<scp>Continuous glucose monitoring</scp> metrics (Mean Glucose, time above range and time in range) are superior to <scp>glycated haemoglobin</scp> for assessment of therapeutic efficacy

Rodbard, David

doi:10.1111/dom.14906

Cited by 16 publications

(4 citation statements)

References 33 publications

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“…Additionally, TAR is a useful measure for re‐evaluation of the treatment plan and insulin dose adjustments. Recently, Rodbard et al argued that TAR may allow a better assessment of therapeutic efficacy compared with TIR or HbA1c 28 . In the present study, we found that GRI can provide a comparable value to TIR, TAR or HbA1c in risk discrimination for DR. Our findings suggest that GRI has the potential to be a valuable research endpoint or clinical measure.…”

Section: Discussionsupporting

confidence: 72%

“…In addition, we compared the predictive value for incident DR between GRI and other glycaemic metrics including TIR, TAR and HbA1c. As evidence has accumulated supporting the associations of TIR with the risk of numerous diabetes-related outcomes, [8][9][10][11][12][13][26][27][28] TIR has been advocated as a key CGM metric. With regard to DR, from our previous analysis of cross-sectional data from 3262 patients with type 2 diabetes, we observed that TIR obtained from 3-day CGM data is related to varying degrees of DR. 14 Furthermore, in a post hoc analysis of the seven-point self-monitored blood glucose data from the Diabetes Control and Complications Trial, TIR was also found to be strongly associated with the risk of retinopathy progression in type 1 diabetes.…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Association between glycaemia risk index (GRI) and diabetic retinopathy in type 2 diabetes: A cohort study

Wang

et al. 2023

Diabetes Obesity Metabolism

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Aim: To investigate the association between a new composite metric, glycaemia risk index (GRI), and incident diabetic retinopathy (DR).Methods: A total of 1204 adults with type 2 diabetes without DR at baseline were included between 2005 and 2019 from a single centre in Shanghai, China. GRI was obtained from continuous glucose monitoring data at baseline. Cox proportion hazard regression analysis was used to assess the association between GRI and the risk of incident DR.Results: During a median follow-up of 8.4 years, 301 patients developed DR. The multivariable-adjusted hazard ratios (HRs) for incident DR across ascending GRI quartiles (≤14 [reference], 15 $ 28, 29 $ 47 and > 47) were 1.00, 1.05 (95% CI 0.74-1.48), 1.33 (95% confidence interval [CI] 0.96-1.84) and 1.53 (95% CI 1.11-2.11), respectively. For each 1-SD increase in GRI, the risk of DR was increased by 20% (HR 1.20, 95% CI 1.07-1.33) after adjustment for confounders. Conclusions:In patients with type 2 diabetes, higher GRI is associated with an increased risk of incident DR. GRI has the potential to be a valuable clinical measure, which needs to be further explored in future studies.

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Section: Discussionsupporting

confidence: 72%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Association between glycaemia risk index (GRI) and diabetic retinopathy in type 2 diabetes: A cohort study

Wang

et al. 2023

Diabetes Obesity Metabolism

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“…Use of CGM metrics has been shown to be superior to glycated hemoglobin (HbA1c) for assessment of therapeutic efficacy. 3 However, because many individuals using CGM are often making critical decisions for insulin adjustments and detection of immediate or impending risk for acute glycemic events, it is important that they know they can rely on the accuracy of their glucose data. 4 Continuous glucose monitoring data have been used to also identify glucotypes to make diagnoses of atypical forms of diabetes.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Point Accuracy Between Two Widely Used Continuous Glucose Monitoring Systems

