Hemodialysis Process–Related Autonomic Imbalance and Cardiac Arrhythmias: Insights From Steady 14‐Day ECG Monitoring

Figure 1.
December 17, 2020 0 Comments

Medical Perspective

What Is New?
  • Nonsustained ventricular tachycardia is extra frequent throughout hemodialysis or inside 6 hours posthemodialysis.

  • In incident hemodialysis sufferers, coronary heart price sharply will increase earlier than nonsustained ventricular tachycardia occasions, suggesting a triggered ventricular tachycardia mechanism.

  • Each‐different‐day hemodialysis preserves physiological circadian rhythm in coronary heart price and coronary heart price variability, whereas the extension of the interdialytic interval for the second day abolishes circadian rhythm and reveals a gradual deterioration in autonomic disbalance.

What Are the Medical Implications?
  • The dangerous impact of the two‐day interval with out hemodialysis means that extra frequent dialysis needs to be thought of the popular prescribed therapy schedule.

  • Enchancment of affected person adherence—avoiding lacking hemodialysis periods—can enhance affected person outcomes.

  • Prognosis of autonomic imbalance in finish‐stage kidney illness sufferers presenting with bradycardia is tough. In finish‐stage kidney illness, an autonomic disbalance is manifested by parasympathetic withdrawal and impaired baroreflex sensitivity, and use of β‐blockers attenuates affiliation of coronary heart price with nonsustained ventricular tachycardia, suggesting potential therapy advantage of β‐blocker use, which needs to be studied additional.


Sudden cardiac demise (SCD) is the commonest explanation for demise in finish‐stage kidney illness (ESKD) sufferers receiving dialysis.1, 2 Each tachy‐ and bradyarrhythmias could play a causative position in SCD in ESKD.3, 4, 5 Importantly, the phases of hemodialysis relate to the speed of SCD.6, 7, 8, 9 Mortality will increase after a protracted interdialytic interval, inside 6 hours after the top of a hemodialysis session.6, 7, 8 The dialysis process itself triggers a number of mechanisms that may improve the propensity to cardiac arrhythmias.10 Oscillations in electrolyte ranges and fluid quantity, a professional‐inflammatory state, repetitive myocardial damage from uremia and different toxins,10 and myocardial beautiful11 are hemodialysis‐particular danger components for SCD. A SCD occasion exemplifies an ideal storm, requiring each a inclined substrate and a set off.12 Collectively the publicity to SCD danger components associated to fluctuating hemodialysis periods and conventional SCD triggers can clarify the extraordinarily excessive price of SCD in dialysis sufferers.

Autonomic imbalance of the guts is historically related to SCD. Underneath regular circumstances, the autonomic system controls coronary heart price and rhythm through a steadiness between the parasympathetic and sympathetic programs. Coronary heart price variability (HRV) is a measure of fluctuations within the autonomic system and baroreflex sensitivity.13, 14 Parasympathetic withdrawal and elevated sympathetic enter decreases HRV and triggers SCD.12 Earlier research utilizing 24‐hour Holter electrocardiogram recordings reported the affiliation of depressed HRV15 with elevated mortality in ESKD sufferers.16, 17, 18 Nevertheless, 24‐ and even 48‐hour Holter ECG recordings are too brief to check the affiliation of fluctuating autonomic tone with the usual 7‐day hemodialysis schedule. Whether or not autonomic imbalance associates with each the dialytic cycle and cardiac arrhythmias in dialysis sufferers stays unknown. Longitudinal modifications in autonomic tone earlier than, throughout, and after hemodialysis procedures, together with their affiliation with brady‐ and tachyarrhythmias, haven’t been beforehand studied.

To deal with this data hole, we carried out an ancillary potential research in a subset of incident hemodialysis sufferers, enrolled within the PACE (Predictors of Arrhythmic and Cardiovascular Danger in Finish Stage Renal Illness) research.2, 19 We hypothesized that in incident hemodialysis sufferers, medical traits and paroxysmal arrhythmias are related to periodic modifications in coronary heart price and HRV in several phases of hemodialysis.


Developed for the info evaluation, software program code is out there at GitHub and could be accessed at https://github.com/Tereshchenkolab/HRV. With the intention to reduce the potential for unintentionally sharing info that can be utilized to re‐determine personal info, a subset of the deidentified information generated for this research is out there at GitHub.20

Research Inhabitants

We carried out a potential ancillary research inside PACE.19 Each the parental PACE research and this ancillary research had been authorized by the Johns Hopkins Institutional Evaluation Board, and all members supplied written knowledgeable consent.

The PACE research design has been beforehand described.2, 19 Briefly, the research enrolled grownup ESKD sufferers who had began in‐middle hemodialysis inside 6 months of enrollment. Sufferers on dwelling hemodialysis, peritoneal dialysis, in hospice or expert nursing facility, and sufferers with an implanted pacemaker or cardioverter‐defibrillator weren’t eligible. At enrollment, members underwent complete cardiovascular analysis, which included a number of varieties of ECG, echocardiogram, cardiac computed tomography, and coronary angiography.

This ancillary research included randomly chosen PACE members who underwent baseline cardiovascular analysis and agreed to endure steady ECG monitoring for at the least 7 days.

Medical Covariates

Prevalent coronary artery illness (CAD), cerebrovascular illness (CVD), congestive coronary heart failure (CHF), hypercholesterolemia, hypertension, and diabetes mellitus had been decided by participant’s self‐report and doctor’s prognosis recorded within the medical file. Contributors had been requested to herald their medicines, and drugs use was recorded in the course of the baseline go to. To evaluate subjective postdialysis restoration time, members answered the query: “How lengthy does it take you to recuperate from a dialysis session?” throughout a phone interview, carried out inside 30 days of ECG monitoring.

Echocardiography was carried out on the PACE echocardiographic core laboratory,19 the place left ventricular ejection fraction, left ventricular dimensions, and left ventricular mass index had been measured as beforehand described.19 Left ventricular hypertrophy was outlined as an echocardiographic left ventricular mass index ≥116 g/m2 in males or ≥104 g/m2 in females.

Adjustments in weight and sitting systolic and diastolic blood strain earlier than and after every dialysis session had been recorded for this research’s members.

Dialysis bathtub (dialysate concentrations of calcium and potassium) information are reported as a 3‐month common. All members acquired a dialysate Mg focus of 1.0 mEq/L, and a dialysate bicarbonate focus of 40 mmol/L. Three‐month averaged intradialytic weight change was calculated. Serum calcium and potassium had been assessed as a 3‐month common of predialysis measures earlier than the research clinic go to.

Steady ECG Monitoring Utilizing ECG Patch

Steady ECG monitoring was carried out utilizing an ECG patch (Zio Patch, iRhythm Applied sciences, Inc., San Francisco, CA). Throughout the research go to, a research coordinator utilized the gadget over the left pectoral area,21 and instructed the participant to activate a set off button within the occasion of cardiac signs (presumed arrhythmia). Contributors had been instructed to put on the adhesive ECG patch for so long as attainable, with the objective of acquiring at the least 7 days of steady ECG recording. After completion of the ECG recording, members mailed the ECG patch to iRhythm Applied sciences, Inc, which supplied their normal US Meals and Drug Administration–authorized report back to the research investigators—through a safe web site. The Zio Patch report was reviewed inside 24 hours by the research investigators, and clinically vital findings had been communicated with members and their healthcare suppliers. As well as, repeatedly recorded uncooked digital ECG sign was supplied by iRhythm Applied sciences, Inc for additional analyses.

Prognosis of cardiac arrhythmias

Per the usual iRhythm Applied sciences protocol, the next arrhythmias had been identified: atrial fibrillation (AF) or flutter (>4 beats), supraventricular tachycardia (>4 beats), pause >3 s, atrioventricular block of the second or the third diploma, ventricular tachycardia (VT, >4 beats), or polymorphic VT/ventricular fibrillation. All arrhythmic occasions captured by the Zio Patch report had been reviewed and validated by at the least 2 research investigators (LGT, RSP, SH).

Phases of Hemodialysis

To find out the affiliation of the intermittent hemodialysis periods with coronary heart price and HRV time‐collection, we used hemodialysis phases accepted within the nephrology subject relative to their proximity to a hemodialysis therapy (Determine 1). Each research participant underwent hemodialysis (4–5 hours, section 1), postdialysis (6 hours instantly after hemodialysis, section 2), between‐hemodialysis (variable size, phases 3, 3–5, and three–7), and predialysis (6 hours previous dialysis, phases 4, 6, and eight) phases. Over the course of the 7‐day cycle, dialysis therapy–adherent research members had been dialyzed each different day for five days (both Monday/Wednesday/Friday or Tuesday/Thursday/Saturday; a complete of three remedies weekly) after which skilled a 2‐day‐lengthy interdialytic interval. For instance, for an adherent Monday–Friday schedule, the common interdialytic interval was ≈32 hours, and the size of the extended interdialytic interval over the weekend was for much longer at about 56 hours. Nonadherent members (n=4) didn’t observe this normal dialytic sample. Their therapy schedule was interrupted by missed hemodialysis remedies, resulting in a variable extended interdialytic interval of at the least 72 hours or longer.

