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Nonlinear t-wave time warping-based sensing model for non-invasive personalised blood potassium monitoring in hemodialysis patients: A pilot study

Abstract:

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 (∆[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 ∆[K+ ] and two time-warping-based T-wave morphological parameters, d<inf>w</inf> and its heart-rate corrected version d<inf>w,c</inf>, have been shown to reliably track ∆[K+ ] from the ECG. The aim of this study is to derive polynomial models relating d<inf>w</inf> and d<inf>w,c</inf> with ∆[K+ ], and to test their ability to reliably sense and quantify ∆[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<inf>w</inf> and d<inf>w,c</inf> 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<inf>d</inf>) between ∆[K+ ] and the corresponding model-estimated values (ˆ∆[K+ ]) were calculated. Results and Discussions: Nonlinear models were the most suitable for ∆[K+ ] estimation, rendering higher Pearson’s correlation (median 0.77 ≤ r ≤ 0.92) and smaller estimation error (median 0.20 ≤ e<inf>d</inf> ≤ 0.43) than the linear model (median 0.76 ≤ r ≤ 0.86 and 0.30 ≤ e<inf>d</inf> ≤ 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 ∆[K+ ] sensors in ESRD-HD patients.