Using Latent Class Analysis to Identify Different Risk Patterns for Patients With Masked Hypertension

Area of Science:

• Cardiology
• Metabolic Syndrome Research
• Hypertension Subtyping

Background:

• Masked hypertension (MHT) management remains controversial.
• Investigating MHT subphenotypes associated with metabolic syndrome (MetS) is essential for risk stratification.

Purpose of the Study:

• To identify distinct subphenotypes of MHT based on metabolic risk.
• To evaluate the prognostic differences between MHT with high-risk versus low-risk MetS.

Main Methods:

• Latent class analysis applied to clinical and biological data from 140 MHT patients.
• Modeling data to assess subphenotype-outcome relationships and medication impact.
• Four-year follow-up to evaluate major adverse cardiovascular events (MACE).

Main Results:

• A two-class model identified high-risk and low-risk MetS subphenotypes within MHT.
• High-risk MetS characterized by increased waist circumference, dyslipidemia, hyperglycemia, and diabetes.
• Subphenotype 1 (high-risk MetS) showed a significantly higher MACE-free survival probability (P=0.016).

Conclusions:

• Two distinct MHT subphenotypes with differing metabolic profiles and prognoses were identified.
• These findings highlight the clinical importance of correlating MHT with metabolic risk factors.
• Antihypertensive therapy may be insufficient for MHT patients with high-risk MetS.