Utility of estimated pulse wave velocity for assessing vascular stiffness: comparison of methods

  1. Stefan Möstl
  2. Fabian Hoffmann
  3. Jan-Niklas Hönemann
  4. Jose Ramon Alvero-Cruz
  5. Jörn Rittweger
  6. Jens Tank
  7. Jens Jordan  Is a corresponding author
  1. Department of Cardiovascular Aerospace Medicine, Institute of Aerospace Medicine, German Aerospace Center, Germany
  2. Department of Cardiology, University Hospital Cologne, Germany
  3. Department of Human Physiology and Physical Sports Education, Faculty of Medicine, University of Málaga, Spain
  4. Department of Muscle and Bone Metabolism, Institute of Aerospace Medicine, German Aerospace Center, Germany
  5. Institute of Aerospace Medicine, German Aerospace Center, Germany
  6. Chair of Aerospace Medicine, University of Cologne, Germany

Abstract

Background:

Pulse wave velocity (PWV) independently predicts cardiovascular risk. Easy to use single-cuff oscillometric methods are utilized in clinical practice to estimate PWV. We applied the approach in master athletes to assess possible beneficial effects of lifelong exercise on vascular health. Furthermore, we compared single-cuff measurements with a two-cuff method in another cohort.

Methods:

We obtained single-cuff upper arm oscillometric measurements thrice in 129 master athletes aged 35–86 years and estimated PWV using the ArcSolver algorithm. We applied the same method in 24 healthy persons aged 24–55 years participating in a head down tilt bedrest study. In the latter group, we also obtained direct PWV measurements using a thigh cuff.

Results:

Estimated pulse velocity very highly correlated with age (R2 = 0.90) in master athletes. Estimated PWV values were located on the same regression line like values obtained in participants of the head down tilt bed rest study. The modest correlation between estimated and measured PWV (R² 0.40; p<0.05) was attenuated after adjusting for age; the mean difference between PWV measurements was 1 m/s.

Conclusions:

Estimated PWV mainly reflects the entered age rather than true vascular properties and, therefore, failed detecting beneficial effects of lifelong exercise.

Funding:

The AGBRESA-Study was funded by the German Aerospace Center (DLR), the European Space Agency (ESA, contract number 4000113871/15/NL/PG), and the National Aeronautics and Space Administration (NASA, contract number 80JSC018P0078). FH received funding by the DLR and the German Federal Ministry of Economy and Technology, BMWi (50WB1816). SM, JT and JJ were supported by the Austrian Federal Ministry for Climate Action, Environment, Energy, Mobility, Innovation, and Technology, BMK (SPACE4ALL Project, FFG No. 866761).

Editor's evaluation

This paper evaluates an algorithm for estimation of aortic pulse wave velocity (a robust measure of aortic stiffness), based on a simple, single-point (brachial artery) measurement. The authors test the algorithm using a number of approaches, including an interesting study of Masters athletes and sedentary controls, where they identify a strong dependency of the algorithm on age, which has been documented previously. The paper, adds to the continuing debate over ideal methods for non-invasive estimation of aortic stiffness and will be of interest to other researchers working in the field of arterial hemodynamics, those interested in examining the health benefits of regular exercise and, possibly, health professionals looking for further tools to improve risk stratification.

https://doi.org/10.7554/eLife.73428.sa0

Introduction

Aortic pulse wave velocity (PWV) which relates to vascular stiffness, independently predicts cardiovascular risk including stroke (Hametner et al., 2013; Vishram-Nielsen et al., 2020). PWV values above 10 m/s have been suggested as threshold indicating increased risk (Van Bortel et al., 2012) and are included in current hypertension guidelines for assessing hypertension-mediated organ damage and guiding secondary prophylaxis (Williams et al., 2018). Local PWV measurements are also feasible using two points close or more distant to each other as well as measurements of pressure-velocity loops at one single spot. However, the guidelines do not specify certain methods to measure PWV. Measurements at different sites including the thigh were used in large scale studies. However, this PWV assessment is difficult to implement in busy clinics or during daily routine. Oscillometric blood pressure monitors estimating PWV based on age and blood pressure could simplify vascular assessment (Hametner et al., 2013; Hametner et al., 2021). Indeed, estimated PWV correlates with age (Schwartz et al., 2019) and invasively measured PWV (Hametner et al., 2013). These monitors operate observer-independent, are easy to use, and are, therefore, applied in clinical practice and in clinical studies alike (Paiva et al., 2020). However, in a study investigating beneficial effects of competitive lifelong physical exercise in elite Masters Athletes, we obtained estimated PWV results suggesting that the approach adds little information to classical cardiovascular risk assessment. We decided comparing the methodology with aortic PWV measurements in an independent set of healthy persons participating in a head-down-tilt bedrest study.

