Siegfried Wassertheurer

AIT Austrian Institute of Technology, Wien, Vienna, Austria

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Publications (51)130.64 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: The non-invasive quantification of arterial wave reflection is an increasingly important concept in cardiovascular research. It is commonly based on pulse wave analysis (PWA) of aortic pressure. Alternatively, wave separation analysis (WSA) considering both aortic pressure and flow waveforms can be applied. Necessary estimates of aortic flow can be measured by Doppler ultrasound or provided by mathematical models. However, this approach has not been investigated intensively up to now in subjects developing systolic heart failure characterized by highly reduced ejection fraction (EF). We used non-invasively generated aortic pressure waveforms and Doppler flow measurements to derive wave reflection parameters in 61 patients with highly reduced and 122 patients with normal EF. Additionally we compared these readings with estimates from three different flow models known from literature (triangular, averaged, Windkessel). After correction for confounding factors, all parameters of wave reflection (PWA and WSA) were comparable for patients with reduced and normal EF. Wave separations assessed with the Windkessel based model were similar to those derived from Doppler flow in both groups. The averaged waveform performed poorer in reduced than in normal EF, whereas triangular flow represented a better approximation for reduced EF. Overall, the non-invasive assessment of WSA parameters based on mathematical models compared to ultrasound seems feasible in patients with reduced EF.
    Physiological measurement. 01/2015; 36(2):179-190.
  • Artery 2014, Masstricht; 10/2014
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    ABSTRACT: We investigated whether aortic characteristic impedance (Zc), that is, the ratio between the pulsatile change in pressure and flow in the proximal aorta, is related to left ventricular hypertrophy and geometry independently of blood pressure (BP). A total of 438 never-treated hypertensive individuals (men 62%, age 48 ± 11 years, BP 147/90 ± 16/10 mmHg) underwent echocardiography and 24 h BP monitoring. Aortic pressure waveform was obtained from radial tonometry with a generalized transfer function (SphygmoCor). Using a validated aortic blood flow model based on higher order Windkessel theory (ARCSolver), aortic Zc, forward (Pf) and backward (Pb) wave amplitudes and their ratio (Pb/Pf = reflection magnitude) were calculated from central waveform.
    Journal of Hypertension 09/2014; · 4.22 Impact Factor
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    David Nunan, Susannah Fleming, Bernhard Hametner, Siegfried Wassertheurer
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    ABSTRACT: We have previously reported that estimation of central blood pressure (BP) and augmentation using an automated oscillometric device are robust and feasible in a community setting. The same method has recently been validated for estimating aortic pulse wave velocity (aPWV) in laboratory settings, and its prognostic value has been confirmed in a prospective clinical trial.
    Blood Pressure Monitoring 07/2014; · 1.18 Impact Factor
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    Siegfried Wassertheurer, Klaus Burkhardt, Uwe Heemann, Marcus Baumann
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    ABSTRACT: Pulse pressure amplification (PPA) reflects large artery function. Its contribution in chronic kidney disease (CKD) remains uncertain. The authors assessed PPA in CKD progression in patients with CKD stage 2 to 4 (n=128) and 89 controls (follow-up: 42 months). PPA was reduced in CKD patients as compared with control patients and associated with decline in renal function. Sixteen renal endpoints, defined by 50% loss of renal function or start of renal replacement therapy, were detected. In Cox regression analysis, PPA, estimated glomerular filtration rate, and proteinuria predicted renal endpoints. Patients with CKD stage 4 and low PPA had the highest risk for developing renal endpoints (unadjusted 8.1; 2.4–27.7 and adjusted for age and proteinuria 5.6; 1.5–21.9, log-rank P<.001). Taken together, PPA is reduced in CKD and is associated with declining renal function. In addition, low PPA predicts renal endpoints in severe CKD. Furthermore, this study emphasizes the role of systolic blood pressure as a major determinant of PPA.
