Predicting hypertension in type 2 diabetes mellitus: Insights from a nomogram model

Abstract

The prevalence of type 2 diabetes mellitus (T2DM) is rising, with hypertension as a common comorbidity that significantly increases cardiovascular and microvascular risks. Accurate prediction of hypertension in T2DM is essential for early intervention and personalized management. In this editorial, we comment on a recent retrospective study by Zhao et al, which developed a nomogram model using a large cohort of 26850 patients to predict hypertension risk in patients with T2DM. The model incorporated key independent risk factors, including age, body mass index, duration of diabetes, low-density lipoprotein cholesterol and urine protein levels, demonstrating promising discriminative power and predictive accuracy in internal validation. However, its external applicability requires further confirmation. This editorial discusses the clinical value and limitations of the predictive model, highlighting the unfavorable impact of hypertension on T2DM patients. Future research should evaluate the potential contribution of other risk factors to enhance risk prediction and improve the management of T2DM comorbidities.

Keywords: Blood pressure variability; Diabetes; Hypertension; Inflammatory markers; Insulin resistance; Nomogram model; Risk prediction; Serum uric acid; Type 2 diabetes mellitus.

Figure 1

Mechanisms contributing to increased susceptibility to hypertension in patients with type 2 diabetes mellitus. Shared risk factors contribute to both type 2 diabetes mellitus (T2DM) and hypertension. In T2DM, hyperglycemia and hyperinsulinemia increase circulating plasma volume during early stages and promote vascular remodeling in later stages. The late stages are further characterized by increased oxidative stress, fibrosis, and activation of the renin-angiotensin-aldosterone system and sympathetic nervous system, which together impair blood pressure regulation and elevate hypertension risk. RAAS: Renin-angiotensin-aldosterone system; SNS: Sympathetic nervous system.

Figure 2

Comparison of risk factors from Zhao et al’s nomogram[25] (left) with additional potential risk factors (right) for predicting hypertension in type 2 diabetes mellitus. The nomogram incorporates age, low-density lipoprotein cholesterol, body mass index, diabetes duration, and urine protein. Additional factors such as insulin resistance (e.g. homeostatic model assessment of insulin resistance, metabolic score for insulin resistance, triglyceride-glucose index), inflammatory markers [e.g. C-reactive protein, interleukin (IL)-6, IL-1β, tumor necrosis factor alpha, interferon-γ, neutrophil-to-lymphocyte ratio, systemic immune-inflammation index], blood pressure (BP) variability (e.g. 24-hour ambulatory BP monitoring, pulse wave velocity) and serum uric acid may further improve risk prediction beyond the original model. This figure was created by BioRender.com (Supplementary material). BMI: Body mass index; LDL-C: Low-density lipoprotein cholesterol; HOMA-IR: Homeostatic model assessment of insulin resistance; METS-IR: Metabolic score for insulin resistance; TyG: Triglyceride-glucose; CRP: C-reactive protein; IL: Interleukin; ABPM: Ambulatory blood pressure monitoring; TNF-α: Tumor necrosis factor alpha; IFN-γ: Interferon-γ; NLR: Neutrophil-to-lymphocyte ratio; SII: Systemic immune-inflammation.