Materials and methods

During the 23rd Masters Athletics Championships 2018 in Málaga, Spain, we approached 163 master athletes. We excluded athletes with atrial fibrillation or significant cardiovascular disease assessed by echocardiography. In the remaining 129 athletes (88 men/41 women, 56 ± 11 [range 35–86] years, 24.0 ± 3.5 kg/m²), we acquired blood pressure, heart rate, and estimated PWV thrice on the same arm after 10 min supine rest (Arc-Solver-Algorithm, CardioCube, AIT, Vienna, Austria).

In 24 healthy participants (16 men/8 women, 33 ± 9 years, 24.3 ± 2.1 kg/m²) of the AGBRESA (artificial gravity bedrest) study, which was conducted in collaboration with NASA and ESA in Cologne, Germany (Hoffmann et al., 2021), we assessed estimated PWV before head-down-tilt bedrest as described above. As the estimated PWV has been validated against invasive catheter measurements derived from the ascending aorta to the aortic bifurcation (Hametner et al., 2013), we mimicked this approach non-invasively by measuring pulse wave arrival time from the electrocardiographic R-peak to the arrival of the pulse wave at an oscillometric thigh cuff. We corrected pulse wave arrival time for isovolumetric contraction time, the time from the R-peak in the ECG to aortic valve opening assessed by 2D-pulsed-wave-doppler echocardiography. Corrected pulse wave arrival time represents pulse wave travel time from the aortic valve opening to the arrival at the thigh. Moreover, in contrast to the carotid-femoral PWV, this approach includes the ascending aorta and the aortic arc, which are commonly affected by aging-associated vascular disease. Dividing jugulum-thigh cuff distance by corrected pulse wave arrival time resulted in measured PWV.

All subjects provided informed consent and consent to publish before enrollment. The bedrest study as well as the study in master athletes was approved by the Northrine-Medical-Association (Ärztekammer Nordrhein, 2018143 and 2018171) ethics committee and registered at the German Clinical Trial Register (DRKS00015677 and DRKS00015172).

According to Kolmogorov-Smirnov test, all data were normally distributed, and results are reported as mean values ± standard deviation. Based on other cardiovascular risk estimate models, we used a quadratic regression model.

Results

Resting heart rate was 61 ± 11 bpm, and blood pressure was 128 ± 15/78 ± 8 mmHg in master athletes. Estimated PWV ranged from 5.5 to 14.5 with a mean of 8.3 ± 1.8 m/s. In a quadratic regression model, age and mean arterial pressure predicted estimated PWV (beta value 0.93 and 0.14, p<0.001), whereas, sex and BMI had no influence. The model explained 95% (R² = 0.95) of estimated PWV’s variance. Age alone explained 90% (R² = 0.90).

Resting heart rate was 62 ± 9 bpm, and blood pressure was 125 ± 11/70 ± 7 mmHg in the AGBRESA bedrest study. Estimated PWV was 5.8 ± 1.1 m/s, and measured PWV was 4.8 ± 0.6. Age and estimated PWV were highly correlated (R² 0.88, p<0.001, Figure 1A). The correlation between measured PWV and age was weaker (R² 0.55, p<0.001). In a quadratic regression model, age (beta value 0.99, p<0.001) but not BMI, sex, or mean arterial pressure predicted estimated PWV. The model explained 98% of estimated PWV’s variance. R² between estimated and measured PWV was 0.40 (p<0.05). We observed an increasing bias between estimated and measured PWV with advancing age with an average 0.96 ± 0.83 m/s difference between methods (Figure 1B). When adjusting the correlation of measured and estimated PWV for age we could no longer observe a significant relationship (p=0.267).

Comparison of two different methodologies to assess pulse wave velocity (PWV) in two different cohorts.

(A) Correlation between estimated PWV and age in 129 Masters Athletes (empty circles) and in 24 AGBRESA study participants (black squares). (B) Regression analysis between the measured PWV and estimated PWV difference with age in 24 AGBRESA study participants. Estimated PWV deviated from measured PWV with increasing age (R² 0.44, p=0.07). (C) Quadratic regression analysis between estimated PWV and entered age in one man being in his 50s. We randomly entered age in decades from 20 to 80 and obtained measurements thrice at each entered age.

