Reproducibility of pulse-wave analysis and pulse-wave velocity determination in chronic kidney disease

Frimodt‐Møller, Marie; Nielsen, Arne Høj; Kamper, Anne-Lise; Strandgaard, Svend

doi:10.1093/ndt/gfm470

Cited by 82 publications

(89 citation statements)

References 21 publications

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“…Some data concerning validation was also published in [29] comprising three sets of recordings for the carotid pressure waveform at left and right carotid arteries, under standardized conditions, in 20 volunteers by three trained operators. Inter and intra-operator differences were calculated being good indicators, similar to other data reported in literature for commercial devices [30].…”

Section: Pwa Measurementssupporting

confidence: 80%

Cardiovascular risk analysis by means of pulse morphology and clustering methodologies

Almeida

Borba

Pereira

et al. 2014

Computer Methods and Programs in Biomedicine

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c o m p u t e r m e t h o d s a n d p r o g r a m s i n b i o m e d i c i n e 1 1 7 ( 2 0 1 4 ) [257][258][259][260][261][262][263][264][265][266] j o u r n a l h o m e p a g e : w w w . i n t l . e l s e v i e r h e a l t h . c o m / j o u r n a l s / c m p b a b s t r a c tThe purpose of this study was the development of a clustering methodology to deal with arterial pressure waveform (APW) parameters to be used in the cardiovascular risk assessment. One hundred sixteen subjects were monitored and divided into two groups. The first one (23 hypertensive subjects) was analyzed using APW and biochemical parameters, while the remaining 93 healthy subjects were only evaluated through APW parameters. The expectation maximization (EM) and k-means algorithms were used in the cluster analysis, and the risk scores (the Framingham Risk Score (FRS), the Systematic COronary Risk Evaluation (SCORE) project, the Assessing cardiovascular risk using Scottish Intercollegiate Guidelines Network (ASSIGN) and the PROspective Cardiovascular Münster (PROCAM)), commonly used in clinical practice were selected to the cluster risk validation. The result from the clustering risk analysis showed a very significant correlation with ASSIGN (r = 0.582, p < 0.01) and a significant correlation with FRS (r = 0.458, p < 0.05). The results from the comparison of both groups also allowed to identify the cluster with higher cardiovascular risk in the healthy group. These results give new insights to explore this methodology in future scoring trials.© 2014 Elsevier Ireland Ltd. All rights reserved. IntroductionThe atherosclerotic cardiovascular disease (CVD) is the most common cause of death worldwide, resulting from the combination of several risk factors [1]. The international guidelines [2,3] consider that individuals with established CVD should be the first priority for preventive measures application. The concern in changing the current healthcare paradigm, from reactive towards preventive care, aims at identify individuals for risk in early stages of disease development, and then, * Corresponding author. Tel.: +351 239410109.E-mail address: vaniagalmeida@lei.fis.uc.pt (V.G. Almeida).direct more efforts and attention to the risk factors modification [4,5]. Fortunately, this is an emergent tendency that can be addressed using the traditional risk scores, but also using innovative predictive algorithms. During the last years many risk estimation systems have been developed in order to assist clinicians in the risk assessment, and in the individual chances prediction, for CVD development. The major challenges of these tools are the capabilities to: (1) identify high risk individuals, (2) weight the individual effects of all risk factors, (3) stratify or organize who needs lifestyle advice or medical therapy, and finally (4) avoid http://dx

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Section: Pwa Measurementssupporting

confidence: 80%

Cardiovascular risk analysis by means of pulse morphology and clustering methodologies

Almeida

Borba

Pereira

et al. 2014

Computer Methods and Programs in Biomedicine

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“…12,27 Both use electrocardiogram-gated sequential tonometric measurements to asses aortic (carotid-femoral) PWV and are widely used in clinical and research practice. [23][24][25] Survival studies in adults indicate that PWV measured by applanation tonometry has a good clinical predictive value. 20 Involving more than 1000 children, our research group has furthermore confirmed the applicability of the PP device to mass screening of children of different age groups.…”

Section: Discussionmentioning

confidence: 99%

“…They are easily applied in adults and children and have a fair reproducibility. [22][23][24][25][26] PP and SC devices have been validated invasively in adults. 12,27 It is claimed that, in children, PWV measurements by applanation tonometry may be difficult to carry out as they are time consuming and require some degree of patient cooperation.…”

