Estimation of potassium levels in hemodialysis patients by T wave nonlinear dynamics and morphology markers

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 patient

Effects of ECG Data Length on Heart Rate Variability Among Young Healthy Adults

The relationship between the robustness of HRV derived by linear and nonlinear methods to the required minimum data lengths has yet to be well understood. The normal electrocardiography (ECG) data of 14 healthy volunteers were applied to 34 HRV measures using various data lengths, and compared with the most prolonged (2000 R peaks or 750 s) by using the Mann–Whitney U test, to determine the 0.05 level of significance. We found that SDNN, RMSSD, pNN50, normalized LF, the ratio of LF and HF, and SD1 of the Poincaré plot could be adequately computed by small data size (60–100 R peaks). In addition, parameters of RQA did not show any significant differences among 60 and 750 s. However, longer data length (1000 R peaks) is recommended to calculate most other measures. The DFA and Lyapunov exponent might require an even longer data length to show robust results. Conclusions: Our work suggests the optimal minimum data sizes for different HRV measures which can potentially improve the efficiency and save the time and effort for both patients and medical care providers

Automatic Analysis of Heart Rate Variability Signals

Táto dizertačná práca sa venuje variabilite srdcového rytmu a metódam jej stanovenia. Predovšetkým sa zameriava na nelineárne metódy a obzvlášť na Poincarého graf. Najprv sa venuje princípu a podstate vzniku variability srdcového rytmu, potom spôsobom jej znázornenia, metódam jej analýzy lineárnym aj nelineárnym a fyziologickým a patologickým vplyvom na zmeny variability srdcového rytmu. Obzvlášť je tu kladený dôraz na metabolický syndróm. V ďalšej časti práce sú porovnávané a vyhodnocované rôzne spôsoby vyjadrenia variability srdcového rytmu a ďalej sú testované vybrané metódy analýzy variability srdcového rytmu na unikátnych dátach pacientov s metabolickým syndrómom a zdravých osôb poskytnutých Ústavem přístrojové techniky (ÚPT) AV ČR. Predovšetkým sú použité Poincarého graf a jeho parametre SD1 a SD2, bežne používané parametre časovej domény a frekvenčnej domény, parametre stanovujúce entropiu signálu a Lyapunovov exponent. SD1 a SD2, ktoré kombinujú výhody metód časovej a frekvenčnej analýzy, dokážu úspešne rozlišovať medzi pacientmi s metabolickým syndrómom a zdravými osobami.This dissertation thesis is dedicated to the heart rate variability and methods of its evaluation. It mainly focuses on nonlinear methods and especially on the Poincaré plot. First it deals with the principle and nature of the heart rate variability, then the ways of its representation, linear and also nonlinear methods of its analysis and physiological and pathophysiological influence on heart rate variability changes. In particular, there is emphasis on the metabolic syndrome. In the next section of the thesis there are compared and evaluated different ways of representation of the heart rate variability and further are tested selected methods of heart rate variability analysis on unique data from patients with the metabolic syndrome and healthy subjects provided by the Institute of Scientific Instruments, Academy of Sciences of Czech Republic. In particular, they are used the Poincaré plot and its parameters SD1 and SD2, commonly used time domain and frequency domain parameters, parameters evaluating signal entropy and the Lyapunov exponent. SD1 and SD2 combining the advantages of time and frequency domain methods of heart rate variability analysis distinguish successfully between patients with the metabolic syndrome and healthy subjects.