This study aims to compare carotid intima-media thickness (CIMT) and layer-specific texture characteristics of the carotid wall between individuals with Type 2 diabetes mellitus (T2DM) and normoglycemic controls, to assess the impact of T2DM on these ultrasound variables and evaluate their ability to discriminate between low and high cardiovascular risk at 10 years.

Cardiovascular disease (CVD) is the leading cause of death worldwide and accounts for approximately 45% of all deaths in Europe. Beyond mortality, CVD has a substantial impact on patients' quality of life and represents a significant economic burden on healthcare systems. T2DM is a key cardiovascular risk factor and an important determinant of serious cardiovascular complications, as it is associated with a worse prognosis after cardiac events and almost doubles the risk of all-cause mortality.

Primary prevention of CVD is a cornerstone of nursing practice, especially in the management of chronic diseases such as T2DM, where lifestyle interventions and long-term follow-up are essential. Several tools are available for the early detection of CVD, including cardiovascular risk (CVR) prediction models and imaging techniques. SCORE2 and SCORE2-Diabetes are widely used algorithms for estimating the 10-year risk of major cardiovascular events in European adults. Imaging modalities, such as carotid ultrasound, are becoming increasingly relevant, not only as diagnostic tools but also as support resources in nurse-led clinical assessment, as they provide objective and visual biomarkers of vascular health.

Carotid ultrasound allows for the assessment of established parameters related to CVR, such as CIMT, echogenicity, echovariation, and wall texture. Intima-media thickness (IMT) is a well-recognized marker of arterial injury and cardiovascular risk, especially in people with T2DM. While echogenicity and echovariation reflect tissue composition and structural heterogeneity, they may not detect early microstructural alterations. In contrast, texture features derived from gray-level co-occurrence matrix (GLCM) analyze spatial relationships between pixels, allowing the detection of subtle arterial changes associated with cardiovascular risk. Therefore, in nursing practice, layer-specific carotid texture analysis may offer a more accurate and personalized assessment of cardiovascular risk.

Inclusion Criteria

• European adults.
• Age between 40 and 69 years.
• Confirmed diagnosis of type 2 diabetes mellitus.
• No established cardiovascular disease.
• Availability of the required clinical and metabolic variables: Age; Sex; Systolic blood pressure; Non-high-density lipoprotein (non-HDL) cholesterol; Smoking status; Duration of diabetes; Glycated hemoglobin (HbA1c); Presence or absence of diabetes-related target organ damage (e.g., albuminuria, retinopathy)

Exclusion Criteria

• History of clinical cardiovascular disease (secondary prevention).
• Type 1 diabetes mellitus.
• Patients with established severe target organ damage or conditions that automatically classify them as very high cardiovascular risk according to ESC guidelines.
• Advanced chronic kidney disease (estimated glomerular filtration rate <30 mL/min/1.73 m²).

European population aged between 40 and 69 years without known cardiovascular disease.

The data associated with this paper will be available in the Zenodo repository