We assessed the prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) and significant liver fibrosis in adults with type 1 diabetes mellitus (T1DM) and the association of MASLD with insulin sensitivity and continuous glucose monitoring metrics.

We consecutively enrolled 198 adults with T1DM undergoing vibration-controlled transient elastography with liver stiffness measurement (LSM) and controlled attenuation parameter (CAP). All participants had a continuous glucose monitoring (CGM) device. Insulin sensitivity was evaluated by estimated glucose disposal rate (eGDR). MASLD was defined as CAP ≥ 248 db/m and the presence of at least one cardiometabolic risk factor. Significant liver fibrosis was defined as LSM ≥ 7 kPa.

Patients had a mean age of 56 years, mean BMI of 26.0 ± 5.9 kg/m2, and mean eGDR of 7.1 ± 2.3 mg/kg/min. 73 (37%) patients had MASLD (using a CAP threshold of 274 dB/m), 16 (8.1%) of whom had significant liver fibrosis. MASLD was associated with a significantly lower eGDR (beta coefficient = -0.367, 95% confidence interval -0.472 to -0.261; p < 0.001). This association remained significant, even after adjustment for age, sex, body mass index, plasma triglycerides, diabetes duration, daily insulin dose, time above the range of glucose levels, LSM and chronic kidney disease. No association was observed between MASLD and CGM-derived metrics. These results were not different when we used a CAP threshold of 274 dB/m for diagnosing MASLD.

In T1DM, MASLD was inversely associated with eGDR and biomarkers of insulin resistance but not with CGM-derived metrics.

People with type 1 diabetes (T1D) are usually considered to exclusively exhibit β-cell failure, but they frequently also feature insulin resistance. This review discusses the mechanisms, clinical features, and therapeutic relevance of insulin resistance by focusing mainly on human studies using gold-standard techniques (euglycemic-hyperinsulinemic clamp). In T1D, tissue-specific insulin resistance can develop early and sustain throughout disease progression. The underlying pathophysiology is complex, involving both metabolic- and autoimmune-related factors operating synergistically. Insulin treatment may play an important pathogenic role in predisposing individuals with T1D to insulin resistance. However, the established lifestyle-related risk factors and peripheral insulin administration inducing glucolipotoxicity, hyperinsulinemia, hyperglucagonemia, inflammation, mitochondrial abnormalities, and oxidative stress cannot always fully explain insulin resistance in T1D, suggesting a phenotype distinct from type 2 diabetes. The mutual interaction between insulin resistance and impaired endothelial function further contributes to diabetes-related complications. Insulin resistance should therefore be considered a treatment target in T1D. Aside from lifestyle modifications, continuous subcutaneous insulin infusion can ameliorate insulin resistance and hyperinsulinemia, thereby improving glucose toxicity compared with multiple injection insulin treatment. Among other concepts, metformin, pioglitazone, incretin-based drugs such as GLP-1 receptor agonists, sodium-glucose cotransporter inhibitors, and pramlintide can improve insulin resistance, either directly or indirectly. However, considering the current issues of high cost, side effects, limited efficacy, and their off-label status, these agents in people with T1D are not widely used in routine clinical care at present.

The estimated glucose disposal rate (eGDR) is recognized as a reliable marker of insulin resistance. However, the association between eGDR and the risk of stroke remains unclear.

A total of 13 706 middle-aged and older participants were enrolled from CHARLS (China Health and Retirement Longitudinal Study). The primary end point was the occurrence of stroke events. The Kaplan-Meier curves, Cox proportional hazard models, and restricted cubic spline analysis were applied to explore the association between eGDR and the risk of stroke according to sex, age, and glycemic status. A total of 1101 stroke events were recorded. Our findings revealed a significant nonlinear relationship between eGDR and the occurrence of stroke. The association was similar between men (hazard ratio [HR], 0.83 [95% CI, 0.80-0.87]) and women (HR, 0.86 [95% CI, 0.80-0.87]), as well as among participants with normal glucose tolerance (HR, 0.83 [95% CI, 0.79-0.87]), prediabetes (HR, 0.85 [95% CI, 0.82-0.89]), and diabetes (HR, 0.87 [95% CI, 0.82-0.92]). However, the association was stronger in middle-aged participants (HR, 0.82 [95% CI, 0.78-0.86]) compared with older individuals (HR, 0.87 [95% CI, 0.83-0.90]; P for interaction=0.019).

This study demonstrates that lower eGDR levels are significantly linked to increased stroke risk. The relationship between eGDR and stroke risk was similar across different sexes and glycemic statuses and was stronger in middle-aged participants compared with older participants.

Individuals with type 1 diabetes are at increased cardiovascular risk, particularly in the presence of insulin resistance. A prothrombotic environment is believed to contribute to this risk but thrombotic pathways in type 1 diabetes are only partially understood and the role of platelets is incompletely studied. We hypothesised that platelets from individuals with type 1 diabetes exhibit platelet hyperactivity due to both increased propensity for activation and diminished sensitivity to inhibition, with an amplified maladaptive phenotype in those with insulin resistance.

Blood samples were obtained from individuals with type 1 diabetes enrolled on the 'Double diabEtes and adVErse cLinical Outcome: identification of mechanistic Pathways' (DEVELOP) study with insulin resistance assessed as estimated glucose disposal rate (eGDR), whereby eGDR >8 or <6 mg kg-1 min-1 indicates normal insulin sensitivity or advanced insulin resistance, respectively. Platelet function was analysed using whole blood multiparameter flow cytometry to simultaneously measure three distinct markers of activation, including integrin αIIbβ3 (PAC-1 binding), P-selectin (CD62P) and phosphatidylserine (PS) (Annexin V). Both activation and inhibition responses of the platelets were investigated, which were subjected to the machine learning tool Full Annotation Shape-constrained Trees (FAUST) to characterise platelet subpopulations.

A total of 32 individuals with type 1 diabetes were studied (median age [range] of 24 [18-34] years, 59% male, diabetes duration [mean ± SD] of 14.0 ± 6.3 years and HbA1c of 65.3 ± 14.0 mmol/mol [8.1%]). An increased basal expression, measured as mean fluorescence intensity, of all three platelet activation markers was detected in the type 1 diabetes group compared with healthy control participants (CD62P expression 521 ± 246 vs 335 ± 67; p<0.001, PAC-1 370 ± 165 vs 231 ± 88; p=0.011 and PS 869 ± 762 vs 294 ± 109; p=0.001). Following platelet stimulation, an enhanced activation of these markers was found in the type 1 diabetes group. Within the type 1 diabetes group, those with advanced insulin resistance (eGDR<6 mg kg-1 min-1) showed increased platelet activation compared with individuals with normal insulin sensitivity (eGDR>8 mg kg-1 min-1) with single agonist stimulation CD62P expression (29,167 ± 2177 vs 22,829 ± 2535, p<0.001 and PAC-1 19,339 ± 11,749 and 5187 ± 2872, p=0.02). Moreover, individuals with type 1 diabetes showed reduced sensitivity to platelet inhibition by prostacyclin (PGI2) compared with control participants. Stratification of individuals with type 1 diabetes by insulin resistance demonstrated that in the presence of PGI2, suppression of stimulated CD62P was 17 ± 11% and 33 ± 12% (p=0.02) for advanced insulin resistance and normal insulin sensitivity groups, respectively, with even larger differences demonstrated for PAC-1 (48 ± 17% and 75 ± 7%; p=0.006) and PS exposure (33 ± 12% and 84 ± 10%; p=0.001). Furthermore, FAUST analysis showed that, under basal conditions, there was a different distribution of the eight platelet subpopulations comparing advanced insulin resistance and normal insulin sensitivity groups, with differences also detected following PGI2 inhibition.