To assess influences of entered rather than chronological age on estimated PWV, we repeated measurements in one male person, who is in his 50s and has normal BMI, and randomly changed the entered age in decades from 30 to 80 years. We obtained measurements in each entered age decade thrice. Again, estimated PWV related to entered age (R² 0.996, p<0.001, Figure 1C) akin to the relationship between estimated PWV and chronological age in athletes and in bedrest study participants.

Discussion

The idea of obtaining vascular measurements, such as PWV, is gaining insight in individual vascular risk above and beyond traditional risk factors. The clinical goal is to target preventive measures to patients most likely to benefit. Similarly to other studies (Schwartz et al., 2019), we observed an almost perfect correlation between estimated PWV and age in two independent cohorts. Strikingly, estimated PWV in elite Master Athletes, which would be expected to benefit from lifelong exercise, and in healthy bedrest study participants of average physical fitness were located on the same regression line. Suffice it to say that many athletes were frustrated when we reported their findings.

Theoretically, our findings could result from methodological limitations of PWV estimates or a rather limited effect of lifelong exercise on aortic stiffness. A previous study showed significantly lower measured PWV in endurance trained compared with sedentary older men (Vaitkevicius et al., 1993) making a methodological limitation more likely. Indeed, in our study, estimated PWV substantially overestimated PWV, particularly in older persons. Moreover, the modest correlation between estimated and measured PWV was attenuated after adjusting for age in our relatively small bedrest cohort. Finally, in a previous study, estimated PWV highly correlated with PWV calculated solely from age and blood pressure (Hametner et al., 2021). Thus, the algorithm providing PWV estimates appears to weigh age so strongly that subtle influences on vascular wall properties caused by hemodynamic changes and physical training cannot be discerned. Even more so, estimated PWV mainly reflects data entered prior to measuring blood pressure rather than true vascular properties. The clinical implication is that estimated PWV is no substitute for measured PWV, which likely limits the utility of the methodology in individualizing risk assessment. In fact, simply asking the patient in front of us for his or her age and measuring blood pressure provides almost as much information as estimating PWV. Instead, vascular aging assessment using established methodologies rather than estimates should be considered (Jordan et al., 2015).

Data availability

As we obtained personal health data from human subjects, we cannot make their raw data publicly available. However, an interested researcher is able to access the original data by sending a project proposal to the corresponding author. This project proposal will be reviewed by the medical board of the DLR Institute of Aerospace Medicine. If the project is scientifically valuable, the committee decides to what extent the original data can be made available. Commercial research is excluded from this option. The syntax used for statistical analysis and the numerical data used to generate the figures are stored in Dryad: https://doi.org/10.5061/dryad.8931zcrsb.

The following data sets were generated
    1. Möstl S
    2. Hoffmann F
    3. Hönemann J
    4. Alvero-Cruz J
    5. Rittweger J
    6. Tank J
    7. Jordan J
    (2021) Dryad Digital Repository
    Estimated pulse wave velocity is of limited utility to assess vascular stiffness.
    https://doi.org/10.5061/dryad.8931zcrsb

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Decision letter

  1. Carmel M McEniery
    Reviewing Editor; University of Cambridge, United Kingdom
  2. Matthias Barton
    Senior Editor; University of Zurich, Switzerland
  3. Jonathan P Mynard
    Reviewer; Murdoch Children's Research Institute, Australia

Our editorial process produces two outputs: i) public reviews designed to be posted alongside the preprint for the benefit of readers; ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Decision letter after peer review:

Thank you for submitting your article "Utility of estimated pulse wave velocity for assessing vascular stiffness: comparison of methods" for consideration by eLife. Your article has been reviewed by 2 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and a Senior Editor. The following individual involved in the review of your submission has agreed to reveal their identity: Jonathan P Mynard (Reviewer #2).

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this letter to help you prepare a revised submission.

Essential revisions:

1) Please address the following point by revising the text of your manuscript:

line 66: not all PWV measurements require a measurement on the thigh. Also, local measurements are feasible (2 points close to each other), as well as single-point measurements using two different biosignals (e.g. PU-loop method).

2) Please address the following point, both in your responses to both Reviewers and in revised text of your manuscript:

Why have you used PAT (corrected by isovolumic contraction time) from the heart to the thigh cuff to estimate PWV? When this reviewer understands the measurement setup correctly, another cuff was placed at the upper arm, which would allow PWV estimation using PTT.

