Title
Potassium Monitoring From Multilead T-wave Morphology Changes During Hemodyalisis: Periodic Versus Principal Component Analysis
Abstract
Background: End-stage renal disease (ESRD) patients undergoing hemodyalisis therapy (HD) experience blood potassium ([K+]) variations that are reflected on the T-wave (TW) morphology. Methods: We evaluated the performance of different lead space reduction (LSR) methods: principal component analysis (PCA), maximising the TW energy, and two derived versions of periodic component analysis (πCA) named πCA <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</sub> and πCA <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</sub> , maximising the QRST or TW beat periodicity. We applied these methods to 12-lead electrocardiogram (ECG) from 24 ESRD-HD patients. Then, we derived three markers of TW morphology changes (d <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">uw</sub> , d <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">w</sub> and d <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">^w,c</sub> ), comparing an average TW derived every 30 min with that at the HD end, from the PCA, πCA <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</sub> and πCA <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</sub> based leads having the highest TW energy content. Similarities between these three methods were assessed by using Bland-Altman plots and the linear fitting error (ϵ) evaluated from the 12 <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> to the 44 <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> h of ECG recordings after the HD onset. Results: All series of d <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">uw</sub> , d <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">w</sub> and d <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">^w,c</sub> values showed good degree of mutual agreement (median bias ≤. 0.5 ms) and a small deviation from linearity in the [K+] increasing stage (median ϵ ≤ 3.3 ms). Conclusions: PCA and πCA can be used interchangeably to track TW changes in ESRD-HD patients, in this type of low noise contamination ECG recordings.
Year
DOI
Venue
2020
10.22489/CinC.2020.199
2020 Computing in Cardiology
Keywords
DocType
ISSN
potassium monitoring,end-stage renal disease patients,principal component analysis,PCA,periodic component analysis,12-lead electrocardiogram,HD end,HD onset,multilead T-wave morphology,hemodyalisis therapy,blood potassium variations,lead space reduction methods,TW beat periodicity,QRST,ESRD-HD patients,TW energy content,Bland-Altman plots,linear fitting error,low noise contamination ECG recordings,time 30.0 min,K+
Conference
2325-8861
ISBN
Citations 
PageRank 
978-1-7281-1105-6
0
0.34
References 
Authors
0
9