Figure 1.

Determine 1. A schematic presentation of the dialytic cycles used for evaluation. Blue shade signifies phases inside 48 hours of the final therapy, inexperienced shade highlights the phases included to research the additional 24 hours between remedies within the 2‐day‐lengthy interdialytic interval, and grey shade symbolizes the phases that had been included to research >72‐hour interdialytic intervals for many who had been nonadherent.

HRV Measurements

A uncooked single‐lead digital ECG sign (sampling price 200 Hz; amplitude decision 4.88 μV) was analyzed within the Tereshchenko laboratory on the Oregon Well being & Science College. Determine 2 reveals examples of the ECG sign and detected cardiac arrhythmia. A customized MATLAB (The MathWorks, Inc, Natick, MA) software program utility was developed (NMR, EAPA, MMK; supplied at https://github.com/Tereshchenkolab/HRV) to robotically detect QRS complexes and choose a single 3‐minute regular sinus rhythm epoch for every hour of recording. The algorithm robotically eradicated epochs with untimely R2 beats if the R1R2 interval was shorter than the previous R0R1 interval by 15% or better. The algorithm equally eradicated epochs with a sudden pause, if subsequently the R1R2 interval was longer than the previous R0R1 interval by 15% or better, to take away epochs with blocked untimely atrial or His extrasystoles, or intermittent sinoatrial or atrioventricular block. Historically, in Holter ECG evaluation, the untimely atrial beat was outlined by a coupling interval of <80% of the imply RR interval.22 We utilized a extra stringent threshold after manually reviewing our ECG information with thresholds starting from 2% to twenty%. A sliding 3‐minute window strategy was used to scan the whole lot of the info: when a untimely beat (or sudden pause) was detected, the untimely beat and subsequent compensatory pause had been skipped, and a brand new 3‐minute window search began thereafter once more. If the algorithm didn’t discover a steady 3‐minute epoch of sinus rhythm in a whole hour, the software program would change the R‐peak detection algorithm23 and repeated all steps described above. The primary R‐peak detection algorithm used was a Pan‐Tompkins,24 adopted by principal part evaluation,25 after which parabolic becoming.26 As a result of the magnitude of R and S peaks diverse inside and between sufferers, the dominant peak of the QRS complicated diverse throughout this ECG monitoring. We paid particular consideration to make sure constant indicators of the dominant QRS peak for the whole 3‐minute epoch. The best common Manhattan distance from baseline to the very best optimistic (R) peak and highest adverse (S) peak was calculated to determine one of the best dominant peak for every 3‐minute epoch. The accuracy of constant dominant (R or S) peaks detection, and accuracy of the number of consecutive regular sinus beat had been validated on an information subset by the investigator (NMR), with the help of a graphical show.

Figure 2.

Determine 2. A consultant instance of (A) a single‐lead ECG with detected R‐peaks and measured RR′ intervals. A 3‐minute epoch is proven, with imply coronary heart price 78 bpm, rMSSD of 11.5 ms, LF energy of two.4 s2, HF energy of 6.3 s2, LF/HF ratio of 0.38, SD1 of 8.2 ms, SD2 of 19.7 ms, SD12 ratio of 0.41, pattern entropy of two.0, and Renyi entropy of 1.4. A ten‐s portion is displayed for nearer examination of ECG morphology. B, Polymorphic ventricular tachycardia, and (C) atrial fibrillation and a pause in a research participant. bpm signifies beats per minute; HF, excessive frequency; LF, low frequency; rMSSD, root imply sq. of the successive regular sinus to regular sinus intervals variations.

HRV was measured in accordance with the Requirements.27, 28 Developed (by MMK) MATLAB (the MathWorks, Inc, Natick, MA) software program code is supplied at https://github.com/Tereshchenkolab/HRV.

Time‐area HRV measures

Coronary heart price and the basis imply sq. of the successive regular sinus to regular sinus (NN) intervals variations (rMSSD) had been calculated for every 3‐minute epoch chosen per hour.

Frequency‐area HRV measures

The low‐frequency (LF; 0.04–0.15 Hz) energy, excessive‐frequency (HF; 0.15–0.4 Hz) energy, and LF/HF ratio of powers had been calculated for every 3‐minute epoch.

Nonlinear HRV measures

Quantitative evaluation of the Poincaré plot was carried out.28 The Poincaré plot was derived from each 3‐minute NN information epoch by plotting the values NNn+1 towards the values of NNn. SD1 was calculated because the SD of the cloud of factors within the route perpendicular to the road‐of‐id. SD2 was calculated because the SD of the cloud of factors within the route of the road‐of‐id. SD1/SD2 ratio was known as SD12.


To quantify the entropy price on a brief‐size NN collection, we elected to measure pattern entropy28 and Renyi entropy for every 3‐minute epoch. Renyi entropy was calculated as described by Cornforth et al.29 We used an α worth equal to 4 due to earlier information suggesting that optimistic α (1–5) offers one of the best discrimination of cardiac autonomic neuropathy, and based mostly on the sampling price of our information.30

Statistical Evaluation

Normality of the distribution of steady variables was evaluated utilizing standardized regular likelihood plots. For comparability of medical traits in members with versus with out detected arrhythmia, usually distributed steady variables had been offered as means±SD and had been in contrast utilizing a t check. Fisher precise check was used to check categorical variables.

The principle information set was structured as a panel of time‐collection, as HRV was measured originally of every hour (assuming equal intervals between 3‐minute epochs). The belief of equal intervals between 3‐minute epochs was confirmed for 81% of epochs beginning within the first second (44%), inside the first 10 minutes (76%), or inside the first 15 minutes (81%) of every hour. The belief of equal intervals between 3‐minute epochs was violated for 10% of epochs beginning within the second half of an hour. To check the robustness of our findings, we carried out a sensitivity evaluation after exclusion of epochs that violated the equal intervals assumption required for time‐collection evaluation.

Inside‐topic and between‐topics SDs had been reported for every section of dialysis. Paired comparability of HRV in several phases of the dialytic cycle was carried out utilizing evaluation of variance inside topics (for repeated measures). As earlier research reported an elevated danger of SCD within the postdialysis section after the lengthy interdialytic weekend,31 we carried out paired comparisons of HRV within the postdialysis section that adopted: (1) regular hemodialysis versus (2) 2‐day‐lengthy interdialytic interval versus (3) longer than 72‐hour interdialytic interval in nonadherent members.

To find out whether or not demographic and medical traits, paroxysmal cardiac arrhythmias, and dialytic and circadian (24‐hour) cycles are related to time‐collection of coronary heart price and HRV metrics, we constructed autoregressive conditional heteroscedasticity (ARCH) and generalized autoregressive conditionally heteroscedastic (GARCH) panel fashions.32 In ARCH time‐collection evaluation, each the imply and variance of the HRV metric had been modeled as time dependent, which allowed modeling volatility that may come up in response to the dialysis process or different unmeasured components. Time collection of coronary heart price and HRV metrics (1‐by‐1) served as an consequence. To determine our ARCH/GARCH mannequin, we first explored the autocorrelation perform (ACF) and partial autocorrelation (PACF) perform of the HRV time‐collection, and ACF/PACF of squared HRV variables’ values. As a result of the ACF and PACF of coronary heart price and HRV time‐collection represented white noise, however ACF/PACF of squared collection tapered (autoregressive of order 1), we constructed ARCH(1/1)/GARCH(1) fashions.

To find out whether or not demographic and medical traits (together with use of β‐blockers) are related to coronary heart price and HRV time‐collection, age, intercourse, race, prevalent CAD, CHF, CVD, historical past of AF, diabetes mellitus, Charlson comorbidity index, and postdialysis restoration time had been included in every ARCH mannequin.

To find out whether or not paroxysmal cardiac arrhythmias are related to time‐collection of coronary heart price and HRV metrics, separate ARCH fashions had been constructed for every kind of paroxysmal arrhythmia (VT, AF, supraventricular tachycardia, and pause). ARCH fashions had been adjusted for age, intercourse, race, prevalent CAD, CHF, CVD, AF, Charlson comorbidity index, and postdialysis restoration time.

