Abstract-The prognostic value of central systolic blood pressure has been established recently. At present, its noninvasive assessment is limited by the need of dedicated equipment and trained operators. Moreover, ambulatory and home blood pressure monitoring of central pressures are not feasible. An algorithm enabling conventional automated oscillometric blood pressure monitors to assess central systolic pressure could be of value. We compared central systolic pressure, calculated with a transfer-function like method (ARCSolver algorithm), using waveforms recorded with a regular oscillometric cuff suitable for ambulatory measurements, with simultaneous high-fidelity invasive recordings, and with noninvasive estimations using a validated device, operating with radial tonometry and a generalized transfer function. Both studies revealed a good agreement between the oscillometric cuff-based central systolic pressure and the comparator. In the invasive study, composed of 30 patients, mean difference between oscillometric cuff/ARCSolverbased and invasive central systolic pressures was 3.0 mm Hg (SD: 6.0 mm Hg) with invasive calibration of brachial waveforms and Ϫ3.0 mm Hg (SD: 9.5 mm Hg) with noninvasive calibration of brachial waveforms. Results were similar when the reference method (radial tonometry/transfer function) was compared with invasive measurements. In the noninvasive study, composed of 111 patients, mean difference between oscillometric cuff/ARCSolver-derived and radial tonometry/transfer function-derived central systolic pressures was Ϫ0.5 mm Hg (SD: 4.7 mm Hg). In conclusion, a novel transfer function-like algorithm, using brachial cuff-based waveform recordings, is suited to provide a realistic estimation of central systolic pressure. A lthough mean blood pressure (MBP) and diastolic blood pressure (DBP) are relatively constant in the conduit arteries, it has been known for decades that systolic blood pressure (SBP) and pulse pressure are higher in the peripheral than in the central arteries. 1 This so-called SBP or pulse pressure amplification is the consequence of the progressive reduction of diameter and increase in stiffness from the proximal to the distal arterial vessels and mostly of the modification in the transit of wave reflections. 2 It seems obvious that central pressures are more relevant than peripheral pressures for the pathogenesis of cardiovascular disease: it is central SBP (cSBP) against the heart ejects (afterload), and it is central pulse pressure that distends the large elastic arteries. 3 Indeed, cSBP and central pulse pressure have been associated more closely with left ventricular hypertrophy and carotid atherosclerosis as markers of hypertensive end-organ damage than brachial pressures in different populations. 4 -6

In the European Society of Cardiology–European Society of Hypertension guidelines of the year 2007, the consequences of arterial stiffness and wave reflection on cardiovascular mortality have a major role. But the investigators claimed the poor availability of devices/methods providing easy and widely suitable measuring of arterial wall stiffness or their surrogates like augmentation index (AIx) or aortic systolic blood pressure (aSBP). The aim of this study was the validation of a novel method determining AIx and aSBP based on an oscillometric method using a common cuff (ARCSolver) against a validated tonometric system (SphygmoCor). aSBP and AIx measured with the SphygmoCor and ARCSolver method were compared for 302 subjects. The mean age was 56 years with an s.d. of 20 years. At least two iterations were performed in each session. This resulted in 749 measurements. For aSBP the mean difference was −0.1 mm Hg with an s.d. of 3.1 mm Hg. The mean difference for AIx was 1.2% with an s.d. of 7.9%. There was no significant difference in reproducibility of AIx for both methods. The variation estimate of inter- and intraobserver measurements was 6.3% for ARCSolver and 7.5% for SphygmoCor. The ARCSolver method is a novel method determining AIx and aSBP based on an oscillometric system with a cuff. The results agree with common accepted tonometric measurements. Its application is easy and for widespread use.

aPWV can be obtained using an oscillometric device with brachial cuffs with acceptable accuracy compared with intra-aortic readings.

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BackgroundHeart 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.MethodsThis 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 σ, 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.ResultsThe 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 σ 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 = 0.2σ.ConclusionsSome 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.

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Rationale : Patients with end-stage renal disease are characterized by increased cardiovascular and all-cause mortality because of advanced remodeling of the macrovascular and microvascular beds. Objective : The aim of this study was to determine whether retinal microvascular function can predict all-cause and cardiovascular mortality in patients with end-stage renal disease. Methods and Results : In the multicenter prospective observational ISAR study (Risk Stratification in End-Stage Renal Disease), data on dynamic retinal vessel analysis were available in a subcohort of 214 dialysis patients (mean age, 62.6±15.0; 32% women). Microvascular dysfunction was quantified by measuring maximum arteriolar dilation and maximum venular dilation (vMax) of retinal vessels in response to flicker light stimulation. During a mean follow-up of 44 months, 55 patients died, including 25 cardiovascular and 30 noncardiovascular fatal events. vMax emerged as a strong independent predictor for all-cause mortality. In the Kaplan-Meier analysis, individuals within the lowest tertile of vMax showed significantly shorter 3-year survival rates than those within the highest tertile (66.9±5.8% versus 92.4±3.3%). Univariate and multivariate hazard ratios for all-cause mortality per SD increase of vMax were 0.62 (0.47–0.82) and 0.65 (0.47–0.91), respectively. Maximum arteriolar dilation and vMax were able to significantly predict nonfatal and fatal cardiovascular events (hazard ratio, 0.74 [0.57–0.97] and 0.78 [0.61–0.99], respectively). Conclusions : Our results provide the first evidence that impaired retinal venular dilation is a strong and independent predictor of all-cause mortality in hemodialyzed end-stage renal disease patients. Dynamic retinal vessel analysis provides added value for prediction of all-cause mortality and may be a novel diagnostic tool to optimize cardiovascular risk stratification in end-stage renal disease and other high-risk cardiovascular cohorts. Clinical Trial Registration : URL: http://www.clinicaltrials.gov . Unique identifier: NCT01152892.

BackgroundThe ISAR study is a prospective, longitudinal, observational cohort study to improve the cardiovascular risk stratification in endstage renal disease (ESRD). The major goal is to characterize the cardiovascular phenotype of the study subjects, namely alterations in micro- and macrocirculation and to determine autonomic function.Methods/designWe intend to recruit 500 prevalent dialysis patients in 17 centers in Munich and the surrounding area. Baseline examinations include: (1) biochemistry, (2) 24-h Holter Electrocardiography (ECG) recordings, (3) 24-h ambulatory blood pressure measurement (ABPM), (4) 24 h pulse wave analysis (PWA) and pulse wave velocity (PWV), (5) retinal vessel analysis (RVA) and (6) neurocognitive testing. After 24 months biochemistry and determination of single PWA, single PWV and neurocognitive testing are repeated. Patients will be followed up to 6 years for (1) hospitalizations, (2) cardiovascular and (3) non-cardiovascular events and (4) cardiovascular and (5) all-cause mortality.Discussion/conclusionWe aim to create a complex dataset to answer questions about the insufficiently understood pathophysiology leading to excessively high cardiovascular and non-cardiovascular mortality in dialysis patients. Finally we hope to improve cardiovascular risk stratification in comparison to the use of classical and non-classical (dialysis-associated) risk factors and other models of risk stratification in ESRD patients by building a multivariable Cox-Regression model using a combination of the parameters measured in the study.Clinical trials identifierClinicalTrials.gov NCT01152892 (June 28, 2010)