Antonio Canichella

Heart rate variability in untreated newly diagnosed temporal lobe epilepsy: Evidence for ictal sympathetic dysregulation

To compare heart rate variability (HRV) parameters in newly diagnosed and untreated temporal lobe epilepsy (TLE) between the interictal, preictal, ictal, and postictal states.

Intraoperative haemodynamic monitoring: A pilot study on integrated data collection, processing and modelling for extracting vital signs and beyond

In this paper we illustrate an ongoing project focused on intraoperative monitoring of haemodynamic stability and cardiorespiratory interactions, and present an example analysis of vital signs recorded synchronously from multiple monitoring devices through a LabView©-based acquisition software termed “Global Collect”. We present two moving average models for the black box estimation of the gains of the cardiopulmonary baroreflex control of arterial resistance and of ventricular contractility, based on invasive, continuous measurements of arterial blood pressure and central venous pressure. As a proof-of-concept, we analyze the effects of a fluid-challenge maneuver performed during major surgery, quantifying the mechanisms through which such maneuvers are able to increase cardiac performance and hence enhance venous return. These preliminary results of a pilot case study demonstrate the potential of investigating autonomic nervous system control of circulation under general anesthesia in advancing intraoperative patient monitoring and aiding maintenance of haemodynamic stability in patients undergoing major surgery.

Fluid responsiveness in liver surgery: comparisons of different indices and approaches

The expected response to fluid infusion is an increase of cardiac output (CO), and this response depends mostly on the current cardiac function of the patient. The importance of the prediction of fluid responsiveness (FR) is based on the fact that fluid loading in hemodynamic unstable patients may be hazardous and dangerous, e.g., by exposing them to the risk of developing pulmonary edema. The objective of this work is to improve the knowledge about the performance of the indices of FR prediction in association with different classification approaches in a particular setting, i.e., liver surgery. The specific aims are (1) the comparison of different CO estimators from invasive arterial blood pressure (ABP) measurement with particular attention to the assessment of CO variation after fluid administration and (2) the comparison of several indices for the prediction of FR to maneuvers classified from the CO measurements provided by a commercial monitor (PiCCO™, Pulsion Medical System, Munich, Germany). The main finding of this work is that pulse pressure variation (PPV) indices are more reliable and computationally feasible than stroke volume variation (SVV) indices. The PPV provided by PiCCO has the best performance in terms of area under curve, sensitivity, and specificity (0.92, 0.88, and 0.86, respectively), when the maneuvers are classified according to the maximum values of CO variation estimated during the second and third minutes after infusion. Moreover, PPVPiCCO is significantly correlated with the CO variation after infusion (rho = 0.51, p value < 0.05). The threshold values produced by the PPV indices (PPV = 13.9% and PPVPiCCO = 14.4%) are in agreement with the literature. From these observations, we conclude that the PPV index can be considered most suitable for the prediction of FR in liver surgery.

Arterial blood pressure regulation following aorta clamping and declamping during surgery

In this paper, we propose the use of black box models for the system identification of the cardiopulmonary baroreflex control of arterial resistance and of ventricular contractility and of arterial baroreflex control of heart rate (HR) from invasive, continuous measurements of arterial blood pressure (ABP) and central venous pressure (CVP), and non invasive, continuous recordings of ECG and respiration. Two crucial phases of the abdominal aortic aneurism (AAA) repair were investigated: the clamping and declamping of aorta. The objective of the present work is to evaluate and to test the ability to monitor baroreflex responses to clamping and declamping maneuvers preceding and following aneurism removal.

Prediction of postoperative outcomes using intraoperative hemodynamic monitoring data

Major surgeries can result in high rates of adverse postoperative events. Reliable prediction of which patient might be at risk for such events may help guide peri- and postoperative care. We show how archiving and mining of intraoperative hemodynamic data in orthotopic liver transplantation (OLT) can aid in the prediction of postoperative 180-day mortality and acute renal failure (ARF), improving upon predictions that rely on preoperative information only. From 101 patient records, we extracted 15 preoperative features from clinical records and 41 features from intraoperative hemodynamic signals. We used logistic regression with leave-one-out cross-validation to predict outcomes, and incorporated methods to limit potential model instabilities from feature multicollinearity. Using only preoperative features, mortality prediction achieved an area under the receiver operating characteristic curve (AUC) of 0.53 (95% CI: 0.44–0.78). By using intraoperative features, performance improved significantly to 0.82 (95% CI: 0.56–0.91, P = 0.001). Similarly, including intraoperative features (AUC = 0.82; 95% CI: 0.66–0.94) in ARF prediction improved performance over preoperative features (AUC = 0.72; 95% CI: 0.50–0.85), though not significantly (P = 0.32). We conclude that inclusion of intraoperative hemodynamic features significantly improves prediction of postoperative events in OLT. Features strongly associated with occurrence of both outcomes included greater intraoperative central venous pressure and greater transfusion volumes.