To explain the circadian (24‐hour) rhythm—whereas accounting for a number of 24‐hour cycles analyzed for a similar affected person (longitudinal/panel information construction)—we constructed periodic regression fashions with mounted (inside) estimators. We used periodic regression to research the conduct of coronary heart price and HRV, which range in a round‐scale 24‐hour cycle. We transformed the round variable “hour in a 24‐hour cycle” from cyclic (hours of the day) to angular (radians) format, after which to trigonometric format (paired items sine and cosine). We studied whether or not coronary heart price and HRV time‐collection responded in a periodic approach to the 24‐hour cycle. We estimated the periodic imply (Mesor) for coronary heart price and HRV metrics, and calculated an amplitude (A) of variation concerning the Mesor within the modeled cycle:

We calculated section angle (acrophase φ) as a time inside the 24‐hour cycle when coronary heart price/HRV is maximized (peak location): φ=arctan(sinβ/cosβ). The minimal is situated 12 hours (0.5 cycles) away from the utmost. As a result of dialysis and the rapid postdialytic section are well-known to considerably have an effect on coronary heart price and HRV,31, 33 dialysis (section 1) and postdialytic section 2 had been excluded from periodic regression analyses. We stratified circadian rhythm analyses by the kind of interdialytic section: in a daily dialytic schedule (phases 3–4), second‐day interdialytic extension (phases 5–6), and interdialytic extension above 72 hours (phases 7–8 in nonadherent members lacking dialysis), as proven in Determine 1.

To find out whether or not the dialytic cycle is related to the guts price and HRV time‐collection after elimination of the impact of circadian rhythm, we constructed periodic panel ARCH/GARCH fashions to find out a change in HRV per hour of remoteness from the primary dialysis hour. ARCH/GARCH fashions had been adjusted for age, intercourse, race, prevalent CAD, CHF, CVD, AF, diabetes mellitus, Charlson comorbidity index, and postdialysis restoration time. As well as, circadian 24‐hour cycles (paired items sine and cosine) had been included in every ARCH mannequin and served to regulate for circadian periodicity.

Sensitivity analyses

To check the robustness of our findings, we excluded 10% of epochs that violated the equal intervals assumption that’s required for time‐collection ARCH fashions. Moreover, we adjusted ARCH fashions for weight and sitting systolic and diastolic blood strain modifications earlier than and after each hemodialysis session throughout ECG monitoring.

Statistical evaluation was carried out utilizing STATA MP 15.1 (StataCorp LP, Faculty Station, TX).


Research Inhabitants

The research inhabitants (Desk 1) included 28 PACE members (imply age 54±13 years; 57% males; 96% black). Roughly one third of the inhabitants had a historical past of structural coronary heart illness with regular left ventricular ejection fraction. The common dialysis restoration time was 16 minutes. All research members had hypertension and used antihypertensive medicines; 83% had been on β‐blockers. Many of the research members acquired an identical dialysate: >70% members acquired dialysate focus of potassium equal to 2 mmol/L and calcium equal to 2.5 mmol/L.

Desk 1. Medical Traits of Research Contributors With and With out Any Clinically Important Cardiac Arrhythmias Recognized Throughout ECG Monitoring

Attribute Complete (n=28)
Age (SD), y 53.9 (12.5)
Male, n (%) 16 (57.1)
Black, n (%) 27 (96.4)
Physique mass index (SD), kg/m2 29.4 (7.4)
Reason behind ESKD:
Glomerulonephritis, n (%) 3 (10.7)
Hypertension, n (%) 5 (17.9)
Diabetes mellitus, n (%) 12 (42.9)
HIV/different/genetic/obstruction, n (%) 7 (25.0)
Unknown, n (%) 1 (3.6)
Hypertension, n (%) 28 (100)
Diabetes mellitus, n (%) 16 (57.1)
Coronary artery illness, n (%) 8 (28.6)
Coronary heart failure, n (%) 9 (32.1)
Cerebrovascular illness, n (%) 8 (28.6)
Historical past of atrial fibrillation, n (%) 10 (35.7)
Hypercholesterolemia, n (%) 19 (67.9)
Smoker present or former, n (%) 15 (53.6)
Drinker present or former, n (%) 23 (82.1)
Use of β‐blockers, n (%) 19/23 (82.6)
Charlson comorbidity index (SD) 5.5 (2.2)
Dialysis restoration time (SD), min 15.9 (3.3)
LV ejection fraction (SD), % 70.3 (9.3)
LV inside dimension diastole (SD), cm 5.3 (0.7)
LV inside dimension systole (SD), cm 3.1 (0.7)
LV mass index (SD), g/m2 146.0 (53.2)
LV hypertrophy, n (%) 17 (70.8)
3‐mo averaged calcium (SD), mg/dL 8.52 (0.65)
3‐mo averaged potassium (SD), mEq/L 4.34 (0.39)
3‐mo averaged intradialytic weight change (SD), kg 2.09 (0.97)
3‐mo averaged dialysis bathtub calcium focus (SD), mmol/L 2.4 (0.2)
3‐mo averaged dialysis bathtub potassium focus (SD), mmol/L 2.2 (0.4)

Cardiac Arrhythmia Occasions

Nearly half of the members (n=13, 46%) had arrhythmias detected throughout monitoring (Desk 2; Determine 2). Aside from 1 affected person with 46% paroxysmal AF burden, all detected occasions had been nonsustained (NS), lasting <30 seconds, and asymptomatic. NSVT occurred extra ceaselessly throughout hemodialysis or inside 6 hours posthemodialysis, as in contrast with pre‐ or between‐hemodialysis (63% versus 37%, P=0.015). Supraventricular tachycardia occurred extra ceaselessly pre‐ or between‐hemodialysis as in contrast with throughout hemodialysis or posthemodialysis (84% versus 16%, P=0.015). All sufferers with NSVT had been free from CAD at baseline.

Desk 2. Cardiac Arrhythmia Occasions Timeline

Occasions 6‐h Predialysis, n (%) Occasions Throughout Dialysis, n (%) Occasions 6‐h Postdialysis, n (%) Occasions Between Dialysis, n (%) Variety of Sufferers (% of inhabitants)
Complete variety of occasions, n=47 12 (26) 8 (17) 9 (19) 18 (38) 13 (46)
VT, n=8 1 (13) 2 (25) 3 (38) 2 (25) 4 (15)
SVT, n=17 5 (29) 1 (6) 2 (12) 9 (53) 9 (32)
AF, n=21 6 (29) 4 (19) 4 (19) 7 (33) 2 (7)
Pauses >3 s, n=1 0 1 (100) 0 0 1 (3.5)

Dynamic Time Collection of Coronary heart Charge and HRV

The common period of analyzed steady ECG recording was 6.5±2.3 days. All 28 members had at the least 1 ECG recording over a 2‐day‐lengthy interdialytic interval, and 4 members missed 1 to 2 dialysis periods throughout ECG monitoring.

Common coronary heart price was quickest inside the first 6 hours postdialysis (Desk 3) and regularly slowed down afterward. Quick‐time period HRV (rMSSD, HF energy, Poincaré SD1) decreased posthemodialysis, then recovered by the point of the following common hemodialysis session. Nevertheless, if hemodialysis was not carried out inside the subsequent 72 hours, brief‐time period HRV regularly diminished additional. In an unadjusted paired comparability, there have been no statistically important variations in HRV posthemodialysis after completely different durations of the previous interdialytic interval (Desk S1).

Desk 3. Coronary heart Charge and HRV in Completely different Phases of the Dialytic Cycle