Our novel characterisation of platelets in type 1 diabetes shows a maladaptive phenotype with increased basal activity together with hyperactivation following stimulation and diminished responses to inhibition. Insulin resistance appears to further drive this adverse thrombotic phenotype, suggesting an enhanced platelet-driven cardiovascular risk in those with type 1 diabetes and reduced insulin sensitivity.

Insulin resistance (IR) plays a major role in increasing the risk of stroke. The objective of this research is to systematically evaluate and compare the impact of cumulative exposure over time to four commonly used IR surrogates-triglyceride-glucose (CumTyG) index, metabolic score for IR (CumMetS-IR), estimated glucose disposal rate (CumeGDR) and triglyceride to high-density lipoprotein cholesterol (CumTG/HDL-C) ratio-on stroke risk, providing insights for optimizing monitoring strategies for primary stroke prevention.

The study population was sourced from the China Health and Retirement Longitudinal Study (CHARLS2011-2018). Cumulative exposure to IR (CumIR) surrogates was calculated as the mean value of IR surrogates measured in the first and third waves of CHARLS, multiplied by the total exposure duration. The primary endpoint was incident stroke, determined through questionnaires in the third and fourth waves of CHARLS. Multivariable Cox regression models were applied to estimate and compare HRs and 95% CIs for stroke across quartiles of CumIR surrogates.

A total of 4,669 participants with no history of stroke at baseline were included. During a median follow-up of 6 years, 347 new stroke events (7.43%) were recorded. The incidence rates of stroke in the highest quartiles of CumTyG index, CumTG/HDL-C ratio, and CumMetS-IR, as well as the lowest quartile of CumeGDR, were 9.67%, 9.93%, 10.45%, and 13.02%, respectively. In terms of risk assessment, the multivariable Cox regression analysis showed that the highest quartiles of CumTyG index, CumTG/HDL-C ratio, and CumMetS-IR and the lowest quartile of CumeGDR were associated with stroke risk, with corresponding HR (95% CI) of 1.48(1.05-2.10), 1.61(1.15-2.24), 1.72(1.21-2.43), and 3.57(2.25-5.68), respectively. In terms of event prediction, receiver operating characteristic analysis revealed that CumeGDR had the highest predictive accuracy for incident stroke compared with other common IR surrogates.

In assessing stroke risk and predicting events in middle-aged and elderly populations, cumulative exposure to eGDR demonstrates significant advantages over other common IR surrogates. Incorporating eGDR as an IR monitoring marker is recommended for primary stroke prevention.

Estimated glucose disposal rate (eGDR) is a measure of insulin sensitivity. While recent evidence suggests its role in cardiovascular risk assessment in Type 1 diabetes, its associations with cardiovascular disease (CVD), diabetic microvascular complications (DMC), and mortality across different populations remain unclear.

We systematically searched Medline, EMBASE, Web of Science, and the Cochrane Library up to September 1st, 2024, following PRISMA guidelines. We examined associations between eGDR and CVD, DMC (including diabetic retinopathy, nephropathy, and peripheral neuropathy), and all-cause mortality using random-effects models. Secondary analysis assessed mean eGDR levels in diabetes populations.

Nineteen observational studies (185,810 participants) examined clinical outcomes, while 50 studies reported mean eGDR values. In patients with Type 1 diabetes (T1DM), each 1-unit (mg/kg/min) increase in eGDR was associated with lower risks of CVD (HR 0.78; 95% CI 0.69-0.87; I2 = 68%) and all-cause mortality (HR 0.83; 95% CI 0.79-0.88; I2 = 0%). The association between eGDR and DMC in T1DM was not statistically significant (HR 0.86; 95% CI 0.72-1.03; I2 = 25%). In patients with Type 2 diabetes (T2DM), each 1-unit (mg/kg/min) increase in eGDR was associated with reduced all-cause mortality (HR 0.90; 95% CI 0.84-0.97; I2 = 62%). Similarly, in the general population, each 1-unit (mg/kg/min) increase in eGDR was associated with decreased mortality risk (HR 0.88; 95% CI 0.82-0.94; I2 = 48%). The pooled mean eGDR was higher in patients with T1DM (8.19 mg/kg/min; 95% CI 7.81-8.57; I2 = 99%) compared to those with T2DM (7.03 mg/kg/min; 95% CI 4.89-9.17; I2 = 100%).

Higher eGDR levels were consistently associated with lower risks of CVD and mortality in T1DM, with similar associations observed for mortality in T2DM. In the general population, higher eGDR levels were associated with reduced mortality risk. The relationship between eGDR and DMC requires further investigation, particularly in T2DM. These findings suggest eGDR's potential utility as a risk assessment tool, though its clinical application may vary across different populations.

Cardiovascular disease (CVD) remains a major global health challenge, particularly affected by glucose metabolism status. However, the relationship between estimated glucose disposal rate (eGDR) and future CVD risk across different glucose metabolism status remains unclear.

We analyzed data from the China Health and Retirement Longitudinal Study (2011-2020) of participants aged ≥ 45 years. The eGDR was calculated using waist circumference, hypertension status, and HbA1c levels. CVD events (stroke or cardiac events) were the outcome. Participants were categorized by glucose metabolism status (normoglycemia, prediabetes, diabetes). Cox proportional hazards models and restricted cubic splines were used to assess associations and potential non-linear relationships.

Among 7,828 participants (52.84% male, mean age 59.01 ± 9.21 years) followed for an average of 8.29 years, 1,944 participants (24.83%) developed CVD. Higher eGDR was inversely associated with CVD risk across all glucose metabolism states. Below the inflection points (11.77, 11.15, and 11.56 mg/kg/min for normoglycemia, prediabetes, and diabetes, respectively), each 1-unit increase in eGDR reduced CVD risk by 14% (HR = 0.86, 95%CI: 0.83-0.89), 10% (HR = 0.90, 95%CI: 0.86-0.93), and 14% (HR = 0.86, 95%CI: 0.81-0.91), respectively.

The eGDR demonstrates a potentially non-linear inverse association with future CVD risk across different glucose metabolism states.

To investigate the association between estimated glucose disposal rate (eGDR), a surrogate marker of insulin resistance, and Parkinson's disease (PD) risk, and to examine the relationship between eGDR and all-cause mortality among PD patients.

