Novel Diabetes Classification Based on Glucose Variability Patterns from CGM Data

Presenter: S. Singla

A novel diabetes classification system was developed using continuous glucose monitoring (CGM) data from 527 patients over 14 days. Glucose variability metrics were analyzed via unsupervised machine learning and five new subgroups were identified: stable hyperglycemia (31%), brittle hypoglycemia-prone (18%), postprandial spike (22%), dawn phenomenon dominant (16%), and erratic fluctuator (13%).

Each subgroup exhibited unique glycemic patterns and differential treatment responses. GLP-1 receptor agonists were most effective for postprandial spikes, SGLT-2 inhibitors for dawn phenomenon, and hybrid closed-loop systems for hypoglycemia-prone patients. This CGM-based classification enables personalized diabetes management by aligning therapies with individual glycemic behavior, offering improved outcomes over traditional etiology-based models. It represents a paradigm shift toward precision medicine in diabetes care.

Distinct Glycaemic Signatures Predict Medication Response and Complication Risk in Diabetes: A Multicentre CGM Analysis

Presenter: S. Patil

This multicenter study analyzed CGM data from 527 diabetes patients to subsequently correlate with complication rates over 6 months.

CGM data revealed five glycemic signatures: sustained hyperglycemia (31%), high-frequency hypoglycemia (18%), postprandial spikes (22%), early morning elevations (16%), and chaotic fluctuations (13%). Specific patterns in therapeutic responses was observed with postprandial spikes responding best to incretin therapies, early morning elevations to SGLT2 inhibitors and high frequency hypoglycemia patterns to insulin infusion. Most significantly, glycemic signatures predicted future hospitalization for acute metabolic complications better than HbA1c, disease duration or known risk factors. (AUC 0.83 vs. 0.67, p<0.001)

The findings support integrating glycemic pattern analysis into routine care to better predict medication efficacy and complication risk thus improving outcomes and reducing adverse events.

Glycaemic Control and Insulin Use Daily and During Shifts in Hospitalised Non-Critically Ill Patients with Type 2 Diabetes

Presenter: M.T. Olsen

In a randomized trial of 166 hospitalized T2DM patients (non-ICU), glucose control and insulin use were compared between CGM-guided and point-of-care (POC) insulin titration arms.

Time in range (TIR, 3.9–10.0 mmol/L) improved progressively to 90% by discharge in the CGM-arm vs. 60% in the POC-arm (p = 0.007) plateauing after 5 days. Both arms showed lowest TIR and highest insulin use during day shifts (07:00–15:00 h). Correctional insulin doses were significantly lower in the CGM-arm: 0.7 IU less during day (p = 0.016), 1.2 IU less in evening (p = 0.005), and 0.3 IU less at night (p = 0.038). Prandial insulin was 1.1 IU (±0.5) lower in CGM-arm during evening shifts (p = 0.021). These results highlight the consistent efficacy of CGM in improving glycemic control during hospitalization.

Sex Differences in the Weight Response to GLP-1RA in People with Type 2 Diabetes: A Long-Term Longitudinal Real-World Study

Presenter: M. Marassi

In a multicentre study of well-balanced cohort of 7847 individuals with type 2 diabetes (60% male), sex-based differences in response to GLP-1 receptor agonists (GLP-1RA) were evaluated over a median 4-year follow-up.

Females showed significantly greater weight loss than males: mean difference: -1.1 ± 0.2 kg (p<0.001) across all GLP molecules. With injectable semaglutide, females lost 2.4 kg more than males. Weight loss ≥5% occurred in 66.5% of females vs. 58.0% of males (p<0.001); ≥10% in 40.0% vs. 30.7% (p<0.001). No sex differences were found in HbA1c reduction (0.4 mmol/mol; p=0.21) or eGFR decline (p=0.78). These results highlight sex as a potential predictor of GLP-1RA therapy response and support individualization of therapy.

The Impact of Early and Intensive HbA1c Control on the Risk of Long-term Macrovascular and Microvascular Complications in Patients with Type 2 Diabetes from the Swedish National Diabetes Register

Presenter: E. Wilkes

In this retrospective longitudinal study from three registers, 14,567, 8,426, and 9,793 patients with newly diagnosed type 2 diabetes (T2D) were assigned to non-early tight control (NETC), adequate control (AC), and early tight control (ETC) cohorts, respectively. Median follow-up ranged from 3.6 to 4.4 years.

ETC significantly reduced the rate of microvascular complications (p < 0.0001) and macrovascular complications (p < 0.001) compared to NETC and AC. Cardiovascular death was reduced by 40% vs. NETC (HR=0.60) and 48% vs. AC (HR=0.52). These findings highlight the importance of early intensive HbA1c management in lowering long-term complication risks in T2D. However, effects beyond the initial 18-month HbA1c assessment period remain to be explored.

