Beschreibung:
<jats:title>Abstract</jats:title><jats:p>Blood potassium concentration ([K<jats:sup>+</jats:sup>]) influences the electrocardiogram (ECG), particularly T-wave morphology. We developed a new method to quantify [K<jats:sup>+</jats:sup>] from T-wave analysis and tested its clinical applicability on data from dialysis patients, in whom [K<jats:sup>+</jats:sup>] varies significantly during the therapy. To elucidate the mechanism linking [K<jats:sup>+</jats:sup>] and T-wave, we also analysed data from long QT syndrome type 2 (LQT2) patients, testing the hypothesis that our method would have underestimated [K<jats:sup>+</jats:sup>] in these patients. Moreover, a computational model was used to explore the physiological processes underlying our estimator at the cellular level. We analysed 12-lead ECGs from 45 haemodialysis and 12 LQT2 patients. T-wave amplitude and downslope were calculated from the first two eigenleads. The T-wave slope-to-amplitude ratio (T<jats:sub>S/A</jats:sub>) was used as starting point for an ECG-based [K<jats:sup>+</jats:sup>] estimate (K<jats:sub>ECG</jats:sub>). Leave-one-out cross-validation was performed. Agreement between K<jats:sub>ECG</jats:sub> and reference [K<jats:sup>+</jats:sup>] from blood samples was promising (error: −0.09 ± 0.59 mM, absolute error: 0.46 ± 0.39 mM). The analysis on LQT2 patients, also supported by the outcome of computational analysis, reinforces our interpretation that, at the cellular level, delayed-rectifier potassium current is a main contributor of K<jats:sub>ECG</jats:sub> correlation to blood [K<jats:sup>+</jats:sup>]. Following a comprehensive validation, this method could be effectively applied to monitor patients at risk for hyper/hypokalemia.</jats:p>