HRV Measure Section 1 N=323; n=26 T=12.4 Section 2 N=480; n=26 T=18.5 Section 3 N=2554; n=28 T=91.2 Section 4 N=438; n=27 T=16.2 Section 5 N=428; n=28 T=15.3 Section 6 N=135; n=26 T=5.2 Section 7 N=221; n=4 T=55.3 Section 8 N=15; n=3 T=5 Inside ANOVA P
Coronary heart price (SD), bpm 74.1 (11.3) 81.3 (13.4) 77.2 (12.2) 75.9 (11.5) 77.6 (14.1) 73.9 (12.2) 70.8 (8.0) 71.0 (5.4) <0.0001
SD between 10.4 11.3 10.1 10.3 12.9 13.2 9.8 5.3
SD inside 6.1 7.6 7.7 6.0 6.0 4.4 4.3 3.1
rMSSD (SD), ms 12.6 (7.8) 9.7 (5.2) 11.0 (6.4) 11.1 (6.7) 11.1 (5.6) 11.8 (5.6) 11.3 (4.1) 9.2 (2.3) <0.0001
SD between 6.1 3.7 4.1 5.2 3.7 4.3 2.7 2.1
SD inside 4.6 3.7 5.1 5.1 4.4 4.2 3.6 1.7
HF energy (SD), s2 4.6 (2.0) 4.1 (1.8) 4.3 (1.9) 4.4 (2.0) 4.5 (2.0) 4.6 (2.2) 5.8 (2.2) 5.1 (2.9) <0.0001
SD between 1.5 1.3 1.4 1.5 1.5 1.7 1.9 2.9
SD inside 1.3 1.4 1.4 1.4 1.3 1.4 1.4 0.9
LF energy (SD), s2 3.1 (1.0) 3.0 (1.0) 3.1 (1.0) 2.9 (0.9) 3.0 (1.0) 3.0 (1.0) 3.1 (1.0) 3.0 (0.8) 0.068
SD between 0.6 0.6 0.6 0.5 0.6 0.7 0.8 0.3
SD inside 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.7
LF/HF ratio (SD) 0.82 (0.46) 0.89 (0.48) 0.87 (0.46) 0.84 (0.45) 0.84 (0.47) 0.80 (0.43) 0.66 (0.39) 0.88 (0.58) 0.006
SD between 0.36 0.36 0.35 0.37 0.36 0.33 0.37 0.61
SD inside 0.27 0.31 0.32 0.32 0.29 0.26 0.24 0.16
Poincaré SD1 (SD), ms 9.0 (5.6) 6.9 (3.7) 7.8 (4.6) 7.9 (4.8) 7.8 (4.0) 8.4 (3.9) 8.0 (2.9) 6.5 (1.6) <0.0001
SD between 4.3 2.6 2.9 3.7 2.6 3.0 1.9 1.5
SD inside 3.3 2.6 3.6 3.6 3.1 2.9 2.6 1.2
Poincaré SD2 (SD), ms 25.8 (18.7) 21.6 (15.9) 23.8 (18.4) 23.7 (17.2) 22.4 (16.5) 24.4 (16.5) 20.3 (15.3) 23.5 (17.0) 0.002
SD between 15.2 11.1 14.9 19.6 12.1 12.5 13.7 16.6
SD inside 11.1 11.6 13.5 11.4 12.2 10.7 10.1 7.4
SD12 (SD), % 0.44 (0.25) 0.42 (0.25) 0.43 (0.24) 0.43 (0.27) 0.46 (0.28) 0.45 (0.27) 0.56 (0.33) 0.47 (0.32) 0.461
SD between 0.20 0.19 0.19 0.20 0.20 0.20 0.34 0.33
SD inside 0.16 0.17 0.18 0.20 0.19 0.18 0.20 0.12
Pattern Entropy (SD) 1.49 (0.40) 1.39 (0.46) 1.39 (0.44) 1.43 (0.44) 1.42 (0.44) 1.43 (0.47) 1.52 (0.43) 1.25 (0.62) 0.0004
SD between 0.25 0.26 0.21 0.24 0.23 0.29 0.23 0.73
SD inside 0.35 0.40 0.39 0.38 0.37 0.38 0.38 0.30
Renyi entropy (SD) 1.31 (0.31) 1.33 (0.28) 1.31 (0.30) 1.33 (0.29) 1.31 (0.31) 1.29 (0.31) 1.23 (0.33) 1.30 (0.36) 0.758
SD between 0.17 0.13 0.09 0.17 0.12 0.15 0.13 0.31
SD inside 0.27 0.26 0.29 0.27 0.29 0.28 0.31 0.24

Affiliation of Medical Traits With Coronary heart Charge and HRV Time Collection

Throughout the common hemodialysis schedule (phases 1–4), prevalent heart problems and its danger components had been related to sooner coronary heart price and additional depressed HRV (Determine 3 and Desk S2). Historical past of AF and use of β‐blockers had been related to slower coronary heart price.

Figure 3.

Determine 3. Affiliation of demographic and medical traits with coronary heart price and brief‐time period HRV in ARCH fashions, stratified by the kind of dialytic cycle. Beta‐coefficient with 95% CI is proven. AF signifies atrial fibrillation; bpm, beats per minute; CAD, coronary artery illness; CCI, Charlson comorbidity index; CHF, congestive coronary heart failure; CVD, cerebrovascular illness; HF, excessive‐frequency energy; HR, coronary heart price; HRV, coronary heart price variability; LF, low‐frequency energy; RenEn, Renyi entropy; rMDDS, root imply sq. of the successive regular sinus to regular sinus intervals variations; SamEn, pattern entropy; SD1, the SD of the Poincare plot cloud of factors within the route perpendicular to the road‐of‐id; SD12, SD1/SD2 ratio; SD2, the SD of the cloud of factors within the route of the road‐of‐id.

In distinction, in the course of the second day with out hemodialysis (phases 5–6), conventional cardiovascular danger components had been related to slower coronary heart charges. Feminine intercourse and prevalent CAD had been related to elevated SD2 and LF energy, suggesting better sympathetic predominance. Apparently, diabetes mellitus was related to a smaller SD2 and LF energy.

In our research, 4 members (100% black; 2 males and a couple of females) missed hemodialysis for >72 hours. They had been CAD‐ and CHF‐free, with a excessive Charlson comorbidity index (6.8±1.2). Throughout missed hemodialysis (phases 7–8), diabetes mellitus and longer perceived dialysis restoration time had been related to better diploma of HRV melancholy (Desk S2 via S4).

Affiliation of Coronary heart Charge and HRV With Cardiac Arrhythmias

In adjusted evaluation, considerably elevated coronary heart price to start with of an hour (as in contrast with the previous hour, by 11.2 [95% CI 10.1–12.3] beats per minute [P<0.0001]) was related to paroxysmal VT occasions occurring at any time inside the identical hour. That affiliation remained important after additional adjustment for using β‐blockers (+8.5 [95% CI 7.1–9.8] beats per minute; P<0.0001). There was no affiliation of VT occasions with HRV. There have been no associations of different varieties of noticed arrhythmias with coronary heart price or HRV.

Circadian Rhythm in Coronary heart Charge and HRV Throughout Completely different Sorts of Dialytic Cycles

Throughout the interdialytic interval within the common dialytic cycle (phases 3–4), coronary heart price and all HRV parameters demonstrated a big circadian sample—as anticipated (Determine 4 and Desk S5). Quick‐time period HRV (rMSSD and SD1) peaked at evening, whereas coronary heart price and SD12 peaked in the course of the day.

Figure 4.

Determine 4. Circadian rhythm in coronary heart price and HRV throughout a 1‐day‐ (black) and a couple of‐day‐lengthy (inexperienced) interdialytic interval. Mesor is proven as a dashed line. BPM signifies beats per minute; HF, excessive‐frequency energy; HR, coronary heart price; HRV, coronary heart price variability; LF, low‐frequency energy; rMDDS, root imply sq. of the successive regular sinus to regular sinus intervals variations; SD1, the SD of the Poincare plot cloud of factors within the route perpendicular to the road‐of‐id; SD12, SD1/SD2 ratio; SD2, the SD of the cloud of factors within the route of the road‐of‐id.

In distinction, the second day of the lengthy interdialytic interval (phases 5–6) abolished circadian rhythms, with few exceptions. Periodic modifications in coronary heart price remained largely unchanged throughout all interdialytic durations, however its acrophase shifted to the afternoon within the ultralong (missed dialysis >72 hours) interdialytic interval (phases 7–8). In phases 5 to six, the amplitude of circadian rhythm in Renyi entropy and SD2 elevated, whereas circadian rhythm in different HRV metrics dissipated. Throughout phases 7 to eight, we noticed a distorted periodic sample briefly‐time period HRV (rMSSD, SD1) with acrophase within the afternoon, whereas circadian rhythm in different HRV metrics remained eradicated.

Affiliation of the Phases of Hemodialysis With Coronary heart Charge and HRV Time‐Collection

In totally adjusted ARCH fashions (Determine 5 and Desk S6), section 1 dialysis and postdialytic section 2 had been characterised by gradual enchancment of parasympathetic tone (rising rMSSD and SD1). Throughout the common interdialytic interval in each‐different‐day hemodialysis cycle (phases 3–4), we noticed only a few important traits: a slight lower in rMSSD and SD1, and the rise in SD2 and pattern entropy. In distinction, in the course of the second day of a 2‐day‐lengthy interdialytic interval (phases 5–6), there have been important and significant modifications in all HRV parameters: coronary heart price regularly elevated, brief‐time period HRV (rMSSD, HF energy, SD1) and SD12 decreased, whereas intermediate HRV (SD2, LF/HF ratio, Renyi entropy) elevated, suggesting depressed parasympathetic and elevated sympathetic influences. Lacking dialysis for >72 hours was related to a gradual improve in SD12 ratio and HF energy (Desk S6).

Figure 5.