Reviewer #1 (Recommendations for the authors):

line 66: not all PWV measurements require a measurement on the thigh. Also local measurements are feasible (2 points close to each other), as well as single-point measurements using two different biosignals (e.g. PU-loop method).

Why have you used PAT (corrected by isovolumic contraction time) from heart to the thigh cuff to estimate PWV? When this reviewer understands the measurement setup correctly, another cuff was placed at the upper arm, which would allow PWV estimation using PTT.

Reviewer #2 (Recommendations for the authors):

The authors used an unconventional (but acceptable) approach to measure aortic PWV, by using the ECG R-wave as the first timing marker, corrected for isovolumic contraction time. I suggest this approach could be made clearer, e.g. by stating that the time of aortic valve opening was used as the first timing marker, and this, in turn, was obtained from the ECG R-wave and echo-derived isovolumic contraction time.

https://doi.org/10.7554/eLife.73428.sa1

Author response

Essential revisions:

1) Please address the following point by revising the text of your manuscript:

line 66: not all PWV measurements require a measurement on the thigh. Also, local measurements are feasible (2 points close to each other), as well as single-point measurements using two different biosignals (e.g. PU-loop method).

We addressed this point in the manuscript (line 64-66). Please also see our comments to the reviewers for more details.

2) Please address the following point, both in your responses to both Reviewers and in revised text of your manuscript:

Why have you used PAT (corrected by isovolumic contraction time) from the heart to the thigh cuff to estimate PWV? When this reviewer understands the measurement setup correctly, another cuff was placed at the upper arm, which would allow PWV estimation using PTT.

We addressed this point in the manuscript (line 106-111). Please also see our comments to the reviewers for more details.

Reviewer #1 (Recommendations for the authors):

line 66: not all PWV measurements require a measurement on the thigh. Also local measurements are feasible (2 points close to each other), as well as single-point measurements using two different biosignals (e.g. PU-loop method).

We responded to the comment and added a sentence regarding different approaches to measure PWV including single point measurements. However, large clinical trials showing the prognostic relevance of aortic or carotid femoral pulse wave velocity employed two point measurements at the carotid artery and femoral artery. Classical tonometric measurements were replaced later on by thigh cuff measurements mainly for practical reasons. We also appreciate the public review of reviewer 1, which comes to the conclusion that the role of different methodologies in estimating PWV remains to be shown. The major aim of our paper was to demonstrate that PWV estimates based on the ArcSolver algorithm exhibit major limitations in detecting changes induced by aging, bedrest, or lifelong physical activity. While some of these limitations have been previously recognized, blood pressure measurement devices incorporating such algorithms appear to promise more than they can keep. The recent literature suggests that clinicians and scientists who are no experts in PWV methodologies may not be aware of this limitation.

Why have you used PAT (corrected by isovolumic contraction time) from heart to the thigh cuff to estimate PWV? When this reviewer understands the measurement setup correctly, another cuff was placed at the upper arm, which would allow PWV estimation using PTT.

The reviewers are correct and we now explain more clearly (see also the comment to reviewer 2) our somewhat unconventional approach to use the R-peak of the ECG as first time marker corrected by the time interval until aortic valve opening (isovolumetric contraction time). Measuring the difference between the two arrival times of the pulse wave at the upper arm and at the thigh excludes the ascending and aortic arch part of the thoracic aorta, which may be relevant. Hence, we aimed with our approach to get a more complete picture comparable to the invasive catheter method or to the newly developed 4D-flow MRI measurements.

Reviewer #2 (Recommendations for the authors):

The authors used an unconventional (but acceptable) approach to measure aortic PWV, by using the ECG R-wave as the first timing marker, corrected for isovolumic contraction time. I suggest this approach could be made clearer, e.g. by stating that the time of aortic valve opening was used as the first timing marker, and this, in turn, was obtained from the ECG R-wave and echo-derived isovolumic contraction time.