Using data from the National Health and Nutrition Examination Survey (NHANES) 2003-2016, we conducted a cross-sectional study of 20,767 participants aged ≥40 years. eGDR was calculated using waist circumference, hypertension status, and HbA1c levels. PD cases were identified through anti-parkinsonian medication use. The association between eGDR and PD was examined using weighted logistic regression models with progressive adjustment for potential confounders. Survival analysis was performed in 255 PD patients to assess the relationship between eGDR and all-cause mortality.

Among participants, 256 had PD (weighted prevalence: 1.23%). Higher eGDR was associated with lower odds of PD in crude analysis (OR: 0.906, 95% CI: 0.856-0.960, P < 0.001). After full adjustment, the highest eGDR tertile showed significantly lower odds of PD compared to the lowest tertile (OR: 0.574, 95% CI: 0.337-0.976, P = 0.040). Restricted cubic spline analysis revealed a significant M-shaped non-linear relationship between eGDR and PD risk (P for non-linearity < 0.001). In survival analysis, higher eGDR was associated with lower mortality risk (adjusted HR: 0.875, 95% CI: 0.775-0.987, P = 0.030), with an inverted U-shaped relationship observed (P for non-linearity = 0.0352).

Higher eGDR levels are associated with lower PD risk and better survival in PD patients, suggesting that insulin sensitivity might play a role in PD pathogenesis and progression. These findings highlight the potential importance of metabolic health in PD.

Previous studies have shown that eGDR and TyG, as indicators of insulin resistance (IR), were key risk factors for cardiovascular disease (CVD). Our study further explored the relationship between eGDR change and new-onset CVD, and compared the predictive value of eGDR change, eGDR and TyG.

A total of 2895 participants without CVD at baseline from the China Health and Retirement Longitudinal Study (CHARLS) were included, using K-means clustering and cumulative eGDR to measure eGDR change between 2012 and 2015. Cox and restricted cubic splines (RCS) regression models assessed the relationship between eGDR change and new-onset CVD. The predictive value of TyG, eGDR and eGDR change for outcomes was evaluated using receiver operating characteristic (ROC) curves, net reclassification improvement (NRI) and integrated discrimination improvement (IDI).

During a mean follow-up of 4.42 years, 581 CVD cases occurred, including 389 heart disease cases and 249 stroke cases. Participants with consistently low eGDR had a higher new-onset CVD risk (HR: 2.51, 95%CI: 2.04-3.09). A stepwise increase of outcomes was observed with the increased cumulative eGDR (p for trend <0.001). Further analysis showed the correlation between cumulative eGDR and outcomes was linear. Compared to eGDR and TyG, cumulative eGDR exerted greater predictive effect as evaluated by area under curve, IDI and NRI.

Sustained low eGDR was related to an increased risk of new-onset CVD in middle-aged and elderly population. Continuous monitoring of eGDR significantly enhances the accuracy of new-onset CVD risk stratification, which may reduce the incidence of new-onset CVD.

To investigate the relationship between estimated glucose disposal rates (eGDR) and the progression of frailty, using longitudinal data.

We analyzed four waves of data from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2018, involving 6,778 middle-aged and older adults. eGDR was calculated using a specific formula, categorizing participants into high and low eGDR groups based on the lowest quartile (8.5). Frailty status was assessed using the frailty index (FI). Linear mixed-effects models were employed to analyze the association between eGDR and frailty progression, as well as the impact of transitions in eGDR.

We found that the baseline FI was significantly higher in the low eGDR group compared to the high eGDR group. Furthermore, participants in the low eGDR group exhibited a faster progression of frailty, compared to those in the high eGDR group. Among non-frail participants at baseline, the association between low eGDR and accelerated frailty progression was even more pronounced. Further analysis revealed that, compared to participants who maintained a stable high eGDR, those who transitioned from high to low eGDR and those who consistently remained in the low eGDR group both experienced significantly accelerated frailty progression. On the contrary, participants who transitioned from low to high eGDR did not show a significant acceleration in frailty progression compared to those who consistently maintained a high eGDR.

Low eGDR is linked to accelerated frailty progression in middle-aged and older Chinese adults. Transitioning from low to high eGDR may mitigate this progression, highlighting the importance of eGDR in frailty management.

Estimated glucose disposal rate (eGDR) is a novel insulin resistance (IR) assessment surrogate. Although it has shown promising potential in other metabolic disease studies, no research has yet explored its relationship with osteoarthritis (OA). Therefore, this study aims to investigate the association between eGDR and OA in a cross-sectional observational cohort.

Data utilized in this cross-sectional study were drawn from the National Health and Nutrition Examination Survey (NHANES). Logistic regression models were used to evaluate the association between eGDR and OA, stratified analysis was applied to assess the stability of the results.

A total of 19,040 participants were included in the study, including 2,001 OA patients and 17,039 non-OA participants with an age distribution ranging from 20 to 85 years. The fully adjusted logistic regression model shows that eGDR were less likely associated with OA compared to those with non-OA (OR = 0.879, 95% CI = 0.846-0.914, P < 0.001). By dispersing the eGDR into quartiles, the correlation between eGDR and OA remained significant (P for trend < 0.0001).

This study suggests that eGDR is independently associated with OA, with lower eGDR values being linked to a higher risk of OA.

Not applicable.

Emerging evidence has identified a correlation between depression and insulin resistance (IR). This study aims to explore the correlation between estimated glucose disposal rate (eGDR)-a noninvasive and practical measure of IR-and depression in patients with diabetes mellitus (DM).

In this cross-sectional study, the data from 3,080 adults aged 18 years old or older with DM obtained from NHANES 1999-2018 were analyzed. The correlation between eGDR and depression were examined through multivariate logistic regression, subgroup analyses, restricted cubic spline (RCS) analysis, and interaction tests. Additionally, mediation analysis was conducted to assess whether leukocytes and neutrophils could mediate the effects of eGDR on depression.

Multivariate logistic regression and RCS analyses demonstrate that eGDR was negative linearly correlated with diabetic depression (OR= 0.89; 95% CI: 0.84, 0.95). Patients with DM in Q3 and Q4 of eGDR exhibited a reduced risk of 28% and 54%, respectively, in depression, compared to those in Q1. Subgroup analyses, stratified by variables such as gender, BMI, age, education level, and medical comorbidities, consistently showed a negative correlation. Mediation analysis further indicates that neutrophils and leukocytes accounted for 4.0% and 3.6% of the correlation between eGDR and depression, respectively.

The results of this study demonstrated a statistically significant inverse linear correlation between eGDR and the prevalence of depression in patients with DM, with leukocytes and neutrophils acting as mediating factors in this correlation.

