Association of Ambulatory Blood Pressure with All-Cause and Cardiovascular Mortality in Hemodialysis Patients: Effects of Heart Failure and Atrial Fibrillation.

BACKGROUND: Evidence on the utility of ambulatory BP monitoring for risk prediction has been scarce and inconclusive in patients on hemodialysis. In addition, in cardiac diseases such as heart failure and atrial fibrillation (common among patients on hemodialysis), studies have found that parameters such as systolic BP (SBP) and pulse pressure (PP) have inverse or nonlinear (U-shaped) associations with mortality. METHODS: In total, 344 patients on hemodialysis (105 with atrial fibrillation, heart failure, or both) underwent ambulatory BP monitoring for 24 hours, starting before a dialysis session. The primary end point was all-cause mortality; the prespecified secondary end point was cardiovascular mortality. We performed linear and nonlinear Cox regression analyses for risk prediction to determine the associations between BP and study end points. RESULTS: During the mean 37.6-month follow-up, 115 patients died (47 from a cardiovascular cause). SBP and PP showed a U-shaped association with all-cause and cardiovascular mortality in the cohort. In linear subgroup analysis, SBP and PP were independent risk predictors and showed a significant inverse relationship to all-cause and cardiovascular mortality in patients with atrial fibrillation or heart failure. In patients without these conditions, these associations were in the opposite direction. SBP and PP were significant independent risk predictors for cardiovascular mortality; PP was a significant independent risk predictor for all-cause mortality. CONCLUSIONS: This study provides evidence for the U-shaped association between peripheral ambulatory SBP or PP and mortality in patients on hemodialysis. Furthermore, it suggests that underlying cardiac disease can explain the opposite direction of associations.

Cardiovascular Mortality Can Be Predicted by Heart Rate Turbulence in Hemodialysis Patients.

BACKGROUND: Excess mortality in hemodialysis patients is mostly of cardiovascular origin. We examined the association of heart rate turbulence (HRT), a marker of baroreflex sensitivity, with cardiovascular mortality in hemodialysis patients. METHODS: A population of 290 prevalent hemodialysis patients was followed up for a median of 3 years. HRT categories 0 (both turbulence onset [TO] and slope [TS] normal), 1 (TO or TS abnormal), and 2 (both TO and TS abnormal) were obtained from 24 h Holter recordings. The primary end-point was cardiovascular mortality. Associations of HRT categories with the endpoints were analyzed by multivariable Cox regression models including HRT, age, albumin, and the improved Charlson Comorbidity Index for hemodialysis patients. Multivariable linear regression analysis identified factors associated with TO and TS. RESULTS: During the follow-up period, 20 patients died from cardiovascular causes. In patients with HRT categories 0, 1 and 2, cardiovascular mortality was 1, 10, and 22%, respectively. HRT category 2 showed the strongest independent association with cardiovascular mortality with a hazard ratio of 19.3 (95% confidence interval: 3.69-92.03; P < 0.001). Age, calcium phosphate product, and smoking status were associated with TO and TS. Diabetes mellitus and diastolic blood pressure were only associated with TS. CONCLUSION: Independent of known risk factors, HRT assessment allows identification of hemodialysis patients with low, intermediate, and high risk of cardiovascular mortality. Future prospective studies are needed to translate risk prediction into risk reduction in hemodialysis patients.

Implementation and verification of an enhanced algorithm for the automatic computation of RR-interval series derived from 24 h 12-lead ECGs.

An important tool in early diagnosis of cardiac dysfunctions is the analysis of electrocardiograms (ECGs) obtained from ambulatory long-term recordings. Heart rate variability (HRV) analysis became a significant tool for assessing the cardiac health. The usefulness of HRV assessment for the prediction of cardiovascular events in end-stage renal disease patients was previously reported. The aim of this work is to verify an enhanced algorithm to obtain an RR-interval time series in a fully automated manner. The multi-lead corrected R-peaks of each ECG lead are used for RR-series computation and the algorithm is verified by a comparison with manually reviewed reference RR-time series. Twenty-four hour 12-lead ECG recordings of 339 end-stage renal disease patients from the ISAR (rISk strAtification in end-stage Renal disease) study were used. Seven universal indicators were calculated to allow for a generalization of the comparison results. The median score of the indicator of synchronization, i.e. intraclass correlation coefficient, was 96.4% and the median of the root mean square error of the difference time series was 7.5 ms. The negligible error and high synchronization rate indicate high similarity and verified the agreement between the fully automated RR-interval series calculated with the AIT Multi-Lead ECGsolver and the reference time series. As a future perspective, HRV parameters calculated on this RR-time series can be evaluated in longitudinal studies to ensure clinical benefit.