Cardiac response to hemodialysis with different cardiovascular tolerance: heart rate variability and QT interval analysis

Estimation of potassium levels in hemodialysis patients by T wave nonlinear dynamics and morphology markers

OBJECTIVE

Noninvasive screening of hypo- and hyperkalemia can prevent fatal arrhythmia in end-stage renal disease (ESRD) patients, but current methods for monitoring of serum potassium (K+) have important limitations. We investigated changes in nonlinear dynamics and morphology of the T wave in the electrocardiogram (ECG) of ESRD patients during hemodialysis (HD), assessing their relationship with K+ and designing a K+ estimator.

METHODS

ECG recordings from twenty-nine ESRD patients undergoing HD were processed. T waves in 2-min windows were extracted at each hour during an HD session as well as at 48 h after HD start. T wave nonlinear dynamics were characterized by two indices related to the maximum Lyapunov exponent (λt, λwt) and a divergence-related index (η). Morphological variability in the T wave was evaluated by three time warping-based indices (dw, reflecting morphological variability in the time domain, and da and daNL, in the amplitude domain). K+was measured from blood samples extracted during and after HD. Stage-specific and patient-specific K+ estimators were built based on the quantified indices and leave-one-out cross-validation was performed separately for each of the estimators.

RESULTS

The analyzed indices showed high inter-individual variability in their relationship with K+. Nevertheless, all of them had higher values at the HD start and 48 h after it, corresponding to the highest K+. The indices η and dw were the most strongly correlated with K+ (median Pearson correlation coefficient of 0.78 and 0.83, respectively) and were used in univariable and multivariable linear K+ estimators. Agreement between actual and estimated K+ was confirmed, with averaged errors over patients and time points being 0.000 ± 0.875 mM and 0.046 ± 0.690 mM for stage-specific and patient-specific multivariable K+ estimators, respectively.

CONCLUSION

ECG descriptors of T wave nonlinear dynamics and morphological variability allow noninvasive monitoring of K+ in ESRD patients.

SIGNIFICANCE

ECG markers have the potential to be used for hypo- and hyperkalemia screening in ESRD patients.

Effect of citric-acid dialysate on the QTC-interval

Lower dialysate calcium (dCa) concentration and dialysate citric-acidification may positively affect calcification propensity in serum of haemodialysis (HD) patients. However, the accompanying lower ionized blood calcium concentration may lead to a prolonged cardiac action potential, which is possibly pro-arrhythmic. The aim of this study is to investigate the influence of citric-acid dialysate on the QT-interval corrected for heart rate (QTc) compared to conventional dialysate with different dCa concentrations. We conducted a four-week multicentre, randomized cross-over trial. In week one and three patients received acetic-acid dialysate with a dCa of 1.50 mmol/l (A1.5), in week two and four acetic-acid dialysate with a dCa of 1.25 mmol/l (A1.25) or citric-acid dialysate (1.0 mmol/l) with a dCa of 1.50 mmol/l (C1.5) depending on randomization. Patients had continuous ECG monitoring during one session in week one, two and four. The data of 13 patients were available for analysis. Results showed a significant though limited increase of QTc with C1.5 (from 427 to 444 ms (start to end); p = 0.007) and with A1.25 (from 431 to 449 ms; p < 0.001), but not with A1.5 (from 439 to 443 ms; p = 0.13). In conclusion, we found that the use of C1.5 or A1.25 is associated with a significant prolongation of QTc which was however relatively limited.

Monitoring blood potassium concentration in hemodialysis patients by quantifying T-wave morphology dynamics

