# The Cardiovascular Burden of Diabetes: Risk Factors, Clinical Phenotypes, and Personalized Cardiometabolic Management

**Authors:** Giuliano Cassataro, Giulio Geraci, Maria Ausilia Giusti, Carlo Maida, Viviana Maggio, Manfredi Rizzo, Alessandro Mattina

PMC · DOI: 10.3390/jcm15062358 · Journal of Clinical Medicine · 2026-03-19

## TL;DR

This paper argues for personalized cardiovascular risk management in type 2 diabetes, as a one-size-fits-all approach is insufficient due to the condition's variability.

## Contribution

The paper introduces a framework for individualized cardiometabolic management of T2D to optimize outcomes and reduce cardiovascular burden.

## Key findings

- T2D is a heterogeneous condition with diverse cardiovascular outcomes beyond hyperglycemia.
- Personalized medicine strategies can improve cardiometabolic outcomes by tailoring interventions to individual phenotypes.
- Traditional risk management approaches are inadequate due to variability in disease presentation and treatment response.

## Abstract

Type 2 diabetes (T2D) exhibits substantial phenotypic heterogeneity, resulting in diverse cardiovascular (CV) outcomes driven by multiple pathophysiological mechanisms beyond hyperglycemia alone. T2D should be recognized as a systemic cardiometabolic condition in which insulin resistance, chronic inflammation, oxidative stress, and endothelial and microvascular dysfunction promote a broad spectrum of cardiovascular diseases. The traditional “one-size-fits-all” approach to cardiovascular risk management has been proven insufficient, as individuals with T2D display marked variability in clinical presentation, disease trajectory, treatment response, and cardiovascular phenotype. In this context, personalized medicine strategies integrating clinical phenotyping, individualized risk stratification, and tailored therapeutic interventions offer the potential to optimize cardiometabolic outcomes while minimizing treatment burden and adverse effects. This narrative review examines the rationale and current evidence supporting personalized cardiovascular risk management in T2D. We discuss the heterogeneity of diabetes-related CV phenotypes, encompassing both atherosclerotic and non-atherosclerotic complications. We further examine the major cardiometabolic risk factors closely linked to diabetes, including dyslipidemia, hypertension, obesity, chronic kidney disease, and metabolic liver disease, which act synergistically to accelerate vascular damage and end-organ injury, and are essential for defining personalized prognostic and therapeutic programs. Finally, we present structured approaches to cardiovascular assessment and highlight contemporary management strategies that prioritize integrated, phenotype-driven risk reduction using cardioprotective glucose-lowering therapies together with optimized lipid-lowering, antihypertensive, antithrombotic, and weight-modifying interventions. The transition from population-based guidelines to individualized, patient-centered care represents a paradigm shift in diabetes management, with the potential to substantially reduce the excess CV burden associated with this condition.

## Linked entities

- **Diseases:** Type 2 diabetes (MONDO:0005148), dyslipidemia (MONDO:0002525), obesity (MONDO:0011122), chronic kidney disease (MONDO:0005300)

## Full-text entities

- **Diseases:** dyslipidemia (MESH:D050171), end-organ injury (MESH:C564816), insulin resistance (MESH:D007333), vascular damage (MESH:D057772), obesity (MESH:D009765), T2D (MESH:D003924), cardiovascular diseases (MESH:D002318), atherosclerotic and non-atherosclerotic complications (MESH:D050197), endothelial and microvascular dysfunction (MESH:D017566), Diabetes (MESH:D003920), metabolic liver disease (MESH:D008107), hyperglycemia (MESH:D006943), hypertension (MESH:D006973), chronic kidney disease (MESH:D051436), inflammation (MESH:D007249)
- **Chemicals:** lipid (MESH:D008055), glucose (MESH:D005947)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC13026839/full.md

## References

98 references — full list in the complete paper: https://tomesphere.com/paper/PMC13026839/full.md

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Source: https://tomesphere.com/paper/PMC13026839