Estimated Pulse Wave Velocity Calculated from Age and Mean Arterial Blood Pressure

Greve, Sara Vikström; Laurent, S; Olsen, Michael Hecht

doi:10.1159/000453073

Cited by 26 publications

(28 citation statements)

References 22 publications

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“…They also concluded that the estimated PWV could predict cardiovascular events independently of the traditional cardiovascular risk factors. However,in another smaller study 49 , Greve et al . claimed that the estimated PWV only predict CVDs in apparently healthy individuals.…”

Section: Resultsmentioning

confidence: 88%

Artificial Intelligence Estimation of Carotid-Femoral Pulse Wave Velocity using Carotid Waveform

Tavallali¹,

Razavi²,

Pahlevan

2018

Sci Rep

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In this article, we offer an artificial intelligence method to estimate the carotid-femoral Pulse Wave Velocity (PWV) non-invasively from one uncalibrated carotid waveform measured by tonometry and few routine clinical variables. Since the signal processing inputs to this machine learning algorithm are sensor agnostic, the presented method can accompany any medical instrument that provides a calibrated or uncalibrated carotid pressure waveform. Our results show that, for an unseen hold back test set population in the age range of 20 to 69, our model can estimate PWV with a Root-Mean-Square Error (RMSE) of 1.12 m/sec compared to the reference method. The results convey the fact that this model is a reliable surrogate of PWV. Our study also showed that estimated PWV was significantly associated with an increased risk of CVDs.Cardiovascular diseases (CVDs) and stroke are among the major causes of death in the United States and the total cost related to them was more than $316 billion in 2011-2012 1,2 . New cardiovascular monitoring methods are urgently needed in order to limit the growing burden of CVDs. Arterial stiffening is one of the risk factors for CVDs 3,4 , which can be assessed non-invasively by calculating the carotid to femoral PWV 5 . This parameter is a gold standard of arterial stiffness, the rate at which pressure waves move down the aortic vessel 6 . Increased arterial stiffness is related to an increased risk of cardiovascular events; therefore, it has become an independent marker for CVDs 6,7 . Because of its clinical significance, there has been a surge in addressing arterial stiffness and PWV 8 . Arterial stiffness and its surrogates such as PWV have been suggested as one of the risk factors along with other biomarkers such as high cholesterol, diabetes, and left ventricular hypertrophy when cardiovascular risk is being evaluated 8 . Past studies have shown a strong correlation between PWV and the presence of CVDs 9-14 .Although carotid-femoral PWV measurement is non-invasive, this process is intrusive as it requires the waveform collection from inguinal region. Obtaining accurate carotid-femoral PWV measurements often requires a well-trained staff within a clinical setting 15 . The need of the medical community is an easy-to-use and non-intrusive method to measure carotid-femoral PWV with acceptable accuracy and precision; see ref. 16 .At the same time, recent advances in the field of artificial intelligence have opened up new areas and methods in creating novel modeling and predictive methods for clinical use 17 . The model and analysis in this paper are in accord to this path of introducing artificial intelligence to the field of medical sciences.In this study, a novel, easy-to-use, and non-invasive approach to estimate carotid-femoral PWV, from a single carotid waveform measurement, is explored. This method is based on the newly developed Intrinsic Frequency (IF) algorithm 18,19 . IF method solely needs one uncalibrated trace of a carotid, or aortic, pressure waveform. Our method takes an un...

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Section: Resultsmentioning

confidence: 88%

Artificial Intelligence Estimation of Carotid-Femoral Pulse Wave Velocity using Carotid Waveform

Tavallali¹,

Razavi²,

Pahlevan

2018

Sci Rep

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“…Though estimated PWV performed well in healthy subjects, it did not add any predictive value in patients with diabetes mellitus or on antihypertensive drugs. As mentioned above, this might be due to high individual variability, which cannot be addressed by using equations coming from another study collective ( Greve et al, 2017 ). Lim et al (2015) observed intraindividually increasing cfPWV with increasing mean BP in healthy subjects.…”

Section: Discussionmentioning

confidence: 99%

Would Oscillometry be Able to Solve the Dilemma of Blood Pressure Independent Pulse Wave Velocity – A Novel Approach Based on Long-Term Pulse Wave Analysis?