Please see the response to reviewer 1. We revised the description of our corrected PAT approach and stated the advantage of using the R-peak of the ECG corrected by the time to aortic valve opening (isovolumetric contraction time) to measure aortic pulse wave travel time including the ascending aorta and the aortic arch.

https://doi.org/10.7554/eLife.73428.sa2

Article and author information

Author details

  1. Stefan Möstl

    Department of Cardiovascular Aerospace Medicine, Institute of Aerospace Medicine, German Aerospace Center, Cologne, Germany
    Contribution
    Data curation, Formal analysis, Investigation, Methodology, Writing - original draft
    Contributed equally with
    Fabian Hoffmann
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4983-4754
  2. Fabian Hoffmann

    1. Department of Cardiovascular Aerospace Medicine, Institute of Aerospace Medicine, German Aerospace Center, Cologne, Germany
    2. Department of Cardiology, University Hospital Cologne, Cologne, Germany
    Contribution
    Data curation, Formal analysis, Visualization, Writing - original draft
    Contributed equally with
    Stefan Möstl
    Competing interests
    No competing interests declared
  3. Jan-Niklas Hönemann

    1. Department of Cardiovascular Aerospace Medicine, Institute of Aerospace Medicine, German Aerospace Center, Cologne, Germany
    2. Department of Cardiology, University Hospital Cologne, Cologne, Germany
    Contribution
    Visualization, Writing - original draft
    Competing interests
    No competing interests declared
  4. Jose Ramon Alvero-Cruz

    Department of Human Physiology and Physical Sports Education, Faculty of Medicine, University of Málaga, Málaga, Spain
    Contribution
    Conceptualization, Project administration, Writing - review and editing
    Competing interests
    No competing interests declared
  5. Jörn Rittweger

    Department of Muscle and Bone Metabolism, Institute of Aerospace Medicine, German Aerospace Center, Cologne, Germany
    Contribution
    Conceptualization, Project administration, Writing - review and editing
    Competing interests
    No competing interests declared
  6. Jens Tank

    Department of Cardiovascular Aerospace Medicine, Institute of Aerospace Medicine, German Aerospace Center, Cologne, Germany
    Contribution
    Conceptualization, Project administration, Resources, Supervision, Writing - review and editing
    Competing interests
    No competing interests declared
  7. Jens Jordan

    1. Institute of Aerospace Medicine, German Aerospace Center, Cologne, Germany
    2. Chair of Aerospace Medicine, University of Cologne, Cologne, Germany
    Contribution
    Resources, Supervision, Writing - original draft
    For correspondence
    Jens.Jordan@dlr.de
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4518-0706

Funding

German Federal Ministry of Economy and Technology (50WB1816)

  • Fabian Hoffmann

Austrian Federal Ministry for Climate Action, Environment, Energy, Mobility, Innovation and Technology (FFG No. 866761)

  • Stefan Möstl
  • Jens Tank
  • Jens Jordan

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We would like to thank Siegfried Wassertheurer, Bernhard Hametner and Martin Bachler from the Austrian Institute of Technology for providing the CardioCube.

Ethics

All subjects provided informed consent and consent to publish before enrollment. The bedrest study as well as the study in master athletes were approved by the Northrine-Medical-Association (Ärztekammer Nordrhein, 2018143 and 2018171) ethics committee and registered at the German Clinical Trial Register (DRKS00015677 and DRKS00015172).

Senior Editor

  1. Matthias Barton, University of Zurich, Switzerland

Reviewing Editor

  1. Carmel M McEniery, University of Cambridge, United Kingdom

Reviewer

  1. Jonathan P Mynard, Murdoch Children's Research Institute, Australia

Publication history

  1. Received: August 27, 2021
  2. Preprint posted: January 13, 2022 (view preprint)
  3. Accepted: May 1, 2022
  4. Accepted Manuscript published: May 3, 2022 (version 1)
  5. Version of Record published: May 11, 2022 (version 2)

Copyright

© 2022, Möstl et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. Stefan Möstl
  2. Fabian Hoffmann
  3. Jan-Niklas Hönemann
  4. Jose Ramon Alvero-Cruz
  5. Jörn Rittweger
  6. Jens Tank
  7. Jens Jordan
(2022)
Utility of estimated pulse wave velocity for assessing vascular stiffness: comparison of methods
eLife 11:e73428.
https://doi.org/10.7554/eLife.73428

Further reading

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    Conclusions:

    Therapeutic strategies to mitigate neutrophil-CAF-tumor cell IL-1β/IL-6/STAT-3 signaling during NAC may improve pathologic responses and/or survival in PDAC.

    Funding:

    Supported by KL2 career development grant by Miami CTSI under NIH Award UL1TR002736, Stanley Glaser Foundation, American College of Surgeons Franklin Martin Career Development Award, and Association for Academic Surgery Joel J. Roslyn Faculty Award (to J. Datta); NIH R01 CA161976 (to N.B. Merchant); and NCI/NIH Award P30CA240139 (to J. Datta and N.B. Merchant).

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