Section: Introductionmentioning

confidence: 99%

Measurement of pulse wave velocity in children and young adults: a comparative study using three different devices

et al. 2011

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To estimate the value of pulse wave velocity (PWV) in pediatric cardiovascular disease, prospective studies are needed. Various instruments based on different measurement principles are proposed for use in children, hence the need to test the comparability of these devices in this younger population. The objective of this study was to compare PWV measured by oscillometry (Vicorder (VIC)) with the gold standard of applanation tonometry (PulsePen (PP), Sphygmocor (SC)). PWV was measured in 98 children and young adults (age: 16.7(6.3-26.6) years (median(range)) with the above three devices at the same visit under standardized conditions. Mean PWV measured by VIC was significantly lower than that measured by SC and PP. There was no difference following path length correction of the VIC measurement (using the distance between the jugular notch and the center of the femoral cuff), (PP: 6.12(1.00), SC: 5.94(0.91), VIC: 6.14(0.75) m s À1 ). Velocities measured by the three devices showed highly significant correlations. Bland-Altman analysis revealed excellent concordance between all three devices, however, there was a small but significant proportional error in the VIC measurements showing a trend toward lower PWV measured by VIC at higher PWV values. Our study provides data on the three most frequently used instruments in pediatrics. Following path length correction of the VIC, all three devices provided comparable results. Thus, our work allows extrapolating data between previously established normal PWV values for children and forthcoming studies using these instruments to assess children at long-term risk of cardiovascular disease. The small proportional error of VIC needs additional technical development to improve the accuracy of the measurements.

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“…To date, repeated PWV measurements have been evaluated only in respect to their reproducibility. 6,7 Recently, in a meta-analysis of 17 longitudinal studies that evaluated aortic PWV and followed up 15 877 subjects for a mean of 7.7 years, the absolute differences/changes of PWV (in m s À1 ) have been 'translated' to a specific change in CVR (1 m s À1 change corresponds to 15% change in CVR)). In addition, normal values of PWV have been also published, 8 allowing the classification of a PWV measurement to normal or abnormal.…”

Section: Introductionmentioning

confidence: 99%

Assessment of differences between repeated pulse wave velocity measurements in terms of ‘bias’ in the extrapolated cardiovascular risk and the classification of aortic stiffness: Is a single PWV measurement enough?

et al. 2011

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Currently, there is no recommendation regarding the minimum number of pulse wave velocity (PWV) measurements to optimize individual's cardiovascular risk (CVR) stratification. The aim of this study was to examine differences between three single consecutive and averaged PWV measurements in terms of the extrapolated CVR and the classification of aortic stiffness as normal. In 60 subjects who referred for CVR assessment, three repeated measurements of blood pressure (BP), heart rate and PWV were performed. The reproducibility was evaluated by the intraclass correlation coefficient (ICC) and mean±s.d. of differences. The absolute differences between single and averaged PWV measurements were classified as: p0.25, 0.26-0.49, 0.50-0.99 and X1 m s À1 . A difference X0.5 m s À1 (corresponding to 7.5% change in CVR, metaanalysis data from 412 000 subjects) was considered as clinically meaningful; PWV values (single or averaged) were classified as normal according to respective age-corrected normal values (European Network data). Kappa statistic was used to evaluate the agreement between classifications. PWV for the first, second and third measurement was 7.0±1.9, 6.9±1.9, 6.9±2.0 m s À1 , respectively (P ¼ 0.319); BP and heart rate did not vary significantly. A good reproducibility between single measurements was observed (ICC40.94, s.d. ranged between 0.43 and 0.64 m s À1 ). A high percent with difference X0.5 m s À1 was observed between: any pair of the three single PWV measurements (26.6-38.3%); the first or second single measurement and the average of the first and second (18.3%); any single measurement and the average of three measurements (10-20%). In only up to 5% a difference X0.5 m s À1 was observed between the average of three and the average of any two PWV measurements. There was no significant agreement regarding PWV classification as normal between: the first or second measurement and the averaged PWV values. There was significant agreement in classification made by the average of the first two and the average of three PWV measurements (j ¼ 0.85, Po0.001). Even when high reproducibility in PWV measurement is succeeded single measurements provide quite variable results in terms of the extrapolated CVR and the classification of aortic stiffness as normal. The average of two PWV measurements provides similar results with the average of three.

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Reproducibility of pulse-wave analysis and pulse-wave velocity determination in chronic kidney disease

Cited by 82 publications

References 21 publications

Cardiovascular risk analysis by means of pulse morphology and clustering methodologies

Cardiovascular risk analysis by means of pulse morphology and clustering methodologies

Measurement of pulse wave velocity in children and young adults: a comparative study using three different devices

Assessment of differences between repeated pulse wave velocity measurements in terms of ‘bias’ in the extrapolated cardiovascular risk and the classification of aortic stiffness: Is a single PWV measurement enough?

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