Determine 5. Affiliation of the section of dialysis with coronary heart price and HRV after adjustment for circadian rhythm and medical traits. bpm signifies beats per minute; HF, excessive‐frequency energy; HR, coronary heart price; HRV, coronary heart price variability; LF, low‐frequency energy; RenEn, Renyi entropy; rMDDS, root imply sq. of the successive regular sinus to regular sinus intervals variations; SamEn, pattern entropy; SD1, the SD of the Poincaré plot cloud of factors within the route perpendicular to the road‐of‐id; SD12, SD1/SD2 ratio; SD2, the SD of the cloud of factors within the route of the road‐of‐id.

Sensitivity evaluation, after exclusion of three‐minute epochs that began within the second half of an hour and thus violated the equal intervals assumption, supplied constantly comparable outcomes (Desk S7). Additional adjustment for modifications in weight and sitting systolic and diastolic blood strain earlier than and after dialysis yielded comparable outcomes (Desk S8).


This steady ECG‐monitoring research of incident in‐middle hemodialysis sufferers revealed a number of vital findings. First, we noticed an affiliation of the phases of dialysis with cardiac arrhythmias; particularly, NSVT occasions had been extra frequent throughout hemodialysis or inside 6 hours posthemodialysis. Within the time‐collection evaluation adjusted for heart problems and danger components, we demonstrated a pointy improve in coronary heart price previous NSVT occasions, suggesting a triggered VT mechanism,34 probably due to sympathetic activation. Second, we discovered that the hemodialysis schedule dramatically influenced the autonomic tone. An each‐different‐day dialysis schedule preserved physiological circadian rhythm in coronary heart price and HRV, whereas the extension of the interdialytic interval for the second day abolished circadian rhythm and displayed a gradual deterioration. The two‐days‐off dialysis led to progressively reducing parasympathetic tone.

Dialysis Section and Paroxysmal Cardiac Arrhythmias Throughout ECG Monitoring

SCD is extra frequent after the lengthy interdialytic interval, throughout hemodialysis, or inside 6 to 12 hours after the top of a hemodialysis session.6, 7, 8 Our statement was according to implantable loop recorder research35 that confirmed the identical sample: NSVT occasions had been extra frequent throughout and postdialysis, and the explanations might be multifactorial.10 We should emphasize that NSVT occasions should not equal to SCD. The predictive worth of NSVT for SCD in ESKD stays unknown. NSVT is related to SCD in lots of,36, 37, 38, 39 however not all40 populations.

Importantly, after rigorous adjustment for heart problems and related danger components, together with use of β‐blockers, we noticed that abruptly elevated coronary heart price precedes subsequent NSVT occasions. Such medical manifestation is typical for triggered VT, which may manifest as polymorphic VT (Determine 2). The triggered VT mechanism can probably41, 42—at the least partially—clarify current outcomes of the ICD2 trial, which confirmed that prophylactic ICD remedy didn’t scale back the speed of SCD or all‐trigger mortality in ESKD sufferers.43

Use of β‐blockers44 could be a potential preventive intervention in such sufferers.3 Of be aware, we noticed an attenuated affiliation of coronary heart price with VT occasions even after adjustment for using β‐blockers, despite 83% of members taking β‐blockers, which highlights the attainable significance of acceptable β‐blocker dose titration.

Dynamic Adjustments in Autonomic Tone within the Dialytic Cycle

Regardless of a number of research reporting unfavorable results of the lengthy 2‐day interdialytic interval6, 7, 8, in‐middle hemodialysis is usually prescribed 3 instances per week. Our research is the primary longitudinal research of coronary heart price and HRV time‐collection throughout a number of hemodialysis periods, permitting direct paired comparability of the impact of the two‐day interdialytic interval. Our findings add to the rising proof of the dangerous penalties of a protracted interdialytic interval. Whereas each‐different‐day hemodialysis preserved comparatively regular cardiovascular autonomic tone, a second day with out hemodialysis was characterised by parasympathetic withdrawal and a gradual improve in sympathetic predominance, which can clarify the beforehand noticed elevated price of SCD after the lengthy interdialytic interval.6, 7, 8 Mounting proof of the dangerous impact of the two‐day interval with out hemodialysis means that extra frequent45, 46 dialysis needs to be thought of the popular prescribed therapy schedule. Whether or not extra frequent hemodialysis attenuates arrhythmic propensity stays to be decided.

HRV in ESKD Sufferers on Hemodialysis, and Impact of Lacking Dialysis

Along with the work in earlier implantable loop recorder research—which equally detected arrhythmias—we additionally analyzed time‐collection of coronary heart price and HRV, which allowed us to make clear the underlying mechanisms. HRV displays a dynamic bidirectional interplay between the guts and the respiratory system, regulated by the autonomic nervous system14 and estimating sympathovagal steadiness.47, 48 Our research highlights the distinctive options of the HRV‐manifestation of autonomic imbalance in ESKD sufferers presenting with bradycardia due to direct adverse chronotropic and dromotropic results of hyperkalemia, hypocalcemia, and attainable uremic toxins. Autonomic imbalance can diminish the cholinergic anti‐inflammatory pathway, resulting in an exaggerated cytokine response and irritation49. Much like different research,50 we noticed that coronary heart price will increase throughout and instantly after hemodialysis.51 In our research members, autonomic imbalance was manifested largely by parasympathetic withdrawal. In contrast to in CHF research,52, 53 we noticed LF/HF ratio <1, probably due to impaired baroreflex sensitivity, or a blunted sympathetic response in our research members. Moak et al13 confirmed that LF energy displays baroreflex‐mediated modifications in cardiovagal and sympathetic noradrenergic outflows. Within the case of baroreflex failure, LF energy is decreased, whatever the standing of cardiac sympathetic innervation. Usually, acute elimination of fluid throughout a hemodialysis session prompts the baroreflex. A number of teams of investigators54, 55, 56, 57 noticed worse medical outcomes in ESKD sufferers with a blunted sympathetic response and a low (<1) LF/HF energy ratio, which was attribute of our affected person inhabitants. Blunted sympathetic response on quantity elimination could be genetically decided by the polymorphism within the gene for angiotensin‐changing enzyme.50 Insufficient baroreflex sensitivity may cause intradialytic hypotension,58 a effectively‐identified danger marker of hostile medical outcomes in ESKD.

In members who missed 1 to 2 hemodialysis periods throughout ECG monitoring, as anticipated, coronary heart price additional slowed, HRV progressively diminished, and circadian rhythm in HRV remained vanished or distorted—all due to deepened autonomic imbalance. Of be aware, sufferers who missed hemodialysis had been characterised by outstanding bradycardia. A number of current research reported bradyarrhythmias throughout monitoring,5, 9, 35, 59 however didn’t remark (or probably didn’t have accessible information) on sufferers’ adherence to therapy. Enchancment of affected person adherence—avoiding lacking hemodialysis periods—can enhance affected person outcomes.

Circadian Rhythm in Coronary heart Charge and HRV

Our discovering of disrupted circadian rhythm aligns with beforehand reported autonomic dysregulation in the course of the regular wake/sleep cycle in ESKD.60 Two mechanisms61 are chargeable for circadian rhythm in coronary heart price: (1) central circadian clock within the suprachiasmatic nucleus within the hypothalamus, performing through the autonomic nervous system, and (2) an area circadian clock within the coronary heart itself. In our research members, the circadian rhythm in coronary heart price remained comparatively preserved in the course of the extended interdialytic interval, whereas the circadian rhythm in HRV was largely abolished. Adjustments within the acrophase of the circadian rhythm in coronary heart price in the course of the ultralong interdialytic (missed hemodialysis) interval—peaking within the afternoon as an alternative of morning hours—could replicate a change within the circadian clock from central to native regulatory mechanisms. A greater understanding of circadian rhythms in coronary heart price and HRV could assist to enhance medical administration and medical outcomes in ESKD sufferers on hemodialysis. Chan et al45 studied the impact of every day dialysis versus each‐different‐day dialysis and located that every day dialysis improved vagal modulation of the guts and elevated brief‐time period HRV, which is according to our research findings. Additional research of the interaction between circadian rhythm and dialytic cycle are wanted to develop an optimum therapy schedule for ESKD sufferers.


The strengths of this research come up from the continual ECG monitoring, offering a possibility for our research—with a number of 24‐hour and dialytic cycles for a similar members—to considerably enhance robustness and scale back error in estimations. Different strengths embrace using superior statistical modeling of time‐collection (ARCH/GARCH) and acceptable use of express periodic regression.

Nevertheless, limitations of the research needs to be thought of. Use of a single‐lead ECG poses goal challenges for discrimination of supraventricular arrhythmia from regular sinus rhythm. On a regular basis bodily exercise manifests via noise and artifacts. To make sure evaluation of regular sinus rhythm, we applied rigorous high quality management procedures, which included semi‐automated evaluation of the info, and handbook evaluate of ECGs. To enhance the standard of included ECG information, we elected to check 3‐minute epochs of repeatedly regular (uninterrupted) clear sinus rhythm.