Metabolic syndrome (MS) is a complex metabolic disorder that is often closely associated with the development of chronic diseases such as cardiovascular disease and diabetes. This study aimed to explore the relationship between estimated glucose metabolic rate (eGDR) and MS. The correlation between eGDR levels and the prevalence of metabolic syndrome was analyzed here based on data from the National Health and Nutrition Examination Survey from 2005 to 2020. The study sample consisted of 63,131 adult participants, and the results showed that lower eGDR levels were significantly associated with a higher prevalence of metabolic syndrome. Further regression analyses showed that eGDR acted as a protective factor and that the risk of MS significantly decreased as its level increased. Subgroup analyses showed that this trend held across gender, age, and BMI categories, and that the protective effect of eGDR was weaker in the higher BMI group. Based on the nonlinear relationship between subjects' eGDR levels and MS prevalence, RCS analyses further confirmed a significant correlation between lower eGDR levels and increased risk of MS. In conclusion, the present study suggests that eGDR levels could serve as a potential biomarker for predicting metabolic syndrome, providing new perspectives for early screening and intervention of MS.

Prediabetes is a chronic condition characterized by elevated blood glucose levels that are not yet high enough to be classified as diabetes. It is particularly prevalent among middle-aged and elderly populations. This study aims to investigate the association between a novel marker of insulin resistance-the estimated glucose disposal rate (eGDR)-and the reversion of prediabetes to normoglycaemia or progression to diabetes in a Chinese population.

This prospective cohort study utilized baseline data from the 2011 China Health and Retirement Longitudinal Study involving 2,600 prediabetic participants aged 45 years and older, along with follow-up data from 2015. The study's endpoints were defined according to the American Diabetes Association criteria, including maintenance of the prediabetic state, reversion to normoglycaemia, or progression to diabetes. Multivariable Cox regression models and restricted cubic spline regression were used to assess the association between eGDR and the reversion or progression of prediabetes in middle-aged and elderly populations, followed by stratified analyses to explore potential population-specific dependencies.

Over a median follow-up period of 4 years, 1,615 (62.1%) participants remained in the prediabetic state, 586 (22.5%) reverted to normoglycaemia, and 399 (15.3%) progressed to diabetes. In multivariable Cox regression analyses, our results indicated that eGDR was positively associated with the reversion of prediabetes to normoglycaemia [Hazard Ratio = 1.14, 95% Confidence Interval: 1.05, 1.23], and negatively associated with the progression of prediabetes to diabetes (HR = 0.81, 95% CI: 0.70, 0.93). Restricted cubic spline analysis revealed a nonlinear, L-shaped association between eGDR and the reversion of prediabetes to normoglycaemia, with segmented Cox regression identifying an eGDR threshold of 6.81 as the point of significant change in the likelihood of prediabetes reversion.

This prospective cohort study among middle-aged and elderly Chinese populations suggested that higher eGDR promoted the reversion of prediabetes and provided a protective effect against its progression to diabetes.

Cardiovascular-Kidney-Metabolic (CKM) syndrome is characterized by the interrelatedness of chronic kidney disease (CKD), cardiovascular disease (CVD), and metabolic disorders. The relationship between estimated glucose disposal rate (eGDR) and CVD risk in CKM syndrome remains unclear.

We analyzed data from 7,849 participants aged ≥ 45 years in the China Health and Retirement Longitudinal Study (CHARLS). The eGDR was calculated using waist circumference, hypertension, and HbA1c. Cox regression and restricted cubic spline (RCS) regression analyses examined the association between eGDR and CVD (stroke or cardiac events).

During a mean follow-up of 8.29 ± 1.67 years, among 7,849 participants (mean age 62.4 ± 8.7 years; 52.82% male), 1,946 CVD events occurred, including 1,504 cardiac events and 663 strokes. CKM stages 0-3 comprised 492 (6.27%), 1,404 (17.89%), 5,462 (69.59%), and 491 (6.26%) of participants, respectively. A U-shaped relationship between eGDR and CVD risk was identified (turning point: 11.82 mg/kg/min). Below this turning point, each unit increase in eGDR decreased CVD risk by 12% (HR: 0.88, 95% CI: 0.86-0.90, P < 0.0001); above it, each unit increase raised the risk by 19% (HR: 1.19, 95% CI: 1.04-1.37, P = 0.0135).

Our findings reveal a U-shaped relationship between eGDR and CVD risk in CKM syndrome stages 0-3. A higher or lower eGDR was associated with an increased CVD risk.

Objectives: This study aims to assess the association between the estimated glucose disposal rate (eGDR) and the risk of diabetic microvascular complications in patients with T1DM.Methods: A systematic search of PubMed, Scopus, and Web of Science was conducted up to August 2024, including studies that examined the relationship between eGDR and diabetic retinopathy (DR), diabetic kidney disease (DKD), and diabetic neuropathy (DN) in patients with T1DM. A meta-analysis was performed to compare the eGDR values in patients with and without microvascular complications and assess the risk of these complications.Results: 22 studies were included. Lower eGDR values were significantly associated with a higher risk of microvascular complications. Specifically, a one-unit increase in eGDR was associated with a 18% reduction in the risk of DKD (ES: 0.82, 95% CI: 0.74-0.92), a 21% reduction in the risk of DR (OR: 0.79, 95% CI: 0.73-0.85). Patients with DKD, DR, and DN had eGDR values significantly lower by 1.29, 0.75, and 0.64 units, respectively, compared to those without complications.Conclusion: This meta-analysis highlights the potential role of eGDR as a non-invasive marker for the early detection of microvascular complications, highlighting the importance of regular eGDR monitoring to facilitate timely interventions.

The relationship between the incidence of major cardiovascular diseases (CVDs) and estimated glucose disposal rate (eGDR), a proxy measurement for insulin resistance (IR), is not well understood in the general population. The predictive value of eGDR and other proxies of IR for CVD incidents have not been examined in previous studies. This study aimed to investigate the association between eGDR and various CVD events, including myocardial infarction (MI), heart failure (HF), atrial fibrillation (AF) and ischemic stroke. Additionally, the predictive values of eGDR, triglyceride-glucose (TyG) index, TyG-waist circumference (WC), TyG-body mass index (BMI), TyG-waist-to-height ratio (WHtR), triglyceride (TG)-to-high density lipoprotein cholesterol (HDL-C) ratio (TG/HDL-C) and the metabolic score for insulin resistance (METS-IR) for CVD events were compared.

The study population was extracted from the UK Biobank, and the CVD events were documented by linking to hospital records. Cox proportional hazards model and the restricted cubic spline model were used to assess the association between eGDR and the risk of CVDs with adjustment for potential confounders. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used to compare the predictive values of eGDR, TyG, TyG-WC, TyG-BMI, TyG-WHtR, TG/HDL-C and METS-IR.

A total of 360 953 participants were included in this study. During a median follow-up of 13.8 years, 12 698 MI, 10 360 HF, 23 638 AF and 6512 ischemic stroke events were documented. Compared with participants in the lowest quartile category of eGDR, those in the highest quartile category had the adjusted hazard ratio (HR) and 95% confidence interval (CI) of 0.59 (0.51-0.67) for MI, 0.66 (0.56-0.76) for HF, 0.88 (0.80-0.98) for AF and 0.73 (0.61-0.89) for ischemic stroke. eGDR outperformed TyG, TyG-WC, TyG-BMI, TyG-WHtR, TG/HDL-C and METS-IR in terms of predicting MI (AUC: 0.661), HF (AUC: 0.690), AF (AUC: 0.653) and ischemic stroke (AUC: 0.646).

eGDR was inversely associated with the incidence of MI, HF, AF and ischemic stroke in the general population. eGDR could serve as a more valuable predictive indicator than TyG, TyG-WC, TyG-BMI, TyG-WHtR, TG/HDL-C and METS-IR for CVD events in clinical practice.

