Key result
Integration of 24-h ambulatory pulse wave analysis with e-health and machine learning technologies facilitates early screening of vascular alterations and may improve cardiovascular risk stratification.
Why the study?
There is currently limited proof of the prognostic significance of 24-h ambulatory pulse wave analysis, despite accumulating data on its ability to aid early screening of vascular alterations and CV risk stratification.
Telehealth-based 24-hour ambulatory pulse wave analysis and machine learning offer a promising approach for dynamic vascular function assessment and cardiovascular risk stratification.
Answers are grounded in this paper and cite their sources.
Ambulatory PWA enables 24-h vascular assessment in daily life; leaves open prognostic value pending validation.
Recent advances in Pulse Wave Analysis (PWA) technology enable Blood Pressure (BP) measuring devices to combine the non-invasive estimation of different vascular biomarkers in ambulatory conditions. This approach allows obtaining a dynamic assessment of vascular function during the 24-h in the conditions of daily life, including night sleep. In spite of the present limited proof of the prognostic significance of 24-h ambulatory PWA, data is accumulating indicating the ability of these techniques to facilitate the early screening of vascular alterations and to improve individual Cardiovascular (CV) risk stratification. The integration of 24-h PWA with e-health and telehealth may help boost the implementation of this approach in the routine clinical evaluation of patients at risk. Telehealth-based 24-h PWA may help standardize the evaluation of recordings by making available to doctors and researchers validated analytical algorithms through dedicated web services. It may facilitate the setup of a worldwide network between expert centres and peripheral hubs in order to improve the quality of the patient’s assessment and to provide personalized care. It may establish communication between healthcare professionals and patients allowing remote monitoring and direct counselling, ultimately improving patients’ health status. The use of telehealth may also allow creating registries and collecting big-data, useful to validate and improve the quality of the algorithms, including Artificial Intelligence (AI) and Machine Learning (ML) tools for predicting patients’ risk and guide clinical care. Preliminary evidence from one of such registries (the Vascular health ASsessment Of The hypertENSive, VASOTENS Registry) seems to indicate that telehealth-based networks may be effective to collect definitive proof of the clinical utility of 24-h PWA.
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Stefano Omboni (2019) conducted a review in Cardiovascular disease and Hypertension. 24-h ambulatory pulse wave analysis (PWA) and e-Health was evaluated. Integration of 24-h ambulatory pulse wave analysis with e-health and machine learning technologies facilitates early screening of vascular alterations and may improve cardiovascular risk stratification.
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