In Italian adults with type 2 diabetes, SGLT2i prescribing aligned more with cardiorenal risk, while GLP-1RA prescribing was driven more by BMI and age.
Evidence
This machine-learning cohort analysis used 2023 Italian AMD Annals registry data from 139,202 adults with type 2 diabetes across four ADA cardiorenal phenotypic subgroups.
Caveat
These are observational prescribing patterns with variable model performance, especially for GLP-1RA prescriptions, so they do not prove clinician reasoning or patient outcome effects.
Simplified
BACKGROUND: Understanding how (SGLT2is) and (GLP-1RAs) are prescribed in relation to cardiorenal risk is crucial for assessing adherence to guidelines and optimize outcomes in type 2 diabetes (T2D). This study aimed to determine whether prescription patterns across different cardiorenal phenotypic subgroups reflect clinical risk or are affected by demographic factors. Explainable artificial intelligence (XAI) was used to identify the key factors influencing therapeutic decisions.
METHODS: We analyzed 139,202 adults with T2D from the Italian AMD Annals registry (2023), stratified into four cardiorenal phenotypic subgroups based on ADA criteria: low risk, chronic kidney disease (CKD) without cardiovascular disease (CVD), atherosclerotic CVD without heart failure, and heart failure. Predictive models were developed using a Logic Learning Machine (XAI algorithm), with variable importance ranked by normalized relevance scores. Business intelligence tools and statistical analysis were used for validation.
RESULTS: SGLT2i prescriptions were strongly associated with cardiorenal markers, including reduced eGFR (31–59 mL/min), intermediate HbA1c (5.5–8.1%), and lower BMI, with model accuracies ranging from 63.7% to 83.1%. Women were consistently less likely to receive SGLT2is across subgroups. GLP-1RA prescriptions were predominantly driven by higher BMI (> 30 kg/m²), younger age, and glycemic extremes (< 5.5% or > 8.1%), with lower model performance (31.6%–54.1%). Individuals with lower BMI were less frequently prescribed GLP-1RAs, even in the presence of renal or cardiovascular risk.
CONCLUSIONS: While SGLT2i prescribing generally aligned with cardiorenal risk, sex-based disparities persist. GLP-1RA use was less consistently linked to clinical indications and more heavily influenced by BMI. These findings highlight missed opportunities to deliver proven cardiorenal protective therapies to high-risk individuals, emphasising the need for more equitable, phenotype-driven prescribing strategies in T2D.
GRAPHICAL ABSTRACT: [Image: see text]
SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40842-025-00251-7.
Key numbers
63.7%–83.1%
Predictive Accuracy
Model performance for predicting prescriptions across subgroups.
31.6%–54.1%
GLP-1RA Predictive Accuracy
Model performance for predicting GLP-1RA prescriptions across subgroups.
139,202
Study Cohort Size
Total number of adults with T2D analyzed in the study.
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