This study investigates the association between estimated glucose disposal rate (eGDR), a measurement of insulin resistance, and microvascular and macrovascular complications in patients with type 2 diabetes (T2D).

This cross-sectional study enrolled 7471 patients with T2D from 2010 to 2023. The eGDR was calculated using waist circumference, HbA1C levels, and hypertension status. Logistic regression analysis and restricted cubic splines were utilised to examine the relationship between eGDR and vascular complications, including nephropathy, retinopathy, and coronary artery disease (CAD). The robustness of the results and between-group interactions were examined by sensitivity and subgroup analysis. Furthermore, receiver operating characteristic (ROC) curve analysis was employed to assess the discriminatory value of the adjusted model for T2D vascular complications.

Among participants, 56.5% were female, with a mean age of 57.04 ± 11.05 years and a median of 8 years of diabetes duration. In the final adjusted model, each unit increase in the standard deviation of eGDR was significantly associated with a 23.6%, 24.8% and 29.6% decrease in the odds of nephropathy, retinopathy, and CAD, respectively. There was a significant association between higher eGDR quartiles compared to Q1 for all complications (p < 0.05). The Q4 group had the lowest adjusted odds ratios (ORs) compared to the Q1 group for all complications; the OR of Q4 was 0.549 for nephropathy, 0.360 for retinopathy, and 0.396 for CAD (p < 0.001). The restricted cubic spline for nephropathy followed a negative nonlinear association with eGDR, whereas for retinopathy and CAD, it followed a negative linear pattern. The effect of eGDR was consistent among different subgroups. The ROC curve analysis of the adjusted model showed good discriminatory power for all complications.

In patients with type 2 diabetes, a higher eGDR was significantly associated with a lower risk of microvascular and macrovascular complications, regardless of well-known confounders.

Frailty is a common geriatric syndrome associated with many adverse health outcomes. Identifying the risk factors of frailty is crucial and the insulin resistance (IR) is considered as a potential target. The estimated glucose disposal rate (eGDR) is a simple and reliable surrogate marker of IR. Associations of eGDR with frailty have not been explored. This study aimed to investigate the associations of eGDR with frailty progression.

We used data from two prospective cohorts of the China Health and Retirement Longitudinal Study (CHARLS) and Health and Retirement Study (HRS). The eGDR was calculated as follows: eGDR (mg/kg/min) = 21.158 - (0.09×waist circumference) - (3.407×hypertension) - (0.551×glycosylated hemoglobin A1c) [waist circumference (cm), hypertension (yes = 1/no = 0), and glycosylated hemoglobin A1c (%)]. Participants were divided into three categories by tertiles of eGDR. Frailty index (FI) was calculated every two years and used to assess the degree of frailty which ranged from 0 to 100. Frailty progression was assessed by repeated measurements of FI during follow-up. Linear mixed-effect models were used to analyze the associations of eGDR with frailty progression.

8872 participants from CHARLS (mean age: 58.9 years, female: 53.3%) and 5864 participants from HRS (mean age: 67.0 years, female: 59.0%) were included. The median follow-up periods were 7.0 years in the CHARLS and 12.8 years in the HRS, respectively. Compared to participants with lower tertile (T1) of eGDR, those with upper tertile (T3) of eGDR showed decelerated FI progression (CHARLS, β: -0.294, 95%CI -0.390 to -0.198, P < 0.001; HRS, β: -0.378, 95%CI -0.474 to -0.281, P < 0.001). Continuous eGDR was also associated with FI progression for significant deceleration in FI progression with per 1 SD increase in eGDR (CHARLS, β: -0.142, 95%CI -0.181 to -0.103, P < 0.001; HRS, β: -0.170, 95%CI -0.209 to -0.130, P < 0.001). These associations were still observed after excluding baseline frail participants. Furthermore, the associations of eGDR with FI progression were consistent among participants with and without diabetes.

Regardless of diabetes or not, a higher level of eGDR was associated with the decelerated frailty progression. Our findings highlight the role of eGDR in frailty progression and recommend taking effective interventions to improve eGDR for preventing frailty progression.

Insulin resistance is a crucial factor in the development of cardiovascular diseases (CVD), yet the relationship between the estimated glucose disposal rate (eGDR), an index reflecting insulin resistance, and the risk of new-onset CVD among individuals with cardiovascular-kidney-metabolic (CKM) syndrome stage 0-3 remains underexplored, and large-scale prospective cohort studies are needed to clarify this relationship.

All data for this study were extracted from the China Health and Retirement Longitudinal Study (CHARLS). The primary outcome was the incidence of new-onset CVD (including heart diseases (HD) and stroke) during the follow-up period (from 2013 to 2020). Multivariable logistic regression models were applied to elucidate the relationship between the eGDR and the risk of developing CVD. The restricted cubic splines (RCS), mediation analysis, and stratified analyses were also employed.

This study included 6752 participants, of whom 1495 (22%) developed CVD. Odds ratios and 95% confidence intervals from lowest eGDR level (<7.37 mg/kg/min) to highest eGDR level (≥ 11.16 mg/kg/min) were 1.00 (reference), 0.81 (0.68, 0.96), 0.72 (0.58, 0.88), and 0.74 (0.58, 0.94) respectively, for the occurrence of CVD; 1.00 (reference), 0.81 (0.67,0.97), 0.72 (0.57,0.90), and 0.75 (0.58,0.97) respectively, for the occurrence of HD; 1.00 (reference), 0.91 (0.74,1.12), 0.80 (0.62,1.04), and 0.71 (0.52,0.97) respectively, for the occurrence of stroke after adjusting for all potential covariates. The RCS analysis discovered an approximately inverse "L" correlation between eGDR and the occurrence of CVD and HD across all individuals with CKM syndrome stages 0-3 (All P for overall < 0.001, All P for nonlinear = 0.005), while there was a negative linear correlation between eGDR and the risk of new-onset stroke (P for overall = 0.026, P for nonlinear = 0.098). Furthermore, the proportions mediated through BMI were 41.98%, 43.05%, and 43.23% for CVD, HD and stroke, respectively. No significant interactions were found.

The eGDR was a novel indicator of new-onset CVD in individuals with CKM syndrome stages 0-3, with BMI serving as a partial mediator in the association between eGDR and CVD risk. Addressing insulin resistance may represent a viable strategy for reducing the risk of CVD in this population.

Estimate glucose disposal rate (eGDR), Chinese visceral adiposity index (CVAI), triglyceride-glucose (TyG), TyG-body mass index (TyG-BMI), metabolic score for insulin resistance (METS-IR), and atherogenic index of plasma (AIP) are considered surrogate indexes of insulin resistance (IR). There is a lack of studies comparing the predictive values of different IR surrogate indexes for stroke risk among individuals with abnormal glucose metabolism. This study aimed to investigate the relationships between six IR surrogate indexes and stroke risk in individuals with abnormal glucose metabolism, evaluate their predictive abilities for stroke risk.