We investigated the ability of time-warping-based ECG-derived markers of T-wave morphology changes in time (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_{w}$$\end{document}dw) and amplitude (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_a$$\end{document}da), as well as their non-linear components (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${d_w^{{\mathrm{NL}}}}$$\end{document}dwNL and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${d_a^{\mathrm{NL}}}$$\end{document}daNL), and the heart rate corrected counterpart (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_{w,c}$$\end{document}dw,c), to monitor potassium concentration (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$[K^{+}]$$\end{document}[K+]) changes (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta [K^+]$$\end{document}Δ[K+]) in end-stage renal disease (ESRD) patients undergoing hemodialysis (HD). We compared the performance of the proposed time-warping markers, together with other previously proposed \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$[K^{+}]$$\end{document}[K+] markers, such as T-wave width (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_w$$\end{document}Tw) and T-wave slope-to-amplitude ratio (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_{S/A}$$\end{document}TS/A), when computed from standard ECG leads as well as from principal component analysis (PCA)-based leads. 48-hour ECG recordings and a set of hourly-collected blood samples from 29 ESRD-HD patients were acquired. Values of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_w$$\end{document}dw, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_a$$\end{document}da, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${d_w^{\mathrm{NL}}}$$\end{document}dwNL, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${d_a^{\mathrm{NL}}}$$\end{document}daNL and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_{w,c}$$\end{document}dw,c were calculated by comparing the morphology of the mean warped T-waves (MWTWs) derived at each hour along the HD with that from a reference MWTW, measured at the end of the HD. From the same MWTWs \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_w$$\end{document}Tw and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_{S/A}$$\end{document}TS/A were also extracted. Similarly, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta [K^+]$$\end{document}Δ[K+] was calculated as the difference between the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$[K^{+}]$$\end{document}[K+] values at each hour and the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$[K^{+}]$$\end{document}[K+] reference level at the end of the HD session. We found that \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_{w}$$\end{document}dw and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_{w,c}$$\end{document}dw,c showed higher correlation coefficients with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta [K^+]$$\end{document}Δ[K+] than \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_{S/A}$$\end{document}TS/A—Spearman’s (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\rho$$\end{document}ρ) and Pearson’s (r)—and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_w$$\end{document}Tw—Spearman’s (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\rho$$\end{document}ρ)—in both SL and PCA approaches being the intra-patient median \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\rho \ge 0.82$$\end{document}ρ≥0.82 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$r \ge 0.87$$\end{document}r≥0.87 in SL and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\rho \ge 0.82$$\end{document}ρ≥0.82 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$r \ge 0.89$$\end{document}r≥0.89 in PCA respectively. Our findings would point at \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_{w}$$\end{document}dw and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_{w,c}$$\end{document}dw,c as the most suitable surrogate of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta [K^+]$$\end{document}Δ[K+], suggesting that they could be potentially useful for non-invasive monitoring of ESRD-HD patients in hospital, as well as in ambulatory settings. Therefore, the tracking of T-wave morphology variations by means of time-warping analysis could improve continuous and remote \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$[K^{+}]$$\end{document}[K+] monitoring of ESRD-HD patients and flagging risk of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$[K^{+}]$$\end{document}[K+]-related cardiovascular events.

Hemodialysis-induced repolarization abnormalities on ECG are influenced by serum calcium levels and ultrafiltration volumes

PURPOSE

Hemodialysis (HD) patients are known to have high cardiovascular mortality rate. Sudden cardiac death (SCD) due to arrhythmias causes most of the cardiac deaths. HD per se may lead to ECG abnormalities and ventricular arrhythmias. Monitoring ECG parameters such as corrected QT interval, QT dispersion (QTd), Tpe interval may be useful to stratify the patients with high risk of arrhythmia and SCD. Herein we aimed to investigate the effects of changes in serum electrolyte levels and pH on ECG parameters before and after the HD.

METHODS

A total of 50 chronic HD patients (mean age 58 ± 19; male 27) were enrolled. Patients with unmeasurable T waves; atrial fibrillation; bundle branch block; use of class I or class III antiarrhythmic drugs were excluded. Serum potassium, magnesium, calcium, urea, creatinine and pH were measured before and after HD treatment. Standard surface 12-lead ECGs were recorded before and after HD. QTc, QTd, Tpe, JT interval, P-wave-duration, P-wave dispersion were determined.

RESULTS

Serum potassium and magnesium decreased, and calcium, pH and bicarbonate levels increased; QRS and Tpe interval were increased after HD. Basal Tpe was correlated with urea (r = 0.31, p = 0.02). Tpe interval was higher in hypocalcemic compared to normocalcemic patients (77 ± 11 vs 70 ± 9 ms, p = 0.02). ∆Tpe was correlated with ∆calcium (r = -0.32, p = 0.02). Basal QTc was correlated with calcium (r = -0.62, p < 0.001). ∆QTc was correlated with basal calcium (r = 0.39, p = 0.005) and ∆calcium (r = -0.46, p < 0.001). Basal JT was correlated with calcium (r = -0.55, p < 0.001). ∆JT was correlated with pH (r = 0.35, p = 0.01), ∆calcium (r = -0.53, p < 0.001) and ∆magnesium (r = -0.30, p = 0.03). Before HD, 12 patients (12%) were hypermagnesemic of whom JT intervals were lower (314 ± 20 vs 332 ± 23 ms, p = 0.02). Ultrafiltration per body weight was associated with ∆QTc (r = -0.40, p = 0.007) and ∆JT (r = -0.36, p = 0.01).