et al. 2020

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The utility of pulse wave velocity (PWV) as a surrogate parameter of arterial vessel damage (AVD) beyond the traditional brachial blood pressure (BP) measurement may be questioned as changes in BP are often accompanied by the corresponding changes in PWV. We sought to establish a new way for BP-independent estimation of AVD with PWV. We retrospectively analyzed data from 507 subjects with at least one available 24 h ambulatory BP- and pulse wave analysis, performed with Mobil-O-Graph (I.E.M., Stolberg, Germany). Individual relationship between eaPWV and central systolic BP (cSBP) was analyzed for every 24 h recording. The analysis revealed linear relation between eaPWV and cSBP in all subjects, which is described by equation eaPWV = a ∗ cSBP + b. We termed “a” as PWVslope and “b” as PWVbaseline. All available demographic parameters and clinical data were correlated with eaPWV, PWVslope and PWVbaseline. 108 subjects had repeated 24 h recordings. Mean age was 60.7 years and 48.7% were female. 92.5% had hypertension, 22.9% were smoker, 20.5% had diabetes mellitus and 29.6% eGFR < 60 ml/min/1,73 m 2 . Direct correlation was observed between age, SBP and eaPWV, while diastolic BP (DBP) and eGFR correlated inversely with eaPWV. PWVbaseline correlated directly with age and inversely with DBP, while PWVslope didn’t correlate with any inputted parameter. Using simple mathematical approach by plotting eaPWV and cSBP values obtained during ABPM, it is possible to visualize unique course of individual PWV related to BP. Using PWVslope and PWVbaseline as novel parameters could be a feasible way to approach BP-independent PWV, though their clinical relevance should be tested in future studies. Our data underline the importance of BP-independent expression of PWV, when we use it as a clinical surrogate parameter for the vascular damage.

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“…Також, враховуючи вік пацієнтів та більшу кількість факторів ризику розвитку атеросклерозу в пацієнтів високого ризику, закономірно, що ці пацієнти продемонстрували найвищі показники ПТ та ШППХ. У дослідженні Greeve et al [15] було запропоновано використання кфШППХ або рШППХ більше 10,0 м/с для переоцінки серцевосудинного ризику за SCORE. При використанні кфШППХ у нашому дослідженні такій переоцінці підлягав би один пацієнт середнього ризику, а при використанні рШППХ -троє пацієнтів.…”

Section: результати та їх обговоренняunclassified

“…СТ обчислювався за допомогою формули: СТ = 1/3 (систолічний АТ-діастолічний АТ)+діастолічний АТ. рШППх обчислювали за формулами, запропонованими дослідниками Європейського товариства кардіологів [15]. Функцію ендотелію, або ендотелій-залежну вазодилатацію (ЕЗВД), досліджували за стандартною методикою Celermajer D.S.…”

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Arterial stiffness, ambulatory blood pressure monitoring and their association with cardiovascular risk in patients with chronic kidney disease and arterial hypertension.

Semenov¹

2018

Medicni Perspektivi (Medical Perspectives)

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Реферат. Жесткость артерий, суточный мониторинг артериального давления и их взаимосвязь с кардиоваскулярным риском у пациентов с хронической болезью почек и артериальной гипертензией. Семенов В.В. Цель работы -исследовать жесткость артерий, суточный профиль артериального давления и их взаимосвязь с кардиоваскулярным (КВ) риском у пациентов с хронической болезью почек (ХБП) и артериальной гипертензией (АГ). Было обследовано 20 пациентов с ХБП стадий 1-2 и АГ 1-2 степени (7 мужчин и 13 женщин, средний возраст 55±8,4 года). В зависимости от КВ риска пациенты были распределены на 3 группы: низкого (<1%), среднего (1-10%) и высокого риска (≥10%). В исследовании преобладали пациенты среднего риска (50%). Выявлена статистически достоверная связь КВ риска и возраста. Жесткость артерий (на основе измерения пульсового давления и скорости проведения пульсовой волны) возрастала с увеличением КВ риска. Наилучшая функция эндотелия наблюдалась в группе высокого риска. Больше половины пациентов имели суточный профиль АД "нон-диппер". У пациентов высокого риска выялено наибольшее среднесуточное систолическое АД и утреннее повышение АД.

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Estimated Pulse Wave Velocity Calculated from Age and Mean Arterial Blood Pressure

Cited by 26 publications

References 22 publications

Artificial Intelligence Estimation of Carotid-Femoral Pulse Wave Velocity using Carotid Waveform

Artificial Intelligence Estimation of Carotid-Femoral Pulse Wave Velocity using Carotid Waveform

Would Oscillometry be Able to Solve the Dilemma of Blood Pressure Independent Pulse Wave Velocity – A Novel Approach Based on Long-Term Pulse Wave Analysis?

Arterial stiffness, ambulatory blood pressure monitoring and their association with cardiovascular risk in patients with chronic kidney disease and arterial hypertension.

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