Data from the China Health and Retirement Longitudinal Study (CHARLS) were analysed in this study. Multivariate logistic regression models were applied to analyse the relationships of IR surrogate indexes with stroke risk. The dose-response relationships between IR surrogate indexes and stroke risk were explored using restricted cubic splines. The areas under the curve (AUCs) of IR surrogate indexes were calculated by receiver operating characteristic (ROC) analysis.

After adjusting for potential confounders, we observed that each standard deviation (SD) increase in eGDR was associated with a reduced risk of stroke, with an adjusted odds ratio (OR) of 0.746 [95% confidence interval (CI): 0.661-0.842]. In contrast, each SD increase in CVAI, TyG, TyG-BMI, METS-IR, and AIP were associated with an increased risk of stroke, with adjusted ORs (95% CIs) of 1.232 (1.106-1.373), 1.246 (1.050-1.479), 1.186 (1.022-1.376), 1.222 (1.069-1.396), and 1.193 (1.050-1.355), respectively. Dose-response analyses showed that eGDR, CVAI, TyG-BMI and METS-IR were linearly associated with stroke risk (Pnonlinear ≥ 0.05), whereas TyG and AIP were nonlinearly associated with stroke risk (Pnonlinear < 0.05). According to ROC analysis, The AUC of eGDR for predicting stroke risk in the overall population with abnormal glucose metabolism (AUC: 0.612, 95% CI: 0.584-0.640) was significantly higher than that of other indexes.

The six IR surrogate indexes were closely associated with high risk of stroke in individuals with abnormal glucose metabolism. The eGDR showed promising potential in predicting stroke risk in Chinese middle-aged and elderly populations with abnormal glucose metabolism.

Across its operational span of more than 25 years, the observational, nationwide, multicentre Finnish Diabetic Nephropathy (FinnDiane) Study has aimed to unravel mechanisms underlying diabetic kidney disease, with a special focus on its metabolic risk factors. We sought to compile key findings relating to this topic and to offer a current perspective on the natural course of diabetic kidney disease among individuals with type 1 diabetes.

In this narrative review, articles relevant to the subject published by the FinnDiane Study were identified and summarized together with work published by others, when relevant.

The FinnDiane Study has underscored the significance of dysglycaemia and insulin resistance, increased visceral fat mass, hypertension and dyslipidaemia-particularly high triglycerides and remnant cholesterol-as risk factors for diabetic kidney disease. Factors like abdominal obesity seem to influence the early stages of the disease, while the presence of the metabolic syndrome becomes implicated at later stages. Epidemiological reports have revealed that after an initial decline, the cumulative incidence of albuminuria plateaued post-1980s, with the progression rate to kidney failure remaining high. Fortunately, 23% of the FinnDiane cohort regressed to less advanced stages of albuminuria, improving their overall prognosis.

A substantial burden of albuminuria associated with type 1 diabetes persists, and therefore, novel kidney-protecting therapies are highly awaited. In addition, given that metabolic factors influence the progression of diabetic kidney disease both in its early and advanced stages, emphasis should be placed on ensuring that their treatment targets are met.

The estimated glucose disposal rate (eGDR) has been linked to incident cardiovascular disease (CVD) in individuals without diabetes. However, few studies have accounted for long-term cumulative eGDR exposure.

The aim of this study was to explore whether long-term cumulative eGDR was independently associated with incident CVD in individuals over the age of 50 years and without diabetes.

This study used data from the China Health and Retirement Longitudinal Study (CHARLS) and Health and Retirement Study (HRS). The cumulative eGDR was calculated as the summation of the average eGDR for each pair of consecutive examinations multiplied by the time between these two consecutive visits, in years. The outcome was incident CVD. Cox proportional hazards regression models and restricted cubic spline (RCS) regression models were used to evaluate the association between cumulative eGDR and incident CVD.

A total of 2430 participants from CHARLS and 2008 participants from HRS were included in the analysis. The median age of the participants in CHARLS at baseline was 59 years [IQR: 55-65 years], and 1205 (49.59%) were men. The median age of the participants in HRS at baseline was 64 years [IQR: 57-70 years], and 705 (35.11%) were men. The RCS regression model showed a negative and linear association between the cumulative eGDR and incidence of CVD (CHARLS: P < 0.001, P for nonlinearity = 0.248; HRS: P = 0.013, P for nonlinearity = 0.121). After multivariate adjustment, the higher levels of cumulative eGDR were independently associated with a lower risk of CVD (per SD, CHARLS: HR: 0.802, 95% CI: 0.716-0.898, HRS: HR: 0.791, 95% CI: 0.665-0.940, pooled analysis: HR: 0.799, 95% CI: 0.726-0.878).

A lower level of cumulative eGDR was associated with an increased risk of incident CVD in individuals over the age of 50 years and without diabetes. Continuous monitoring of cumulative eGDR exposure over time, based on consideration of traditional risk factors, may prove beneficial for the early identification and intervention of individuals at high risk of CVD. In regions with limited healthcare resources, among individuals with limited ability to access, process, and understand health information and services, cumulative eGDR may offer improved clinical applicability.

BACKGROUNDWe aimed to characterize factors associated with the under-studied complication of cognitive decline in aging people with long-duration type 1 diabetes (T1D).METHODSJoslin "Medalists" (n = 222; T1D ≥ 50 years) underwent cognitive testing. Medalists (n = 52) and age-matched nondiabetic controls (n = 20) underwent neuro- and retinal imaging. Brain pathology (n = 26) was examined. Relationships among clinical, cognitive, and neuroimaging parameters were evaluated.RESULTSCompared with controls, Medalists had worse psychomotor function and recall, which associated with female sex, lower visual acuity, reduced physical activity, longer diabetes duration, and higher inflammatory cytokines. On neuroimaging, compared with controls, Medalists had significantly lower total and regional brain volumes, equivalent to 9 years of accelerated aging, but small vessel disease markers did not differ. Reduced brain volumes associated with female sex, reduced psychomotor function, worse visual acuity, longer diabetes duration, and higher inflammation, but not with glycemic control. Worse cognitive function, lower brain volumes, and diabetic retinopathy correlated with thinning of the outer retinal nuclear layer. Worse baseline visual acuity associated with declining psychomotor function in longitudinal analysis. Brain volume mediated the association between visual acuity and psychomotor function by 57%. Brain pathologies showed decreased volumes, but predominantly mild vascular or Alzheimer's-related pathology.CONCLUSION To our knowledge, this is the first comprehensive study of cognitive function, neuroimaging, and pathology in aging T1D individuals demonstrated that cognitive decline was related to parenchymal rather than neurovascular abnormalities, unlike type 2 diabetes, suggestive of accelerated aging in T1D. Improving visual acuity could perhaps be an important preventive measure against cognitive decline in people with T1D.FUNDINGThe Beatson Foundation, NIH/NIDDK grants 3P30DK036836-34S1 and P30DK036836-37, and Mary Iacocca fellowships.