Impaired baroreflex sensitivity could be measured by coronary heart price turbulence, which was not measured on this research. Additional research of coronary heart price turbulence in ESKD sufferers on dialysis is required. Outcomes of frequency‐area HRV needs to be thought of with warning. We measured HRV on every 3‐minute phase, which at the least partially explains the variations between HF and LF energy reported in our research as in contrast with the 24‐hour energy spectrum analyses.52, 53 To beat limitations of remoted HRV metrics, we evaluated a number of HRV measures presumably reflecting parasympathetic tone (rMSSD, SD1, HF energy), and sympathovagal steadiness (SD2, SD12, LF/HF ratio). Constant findings throughout the complete set of HRV metrics improve the validity of our outcomes.

The scale of this research is comparatively small, and members had been predominantly black, which limits generalizability. Nonetheless, these had been members with identified structural coronary heart illness and in‐depth information for a protracted time period to check utilizing inside‐individual comparability. On common, the research participant had 156±55 hours of knowledge, offering passable energy for the analyses of coronary heart price and brief‐time period HRV (rMSSD, SD1) utilizing the periodic regression and time‐collection evaluation, in all stratified time intervals. Nevertheless, the statistical powers of the stratified ARCH analyses of LF/HF energy, SD12, and entropy measures weren’t enough in phases 3 to 4 and 5 to six. Thus, a few of the nonsignificant findings is perhaps due to low statistical energy.

The belief of equal intervals between 3‐minute epochs was violated for ≈10% of epochs. To deal with this limitation, sensitivity analyses had been carried out and epochs that began within the second half of an hour had been excluded from ARCH fashions, which didn’t change the affiliation of dialytic cycle with HRV time‐collection. Solely 4 research members missed hemodialysis, and subsequently, outcomes of this subgroup evaluation needs to be thought of with warning. The explanation for the missed hemodialysis periods was unknown.

Medical Implications

In abstract, this potential steady ECG‐monitoring research confirmed that cardiac arrhythmias are frequent in hemodialysis sufferers. In time‐collection evaluation, paroxysms of VT are preceded by sooner (than in a earlier hour) coronary heart price, suggesting a triggered mechanism of VT. Each‐different‐day hemodialysis preserves physiological circadian rhythm in coronary heart price and HRV, whereas the extended interdialytic interval abolishes the circadian rhythm and shows a steadily worsening autonomic imbalance. The armamentarium of units able to repeatedly monitoring ECG is quick‐rising. Additional research are wanted to develop an individualized prediction of cardiac arrhythmias based mostly on analyses of coronary heart price and HRV time‐collection.

Sources of Funding

The PACE Research was supported by the NIH grant R01DK072367 (to Parekh). This research was supported partly by the NIH grant HL118277 (to Tereshchenko).




*Correspondence to: Larisa Tereshchenko, MD, PhD, 3181 SW Sam Jackson Park Rd, UHN62, Portland, OR 97239. E‐mail: [email protected]edu