    Journal of Clinical Hypertension 04/2014; · 2.36 Impact Factor
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    ABSTRACT: Chronic kidney disease (CKD) is characterized by aortic stiffness and increased cardiovascular mortality. In end-stage renal disease, aortic stiffness predicts mortality, whereas this role remains uncertain in mild-to-moderate CKD. We aimed to investigate whether aortic pulse wave velocity (aPWV) predicts mortality and renal disease progression in CKD patients. We enrolled 135 CKD patients stages 2-4 [estimated glomerular filtration rate (eGFR): 41.1 (28.5-61.6) ml/min per 1.73 m] in the study and assessed aPWV. The combined renal end-point was defined as at least 50% decline in renal function and/or start of renal replacement therapy. During the observational period of 42 (30-50) months six patients were lost of follow-up, 13 patients died and 16 patients reached the combined renal end-point. Stratification according to the mean of aPWV (10 m/s), Kaplan-Meier analysis revealed increased mortality with aPWV ≥10 m/s (log-rank P < 0.05). Stepwise logistic regression analysis confirmed aPWV as an independent predictor for mortality in CKD stage 2-4. The hazard ratio of mortality in the cohort with an aPWV at least 10 m/s was 5.1 (1.1-22.9). By contrast, Kaplan-Meier analysis revealed no effect of aPWV on the combined renal end-point (log-rank P = 0.90). These results provide the first direct evidence that in patients with CKD stage 2-4, increased aortic stiffness determined by aPWV is a strong independent predictor of all-cause mortality.
    Journal of Hypertension 04/2014; 32(4):899-903. · 4.22 Impact Factor
  • Journal of the American College of Cardiology 02/2014; · 15.34 Impact Factor
  • Thomas Weber, Siegfried Wassertheurer
    Hypertension 01/2014; · 7.63 Impact Factor
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    ABSTRACT: BACKGROUND:Heart rate variability is the variation of the time interval between consecutive heartbeats. Entropy is a commonly used tool to describe the regularity of data sets. Entropy functions are defined using multiple parameters, the selection of which is controversial and depends on the intended purpose. This study describes the results of tests conducted to support parameter selection, towards the goal of enabling further biomarker discovery.METHODS:This study deals with approximate, sample, fuzzy, and fuzzy measure entropies. All data were obtained from PhysioNet, a free-access, on-line archive of physiological signals, and represent various medical conditions. Five tests were defined and conducted to examine the influence of: varying the threshold value r (as multiples of the sample standard deviation sigma, or the entropy-maximizing rChon), the data length N, the weighting factors n for fuzzy and fuzzy measure entropies, and the thresholds rF and rL for fuzzy measure entropy. The results were tested for normality using Lilliefors' composite goodness-of-fit test. Consequently, the p-value was calculated with either a two sample t-test or a Wilcoxon rank sum test.RESULTS:The first test shows a cross-over of entropy values with regard to a change of r. Thus, a clear statement that a higher entropy corresponds to a high irregularity is not possible, but is rather an indicator of differences in regularity. N should be at least 200 data points for r = 0.2 sigma and should even exceed a length of 1000 for r = rChon. The results for the weighting parameters n for the fuzzy membership function show different behavior when coupled with different r values, therefore the weighting parameters have been chosen independently for the different threshold values. The tests concerning rF and rL showed that there is no optimal choice, but r = rF = rL is reasonable with r = rChon or r = 0.2sigma.CONCLUSIONS:Some of the tests showed a dependency of the test significance on the data at hand. Nevertheless, as the medical conditions are unknown beforehand, compromises had to be made. Optimal parameter combinations are suggested for the methods considered. Yet, due to the high number of potential parameter combinations, further investigations of entropy for heart rate variability data will be necessary.
    BMC Bioinformatics 01/2014; 15(Suppl 6):S2. · 2.67 Impact Factor
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    ABSTRACT: Analysis of the arterial pressure curve plays an increasing role in cardiovascular risk stratification. Measures of wave reflection and aortic stiffness have been identified as independent predictors of risk. Their determination is usually based on wave propagation models of the circulation. Another modeling approach relies on modified Windkessel models, where pressure curves can be divided into reservoir and excess pressure. Little is known of their prognostic value. The aim of this study is to evaluate the predictive value of parameters gained from reservoir theory applied to aortic pressure curves in a cohort of high-risk patients. Furthermore the relation of these parameters to those from wave separation analysis is investigated. Central pressure curves from 674 patients with preserved ejection fraction, measured by radial tonometry and a validated transfer function, were analyzed. A high correlation between the amplitudes of backward traveling pressure waves and reservoir pressures was found (R=0.97). Various parameters calculated from the reservoir and excess pressure waveforms predicted cardiovascular events in univariate Cox proportional hazards modeling. In a multivariate model including several other risk factors such as brachial blood pressure, the amplitude of reservoir pressure remained a significant predictor (HR=1.37 per SD, p=0.016). Based on very different models, parameters from reservoir theory and wave separation analysis are closely related and can predict cardiovascular events to a similar extent. Although Windkessel models cannot describe all of the physiological properties of the arterial system, they can be useful to analyze its behavior and to predict cardiovascular events.