Insulin resistance (IR) is a central pathophysiological factor in metabolic syndrome (MetS) and an essential driver of cardiovascular disease (CVD) and mortality. The estimated glucose disposal rate (eGDR) is a reliable marker of IR and has been associated with CVD prognosis. This study aims to examine the relationship between eGDR, MetS, and their predictive roles in clinical outcomes.

Data from the NHANES (2001-2018) were utilized, with a cross-sectional design applied to evaluate the association between eGDR and MetS prevalence, and a cohort design employed for mortality follow-up. Weighted logistic regression models were used to examine the association between eGDR and MetS. Weighted Cox proportional hazard models were applied to assess the link between eGDR and both all-cause and CVD mortality. To examine the non-linear associations between the eGDR, MetS, and mortality outcomes, restricted cubic spline (RCS) analysis was applied. Additionally, the predictive performance of eGDR, and other IR indices (TyG, HOMA-IR), for mortality was assessed using the C-statistic.

A robust negative association between eGDR and MetS prevalence was found, following full covariate adjustment (p < 0.001). The core findings were consistent across subgroups (all p < 0.001). Cox regression analysis indicated that in individuals with MetS, each standard deviation (SD) increment in eGDR was associated with an 11% and 18% decrement in the risk of all-cause and CVD mortality, respectively. RCS analysis displayed a non-linear association between eGDR and MetS prevalence, while a linear association between eGDR and mortality. The C-statistic showed that eGDR, compared to the TyG index and HOMA-IR, significantly improved predictive power for all-cause mortality (p = 0.007).

eGDR is strongly associated with MetS and predicts all-cause and CVD mortality in individuals with MetS. Compared to TyG and HOMA-IR, eGDR offers superior predictive value for all-cause mortality, highlighting its potential as a useful tool in clinical risk assessment.

The Estimated Glucose Disposal Rate (eGDR) serves as a surrogate marker for insulin resistance, with numerous studies highlighting its significant prognostic value. This paper aims to analyze the impact of eGDR on cardiovascular and all-cause mortality across different glycemic metabolic statuses, including normal fasting glucose (NFG), prediabetes, and diabetes.

This study included 46,016 American adults who underwent health examinations as part of the National Health and Nutrition Examination Survey from 1999 to 2018. Multivariable Cox regression was employed to explore the relationships between eGDR and mortality rates under varying glycemic states. Additionally, Kaplan-Meier curves were used to compare the cumulative incidence of cardiovascular and all-cause mortality across different metabolic statuses. Finally, the predictive value of eGDR for mortality was assessed using receiver operating characteristic curves.

During an average follow-up of 115 months, a total of 6,906 (15.01%) participants experienced all-cause mortality, with 1,798 (3.91%) deaths attributed to cardiovascular causes. Kaplan-Meier analysis revealed that higher eGDR levels were associated with gradually reduced mortality rates. After adjusting for confounders, elevated eGDR levels were protective against both cardiovascular and all-cause mortality; the protective effect was notably stronger for cardiovascular mortality [Cardiovascular mortality hazard ratio: 0.92; All-cause mortality hazard ratio: 0.94]. Further interaction tests indicated that glycemic status significantly modified the protective effect of eGDR (P-interaction<0.0001); specifically, high eGDR conferred stronger protection against cardiovascular and all-cause mortality in individuals with NFG and prediabetes compared to those with diabetes. Receiver operating characteristic analysis suggested that eGDR had superior predictive value for mortality in the NFG and prediabetic populations compared to the diabetic group.

eGDR is a straightforward surrogate for insulin resistance, acting as a protective factor against cardiovascular and all-cause mortality in American adults, with glycemic status modifying this protective effect. Specifically, high eGDR levels offer stronger protection in individuals with NFG and prediabetes compared to those with diabetes; moreover, eGDR appears to be more suitable for predicting mortality events in the NFG and prediabetic populations.

This mini review explores the increasing prevalence of obesity in type 1 diabetes (T1D) and the challenges patients face in achieving optimal glycemic control with current treatments. It discusses the evidence supporting the use of glucagon-like peptide-1 receptor agonists (GLP-1RA) as potential adjunctive therapy in T1D to reduce weight and improve insulin resistance. Potential benefits need to be weighed against the risk of hypoglycemia and lack of long-term data.

This study investigated whether the delta-over-baseline of exhaled 13CO2 (Δ13CO2), generated from a 13C glucose breath test (13C-GBT), measured insulin resistance (IR) in people with type 1 diabetes, using the hyperinsulinemic-euglycemic clamp (HEC) as a reference method. The secondary objective was to compare the 13C-GBT with the estimated glucose disposal rate (eGDR).

A 40 mU/m2/min HEC and 2 separate 13C-GBTs (euglycemic with insulin bolus and hyperglycemic without bolus) were consecutively performed in 44 adults with type 1 diabetes with varying body compositions. eGDR was calculated based on hemoglobin A1c (HbA1c), presence of hypertension, and waist circumference.

The mean glucose disposal rate (M-value) was 5.9 ± 3.1 mg/kg/min and mean euglycemic Δ13CO2 was 6.4 ± 2.1 δ‰, while median eGDR was 5.9 [4.3-9.8] mg/kg/min. The hyperglycemic Δ13CO2 did not correlate with the M-value, while the euglycemic Δ13CO2 and the M-value correlated strongly (r = 0.74, P < .001). The correlation between M-value and eGDR was more moderate (Spearman's rho = 0.63, P < .001). Linear regression showed an association between Δ13CO2 and M-value, adjusted for age, sex, and HbA1c ]adjusted R² = 0.52, B = 1.16, 95% confidence interval (CI) .80-1.52, P < .001]. The area under the receiver-operator characteristics curve for Δ13CO2 to identify subjects with IR (M-value < 4.9 mg/kg/min) was 0.81 (95% CI .68-.94, P < .001). The optimal cut-off for Δ13CO2 to identify subjects with IR was ≤ 5.8 δ‰.

Under euglycemic conditions, the 13C-GBT accurately identified individuals with type 1 diabetes and concurrent IR, suggesting its potential as a valuable noninvasive index. Clinical Trial Identifier: NCT04623320.

Estimated glucose disposal rate (eGDR), is an index of insulin resistance. It is intimately correlated with inflammation and endothelial dysfunction, both of which are contributory factors in the pathogenesis of cardiovascular disease (CVD) and premature mortality. This study aims to explore the correlation between eGDR and both all-cause and CVD-related mortality in adults with metabolic syndrome (MetS).

A total of 8215 subjects with MetS screened from the National Health and Nutrition Examination Survey (NHANES) during the period from 1999 to 2018 were evaluated for the predictive value of eGDR for CVD and all-cause mortality.