Intraoperative hemodynamics predict postoperative mortality in orthotopic liver transplantation.

Liver transplantation remains the only curative treatment option for a variety of end-stage liver diseases. Prediction of major adverse events following surgery has traditionally focused on static predictors that are known prior to surgery. The effects of intraoperative management can now be explored due to the archiving of high-resolution monitoring data. We extracted intraoperative hemodynamic trend data of 55 patients undergoing orthotopic liver transplantation (OLT) and computed 12 features from the systolic arterial blood pressure (ABP), cardiac index, central venous pressure (CVP), and stroke volume variation (SVV) signals. Using a logistic regression classifier with a leave-one-out cross-validation procedure, we selected subsets of these features to predict mortality up to 180 days after surgery. Best performance was achieved with a combination of 3 features - median absolute deviation (MAD) of ABP, median CVP, and time spent with SVV <; 10% - reaching an area under the receiver-operating characteristic (or c-statistic) of 0.808. Odds ratios (OR) computed from the coefficients of the multivariate logistic regression model constructed from these features showed that greater time spent with SVV <; 10% (OR = 0.981 min-1, p = 0.001) and greater MAD of systolic ABP (OR = 0.696 mmHg-1, p = 0.026) were significantly associated with survival. Adding preoperative measures such as age and serum concentrations of albumin, bilirubin, and creatinine failed to improve performance of the prediction model. These results show that the course of intraoperative hemodynamics can predict 180-day mortality after OLT.

STABILITY AND RESPONSIVENESS OF THE CARDIOVASCULAR SYSTEM UNDER A PHYSIOLOGICALLY INSPIRED BAROREFLEX MODEL

We investigate the Seidel–Herzel model of the human baroreflex feedback control mechanism in terms of parameter choices and its ability to mimic heart rate physiology. We show that this model has the potential to be re-parameterized to better mimic features commonly observed in human physiology. We investigate the modification of the RR return maps as a function of parameter values and show that the model exhibits chaotic behavior. Extensive simulations are performed to establish which parameters mostly contribute to model flexibility in terms of observable output, and critical considerations are cast about potential pitfalls in model re-parameterization to mimic health and pathological behaviors. The Seidel–Herzel model is then merged with a detailed 21-compartment model for the vascular bed in order to examine sensitivity of RR dynamics to whole body simulation parameters. Pathological situations are simulated by altering total blood volume, ventricular compliances and baroreflex gains. The RR solutions show bifurcation diagrams typical of chaotic behavior, where the extension of the chaotic regions is in general smaller in simulated pathological states when compared to baseline (healthy) situations. We speculate that, despite the limits of the model and the limitations of the physiological parameterization, a loss of chaotic behavior correlates with the presence of disease-related aberrations.

Estimation of baroreflex sensitivity during anesthesia induction with propofol

This paper presents the analysis of the autonomic nervous system (ANS) control and cardiac baroreflex sensitivity in patients undergoing general anesthesia for major surgery, with the goal of evaluating the effects of anesthesia bolus induction with propofol on autonomic control of heart rate (HR) and arterial blood pressure (ABP). The increase in baroreflex gain in the LF band observed through two different methods hints at the fact that the baroreflex may increase heart period (HP) following a transient ABP decrease, but its response displays a larger amplitude, to compensate for the blunting of the sympathetic action on heart rate and vascular resistance.

Intra- and inter-beat modeling of cardiovascular dynamics and control: Assessing haemodynamic stability and responsiveness

In critical care patient management, extensive and invasive patient monitoring is routinely performed in order to quantify patient status in view of therapeutic interventions. Little quantitative integration is performed when collecting information from multiple monitors, and processing algorithms are often based on little physiological understanding. Mechanistic modeling can offer insight into the mechanisms underlying patient stability and sensitivity to alterations in physiological variables. Starting from existing models, we construct an integrated model which combines detailed neural cardiovascular regulation with realistic circulation modeling, using Monte-Carlo techniques for reparameterisation when merging the two models. The combined model is analyzed in terms of its dynamical stability and sensitivity to parameter perturbations under simulated conditions of fluid deficit, anaesthesia, and dilatative cardiomyopathy. The results exemplify how a structural model can serve as a quantitative guide in assessing how different underlying patient states can alter the haemodynamics impact of external therapeutic intervention.