  • 1 United States Renal Information System. 2018. USRDS annual information report: Epidemiology of kidney illness in america. Nationwide Institutes of Well being, Nationwide Institute of Diabetes and Digestive and Kidney Ailments, Bethesda, MD, 2018.Google Scholar
  • 2 Tereshchenko LG, Kim ED, Oehler A, Meoni LA, Ghafoori E, Rami T, Maly M, Kabir M, Hawkins L, Tomaselli GF, Lima JA, Jaar BG, Sozio SM, Estrella M, Kao WH, Parekh RS. Electrophysiologic substrate and danger of mortality in incident hemodialysis. J Am Soc Nephrol. 2016; 27:3413–3420.CrossrefMedlineGoogle Scholar
  • 3 Sacher F, Jesel L, Borni‐Duval C, De Precigout V, Lavainne F, Bourdenx JP, Haddj‐Elmrabet A, Seigneuric B, Keller A, Ott J, Savel H, Delmas Y, Bazin‐Kara D, Klotz N, Ploux S, Buffler S, Ritter P, Rondeau V, Bordachar P, Martin C, Deplagne A, Reuter S, Haissaguerre M, Gourraud JB, Vigneau C, Mabo P, Maury P, Hannedouche T, Benard A, Combe C. Cardiac rhythm disturbances in hemodialysis sufferers: early detection utilizing an implantable loop recorder and correlation with organic and dialysis parameters. JACC Clin Electrophysiol. 2018; 4:397–408.CrossrefMedlineGoogle Scholar
  • 4 Makar MS, Pun PH. Sudden cardiac demise amongst hemodialysis sufferers. Am J Kidney Dis. 2017; 69:684–695.CrossrefMedlineGoogle Scholar
  • 5 Turakhia MP, Blankestijn PJ, Carrero JJ, Clase CM, Deo R, Herzog CA, Kasner SE, Passman RS, Pecoits‐Filho R, Reinecke H, Shroff GR, Zareba W, Cheung M, Wheeler DC, Winkelmayer WC, Wanner C, Convention Participation. Power kidney illness and arrhythmias: conclusions from a Kidney Illness: enhancing World Outcomes (KDIGO) Controversies Convention. Eur Coronary heart J. 2018; 39:2314–2325.CrossrefMedlineGoogle Scholar
  • 6 Bleyer AJ, Hartman J, Brannon PC, Reeves‐Daniel A, Satko SG, Russell G. Traits of sudden demise in hemodialysis sufferers. Kidney Int. 2006; 69:2268–2273.CrossrefMedlineGoogle Scholar
  • 7 Foley RN, Gilbertson DT, Murray T, Collins AJ. Lengthy interdialytic interval and mortality amongst sufferers receiving hemodialysis. N Engl J Med. 2011; 365:1099–1107.CrossrefMedlineGoogle Scholar
  • 8 Perl J, Chan CT. Timing of sudden demise relative to the hemodialysis process. Nat Clin Pract Nephrol. 2006; 2:668–669.CrossrefMedlineGoogle Scholar
  • 9 Wong MC, Kalman JM, Pedagogos E, Toussaint N, Vohra JK, Sparks PB, Sanders P, Kistler PM, Halloran Ok, Lee G, Joseph SA, Morton JB. Temporal distribution of arrhythmic occasions in power kidney illness: highest incidence within the lengthy interdialytic interval. Coronary heart Rhythm. 2015; 12:2047–2055.CrossrefMedlineGoogle Scholar
  • 10 Tereshchenko LG, Posnack NG. Does plastic chemical publicity contribute to sudden demise of sufferers on dialysis?Coronary heart Rhythm. 2019; 16:312–317.CrossrefMedlineGoogle Scholar
  • 11 Burton JO, Jefferies HJ, Selby NM, McIntyre CW. Hemodialysis‐induced cardiac damage: determinants and related outcomes. Clin J Am Soc Nephrol. 2009; 4:914–920.CrossrefMedlineGoogle Scholar
  • 12 Zipes DP, Wellens HJ. Sudden cardiac demise. Circulation. 1998; 98:2334–2351.CrossrefMedlineGoogle Scholar
  • 13 Moak JP, Goldstein DS, Eldadah BA, Saleem A, Holmes C, Pechnik S, Sharabi Y. Supine low‐frequency energy of coronary heart price variability displays baroreflex perform, not cardiac sympathetic innervation. Coronary heart Rhythm. 2007; 4:1523–1529.CrossrefMedlineGoogle Scholar
  • 14 Saul JP, Berger RD, Albrecht P, Stein SP, Chen MH, Cohen RJ. Switch perform evaluation of the circulation: distinctive insights into cardiovascular regulation. Am J Physiol. 1991; 261:H1231–H1245.MedlineGoogle Scholar
  • 15 Secemsky EA, Verrier RL, Cooke G, Ghossein C, Subacius H, Manuchehry A, Herzog CA, Passman R. Excessive prevalence of cardiac autonomic dysfunction and T‐wave alternans in dialysis sufferers. Coronary heart Rhythm. 2011; 8:592–598.CrossrefMedlineGoogle Scholar
  • 16 Fukuta H, Hayano J, Ishihara S, Sakata S, Mukai S, Ohte N, Ojika Ok, Yagi Ok, Matsumoto H, Sohmiya S, Kimura G. Prognostic worth of coronary heart price variability in sufferers with finish‐stage renal illness on power haemodialysis. Nephrol Dial Transplant. 2003; 18:318–325.CrossrefMedlineGoogle Scholar
  • 17 Oikawa Ok, Ishihara R, Maeda T, Yamaguchi Ok, Koike A, Kawaguchi H, Tabata Y, Murotani N, Itoh H. Prognostic worth of coronary heart price variability in sufferers with renal failure on hemodialysis. Int J Cardiol. 2009; 131:370–377.CrossrefMedlineGoogle Scholar
  • 18 Suzuki M, Hiroshi T, Aoyama T, Tanaka M, Ishii H, Kisohara M, Iizuka N, Murohara T, Hayano J. Nonlinear measures of coronary heart price variability and mortality danger in hemodialysis sufferers. Clin J Am Soc Nephrol. 2012; 7:1454–1460.CrossrefMedlineGoogle Scholar
  • 19 Parekh RS, Meoni LA, Jaar BG, Sozio SM, Shafi T, Tomaselli GF, Lima JA, Tereshchenko LG, Estrella MM, Kao WH. Rationale and design for the Predictors of Arrhythmic and Cardiovascular Danger in Finish Stage Renal Illness (PACE) research. BMC Nephrol. 2015; 16:63.CrossrefMedlineGoogle Scholar
  • 20 Tereshchenko Larisa G. PACE deidentified ECGpatch HRV dataset 28pts. Accessible at: https://github.com/Tereshchenkolab/HRV: GitHub; August 13, 2019. Accessed August 13, 2019.Google Scholar
  • 21 Steinberg JS, Varma N, Cygankiewicz I, Aziz P, Balsam P, Baranchuk A, Cantillon DJ, Dilaveris P, Dubner SJ, El‐Sherif N, Krol J, Kurpesa M, La Rovere MT, Lobodzinski SS, Locati ET, Mittal S, Olshansky B, Piotrowicz E, Saxon L, Stone PH, Tereshchenko L, Turitto G, Wimmer NJ, Verrier RL, Zareba W, Piotrowicz R. 2017 ISHNE‐HRS professional consensus assertion on ambulatory ECG and exterior cardiac monitoring/telemetry. Coronary heart Rhythm. 2017; 14:e55–e96.CrossrefMedlineGoogle Scholar
  • 22 Conen D, Adam M, Roche F, Barthelemy J‐C, Dietrich DF, Imboden M, Künzli N, Eckardstein Av, Regenass S, Hornemann T, Rochat T, Gaspoz J‐M, Probst‐Hensch N, Carballo D. Untimely atrial contractions within the normal inhabitants. Circulation. 2012; 126:2302–2308.LinkGoogle Scholar
  • 23 Pahlm O, Sörnmo L. Software program QRS detection in ambulatory monitoring—a evaluate. Med Biol Eng Compu. 1984; 22:289–297.CrossrefMedlineGoogle Scholar
  • 24 Pan J, Tompkins W. An actual‐time QRS detection algorithm. IEEE Transac Bio‐Med Eng. 1985; 32:230–236.CrossrefMedlineGoogle Scholar
  • 25 Castells F, Laguna P, Sörnmo L, Bollmann A, Roig JM. Principal part evaluation in ECG sign processing. EURASIP J Adv Sign Course of. 2007; 2007:074580.CrossrefGoogle Scholar
  • 26 Manriquez AI, Zhang Q. An algorithm for QRS onset and offset detection in single lead electrocardiogram information. Conf Proc IEEE Eng Med Biol Soc. 2007; 2007:541–544.MedlineGoogle Scholar
  • 27 Coronary heart price variability: requirements of measurement, physiological interpretation and medical use. Job Power of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Circulation. 1996; 93:1043–1065.CrossrefMedlineGoogle Scholar
  • 28 Sassi R, Cerutti S, Lombardi F, Malik M, Huikuri HV, Peng CK, Schmidt G, Yamamoto Y. Advances in coronary heart price variability sign evaluation: joint place assertion by the e‐Cardiology ESC Working Group and the European Coronary heart Rhythm Affiliation co‐endorsed by the Asia Pacific Coronary heart Rhythm Society. Europace. 2015; 17:1341–1353.CrossrefMedlineGoogle Scholar
  • 29 Cornforth DJ, Tarvainen MP, Jelinek HF. How you can calculate Renyi entropy from coronary heart price variability, and why it issues for detecting cardiac autonomic neuropathy. Entrance Bioeng Biotechnol. 2014; 2:34.CrossrefMedlineGoogle Scholar
  • 30 Cornforth DJ, Tarvainen MP, Jelinek HF. Utilizing Renyi entropy to detect early cardiac autonomic neuropathy. Conf Proc IEEE Eng Med Biol Soc. 2013; 2013:5562–5565.MedlineGoogle Scholar
  • 31 Rhee CM, Chou JA, Kalantar‐Zadeh Ok. Dialysis prescription and sudden demise. Semin Nephrol. 2018; 38:570–581.CrossrefMedlineGoogle Scholar
  • 32 Higgins ML, Bera A. A category of nonlinear ARCH fashions. Int Econ Rev. 1992; 33:137–158.CrossrefGoogle Scholar
  • 33 Weise F, London GM, Pannier BM, Guerin AP, Elghozi JL. Impact of hemodialysis on cardiovascular rhythms in finish‐stage renal failure. Kidney Int. 1995; 47:1443–1452.CrossrefMedlineGoogle Scholar
  • 34 Josephson ME. Medical cardiac electrophysiology : methods and interpretations, 4th ed. Philadelphia, PA: Wolters Kluwer/Lippincott Williams & Wilkins, Well being; 2008.Google Scholar
