Patient-specific pulse wave propagation model identifies cardiovascular risk characteristics in hemodialysis patients

Risk of cardiovascular associated death in dialysis patients is the highest among all other co-morbidities. Improving the identification of patients with the highest cardiovascular risk to design an adequate treatment is, therefore, of utmost importance. There are several non-invasive cardiovascular state biomarkers based on the pulse (pressure) wave propagation properties, but their major determinants are not fully understood. In the current study we aimed to provide a framework to precisely dissect the information available in non-invasively recorded pulse wave in hemodialysis patients. Radial pressure wave profiles were recorded before, during and after two independent hemodialysis sessions in 35 anuric prevalent hemodialysis patients and once in a group of 32 healthy volunteers. Each recording was used to estimate six subject-specific parameters of pulse wave propagation model. Pressure profiles were also analyzed using SphygmoCor software (AtCor Medical, Australia) to derive values of already established biomarkers, i.e. augmentation index and sub-endocardial viability ratio (SEVR). Data preprocessing using propensity score matching allowed to compare hemodialysis and healthy groups. Augmentation index remained on average stable at 142 ± 28% during dialysis and had similar values in both considered groups. SEVR, whose pre-dialytic value was on average lower by 12% compared to healthy participants, was improved by hemodialysis, with post-dialytic values indistinguishable from those in healthy population (p-value > 0.2). The model, however, identified that the patients on hemodialysis had significantly increased stiffness of both large and small arteries compared to healthy counterparts (> 60% before dialysis with p-value < 0.05 or borderline) and that it was only transiently decreased during hemodialysis session. Additionally, correlation-based clustering revealed that augmentation index reflects the shape of heart ejection profile and SEVR is associated with stiffness of larger arteries. Patient-specific pulse wave propagation modeling coupled with radial pressure profile recording correctly identified increased arterial stiffness in hemodialysis patients, while regular pulse wave analysis based biomarkers failed to show significant differences. Further model testing in larger populations and investigating other biomarkers are needed to confirm these findings.

[1]  J. Cockcroft,et al.  Use of arterial transfer functions for the derivation of central aortic waveform characteristics in subjects with type 2 diabetes and cardiovascular disease. , 2004, Diabetes care.

[2]  K. Hruska,et al.  Pathophysiological mechanisms of vascular calcification in end-stage renal disease. , 2001, Kidney international.

[3]  Aortic Pulse Wave Analysis Is Not a Surrogate for Central Arterial Pulse Wave Velocity , 2009, Experimental biology and medicine.

[4]  M. Karamanoglu,et al.  An analysis of the relationship between central aortic and peripheral upper limb pressure waves in man. , 1993, European heart journal.

[5]  M. Olufsen,et al.  Numerical Simulation and Experimental Validation of Blood Flow in Arteries with Structured-Tree Outflow Conditions , 2000, Annals of Biomedical Engineering.

[6]  Michael F O'Rourke,et al.  Changes in wave reflection with advancing age in normal subjects. , 2004, Hypertension.

[7]  J. Staessen,et al.  Clinical applications of arterial stiffness; definitions and reference values. , 2002, American journal of hypertension.

[8]  H. Struijker‐Boudier,et al.  Expert consensus document on arterial stiffness: methodological issues and clinical applications. , 2006, European heart journal.

[9]  Knut M. Wittkowski,et al.  Friedman-Type Statistics and Consistent Multiple Comparisons for Unbalanced Designs with Missing Data , 1988 .

[10]  W Huberts,et al.  A sensitivity analysis of a personalized pulse wave propagation model for arteriovenous fistula surgery. Part B: Identification of possible generic model parameters. , 2013, Medical engineering & physics.

[11]  I. Meredith,et al.  Use of arterial transfer functions for the derivation of central aortic waveform characteristics in subjects with type 2 diabetes and cardiovascular disease. , 2004, Diabetes care.

[12]  E. Lehmann Where is the evidence that radial artery tonometry can be used to accurately and noninvasively predict central aortic blood pressure in patients with diabetes? , 2000, Diabetes care.

[13]  W. Nichols,et al.  Augmentation index as a measure of peripheral vascular disease state. , 2002, Current opinion in cardiology.

[14]  Gary King,et al.  MatchIt: Nonparametric Preprocessing for Parametric Causal Inference , 2011 .

[15]  J.H.M. Tordoir,et al.  A sensitivity analysis of a personalized pulse wave propagation model for arteriovenous fistula surgery. Part A: Identification of most influential model parameters. , 2013, Medical engineering & physics.

