Notes

Health-related habits after 1 year of kidney hair transplant.
The analysis of complex heartbeat dynamics has been widely used to characterize heartbeat autonomic control in healthy and pathological conditions. However, underlying physiological correlates of complexity measurements from heart rate variability (HRV) series have not been identified yet. To this extent, we investigated intrinsic irregularity and complexity of cardiac sympathetic and vagal activity time series during postural changes. We exploited our recently proposed HRV-based, time-varying Sympathetic and Parasympathetic Activity Indices (SAI and PAI) and performed Sample Entropy, Fuzzy Entropy, and Distribution Entropy calculations on publicly-available heartbeat series gathered from 10 healthy subjects undergoing resting state and passive slow tilt sessions. Results show significantly higher entropy values during the upright position than resting state in both SAI and PAI series. We conclude that an increase in HRV complexity resulting from postural changes may derive from sympathetic and vagal activities with higher complex dynamics.This work proposes an empirical mode decomposition (EMD) method to assess the strength of the interactions between heart period (HP) and systolic arterial pressure (SAP) variability. EMD was exploited to decompose the original series (OR) into its first, and fastest, intrinsic mode function (IMF1) and the residual (RES) computed by subtracting the IMF1 from OR. EMD procedure was applied to both HP and SAP variability series. Then, the cross correlation function (CCF) was computed over OR, IMF1 and RES series derived from HP and SAP variability in 13 healthy subjects (age 27±8 yrs, 5 males) at rest in supine position (REST) and during head-up tilt (TILT). The first CCF maximum at negative time lags and the first CCF minimum at positive time lags were taken respectively as indexes of the coupling along the feedback baroreflex and feedforward mechanical arms of HP-SAP closed-loop control. Results showed that the coupling strength is increased during TILT on both arms and this result holds on REST. At REST the coupling along both arms was stronger when computed over IMF1 because interactions were mainly governed by respiration. This result was not observed during TILT possibly due to the reduced importance of respiration compared to other mechanisms acting at slower time scales. The proposed method allowed the investigation of the strength of HP-SAP variability interactions according to the time scales of the physiological mechanisms.The proposed EMD-based method allows the quantification of the strength of the HP-SAP closed-loop variability interactions according to the different time scales of respiration and slower baroreflex-mediated reflexes.We assessed the effect of surgical aortic valve replacement (SAVR) on cardiovascular and cerebrovascular controls with particular attention to their complexity and presence of nonlinear behaviors via the analysis of spontaneous variability of heart period (HP), systolic and diastolic arterial pressure (SAP and DAP) and mean cerebral blood flow (MCBF). Variability series were acquired before (PRE) and after (POST) SAVR in 12 patients (age 76±4.7 yrs, 7 males) at rest in supine position and during active standing. Complexity was assessed via a local nonlinear prediction approach exploiting the k-nearest neighbor strategy. The presence of nonlinear dynamics was checked by comparing the complexity marker computed over the original series with the distribution of values assessed over 100 surrogates preserving distribution and power spectral density of the original series but with random phases. read more We found that i) HP variance was significantly reduced in POST; ii) the complexity of SAP and DAP variabilities increased in POST with a greater likelihood of observing nonlinear dynamics over SAP compared to PRE at supine rest; iii) the amplitude of MCBF fluctuations and its complexity in POST remained similar to PRE. SAVR induces important changes of the cardiac and vascular autonomic controls, while cerebrovascular regulation seems to be less affected.In this study, we developed and analyzed different patient-specific 3D anatomical models of the left atrium including left atrial Appendage, in order to investigate the local hemodynamics. Particularly, we focused on the left atrial appendage and its impact on thrombus formation due to wall shear stress alterations. A 3D semi-automated reconstruction approach was carried out to segment and reconstruct the left atrium from CT scans. Six different patients were studied applying their patient-specific clinical data. Three different velocity profiles simulated for each patient case, representing one normal and two abnormal conditions. Simulations varied significantly according to different appendage morphologies. Our scope is to describe the hemodynamic behavior at the left atrium and the left atrial appendage according to different blood velocities based on their anatomic variety (chicken wing 0.14 m/s, windsock 0.10, cactus 0.08, and cauliflower 0.04). Wall shear stress results were demonstrated and correlated with the velocities and the thrombus formation inside the appendage cavity.
We investigate an optimized non-uniform sampling strategy for blood pressure time series from the operating room (OR). Our aim is to obtain an approximate bound on the achievable reconstruction fidelity given an average sampling rate constraint.

Our data set consists of 117 hours of recordings of continuous invasive blood pressure from 28 surgery patients. We evaluate the root mean squared error (RMSE) of the zero-order hold sampling reconstruction of the blood pressure time series. We quantitatively compare the errors achieved by uniform versus optimized non-uniform sample placements for several average sample rates, ranging from 2 to 24 measurements per hour.

An optimized non-uniform measurement schedule can lead to approximately 50% reduction of reconstruction RMSE for systolic, mean, and diastolic blood pressure time series with respect to uniform sampling, while maintaining the same average sampling rate.
An optimized non-uniform measurement schedule can lead to approximately 50% reduction of reconstruction RMSE for systolic, mean, and diastolic blood pressure time series with respect to uniform sampling, while maintaining the same average sampling rate.
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