CONCLUSION

QRS and Tpe intervals were increased after HD. Tpe interval was longer in hypocalcemic patients. Change in Tpe was negatively associated with the change in calcium. Ultrafiltration was associated with ∆QTc and ∆JT. Calcium and ultrafiltration seem to be the most important determinants of ECG parameters of HD-induced repolarization abnormalities.

Inflammation and prolonged QT time: results from the Cardiovascular Disease, Living and Ageing in Halle (CARLA) study

Background

Previous research found an association of CRP with QT time in population based samples. Even more, there is evidence of a substantial involvement of the tumor necrosis factor-alpha system in the pathophysiology of cardiac arrhythmia, while the role of Interleukin 6 remains inconclusive.

Objective

To determine the association between inflammation with an abnormally prolonged QT-time (APQT) in men and women of the elderly general population.

Methods

Data descend from the baseline examination of the prospective, population-based Cardiovascular Disease, Living and Ageing in Halle (CARLA) Study. After exclusion of subjects with atrial fibrillation and missing ECG recording the final study cohort consisted of 919 men and 797 women. Blood parameters of inflammation were the soluble TNF-Receptor 1 (sTNF-R1), the high-sensitive C-reactive protein (hsCRP), and Interleukin 6 (IL-6). In accordance with major cardiologic societies we defined an APQT above a QT time of 460 ms in women and 450 ms in men. Effect sizes and the corresponding 95% confidence intervals (CI) were estimated by performing multiple linear and logistic regression analyses including the analysis of sex differences by interaction terms.

Results

After covariate adjustment we found an odds ratio (OR) of 1.89 (95% CI: 1.13, 3.17) per 1000 pg/mL increase of sTNF-R1 in women, and 0.74 (95% CI: 0.48, 1.15) in men. In the covariate adjusted linear regression sTNF-R1 was again positively associated with QT time in women (5.75 ms per 1000 pg/mL, 95% CI: 1.32, 10.18), but not in men. Taking possible confounders into account IL-6 and hsCRP were not significantly related to APQT in both sexes.

Conclusion

Our findings from cross-sectional analyses give evidence for an involvement of TNF-alpha in the pathology of APQT in women.

Effects of fluid overload on heart rate variability in chronic kidney disease patients on hemodialysis

Background

While fluid overload (FO) and alterations in the autonomic nervous system (ANS) such as hypersympathetic activity, are known risk factors for cardiovascular morbidity and mortality in patients on chronic hemodialysis (HD), their relationship has not been thoroughly studied.

Methods

In this observational study involving 69 patients on chronic HD, FO was assessed by whole body bioimpedance measurements before the midweek HD session and ANS activity reflected by Heart Rate Variability (HRV) was measured using 24-hour Holter electrocardiogram recordings starting before the same HD treatment. In total, 13 different HRV indices were analyzed, comprising a mixture of time domain, frequency domain and complexity parameters. A correlation analysis was performed between the HRV indices and hydration status indices. Successively, patients were retrospectively assigned to a high FO (H, FO > 2.5 L) or low FO (L, FO ≤ 2.5 L) group and these were further compared also after stratification by diabetes mellitus. Finally, a small number of patients without diabetes with significant and persistent FO were followed up for 3 months post-study to investigate how normalization of fluid status affects HRV.

Results

SDANN, VLF, LZC and HF% parameters significantly correlate with FO (correlation coefficients were respectively r = –0.40, r = –0.37, r = –0.28 and r = 0.26, p-value < 0.05). Furthermore, LF% and LF/HF were inversely correlated with hydration status (correlation coefficients were respectively r = –0.31 and r = -0.33, p-value < 0.05). These results indicate an association between FO and reduced HRV, higher parasympathetic activation and reduced sympathetic response to the HD session. Indeed, group H tended to have lower values of SDANN, VLF and LZC, and higher values of HF% than patients in the L group. Finally, there was a trend towards lower LF% measured during the last 30 minutes of HD for the H group versus the L group. Reduction in FO achieved over 3 months by implementation of a strict fluid management plan resulted in an increase of HRV.

Conclusions

Our results suggest that depressed HRV is associated with fluid overload and that normalization of hydration status is accompanied by improved HRV.