[16]  A. Struthers,et al.  Pulse wave analysis and pulse wave velocity: a critical review of their strengths and weaknesses , 2003, Journal of hypertension.

[17]  Mark Butlin,et al.  Arterial blood pressure measurement and pulse wave analysis—their role in enhancing cardiovascular assessment , 2010, Physiological measurement.

[18]  B. D. Di Iorio,et al.  Influence of haemodialysis on variability of pulse wave velocity in chronic haemodialysis patients. , 2010, Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association.

[19]  N. Cable,et al.  The impact of exercise on derived measures of central pressure and augmentation index obtained from the SphygmoCor device. , 2009, Journal of applied physiology.

[20]  A. Gurovich,et al.  Pulse wave analysis and pulse wave velocity techniques: are they ready for the clinic? , 2011, Hypertension Research.

[21]  N. Westerhof,et al.  Aortic Input Impedance in Normal Man: Relationship to Pressure Wave Forms , 1980, Circulation.

[22]  G. London,et al.  Vascular Calcifications, Arterial Aging and Arterial Remodeling in ESRD , 2013, Blood Purification.

[23]  I. Meredith,et al.  ‘Generalizability’ of a radial-aortic transfer function for the derivation of central aortic waveform parameters , 2007, Journal of hypertension.

[24]  G. Mancia,et al.  Central blood pressure measurements and antihypertensive therapy: a consensus document. , 2007, Hypertension.

[25]  Kozo Hirata,et al.  Noninvasive pulse waveform analysis in clinical trials: similarity of two methods for calculating aortic systolic pressure. , 2007, American journal of hypertension.

[26]  A. Sassano,et al.  The impact of arteriovenous fistula formation on central hemodynamic pressures in chronic renal failure patients: a prospective study. , 2002, American journal of kidney diseases : the official journal of the National Kidney Foundation.

[27]  João Cardoso,et al.  Pulse pressure waveform estimation using distension profiling with contactless optical probe. , 2014, Medical engineering & physics.

[28]  M. O'Rourke,et al.  Prospective Evaluation of a Method for Estimating Ascending Aortic Pressure From the Radial Artery Pressure Waveform , 2001, Hypertension.

[29]  A P Avolio,et al.  Effects of aging on changing arterial compliance and left ventricular load in a northern Chinese urban community. , 1983, Circulation.

[30]  A. Hughes,et al.  Validation of non-invasive central blood pressure devices: ARTERY Society task force consensus statement on protocol standardization , 2017, European heart journal.

[31]  Jan Poleszczuk,et al.  Subject-specific pulse wave propagation modeling: Towards enhancement of cardiovascular assessment methods , 2018, PloS one.

[32]  Patrick Segers,et al.  Assessment of pressure wave reflection: getting the timing right! , 2007, Physiological measurement.

[33]  W Huberts,et al.  A pulse wave propagation model to support decision-making in vascular access planning in the clinic. , 2012, Medical engineering & physics.

[34]  H. Bøtker,et al.  Estimated aortic blood pressure based on radial artery tonometry underestimates directly measured aortic blood pressure in patients with advancing chronic kidney disease staging and increasing arterial stiffness. , 2016, Kidney international.

[35]  Richard B. Devereux,et al.  Central Pressure More Strongly Relates to Vascular Disease and Outcome Than Does Brachial Pressure: The Strong Heart Study , 2007, Hypertension.

[36]  J. Filipovský,et al.  Expert consensus document on the measurement of aortic stiffness in daily practice using carotid-femoral pulse wave velocity. , 2012, Journal of hypertension.

[37]  C. H. Chen,et al.  Estimation of central aortic pressure waveform by mathematical transformation of radial tonometry pressure. Validation of generalized transfer function. , 1997, Circulation.

[38]  J. Floege,et al.  Vascular calcification in patients with end-stage renal disease. , 2004, Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association.

[39]  Carlos Correia,et al.  Novel Methods for Pulse Wave Velocity Measurement , 2015, Journal of Medical and Biological Engineering.

[40]  R. Foley,et al.  United States Renal Data System public health surveillance of chronic kidney disease and end-stage renal disease , 2015, Kidney international supplements.

[41]  Alice Stanton,et al.  Differential Impact of Blood Pressure–Lowering Drugs on Central Aortic Pressure and Clinical Outcomes: Principal Results of the Conduit Artery Function Evaluation (CAFE) Study , 2006, Circulation.