Nonlinear T-Wave Time Warping-Based Sensing Model for Non-Invasive Personalised Blood Potassium Monitoring in Hemodialysis Patients: A Pilot Study.

Background: End-stage renal disease patients undergoing hemodialysis (ESRD-HD) therapy are highly susceptible to malignant ventricular arrhythmias caused by undetected potassium concentration ([ K + ]) variations ( Δ [ K + ] ) out of normal ranges. Therefore, a reliable method for continuous, noninvasive monitoring of [ K + ] is crucial. The morphology of the T-wave in the electrocardiogram (ECG) reflects Δ [ K + ] and two time-warping-based T-wave morphological parameters, d w and its heart-rate corrected version d w , c , have been shown to reliably track Δ [ K + ] from the ECG. The aim of this study is to derive polynomial models relating d w and d w , c with Δ [ K + ] , and to test their ability to reliably sense and quantify Δ [ K + ] values. Methods: 48-hour Holter ECGs and [ K + ] values from six blood samples were collected from 29 ESRD-HD patients. For every patient, d w and d w , c were computed, and linear, quadratic, and cubic fitting models were derived from them. Then, Spearman's (ρ) and Pearson's (r) correlation coefficients, and the estimation error ( e d ) between Δ [ K + ] and the corresponding model-estimated values ( Δ ^ [ K + ] ) were calculated. Results and Discussions: Nonlinear models were the most suitable for Δ [ K + ] estimation, rendering higher Pearson's correlation (median 0.77 ≤ r ≤ 0.92) and smaller estimation error (median 0.20 ≤ e d ≤ 0.43) than the linear model (median 0.76 ≤ r ≤ 0.86 and 0.30 ≤ e d ≤ 0.40), even if similar Spearman's ρ were found across models (median 0.77 ≤ ρ ≤ 0.83). Conclusion: Results support the use of nonlinear T-wave-based models as Δ [ K + ] sensors in ESRD-HD patients. [ABSTRACT FROM AUTHOR]