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Arrhythmia and Time of Day in Maintenance Hemodialysis: Secondary Analysis of the Monitoring in Dialysis Study

Authors :
Qandeel H. Soomro
Bruce A. Koplan
Alexandru I. Costea
Prabir Roy-Chaudhury
James A. Tumlin
Vijay Kher
Don E. Williamson
Saurabh Pokhariyal
Candace K. McClure
David M. Charytan
Don Williamson
James Tumlin
Vikranth Reddy
Kowdle Chandrasekhar Prakash
David Charytan
Suresh Chandra Tiwari
Amber Podoll
Sanjeev Jasuja
G. Leslie Walters
Kraig Wangsnes
Alexandru Costea
Selcuk Tombul
Balbir Singh
Brajesh Mishra
Sachin Yalagudri
Abhijeet Shelke
Calambur Narasimhan
A.M. Karthigesan
Abraham Oomman
K.P. Pramod Kumar
Bruce Koplan
Upendra Kaul
Tapan Ghose
Ripen Gupta
Arvind Sethi
Nikhil Kumar
Ramesh Hariharan
Rajnish Sardana
Arif Wahab
N.N. Khanna
Mark Smith
Suresh Kamath
Claude Galphin
Puneet Sodhi
Rajsekara Chakravarthy
Subba Rao Budithi
Finnian McCausland
Sanjeev Gulati
Munawer Dijoo
Upendra Singh
Salil Jain
Vishal Saxena
Gaurav Sagar
Rachel Fissell
Robert Foley
Charles A. Herzog
Peter McCullough
John D. Rogers
Peter Zimetbaum
Manish Assar
Mark Kremers
Wolfgang C. Winkelmayer
Source :
Kidney Medicine, Vol 6, Iss 4, Pp 100799- (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

Rationale & Objective: The incidence of arrhythmia varies by time of day. How this affects individuals on maintenance dialysis is uncertain. Our objective was to quantify the relationship of arrhythmia with the time of day and timing of dialysis. Study Design: Secondary analysis of the Monitoring in Dialysis study, a multicenter prospective cohort study. Settings & Participants: Loop recorders were implanted for continuous cardiac monitoring in 66 participants on maintenance dialysis with a follow up of 6 months. Exposure: Time of day based on 6-hour intervals. Outcomes: Event rates of clinically significant arrhythmia. Analytical Approach: Negative binomial mixed effects regression models for repeated measures were used to evaluate data from the Monitoring in Dialysis study for differences in diurnal patterns of clinically significant arrhythmia among those with end-stage kidney disease with heart failure and end-stage kidney disease alone. We additionally analyzed rates according to presence of heart failure, time of dialysis shift, and dialysis versus nondialysis day. Results: Rates of clinically significant arrhythmia peaked between 12:00 AM and 5:59 AM and were more than 1.5-fold as frequent during this interval than the rest of the day. In contrast, variations in atrial fibrillation peaked between 6:00 AM and 11:59 AM, but variations across the day were qualitatively small. Clinically significant arrhythmia occurred at numerically higher rate in individuals with end-stage kidney disease and heart failure (5.9 events/mo; 95% CI, 1.3-26.8) than those without heart failure (4.0 events/mo; 95% CI, 0.9-17.9). Although differences in overall rate were not significant, their periodicity was significantly different (P

Details

Language :
English
ISSN :
25900595
Volume :
6
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Kidney Medicine
Publication Type :
Academic Journal
Accession number :
edsdoj.f6e169f95a494bcf967a13ba423e0e2d
Document Type :
article
Full Text :
https://doi.org/10.1016/j.xkme.2024.100799