    International journal of cardiology 11/2013; · 6.18 Impact Factor
  • M. Bachler, C. Mayer, B. Hametner, S. Wassertheurer
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    ABSTRACT: Pulse wave velocity (PWV) in arteries is an estimator for arterial stiffness. As velocity is calculated as distance per time, the accuracy and reliability of PWV measurements depends heavily on the estimation of the pulse transit time (PTT). Several methods for the estimation of the PTT exist, often resulting in different PWV values. They rely on the exact determination of specific points in the pulse wave, which are easily affected by small changes of the signal. As there is still no agreement on the accuracy of these methods, only the reliability and stability of these commonly used "foot-to-foot" algorithms are compared in this paper. These algorithms are based on the detection of the diastole-minimum, the maximum of the first or second derivative or combinations thereof. We also adapted a new approach called "diastole-patching" based on the matching of a specific region of the pulse waves. The methods were tested using 2348 pulse waves from the MIMIC Database, collected from 46 subjects. Intra-subject deviation and relative outliers per subject were lowest in the adapted diastole-patching algorithm (4.9 ± 3ms and 0.6 ± 2.7%, respectively). Therefore, this study has shown that the diastole-patching method is the most stable and reliable of the algorithms under investigation.
    Proceedings of the 2013 8th EUROSIM Congress on Modelling and Simulation; 09/2013
  • B Hametner, T Weber, C Mayer, J Kropf, S Wassertheurer
    Mathematical and Computer Modelling of Dynamical Systems 08/2013; · 0.98 Impact Factor
  • S Wassertheurer, B Hametner
    Journal of human hypertension 07/2013; · 2.80 Impact Factor
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    ABSTRACT: OBJECTIVES: Recently, a novel method to estimate aortic pulse wave velocity (aPWV) noninvasively from an oscillometric single brachial cuff waveform reading has been introduced. We investigated whether this new approach provides acceptable estimates of aPWV compared with intra-aortic catheter measurements. METHODS: Estimated values of aPWV obtained from brachial cuff readings were compared with those obtained using an intra-aortic catheter in 120 patients (mean age 61.8±10.8 years) suspected for coronary artery disease undergoing cardiac catheterization. Differences between aPWV values obtained from the test device and those obtained from catheter measurements were estimated using Bland-Altman analysis. RESULTS: The mean difference±SD between brachial cuff-derived values and intra-aortic values was 0.43±1.24 m/s. Comparison of aPWV measured by the two methods showed a significant linear correlation (Pearson's R=0.81, P<0.0001). The mean difference for repeated oscillometric measurements of aPWV was 0.05 m/s, with 95% confidence interval limits from -0.47 to 0.57 m/s. CONCLUSION: aPWV can be obtained using an oscillometric device with brachial cuffs with acceptable accuracy compared with intra-aortic readings.
    Blood pressure monitoring 04/2013; · 1.62 Impact Factor
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    ABSTRACT: OBJECTIVES: To test whether measures of pulsatile arterial function are useful for diagnosing heart failure with preserved ejection fraction (HFPEF), in comparison with and in addition to Tissue Doppler Echocardiography (TDE). BACKGROUND: Increased arterial stiffness and wave reflections are present in most patients with HFPEF. METHODS: Patients with dyspnea as major symptom were categorized as having HFPEF or no HFPEF, based on invasively derived filling pressures and natriuretic peptide levels. Pulse wave velocity was measured invasively (aoPWV). Aortic pulse pressure (aoPP) and its components (incident pressure wave height - P1, forward wave amplitude - Pf; augmented pressure - AP; backward wave amplitude - Pb) were quantified non-invasively. RESULTS: 71 patients were classified as HFPEF, and 65 as no HFPEF (223 patients had intermediate results). Patients with HFPEF were older, more often had hypertension and diabetes, had larger left atria and higher left ventricular mass. Brachial (bPP) and aortic pulse pressures and all measures of arterial stiffness and wave reflections were higher in HFPEF patients. Receiver operating curve analysis derived area under the curve (AUC) values for separating HFPEF from no HFPEF were 0.823 for E/E'med, the best TDE parameter, 0.816 for bPP, and 0.867, 0.851, and 0.825 for aoPWV, aoPP, and Pb, respectively. Adding measures of pulsatile function to TDE resulted in an increase in AUC to 0.875 (bPP; p=0.03) and 0.901 (aoPP; p=0.005). In comparison with a TDE-based algorithm, net reclassification improvement was 32.9 % (p<0.0001). CONCLUSION: Measures of pulsatile arterial hemodynamics may complement TDE for the diagnosis of HFPEF.
