Resumen: Noninvasive screening of hypo- and hyperkalemia can prevent fatal arrhythmia in end-stage renal disease (ESRD) patients, but current methods for monitoring of serum potassium (K+) have important limitations. We investigated changes in nonlinear dynamics and morphology of the T wave in the electrocardiogram (ECG) of ESRD patients during hemodialysis (HD), assessing their relationship with K+ and designing a K+ estimator. Methods: ECG recordings from twenty-nine ESRD patients undergoing HD were processed. T waves in 2-min windows were extracted at each hour during an HD session as well as at 48 h after HD start. T wave nonlinear dynamics were characterized by two indices related to the maximum Lyapunov exponent (¿t, ¿wt) and a divergence-related index (¿). Morphological variability in the T wave was evaluated by three time warping-based indices (dw, reflecting morphological variability in the time domain, and da and daNL, in the amplitude domain). K+was measured from blood samples extracted during and after HD. Stage-specific and patient-specific K+ estimators were built based on the quantified indices and leave-one-out cross-validation was performed separately for each of the estimators. Results: The analyzed indices showed high inter-individual variability in their relationship with K+. Nevertheless, all of them had higher values at the HD start and 48 h after it, corresponding to the highest K+. The indices ¿ and dw were the most strongly correlated with K+ (median Pearson correlation coefficient of 0.78 and 0.83, respectively) and were used in univariable and multivariable linear K+ estimators. Agreement between actual and estimated K+ was confirmed, with averaged errors over patients and time points being 0.000 ± 0.875 mM and 0.046 ± 0.690 mM for stage-specific and patient-specific multivariable K+ estimators, respectively.ariability allow noninvasive
monitoring of [K+] in ESRD patients.
Significance: ECG markers have the potential to be used for hypo- and hyperkalemia screening in ESRD patients Idioma: Inglés DOI: 10.1016/j.compbiomed.2022.105304 Año: 2022 Publicado en: Computers in biology and medicine 143 (2022), 105304 [13 pp] ISSN: 0010-4825 Factor impacto JCR: 7.7 (2022) Categ. JCR: BIOLOGY rank: 7 / 92 = 0.076 (2022) - Q1 - T1 Categ. JCR: MATHEMATICAL & COMPUTATIONAL BIOLOGY rank: 4 / 55 = 0.073 (2022) - Q1 - T1 Categ. JCR: ENGINEERING, BIOMEDICAL rank: 16 / 96 = 0.167 (2022) - Q1 - T1 Categ. JCR: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS rank: 18 / 110 = 0.164 (2022) - Q1 - T1 Factor impacto CITESCORE: 9.2 - Medicine (Q1) - Computer Science (Q1)