Comparison of sustained low-efficiency dialysis with acetate-free and acetate-containing bicarbonate dialysate in unstable patients

This work is focused on the problem of maintenance of intradialytic hemodynamic safety in unstable patients with acute kidney injury (AKI). A hypothesis that "small" quantities of acetate in standard bicarbonate dialysate can cause pronounced acetatemia and exacerbate cardiovascular instability was tested. In this prospective randomized study, a group of patients with AKI after cardiac surgery was treated with sustained low-efficiency dialysis with either acetate-containing bicarbonate dialysate or acetate-free dialysate, where acetate is replaced by hydrochloric acid. It was demonstrated that application of acetate-containing bicarbonate dialysate results in blood acetate levels up to 12 times the normal level. Additionally, it is associated with a 3.8-fold-increased risk of hemodynamic complications in comparison with acetate-free dialysate. The choice of acetate-free or acetate-containing bicarbonate dialysate does not influence adequacy of correction of the acid-base and electrolyte content of blood.

QT interval in CKD and haemodialysis patients

Cardiovascular (CV) disease is the leading cause of morbidity and mortality in chronic kidney disease (CKD) patients. Although about half of the deaths are due to CV causes, only a minority are directly linked to myocardial infarction and it is estimated that cardiac arrest or cardiac arrhythmias account for about a quarter of all deaths registered in dialysis patients. Thus, simple non-invasive tools such as electrocardiogram (ECG) may detect those patients at increased risk for arrhythmias. The QT interval on the standard 12-lead ECG is the time from ventricular depolarization (Q wave onset) to cardiac repolarization completion (end of the T wave) and represents a marker of cardiac repolarization defects. Numerous studies suggest a direct association between QT abnormalities and poor prognosis in the general population, CKD patients and dialysis patients. Of note, multivariable adjustments for different traditional and CKD-specific risk factors for CV events attenuate but do not cancel these associations. We herein review the clinical significance of simple non-invasive tools such as the QT tract on ECG for detecting those patients at increased risk of CV event and possibly for treatment individualization.

QT Interval and QT Dispersion in Patients Undergoing Hemodialysis: Revisiting the Old Theory

AIMS

We sought to explore the response of the corrected QT (QTc) interval duration and QT dispersion (QTD) to hemodialysis.

METHODS

We enrolled 50 patients with end-stage renal disease undergoing regular hemodialysis. Blood samples were drawn for measurement of serum electrolytes, and a 12-lead ECG was performed to measure the QTc interval duration and QTD, immediately before and just after dialysis sessions.

RESULTS

The mean age of the cohort was 42.8 ± 12.2 years (58% males). Both the QTc duration and QTD showed marked variability after hemodialysis. A significant correlation was found between the decrease of both serum potassium and magnesium levels after dialysis and the post-dialysis QTc interval duration, with Pearson's correlation coefficients r = -0.43 and r = -0.34, p = 0.002 and p = 0.01, respectively. Patients with a post-dialysis increase of QTc interval duration had a significantly higher percentage of reduction of serum potassium (p = 0.029), whereas patients with a post-dialysis increase of QTD had a significantly higher percentage of reduction of serum magnesium (p = 0.03).

CONCLUSION

Our findings suggest a highly variable response of the QTc interval duration and QTD to hemodialysis. The post-dialysis QTc interval duration inversely correlated with the decrease of both serum potassium and magnesium levels after dialysis.

Differential effects of hemofiltration and of coupled plasma filtration adsorption on cardiac repolarization in pigs with hyperdynamic septic shock

The aim was to investigate effects of continuous hemofiltration (CHF) and of coupled plasma filtration adsorption (CPFA) on electrophysiological properties of the septic heart. Sepsis was induced in anesthetized pigs by fecal peritonitis and continued for 22 h either without intervention (control sepsis) or with intervention (CHF or CPFA) applied for the last 10 h of this period. Electrocardiograms were recorded at baseline, before induction of peritonitis, and 22 h later, at the end of in vivo experiment. In vitro, action potentials were recorded in right ventricular trabeculae. RR, QT, and QTc (QT corrected for heart rate) intervals were shortened by sepsis. Action potential durations (APDs) were shortened by CHF, but not by CPFA, compared with control sepsis. Continuous hemofiltration prolonged APD. Coupled plasma filtration adsorption filtrate did not exert any effect on APD. Plasma separated during CPFA prolonged APD. Continuous hemofiltration shortened cardiac repolarization, and this effect was reversed by the hemofiltrate. In contrast, neither CPFA nor the CPFA filtrate influenced APD. The data indicate that some inflammatory mediators able to delay cardiac repolarization were removed from plasma to hemofiltrate by CHF but not by CPFA.