Beyond A1C: exploring continuous glucose monitoring metrics in managing diabetes

Primary care diabetes assessment when HbA1c and other measures of glycemia disagree

AIMS

Although diabetes management decisions in primary care are typically based largely on HbA1c, mismatches between HbA1c and other measures of glycemia that are increasingly more available present challenges to optimal management. This study aimed to assess a systematic approach to identify the frequency of mismatches of potential clinical significance amongst various measures of glycemia in a primary care setting.

METHODS

Following screening to exclude conditions known to affect HbA1c interpretation, HbA1c, and fructosamine were obtained and repeated after ∼90 days on 53 adults with prediabetes or type 2 diabetes. A subset of 13 participants with repeat labs wore continuous glucose monitoring (CGM) for 10 days.

RESULTS

As expected, HbA1c and fructosamine only modestly correlated (initial R2 = 0.768/repeat R2 = 0.655). The HbA1c/fructosamine mismatch frequency of ± 0.5% (using the following regression HbA1c = 0.015 *fructosamine + 2.994 calculated from the initial sample) was 27.0%. Of the 13 participants with CGM data, HbA1c and CGM-based Glucose Management Indicator correlated at R2 = 0.786 with a mismatch frequency of ± 0.5% at 46.2% compared to a HbA1c/fructosamine mismatch frequency of ± 0.5% at 30.8%.

CONCLUSIONS

HbA1c is frequently mismatched with fructosamine and CGM data. As each of the measures has strengths and weaknesses, the utilization of multiple different measures of glycemia may be informative for diabetes assessment in the clinical setting.

Future of Time-in-Range Goals in the Era of Advanced Hybrid Closed-Loop Automated Insulin Delivery Systems

The concept of maintaining blood glucose levels within the 70-180 mg/dL range, known as time-in-range, has raised questions regarding its representation of true physiological euglycemia. Some have speculated that focusing on the time spent within the 70-140 mg/dL range, introduced as time in tight range (TITR) through the International Consensus statement, could serve as a more precise metric for assessing normoglycemia in individuals with type 1 diabetes. This article delves into the current status of TITR as an emerging marker and explores how advanced hybrid closed-loop systems may offer a promising avenue for achieving this higher level of glycemic control.

Effects of continuous glucose monitoring on glycaemic control in type 2 diabetes: A systematic review and network meta-analysis of randomized controlled trials

AIMS

The aim of this study was to assess the efficacy of continuous glucose monitoring (CGM) versus self-monitoring of blood glucose (SMBG) in maintaining glycaemic control among people with type 2 diabetes mellitus (T2DM).

MATERIALS AND METHODS

The protocol was registered in PROSPERO (CRD42023387583). PubMed, Web of Science, EMBASE and OVID databases were searched from 1 January 2000 until 31 December 2022 for randomized controlled trials comparing CGM with SMBG in glycaemic control among the outpatients with T2DM. The primary endpoint was glycated haemoglobin, while the secondary endpoints included time in range, time below range and time above range. Both traditional and network meta-analyses were conducted to explore the efficacy of CGM on glycaemic control in T2DM.

RESULTS

Eleven high-quality studies, involving 1425 individuals with T2DM, were identified. Traditional meta-analysis revealed that CGM exhibited a significantly decreased [mean difference (MD): -0.31, 95% confidence interval (CI) (-0.45, -0.18)], time above range [MD: -9.06%, 95% CI (-16.00, -2.11)], time below range [MD: -0.30%, 95% CI (-0.49, -0.12)] and a significantly increased time in range [MD: 8.49%, 95% CI (3.96, 13.02)] compared with SMBG. The network meta-analysis showed that real-time CGM can improve the glycaemic control of patients with T2DM to the most extent.

CONCLUSIONS

CGM could provide T2DM with greater benefits in glycaemic management compared with SMBG, particularly in patients using real-time CGM. These findings provide an updated perspective on previous research and offer guidance for CGM use in T2DM.