose and insulin level. HOMA2 ≥ 1.4 was considered as the threshold of IR according to the previous studies. The glycemic variability (GV) indices were calculated by fingertip blood glucose concentration at an interval of 2 h within 24 h to explore the relationship between IR and GV. The outcome was the 6-month neurological outcome evaluated with the Glasgow outcome scale.

Results

A total of 85 patients with isolated moderate-to-severe TBI (admission GCS ≤ 12) were finally included in our study, 34 (40%) were diagnosed with IR with HOMA2 ≥ 1.4. After propensity score matching (PSM), 22 patients in IR group were matched to 34 patients in non-IR group. Patients with IR suffered increased systemic glycemic variation after isolated moderate-to-severe TBI. IR was a significant factor for the poor prognosis after TBI (OR = 3.25, 95% CI 1.03–10.31, p = 0.041).

Conclusions

The IR estimated by HOMA2 was associated with greater GV and an unfavorable outcome after isolated moderate-to-severe TBI. Ameliorating impaired insulin sensitivity may be a potential therapeutic strategy for the management of TBI patients.

Acute glycemic variability and mortality of patients with acute stroke: a meta-analysis

BACKGROUND

Increased glucose fluctuation has been related to poor prognosis in patients with critical illnesses, while its prognostic role in patients with acute stroke remains unknown. The meta-analysis aimed to evaluate the association between the acute glycemic variation (GV) and mortality risk in patients with acute stroke.

METHODS

Cohort studies were obtained by searching Medline, Web of Science, Embase, Wanfang and CNKI databases. A random-effect model which incorporates the intra-study heterogeneity was chosen to pool the results.

RESULTS

Ten cohort studies with 1433 patients were included, and 280 (19.5%) of them died within 90 days of disease onset. Results of the meta-analyses showed that a higher acute GV was associated with an increased risk of early mortality in patients with acute stroke, as indicated by GV measured with the coefficient of variation of blood glucose (CVBG, odds ratio [OR]: 2.24, 95% CI 1.40 to 3.58, p < 0.001, I2 = 73%), the standard deviation of blood glucose (SDBG, OR: 2.31, 95% CI 1.70 to 3.13, p < 0.001, I2 = 50%), and the mean amplitude of glycemic excursion (OR: 3.57, 95% CI 1.44 to 8.85, p = 0.006, I2 = 23%). For acute GV measured with CVBG and SDBG, subgroup analyses showed consistent results in patients with acute ischemic and hemorrhagic stroke, and for studies reporting 28-day and 90-day all-cause mortality (p for subgroup analysis all > 0.05).

CONCLUSIONS

Higher acute GV may be an independent risk factor of early mortality in patients with acute stroke.

Acute glycemic variability and risk of mortality in patients with sepsis: a meta-analysis

BACKGROUND

Acute glycemic variability (GV) has been correlated with the severity of sepsis. The aim of the study was to evaluate the potential association between acute GV and mortality risk in patients with sepsis.

METHODS

Cohort studies comparing the risk of death within 3 months between septic patients with higher versus lower acute GV were retrieved by systematic search of Medline, Embase, Web of Science, Wanfang and CNKI databases. We used a random-effect model to pool the data by incorporating the between-study heterogeneity. Sensitivity analyses were performed to evaluate the stability of the findings.

RESULTS

Ten studies including 4296 patients were available for the meta-analysis. Pooled results showed that septic patients with higher acute GV had significantly increased mortality risk compared to those with lower acute GV, as evidenced by results using different parameters including standard deviation of blood glucose (SDBG, risk ratio [RR]: 1.74, 95% confidence interval [CI] 1.36-2.24, p < 0.001; I² = 0%), coefficient of variation of blood glucose (RR: 1.91, 95% CI 1.57-2.31, p < 0.001; I² = 0%), mean amplitude of glycemic excursion (RR: 1.81. 95% CI 1.36-2.40, p < 0.001; I² = 0%), and glycemic lability index (RR: 2.52, 95% CI 1.72-3.68, p < 0.001; I² = 0%). Sensitivity analyses by excluding one study at a time did not significantly affect the results (p all < 0.05).

CONCLUSIONS

Higher acute GV may be a predictor of mortality risk in patients with sepsis.

New Horizons: Next-Generation Insulin Analogues: Structural Principles and Clinical Goals

Design of "first-generation" insulin analogues over the past 3 decades has provided pharmaceutical formulations with tailored pharmacokinetic (PK) and pharmacodynamic (PD) properties. Application of a molecular tool kit-integrating protein sequence, chemical modification, and formulation-has thus led to improved prandial and basal formulations for the treatment of diabetes mellitus. Although PK/PD changes were modest in relation to prior formulations of human and animal insulins, significant clinical advantages in efficacy (mean glycemia) and safety (rates of hypoglycemia) were obtained. Continuing innovation is providing further improvements to achieve ultrarapid and ultrabasal analogue formulations in an effort to reduce glycemic variability and optimize time in range. Beyond such PK/PD metrics, next-generation insulin analogues seek to exploit therapeutic mechanisms: glucose-responsive ("smart") analogues, pathway-specific ("biased") analogues, and organ-targeted analogues. Smart insulin analogues and delivery systems promise to mitigate hypoglycemic risk, a critical barrier to glycemic control, whereas biased and organ-targeted insulin analogues may better recapitulate physiologic hormonal regulation. In each therapeutic class considerations of cost and stability will affect use and global distribution. This review highlights structural principles underlying next-generation design efforts, their respective biological rationale, and potential clinical applications.