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Phenotyping of masked hypertension based on the clustering of 24-hour blood pressure monitoring data

https://doi.org/10.15829/1560-4071-2020-3-3286

Abstract

Aim. Phenotyping of masked hypertension (MH) based on clustering of 24-hour ambulatory blood pressure monitoring (ABPM) results data and comparing it with indicators of target organ damage.

Material and methods. We retrospectively analyzed medical records of 207 men with a median age of 34,6 years and normal office blood pressure (BP), who were systematically exposed to occupational stressors and were undergoing a routine in-patient examination. All patients underwent ABPM, echocardiography, carotid ultrasound, glomerular filtration rate estimation. The clustering of ABPM data was carried out using the Kohonen self-organizing neural networks and K-means algorithm. Data processing was performed in the R programming language using the RStudio environment.

Results. MH was diagnosed in 142 (68,6%) patients which were divided into 3 clusters according to 4 criteria factors of ABPM: systolic-diastolic (SDMH) — 50,7%, isolated systolic (ISMH) — 27,5% and isolated diastolic (IDMH) — 21,8%. Majority (51,4%) of patients with SDMH were characterized by a relatively balanced distribution of episodes of increased systolic and diastolic BP during the day, and other ratios were much less common. In patients with ISMH, hypertension prevailed in the daylight, and in IDMР — nighttime. Individual clusters differed significantly in terms of the 24-hour BP profile and signs of target organ damage. Various types of cardiac remodeling were recorded in 24 (17%) patients with MH, 16 (66,7%) of which belonged to the SDMH phenotype. Intima-media thickening >0,9 mm occurred in 40% of patients with IDMH, in 30% — SDMH and only 9% — ISMH. At the same time, the majority of patients with glomerular hyperfiltration was recorded in patients with ISMH (20,5%), and with hypofiltration — IDMH (29%) and SDMH (23,6%).

Conclusion. Modern technologies of clustering increase the effectiveness of risk stratification for patients with MH, and contribute to the personification of preventive and therapeutic programs.

About the Authors

B. I. Geltser
Far Eastern Federal University
Russian Federation

School of Biomedicine

Vladivostok


Competing Interests: конфликт интересов отсутствует


K. I. Shakhgeldyan
Far Eastern Federal University; Vladivostok State University of Economics and Service
Russian Federation

School of Biomedicine, 

School of Information Technologies

Vladivostok


Competing Interests: конфликт интересов отсутствует


V. N. Kotelnikov
Far Eastern Federal University
Russian Federation

School of Biomedicine

Vladivostok



O. O. Vetrova
Far Eastern Federal University
Russian Federation

School of Biomedicine

Vladivostok


Competing Interests: конфликт интересов отсутствует


V. V. Orlova-Ilyinskaya
Far Eastern Federal University
Russian Federation

School of Biomedicine

Vladivostok


Competing Interests: конфликт интересов отсутствует


R. S. Karpov
Tomsk National Research Medical Center, Cardiology Research Institute
Russian Federation
Tomsk
Competing Interests: конфликт интересов отсутствует


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Review

For citations:


Geltser B.I., Shakhgeldyan K.I., Kotelnikov V.N., Vetrova O.O., Orlova-Ilyinskaya V.V., Karpov R.S. Phenotyping of masked hypertension based on the clustering of 24-hour blood pressure monitoring data. Russian Journal of Cardiology. 2020;25(3):3286. (In Russ.) https://doi.org/10.15829/1560-4071-2020-3-3286

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ISSN 1560-4071 (Print)
ISSN 2618-7620 (Online)