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Li-Pershing, Y.

Publications and source records attributed to Li-Pershing, Y..

2 recordsLinked to original sources
bioRxiv2019

The Dialysis Procedure Triggers Autonomic Imbalance and Cardiac Arrhythmias: Insights from Continuous 14-day ECG Monitoring

BackgroundIn end-stage kidney disease the dialytic cycle relates to the rate of sudden cardiac death. We hypothesized that circadian, dialytic cycles, paroxysmal arrhythmias, and cardiovascular risk factors are associated with periodic changes in heart rate and heart rate variability (HRV) in incident dialysis patients.\n\nMethodsWe conducted a prospective ancillary study of the Predictors of Arrhythmic and Cardiovascular Risk in End Stage Renal Disease cohort (n=28; age 54{+/-}13 y; 57% men; 96% black; 33% with a history of structural heart disease; left ventricular ejection fraction 70{+/-}9%). Continuous ECG monitoring was performed using an ECG patch (Zio Patch, iRhythm) and short-term HRV was measured for three minutes every hour. HRV was measured by root mean square of the successive normal-to-normal intervals (rMSSD), high and low frequency power, Poincare plot, and sample and Renyi entropy.\n\nResultsArrhythmias were detected in 46% (n=13). Non-sustained ventricular tachycardia (VT) was more frequent during dialysis or within 6 hours post-dialysis, as compared to pre-or between-dialysis (63% vs. 37%, P=0.015), whereas supraventricular tachycardia was more frequent pre-/ between-dialysis, as compared to during-/ post-dialysis (84% vs. 16%, P=0.015). In adjusted for cardiovascular disease and its risk factors autoregressive conditional heteroscedasticity panel (ARCH) model, VT events were associated with increased heart rate by 11.2 (95%CI 10.1-12.3) bpm (P<0.0001). During regular dialytic cycle, rMSSD demonstrated significant circadian pattern (Mesor 10.6(0.9-11.2) ms; Amplitude 1.5(1.0-3.1) ms; Peak at 02:01(20:22-03:16) am; P<0.0001), which was abolished on a second day interdialytic extension (adjusted ARCH trend for rMSSD -1.41(-1.67 to -1.15) ms per 24h; P<0.0001).\n\nConclusionCardiac arrhythmias associate with dialytic phase. Regular dialytic schedule preserves physiological circadian rhythm, but the second day without dialysis is characterized by parasympathetic withdrawal and a steady increase in sympathetic predominance.\n\nSubject TermsArrhythmias, Autonomic Nervous System, Electrocardiology (ECG), Treatment.

epidemiology↗
bioRxiv2019

Dynamic Predictive Accuracy of Electrocardiographic Biomarkers of Sudden Cardiac Death within a Survival Framework: The Atherosclerosis Risk in Communities (ARIC) study

BackgroundThe risk of sudden cardiac death (SCD) is known to be dynamic. However, an accuracy of a dynamic SCD prediction, and \"expiration date\" of ECG biomarkers is unknown. Our goal was to measure dynamic predictive accuracy of ECG biomarkers of SCD and competing outcomes.\n\nMethodsAtherosclerosis Risk In Community study participants with analyzable digital ECGs were included (n=15,768; 55% female, 73% white, age 54.2{+/-}5.8 y). ECGs of 5 follow-up visits were analyzed. Global electrical heterogeneity (GEH) and traditional ECG metrics were measured. Adjudicated SCD served as the primary outcome; non-sudden cardiac death served as competing outcome. Time-dependent area under the (receiver operating characteristic) curve (AUC) analysis was performed to assess prediction accuracy of a continuous biomarker in a period of 3,6,9 months, and 1,2,3,5,10, and 15 years, using survival analysis framework.\n\nResultsOver a median 24.4 y follow-up, there were 581 SCDs (incidence 1.77 (95%CI 1.63-1.92)/1,000 person-years), and 838 nonSCDs [2.55 (95%CI 2.39-2.73)]. Resting heart rate was the strongest (AUC 0.930) short-term (3-month) non-specific SCD predictor, whereas spatial peak QRS-T angle predicted specifically SCD 15 years after ECG recording (AUC 0.719). QRS duration (AUC 0.885) and QTc (AUC 0.711) short-term predicted advanced structural heart disease better than SCD. \"Expiration date\" for most ECG biomarkers was two years after ECG recording. GEH significantly improved reclassification of SCD risk beyond age, sex, race, diabetes, hypertension, coronary heart disease and stroke.\n\nConclusionShort-term predictors of SCD, nonSCD, and biomarkers of long-term SCD risk differed, reflecting differences in transient vs. persistent SCD substrates.

epidemiology↗