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Objectives: The first aim of this study was to assess the predictive power of Tend interval (Te) and non-invasive hemodynamic markers, based on bioimpedance in decompensated chronic heart failure (CHF). The second one was to verify the possible differences in repolarization and hemodynamic data between CHF patients grouped by level of left ventricular ejection fraction (LVEF). Finally, we wanted to check if repolarization and hemodynamic data changed with clinical improvement or worsening in CHF patients. Methods: Two hundred and forty-three decompensated CHF patients were studied by 5 min ECG recordings to determine the mean and standard deviation (TeSD) of Te (first study). In a subgroup of 129 patients (second study), non-invasive hemodynamic and repolarization data were recorded for further evaluation. Results: Total in-hospital and cardiovascular mortality rates were respectively 19 and 9%. Te was higher in the deceased than in surviving subjects (Te: 120 ± 28 vs. 100 ± 25 ms) and multivariable logistic regression analysis reported that Te was related to an increase of total (χ2: 35.45, odds ratio: 1.03, 95% confidence limit: 1.02–1.05, p < 0.001) and cardiovascular mortality (χ2: 32.58, odds ratio: 1.04, 95% confidence limit: 1.02–1.06, p < 0.001). Subjects with heart failure with reduced ejection fraction (HFrEF) reported higher levels of repolarization and lower non-invasive systolic hemodynamic data in comparison to those with preserved ejection fraction (HFpEF). In the subgroup, patients with the NT-proBNP reduction after therapy showed a lower rate of Te, heart rate, blood pressures, contractility index, and left ventricular ejection time in comparison with the patients without NT-proBNP reduction. Conclusion: Electrical signals from ECG and bioimpedance were capable of monitoring the patients with advanced decompensated CHF. These simple, inexpensive, non-invasive, easily repeatable, and transmissible markers could represent a tool to remotely monitor and to intercept the possible worsening of these patients early by machine learning and artificial intelligence tools.

The head-up/-down tilt test acutely modifies the autonomic nervous system balance throughout a deactivation of the cardiopulmonary reflexes. The present study examines the influence of head-up/-down tilt on a number of ECG segments. A total of 20 healthy subjects underwent a 5 min ECG and noninvasive hemodynamic bio-impedance recording, during free and controlled breathing, lying at (a) 0°; (b) −45°, tilting up at 45°, and tilting up at 90°. Heart rate variability power spectral analysis was obtained throughout some ECG intervals: P-P (P), P-Q (PQ), PeQ (from the end of P to Q wave), Q-R peak (QR intervals), Q-R-S (QRS), Q-T peak (QTp), Q-T end (QTe), STp, STe, T peak-T end (Te), and, eventually, the TeP segments (from the end of T to the next P waves). Results: In all study conditions, the Low Frequency/High FrequencyPP and LFPP normalized units (nu) were significantly lower than the LF/HFRR and LFRRnu, respectively. Conversely, the HFPP and HFPPnu were significantly higher in all study conditions. STe, QTp, and QTe were significantly related to the PP and RR intervals, whereas the T wave amplitude was inversely related to the standard deviations of all the myocardial repolarization variables and to the left ventricular end-systolic volume (LVEDV). The T wave amplitude diminished during head-up tilt and significantly correlated with the LVEDV.

Acutely decompensated chronic heart failure (adCHF) is among the most important causes of in-hospital mortality. R-wave peak time (RpT) or delayed intrinsicoid deflection was proposed as a risk marker of sudden cardiac death and heart failure decompensation. Authors want to verify if QR interval or RpT, obtained from 12-lead standard ECG and during 5-min ECG recordings (II lead), could be useful to identify adCHF. At hospital admission, patients underwent 5-min ECG recordings, obtaining mean and standard deviation (SD) of the following ECG intervals: QR, QRS, QT, JT, and T peak–T end (Te). The RpT from a standard ECG was calculated. Patients were grouped by the age-stratified Januzzi NT-proBNP cut-off. A total of 140 patients with suspected adCHF were enrolled: 87 (mean age 83 ± 10, M/F 38/49) with and 53 (mean age: 83 ± 9, M/F: 23/30) without adCHF. V5-, V6- (p < 0.05) RpT, and QRSD, QRSSD, QTSD, JTSD, and TeSDp < 0.001 were significantly higher in the adCHF group. Multivariable logistic regression analysis demonstrated that the mean of QT (p < 0.05) and Te (p < 0.05) were the most reliable markers of in-hospital mortality. V6 RpT was directly related to NT-proBNP (r: 0.26, p < 0.001) and inversely related to a left ventricular ejection fraction (r: 0.38, p < 0.001). The intrinsicoid deflection time (obtained from V5-6 and QRSD) could be used as a possible marker of adCHF.

Using bio-impedance to deduce some hemodynamic parameters combined with some short-term ECG temporal dispersion intervals, and measuring myocardial depolarization, intraventricular conduction, and repolarization. A total of 65 in-hospital patients (M/F:35/30) were enrolled, 39 with HFrEF and 26 HFpEF, in New York Heart Association (NYHA) class IV. Stroke volume (SVI), cardiac indexes (CI), left ventricular ejection fraction (LVEFBIO), end diastolic volume (LV-EDV), and other systolic and diastolic parameters were noninvasively obtained at enrollment and at hospital discharge. At the same time, QR, QRS, QT, ST, Tpeak-Tend (Te) interval mean, and standard deviation (SD) from 5 min ECG recordings were obtained. At baseline, HFrEF patients reported significantly lower SVI (p < 0.05), CI (p < 0.05), and LVEF (p < 0.001) than HFpEF patients; moreover, HFrEF patients also showed increased LV-EDV (p < 0.05), QR, QRS, QT, ST, and Te means (p < 0.05) and standard deviations (p < 0.05) in comparison to HFpEF subjects. Multivariable logistic regression analysis reported a significant correlation between hospital mortality and Te mean (odds ratio: 1.03, 95% confidence limit: 1.01–1.06, p: 0.01). Fifty-seven percent of patients were considered responders to optimal medical therapy and, at discharge, they had significantly reduced NT-proBNP, (p < 0.001), heart rate (p < 0.05), and TeSD (p < 0.001). LVEF, obtained by transthoracic echocardiography, and LVEFBIO were significantly related (r: 0.781, p < 0.001), but these two parameters showed a low agreement limit. Noninvasive hemodynamic and ECG-derived parameters were useful to highlight the difference between HFrEF and HFpEF and between responders and nonresponders to the optimal medical therapy. Short-period bioimpedance and electrocardiographic data should be deeply evaluated to determine possible advantages in the therapeutic and prognostic approach in severe CHF.