Over a median follow-up for 8.3 years, a total of 1537 all-cause deaths (18.7%) and 467 CVD-related deaths (5.7%) were recorded. Logistic regression analyses revealed a significant inverse correlation between eGDR and the risk of having CVD (OR:0.845, 95%CI:0.807-0.884, p < 0.01). Multivariate Cox regression analysis and restricted cubic splines analysis demonstrated that eGDR is non-linearly correlated with both the mortality of CVD (HR: 0.906, 95% CI: 0.850-0.967, p = 0.003) and all-cause mortality (HR: 0.944, 95% CI: 0.912-0.977, p = 0.001), with an identified inflection point at 5.918. Further subgroup analyses indicated a more pronounced correlation between eGDR and all-cause mortality in individuals under 60 years old (HR: 0.893, 95%CI:0.823-0.970) or those with obesity (HR:0.891, 95%CI:0.839-0.946). Mediation analysis revealed that neutrophil to lymphocyte ratio mediated 8.9% of the correlation between eGDR and all-cause mortality.

This study demonstrates, for the first time, that a decrease in eGDR is associated with an increased risk of all-cause and CVD mortality in adults with MetS. The eGDR indices could serve as surrogate biomarkers for monitoring patients with MetS.

The estimated glucose disposal rate (eGDR) is an easily accessible clinical parameter for assessing insulin resistance in patients with diabetes mellitus. In this study, we aimed to investigate the link between eGDR and subclinical coronary atherosclerosis in an asymptomatic middle-aged Korean population.

This study involved 4004 subjects who underwent routine health checkups with coronary multidetector computed tomography (MDCT) at Asan Medical Center from 2007 to 2011, among whom 913 had a follow-up analysis through 2014. The eGDR was calculated using: 21.16 - (0.09 ∗ waist circumference [cm]) - (3.41 ∗ hypertension) - (0.55 ∗ glycated hemoglobin [%]). Patients were categorized into three groups according to the tertiles of eGDR. Subclinical coronary atherosclerosis was defined by significant coronary stenosis (≥50%), presence of plaques, coronary artery calcification (CAC) score, and its progression. As a result, a lower eGDR level was associated with higher prevalence of significant coronary stenosis, plaques, moderate to severe CAC, and CAC progression. Compared to other markers or risk scores, eGDR was superior to other biomarkers of insulin resistance but did not provide additional information beyond classic cardiovascular risk models like the Framingham Risk Score and Pooled Cohort Equations.

Decreased eGDR values were significantly associated with higher subclinical coronary atherosclerosis burdens in an asymptomatic middle-aged Korean population. However, its clinical implications remain uncertain due to its weaker performance compared to established cardiovascular risk models.

This study seeks to evaluate the prognostic significance of eGDR in predicting mortality outcomes within non-diabetic older adults.

8131 non-diabetic participants aged ≥60 years from the National Health and Nutrition Examination Survey (2001-2018) was included in this study. eGDR was calculated as: eGDR (mg/kg/min) = 21.158 - [0.09 × waist circumference (cm)] - [3.407 × Hypertension (Yes = 1/No = 0)] - [0.551 × HbA1c (%)]. Weighted Cox proportional hazards models, cumulative hazard curves, restricted cubic spline (RCS), and threshold effects analyses were performed to explore the relationship between eGDR and mortality outcomes. Subgroup analyses and mediation effects analyses were conducted.

2566 all-cause deaths and 689 cardiovascular deaths were recorded. Lower eGDR was associated with higher all-cause (HR = 0.76, 95 % CI: 0.63-0.91) and cardiovascular mortality (HR = 0.56, 95 % CI: 0.40-0.80). Inflection points were identified through RCS curve analyses, and the threshold effect was significant. The eGDR-mortality association remained consistent across subgroups. Mediation analyses showed that neutrophil to high-density lipoprotein cholesterol ratio mediated the association.

Lower eGDR levels are linked to higher risk of both all-cause and cardiovascular mortality in non-diabetic older adults, suggesting its potential utility for risk assessment among this population.

The concept of metabolically healthy obesity (MHO) has not been studied in type 1 diabetes (T1D). By analysing datasets from the DCCT/EDIC study, we compared the development of diabetic complications by obesity and metabolic health over 30 years of follow up.

Insulin resistance was calculated by estimated glucose disposal rate (eGDR). The participants (n = 1127) were then divided into four groups based on time-weighted mean body mass index and mean eGDR: metabolically healthy non-obesity (MHN, n = 874), metabolically unhealthy non-obesity (MUN, n = 66), MHO (n = 146) and metabolically unhealthy obesity (MUO, n = 41). Diabetic complications and cardiovascular events were compared across the four groups.

MUO and MUN groups had significantly higher risk for peripheral neuropathy (p = 0.001 in MUO and p < 0.001 in MUN vs. MHN), cardiac autonomic neuropathy (p < 0.001 in both MUO and MUN vs. MHN), retinopathy (p = 0.001 in MUO and p < 0.001 in MUN vs. MHN) and microalbuminuria (p < 0.001 in both MUO and MUN vs. MHN) than MHN group. Moreover, MUO and MUN groups had significantly higher risks (HR [95%CI]) in any cardiovascular events (2.78 [1.51-5.11] and 1.88 [1.05-3.36]) and major atherosclerotic cardiovascular events (2.72 [1.16-6.37] and 2.31 [1.05-5.10]) compared to MHN group. However, the risk of these complications and cardiovascular events (except peripheral neuropathy and cardiac autonomic neuropathy) in MHO group was not different from that in MHN group.

This study highlights the importance of metabolic health represented by insulin resistance in the development of diabetic complications and cardiovascular events in T1D beyond their weight status.

Impaired myocardial mechano-energetic efficiency (MEE) has been associated with cardiac insulin resistance measured by dynamic positron emission tomography (PET) with 18F-fluorodeoxyglucose (18F-FDG) combined with euglycemic-hyperinsulinemic clamp. Estimate glucose disposal rate (eGDR) index has a good correlation with whole-body insulin sensitivity. It remains unsettled whether eGDR index is a suitable proxy of cardiac insulin sensitivity as well as its association with myocardial MEE. The aims of this study were: 1) to compare eGDR index with HOMA-IR, QUICKI and FIRI indexes for association with myocardial glucose metabolic rate (MrGlu); and 2) to determine the association of eGDR index with myocardial MEE.

We evaluated MrGlu using PET with 18F-FDG combined with euglycemic-hyperinsulinemic clamp in 50 individuals without history of coronary heart disease. Myocardial MEE per gram of left ventricular mass (MEEi) was measured in 1181 subjects by echocardiography. eGDR (mg kg-1/min) was calculated as: 21.158 - (0.09 × waist circumference in cm) - (3.407 × hypertension, 1 = yes 0 = no) - (0.551 × HbA1c%).

eGDR index was more strongly associated with myocardial MrGlu than HOMA-IR, QUICKI, and FIRI indexes (r = -0.662, r = -0.492, r = 0.570, and r = -0.492, respectively). Individuals in the lower tertiles of eGDR exhibited a significant reduction of MEEi as compared to those in the highest tertile (P < 0.001). In a stepwise multivariate linear regression analysis eGDR index was the major determinant of MEEi independently of well-established cardio-metabolic risk factors.

These data suggest that the eGDR index may be a useful marker to identifying individuals at high cardiovascular risk.