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Can we detect masked hypertension and masked uncontrolled hypertension using simple metrics? A novel clinical model for latino population

Journal of Human Hypertension volume 39, pages 189–191 (2025)Cite this article

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Arterial hypertension still represents a significant global burden, with approximately 1.13 billion individuals affected with this condition worldwide [1]. This has led to an increasing interest in exploring new phenotypes of arterial hypertension [2]. Masked Hypertension (MH) has emerged as a relevant phenotype within clinical and epidemiological studies. MH can be defined as an underdiagnosed condition where a person has normal blood pressure (BP) measurements in a clinical setting but elevated out-of-office BP readings. Conversely, masked uncontrolled hypertension (MUCH) refers to the same diagnosis but among individuals undergoing hypertension treatment. Both MH and MUCH represent risk factors for developing hypertension-mediated organ damage and cardiovascular diseases (CVD) [3].

A potential approach to diminish these gaps is presented in this issue of the Journal of Human Hypertension, where Minetto J. and colleagues developed a prediction model for MH and MUMH based on simple and accessible parameters within a Latino sample using a cross-sectional design. The authors developed their model between September 2014 to December 2022 at a secondary-tier care center in Argentina, where they recruited 506 participants (70% women with a median age of 42 years). Patients underwent an extensive physical assessments which included clinical variables and anthropometric measurements. Individuals with an office BP below 140/90 mmHg and a valid ABPM were included. Conversely, the exclusion criteria were pregnant or postpartum women. Using automatic arm devices, BP was measured in the office on three separate occasions. On the same day, an authenticated ABPM was conducted, recording measurements during both day and night for 24 h. MH was defined by the ESC as MH characterized by clinic BP lower than 140/90 mmHg, paired with at least one of the following: a 24-h BP of 130/80 mmHg or higher, daytime BP of 135/85 mmHg or above, or nighttime BP exceeding 120/70 mmHg [9]. The approach used to build the model was a binomial logistic regression, which identified key predictors of MH. In the studied sample, MH was found in 30.8% (n = 136), based on having at least one abnormal ABPM measurement. Additionally, only 18% (n = 91) were classified with MH based on the 24-h BP results, with a prevalence of nocturnal MH at 13%. The model included the following covariates sex, office diastolic BP, waist circumference and pulse pressure as their main predictors. Overall, the model proposed by the authors demonstrated a satisfactory performance, resulting in the development of a clinical score which yielded a continuous metric that classified the probability of having MH and MUMH, with good sensitivity and specificity. One of the advantages of this score is its flexibility, allowing for adjustments to the criteria based on the current medical context, making it a practical feature [10].

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Fig. 1: Comorbidities that are strongly linked to risk factors that lead to Masked Hypertension.

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Acknowledgements

Figure 1 was designed using BioRender ® (https://www.biorender.com).

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Authors and Affiliations

  1. Mexican Faculty of Medicine, La Salle University, Mexico City, Mexico

    Camila Ponce-Acosta

  2. Department of Endocrinology, National Institute of Cardiology Ignacio Chavez, Mexico City, Mexico

    Neftali Eduardo Antonio-Villa

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  1. Camila Ponce-Acosta
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  2. Neftali Eduardo Antonio-Villa
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Manuscript drafting: CPA and NEAV. Supervision or mentorship: NEAV. Figure drafting: CPA. Each author contributed important intellectual content during manuscript drafting or revision and accepted accountability for the overall work by ensuring that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved.

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Correspondence to Neftali Eduardo Antonio-Villa.

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Ponce-Acosta, C., Antonio-Villa, N.E. Can we detect masked hypertension and masked uncontrolled hypertension using simple metrics? A novel clinical model for latino population. J Hum Hypertens 39, 189–191 (2025). https://doi.org/10.1038/s41371-025-00996-9

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