Hanson,

Kipnes,

Tran

2024

J Diabetes Sci Technol

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Background: Safe and effective self-management of glucose levels requires immediate access to accurate data. We assessed the point accuracy of the Dexcom G7 Continuous Glucose Monitoring System (Dexcom, Inc., San Diego, CA, USA) and FreeStyle Libre 3 (Abbott Diabetes Care, Alameda, CA, USA) sensors in a head-to-head comparison. Method: Multicenter, single-arm, prospective, nonsignificant risk evaluation enrolled adults (≥ 18 years) with diagnosed type 1 diabetes (T1D) or type 2 diabetes (T2D). Accuracy was assessed by comparing sensor data to laboratory reference values Yellow Springs Instrument [YSI] and capillary blood glucose values. Outcome measures were differences in mean absolute relative difference (MARD), number and percentage of matched glucose pairs within ±20 mg/dL/±20 of reference values within glucose ranges: < 54, 54 to 69, 70 to 180, 181 to 250, > 250 mg/dL, and combined. Results: Data from 55 adults were included in the analysis. Analysis showed significantly lower MARD with the FreeStyle Libre 3 sensor vs the Dexcom G7 sensor (8.9% vs 13.6%, respectively, P < .0001) with a higher percentage of glucose values within ±20 mg/dL/±20 of reference (91.4% vs 78.6%). The MARD values for both continuous glucose monitoring (CGM) sensors were similar during the first 12 hours; however, the FreeStyle Libre 3 MARD was notably lower than the Dexcom G7 MARD during the next 12 hours (10.0% vs 15.1%, respectively, P < .0001) and throughout the study period. Conclusions: The FreeStyle Libre 3 sensor was more accurate than the Dexcom G7 sensor in all metrics evaluated throughout the study period. This is the first head-to-head study to our knowledge that compares the flagship products currently in widespread use of the two largest CGM manufacturers.

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Discordance between mean glucose and time in range in relation to HbA1c in individuals with type 1 diabetes: results from the GOLD and SILVER trials

Sterner Isaksson,

Imberg,

Hirsch

et al. 2024

Diabetologia

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Aims/hypothesis Previous studies have shown that individuals with similar mean glucose levels (MG) or percentage of time in range (TIR) may have different HbA1c values. The aim of this study was to further elucidate how MG and TIR are associated with HbA1c. Methods Data from the randomised clinical GOLD trial (n=144) and the follow-up SILVER trial (n=98) of adults with type 1 diabetes followed for 2.5 years were analysed. A total of 596 paired HbA1c/continuous glucose monitoring measurements were included. Linear mixed-effects models were used to account for intra-individual correlations in repeated-measures data. Results In the GOLD trial, the mean age of the participants (± SD) was 44±13 years, 63 (44%) were female, and the mean HbA1c (± SD) was 72±9.8 mmol/mol (8.7±0.9%). When correlating MG with HbA1c, MG explained 63% of the variation in HbA1c (r=0.79, p<0.001). The variation in HbA1c explained by MG increased to 88% (r=0.94, p value for improvement of fit <0.001) when accounting for person-to-person variation in the MG–HbA1c relationship. Time below range (TBR; <3.9 mmol/l), time above range (TAR) level 2 (>13.9 mmol/l) and glycaemic variability had little or no effect on the association. For a given MG and TIR, the HbA1c of 10% of individuals deviated by >8 mmol/mol (0.8%) from their estimated HbA1c based on the overall association between MG and TIR with HbA1c. TBR and TAR level 2 significantly influenced the association between TIR and HbA1c. At a given TIR, each 1% increase in TBR was related to a 0.6 mmol/mol lower HbA1c (95% CI 0.4, 0.9; p<0.001), and each 2% increase in TAR level 2 was related to a 0.4 mmol/mol higher HbA1c (95% CI 0.1, 0.6; p=0.003). However, neither TIR, TBR nor TAR level 2 were significantly associated with HbA1c when accounting for MG. Conclusions/interpretation Inter-individual variations exist between MG and HbA1c, as well as between TIR and HbA1c, with clinically important deviations in relatively large groups of individuals with type 1 diabetes. These results may provide important information to both healthcare providers and individuals with diabetes in terms of prognosis and when making diabetes management decisions. Graphical Abstract

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Continuous glucose monitoring metrics (Mean Glucose, time above range and time in range) are superior to glycated haemoglobin for assessment of therapeutic efficacy

Cited by 16 publications

References 33 publications

Association between glycaemia risk index (GRI) and diabetic retinopathy in type 2 diabetes: A cohort study

Association between glycaemia risk index (GRI) and diabetic retinopathy in type 2 diabetes: A cohort study

Comparison of Point Accuracy Between Two Widely Used Continuous Glucose Monitoring Systems

Discordance between mean glucose and time in range in relation to HbA1c in individuals with type 1 diabetes: results from the GOLD and SILVER trials

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