    Journal of the American College of Cardiology 03/2013; · 15.34 Impact Factor
  • Artery Research 12/2012; 6(4):142.
  • B Hametner, S Wassertheurer, J Kropf, C Mayer, B Eber, T Weber
    Artery Research 12/2012; 6(4):147-148.
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    ABSTRACT: Duration and dynamic changes of QT and PR intervals as well as QRS complexes of ECG measurements are well established parameters in monitoring and diagnosis of cardiac diseases. Since automated annotations show numerous advantages over manual methods, the aim was to develop an algorithm suitable for online (real time) and offline ECG analysis. In this work we present this algorithm, its verification and the development process. The algorithm detects R peaks based on the amplitude, the first derivative and local statistic characteristics of the signal. Classification is performed to distinguish premature ventricular contractions from normal heartbeats. To improve the accuracy of the subsequent detection of QRS complexes, P and T waves, templates are built for each class of heartbeats. Using a continuous integration system, the algorithm was automatically verified against PhysioNet databases and achieved a sensitivity of 98.2% and a positive predictive value of 98.7%, respectively.
    Proceedings of the 2012 international conference on Pervasive Computing and the Networked World; 11/2012
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    ABSTRACT: Within the last decade the quantification of pulse wave reflections mainly focused on measures of central aortic systolic pressure and its augmentation through reflections based on pulse wave analysis (PWA). A complementary approach is the wave separation analysis (WSA), which quantifies the total amount of arterial wave reflection considering both aortic pulse and flow waves. The aim of this work is the introduction and comparison of aortic blood flow models for WSA assessment. To evaluate the performance of the proposed modeling approaches (Windkessel, triangular and averaged flow), comparisons against Doppler measurements are made for 148 patients with preserved ejection fraction. Stepwise regression analysis between WSA and PWA parameters are performed to provide determinants of methodological differences. Against Doppler measurement mean difference and standard deviation of the amplitudes of the decomposed forward and backward pressure waves are comparable for Windkessel and averaged flow models. Stepwise regression analysis shows similar determinants between Doppler and Windkessel model only. The results indicate that the Windkessel method provides accurate estimates of wave reflection in subjects with preserved ejection fraction. The comparison with waveforms derived from Doppler ultrasound as well as recently proposed simple triangular and averaged flow waves showed that this approach may reduce variability and provide realistic results.
    Computer methods and programs in biomedicine 10/2012; · 1.56 Impact Factor
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    ABSTRACT: Large artery stiffening and wave reflections are independent predictors of adverse events. To date, their assessment has been limited to specialised techniques and settings. A new, more practical method allowing assessment of central blood pressure from waveforms recorded using a conventional automated oscillometric monitor has recently been validated in laboratory settings. However, the feasibility of this method in a community based setting has not been assessed. One-off peripheral and central haemodynamic (systolic and diastolic blood pressure (BP) and pulse pressure) and wave reflection parameters (augmentation pressure (AP) and index, AIx) were obtained from 1,903 volunteers in an Austrian community setting using a transfer-function like method (ARCSolver algorithm) and from waveforms recorded with a regular oscillometric cuff. We assessed these parameters for known differences and associations according to gender and age deciles from <30 years to >80 years in the whole population and a subset with a systolic BP < 140 mmHg. We obtained 1,793 measures of peripheral and central BP, PP and augmentation parameters. Age and gender associations with central haemodynamic and augmentation parameters reflected those previously established from reference standard non-invasive techniques under specialised settings. Findings were the same for patients with a systolic BP below 140 mmHg (i.e. normotensive). Lower values for AIx in the current study are possibly due to differences in sampling rates, detection frequency and/or averaging procedures and to lower numbers of volunteers in younger age groups. A novel transfer-function like algorithm, using brachial cuff-based waveform recordings, provides robust and feasible estimates of central systolic pressure and augmentation in community-based settings.
    BMC Cardiovascular Disorders 06/2012; 12:48. · 1.50 Impact Factor

Publication Stats

232 Citations
130.64 Total Impact Points


  • 2010–2014
    • AIT Austrian Institute of Technology
      • Department of Health & Environment
      Wien, Vienna, Austria
  • 2013
    • Imperial College London
      Londinium, England, United Kingdom
    • Paracelsus Medical University Salzburg
      Salzburg, Salzburg, Austria
  • 2011
    • Klinikum Wels-Grieskirchen
      Wels, Upper Austria, Austria
  • 2003
    • Vienna University of Technology
      Wien, Vienna, Austria
    • CE Delft
      Delft, South Holland, Netherlands