  • 35 Roy‐Chaudhury P, Tumlin JA, Koplan BA, Costea AI, Kher V, Williamson D, Pokhariyal S, Charytan DM, Williamson D, Roy‐Chaudhury P, Tumlin J, Kher V, Reddy V, Prakash KC, Charytan D, Tiwari SC, Pokhariyal S, Podoll A, Jasuja S, Walters GL, Wangsnes Ok, Costea A, Tombul S, Singh B, Mishra B, Yalagudri S, Shelke A, Narasimhan C, Karthigesan AM, Oomman A, Kumar KPP, Koplan B, Kaul U, Ghose T, Gupta R, Sethi A, Kumar N, Hariharan R, Sardana R, Wahab A, Khanna NN, Smith M, Kamath S, Galphin C, Sodhi P, Chakravarthy R, Budithi SR, McCausland F, Gulati S, Dijoo M, Singh U, Jain S, Saxena V, Sagar G, Charytan D, Fissell R, Foley R, Herzog CA, McCullough P, Rogers JD, Tumlin JA, Zimetbaum P, Assar M, Kremers M, Winkelmayer WC. Major outcomes of the Monitoring in Dialysis Research point out that clinically important arrhythmias are frequent in hemodialysis sufferers and associated to dialytic cycle. Kidney Int. 2018; 93:941–951.CrossrefMedlineGoogle Scholar
  • 36 Wang W, Lian Z, Rowin EJ, Maron BJ, Maron MS, Hyperlink MS. Prognostic implications of nonsustained ventricular tachycardia in excessive‐danger sufferers with hypertrophic cardiomyopathy. Circ Arrhythm Electrophysiol. 2017; 10:e004604.LinkGoogle Scholar
  • 37 Priori SG, Napolitano C, Memmi M, Colombi B, Drago F, Gasparini M, DeSimone L, Coltorti F, Bloise R, Keegan R, Filho FESC, Vignati G, Benatar A, DeLogu A. Medical and molecular characterization of sufferers with catecholaminergic polymorphic ventricular tachycardia. Circulation. 2002; 106:69–74.LinkGoogle Scholar
  • 38 Cadrin‐Tourigny J, Bosman LP, Nozza A, Wang W, Tadros R, Bhonsale A, Bourfiss M, Fortier A, Lie OH, Saguner AM, Svensson A, Andorin A, Tichnell C, Murray B, Zeppenfeld Ok, van den Berg MP, Asselbergs FW, Wilde AAM, Krahn AD, Talajic M, Rivard L, Chelko S, Zimmerman SL, Kamel IR, Crosson JE, Choose DP, Yap SC, van der Heijden JF, Tandri H, Jongbloed JDH, Guertin MC, van Tintelen JP, Platonov PG, Duru F, Haugaa KH, Khairy P, Hauer RNW, Calkins H, Te Riele A, James CA. A brand new prediction mannequin for ventricular arrhythmias in arrhythmogenic proper ventricular cardiomyopathy. Eur Coronary heart J. 2019; 40:1850–1858.CrossrefMedlineGoogle Scholar
  • 39 Scirica BM, Braunwald E, Belardinelli L, Hedgepeth CM, Spinar J, Wang W, Qin J, Karwatowska‐Prokopczuk E, Verheugt FW, Morrow DA. Relationship between nonsustained ventricular tachycardia after non‐ST‐elevation acute coronary syndrome and sudden cardiac demise: observations from the metabolic effectivity with ranolazine for much less ischemia in non‐ST‐elevation acute coronary syndrome‐thrombolysis in myocardial infarction 36 (MERLIN‐TIMI 36) randomized managed trial. Circulation. 2010; 122:455–462.AbstractGoogle Scholar
  • 40 Teuwen CP, Ramdjan TT, Gotte M, Brundel BJ, Evertz R, Vriend JW, Molhoek SG, Reinhart Dorman HG, van Opstal JM, Konings TC, van der Voort P, Delacretaz E, Wolfhagen NJ, van Gastel V, de Klerk P, Theuns DA, Witsenburg M, Roos‐Hesselink JW, Triedman JK, Bogers AJ, de Groot NM. Non‐sustained ventricular tachycardia in sufferers with congenital coronary heart illness: an vital signal?Int J Cardiol. 2016; 206:158–163.CrossrefMedlineGoogle Scholar
  • 41 Miyake CY, Webster G, Czosek RJ, Kantoch MJ, Dubin AM, Avasarala Ok, Atallah J. Efficacy of implantable cardioverter defibrillators in younger sufferers with catecholaminergic polymorphic ventricular tachycardia: success depends upon substrate. Circ Arrhythm Electrophysiol. 2013; 6:579–587.LinkGoogle Scholar
  • 42 Roston TM, Vinocur JM, Maginot KR, Mohammed S, Salerno JC, Etheridge SP, Cohen M, Hamilton RM, Pflaumer A, Kanter RJ, Potts JE, LaPage MJ, Collins KK, Gebauer RA, Temple JD, Batra AS, Erickson C, Miszczak‐Knecht M, Kubuš P, Bar‐Cohen Y, Kantoch M, Thomas VC, Hessling G, Anderson C, Younger M‐L, Cabrera Ortega M, Lau YR, Johnsrude CL, Fournier A, Kannankeril PJ, Sanatani S. Catecholaminergic polymorphic ventricular tachycardia in kids: evaluation of therapeutic methods and outcomes from a global multicenter registry. Circ Arrhyth Electrophysiol. 2015; 8:633–642.LinkGoogle Scholar
  • 43 Jukema JW, Timal RJ, Rotmans JI, Hensen LCR, Buiten MS, de Bie MK, Putter H, Zwinderman AH, van Erven L, Krol‐van Straaten MJ, Hommes N, Gabreels B, van Dorp W, van Dam B, Herzog CA, Schalij MJ, Rabelink TJ. Prophylactic use of implantable cardioverter‐defibrillators within the prevention of sudden cardiac demise in dialysis sufferers. Circulation. 2019; 139:2628–2638.LinkGoogle Scholar
  • 44 Tory Ok, Horvath E, Suveges Z, Fekete A, Sallay P, Berta Ok, Szabo T, Szabo AJ, Tulassay T, Reusz GS. Impact of propranolol on coronary heart price variability in sufferers with finish‐stage renal illness: a double‐blind, placebo‐managed, randomized crossover pilot trial. Clin Nephrol. 2004; 61:316–323.CrossrefMedlineGoogle Scholar
  • 45 Chan CT, Chertow GM, Daugirdas JT, Greene TH, Kotanko P, Larive B, Pierratos A, Stokes JB. Results of every day hemodialysis on coronary heart price variability: outcomes from the Frequent Hemodialysis Community (FHN) Each day Trial. Nephrol Dial Transplant. 2014; 29:168–178.CrossrefMedlineGoogle Scholar
  • 46 Gul A, Miskulin DC, Harford A, Zager P. In‐middle hemodialysis: time for a paradigm shift. J Am Soc Nephrol. 2018; 29:2452–2454.CrossrefMedlineGoogle Scholar
  • 47 Sedaghat G, Gardner RT, Kabir MM, Ghafoori E, Habecker BA, Tereshchenko LG. Correlation between the excessive‐frequency content material of the QRS on murine floor electrocardiogram and the sympathetic nerves density in left ventricle after myocardial infarction: experimental research. J Electrocardiol. 2017; 50:323–331.CrossrefMedlineGoogle Scholar
  • 48 Anrep G, Pascual W, Rössler R. Respiratory variations of the guts price‐II—the central mechanism of the respiratory arrhythmia and the inter‐relations between the central and the reflex mechanisms. Proc R Soc London B Biol Sci. 1936; 119:218–230.CrossrefGoogle Scholar
  • 49 Seibert E, Zohles Ok, Ulrich C, Kluttig A, Nuding S, Kors JA, Swenne CA, Werdan Ok, Fiedler R, Girndt M. Affiliation between autonomic nervous dysfunction and mobile irritation in finish‐stage renal illness. BMC Cardiovasc Disord. 2016; 16:210.CrossrefMedlineGoogle Scholar
  • 50 Ribas Ribeiro L, Flores de Oliveira J, Bueno Orcy R, Castilho Barros C, Dame Hense J, Santos F, Irigoyen MC, Gonzalez MC, Oses JP, Bohlke M. Exploring the complexity: the interaction between the angiotensin‐changing enzyme insertion/deletion polymorphism and the sympathetic response to hemodialysis. Am J Physiol Coronary heart Circ Physiol. 2018; 315:H1002–H1011.CrossrefMedlineGoogle Scholar
  • 51 Waks JW, Tereshchenko LG, Parekh RS. Electrocardiographic predictors of mortality and sudden cardiac demise in sufferers with finish stage renal illness on hemodialysis. J Electrocardiol. 2016; 49:848–854.CrossrefMedlineGoogle Scholar
  • 52 Stein PK, Tereshchenko L, Domitrovich PP, Kleiger RE, Perez A, Deedwania P. Diastolic dysfunction and autonomic abnormalities in sufferers with systolic coronary heart failure. Eur J Coronary heart Fail. 2007; 9:364–369.CrossrefMedlineGoogle Scholar
  • 53 Kleiger RE, Stein PK, Greater JT. Coronary heart price variability: measurement and medical utility. Ann Noninvasive Electrocardiol. 2005; 10:88–101.CrossrefMedlineGoogle Scholar
  • 54 Chou YH, Huang WL, Chang CH, Yang CCH, Kuo TBJ, Lin SL, Chiang WC, Chu TS. Coronary heart price variability as a predictor of speedy renal perform deterioration in power kidney illness sufferers. Nephrology. 2019; 24:806–813.CrossrefMedlineGoogle Scholar
  • 55 Pei J, Tang W, Li LX, Su CY, Wang T. Coronary heart price variability predicts mortality in peritoneal dialysis sufferers. Ren Fail. 2015; 37:1132–1137.CrossrefMedlineGoogle Scholar
  • 56 Huang J‐C, Chen C‐F, Chang C‐C, Chen S‐C, Hsieh M‐C, Hsieh Y‐P, Chen H‐C. Results of stroke on modifications in coronary heart price variability throughout hemodialysis. BMC Nephrol. 2017; 18:90.CrossrefMedlineGoogle Scholar
  • 57 Poulikakos D, Hnatkova Ok, Banerjee D, Malik M. Affiliation of QRS‐T angle and coronary heart price variability with main cardiac occasions and mortality in hemodialysis sufferers. Ann Noninvasive Electrocardiol. 2018; 23:e12570.CrossrefMedlineGoogle Scholar
  • 58 Park S, Kim WJ, Cho NJ, Choi CY, Heo NH, Gil HW, Lee EY. Predicting intradialytic hypotension utilizing coronary heart price variability. Sci Rep. 2019; 9:2574.CrossrefMedlineGoogle Scholar
  • 59 Wong MCG, Kalman JM, Pedagogos E, Toussaint N, Vohra JK, Sparks PB, Sanders P, Kistler PM, Halloran Ok, Lee G, Joseph SA, Morton JB. Bradycardia and asystole is the predominant mechanism of sudden cardiac demise in sufferers with power kidney illness. J Am Coll Cardiol. 2015; 65:1263–1265.CrossrefMedlineGoogle Scholar
  • 60 Roumelioti ME, Ranpuria R, Corridor M, Hotchkiss JR, Chan CT, Unruh ML, Argyropoulos C. Irregular nocturnal coronary heart price variability response amongst power kidney illness and dialysis sufferers throughout wakefulness and sleep. Nephrol Dial Transplant. 2010; 25:3733–3741.CrossrefMedlineGoogle Scholar
  • 61 Black N, D’Souza A, Wang Y, Piggins H, Dobrzynski H, Morris G, Boyett MR. Circadian rhythm of cardiac electrophysiology, arrhythmogenesis, and the underlying mechanisms. Coronary heart Rhythm. 2019; 16:298–307.CrossrefMedlineGoogle Scholar

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