Glycaemic Variability Fingerprints: Early Predictors of Diabetes Complications and Treatment Failure

Presenter: S. Singla

This retrospective study utilized an advanced multi-dimensional time-series analysis algorithm to study the CGM data in 134 patients (12,048 CGM hours), matched against 5-year retrospective clinical histories. The predictive value of the algorithm was validated in 18-month follow-up phase. Six distinct glycemic variability fingerprints (GVFs) having a robust association with future diabetes complications were identified.

Patterns included: A (23.1%) linked to autonomic neuropathy (HR: 6.3, p<0.0001); B (18.7%) linked to nephropathy (GFR decline >10 ml/min/year, HR: 4.2, p<0.001); C (15.7%) linked to retinopathy (HR: 5.1, p<0.001); D (16.4%) linked to recurrent DKA/HHS (HR: 7.8, p<0.0001); E (14.2%) linked to treatment resistance (HR: 3.9, p<0.001); F (11.9%) linked to hypoglycemia unawareness (HR: 8.2, p<0.0001). GVF patterns preceded complications by 11–32 months even when HbA1c, time-in-range, and standard CGM metrics appeared optimal. GVF-guided therapy reduced complication rates by 62% and hospitalizations by 41%, assuring improved patient outcomes (p<0.0001).

Long-Term Incidence and Case-Fatality Rates of Myocardial Infarction in People with Newly Diagnosed Diabetes and Impaired Glucose Tolerance: The Da Qing Diabetes 34-Year Follow-Up

Presenter: J. Xu

In a 34-year follow up cohort study of 1,632 adults in Da Qing, China, myocardial infarction (MI) incidence and case-fatality rates (CFR) were evaluated across groups with newly diagnosed diabetes (NDD), impaired glucose tolerance (IGT), and normal glucose tolerance (NGT).

After adjusting for key risk factors, NDD had significantly elevated MI risk (HR: 3.54), IGT non-intervention group (HR: 2.34) and intervention group (HR: 1.86) compared to NGT. Compared to NDD, those with IGT who received a 6-year lifestyle intervention had a significantly lower risk of MI (HR: 0.56), while the non-intervention IGT group showed no significant difference (HR: 0.68). CFR for MI was significantly elevated in NDD (HR: 1.62) and trended higher in IGT without intervention (HR: 1.50), whereas IGT with intervention showed reduced mortality risk (HR: 0.83). Early lifestyle intervention in IGT effectively lowered MI incidence and mortality.

The Normalisation of Insulin Resistance Before Stroke Improves Functional Outcome in Type 2 Diabetes

Presenter: V. Darsalia

This study explored the potential efficacy in normalizing hyperglycemia (HG) or insulin resistance (IR) before stroke improves outcomes in type 2 diabetes (T2D).

Using an obese/T2D experimental model, glucagon-induced weight loss (∼30%) improved IR (p < 0.001) and reduced serum insulin (1±0.5 vs. 7±3 ng/ml in T2D controls; p < 0.05), while insulin only lowered HbA1c (25 ± 2 vs. 28 ± 5 mmol/mol; p < 0.001). Stroke reduced grip strength in all groups, but full recovery occurred only in glucagon-treated mice (100 ± 2 g vs. 82 ± 3 in T2D controls; p < 0.001). Glucagon also reduced neuroinflammation by 40% (p < 0.05).

The study demonstrated that pre-stroke IR normalization significantly improves functional recovery. These findings motivate to explore insulin-sensitizing strategies for stroke prevention in T2D.

Tirzepatide as a Potential Strategy to Overcome Leptin Resistance in Obesity

Presenter: R. Izumi

This study investigates whether tirzepatide, a dual GIP/GLP-1 receptor agonist, enhances leptin sensitivity in obesity.

Using leptin-resistant Wistar rats and leptin-deficient Zucker fatty rats, researchers compared effects of tirzepatide, leptin, and their combination. Co-administration significantly reduced body weight and food intake more than either agent alone, even in leptin-resistant states. Tirzepatide also lowered triglycerides and activated brown adipose tissue, suggesting both leptin-dependent and independent mechanisms. In Zucker rats, tirzepatide alone reduced weight and intake, confirming leptin-independent effects. These findings suggest tirzepatide may potentially overcome leptin resistance in obesity treatment.

Cardiometabolic and Kidney Outcomes Validate the Prognostic Value of Adiposity-Based Obesity Classification System: A Longitudinal Analysis of The UK Biobank

Presenter: S. Gunnarsson

This study assessed a new obesity classification system using body fat percentage (BF%) and waist circumference (WC) to better predict cardiometabolic and kidney disease risks.

Analyzing data from 332,136 UK Biobank participants with BMI ≥ 25, researchers grouped individuals into five risk ascending categories (group 1-5) based on BF%-WC classification. Group 5 showed the significantly elevated risk for major cardiovascular events, type 2 diabetes, and chronic kidney disease compared to group 1. Genetic and proteomic analyses revealed obesity-related genetic profiles and inflammation-linked pathways in high-risk groups. The BF%-WC system performed similarly to the BMI-WC model, highlighting its clinical value in refining obesity-related risk prediction and guiding targeted prevention strategies.

EASD 2025, 15th – 19th Sept 2025, Vienna, Austria.