Orthographic Depth May Influence the Degree of Severity of Maze Learning Performance in Children at Risk for Reading Disorder.

Reading disability (RD), which affects between 5 and 17% of the population worldwide, is the most prevalent form of learning disability, and is associated with underactivation of a universal reading network in children. However, recent research suggests there are differences in learning rates on cognitive predictors of reading performance, as well as differences in activation patterns within the reading neural network, based on orthographic depth (i.e., transparent/shallow vs. deep/opaque orthographies) in children with RD. Recently, we showed that native English-speaking children with RD exhibit impaired performance on a maze learning task that taps into the same neural networks that are activated during reading. In addition, we demonstrated that genetic risk for RD strengthens the relationship between reading impairment and maze learning performance. However, it is unclear whether the results from these studies can be broadly applied to children from other language orthographies. In this study, we examined whether low reading skill was associated with poor maze learning performance in native English-speaking and native German-speaking children, and the influence of genetic risk for RD on cognition and behavior. In addition, we investigated the link between genetic risk and performance on this task in an orthographically diverse sample of children attending an English-speaking international school in Germany. The results from our data suggest that children with low reading skill, or with a genetic risk for reading impairment, exhibit impaired performance on the maze learning task, regardless of orthographic depth. However, these data also suggest that orthographic depth influences the degree of impairment on this task. The maze learning task requires the involvement of various cognitive processes and neural networks that underlie reading, but is not influenced by potential differences in reading experience due to lack of text or oral reporting. As a fully automated tool, it does not require specialized training to administer, and current results suggest it may be a practicable screening tool for early identification of reading impairment across orthographies.

Minimally Invasive Monitoring of Cardiac Function for Patients with Rotary VAD Support, a Frequency Domain Approach.

A new cardiac function estimation algorithm has been developed to monitor a patient's myocardial contractility while supported by a rotary ventricular device (VAD). This algorithm uses the raw air pressure signal from the cuff pressure sensor, filters the signal with a bandpass filter, and then processes the signal through the Fast Fourier Transform to detect the first and second highest magnitude components. A systematic study by using a computer model to simulate the interaction between the cardiovascular system and the rotary VAD under different contractual states of the heart (failure, recovery, and healthy) demonstrated that these two magnitude components increased when the healthy status of the heart improved. Determination of these two magnitude components does not need any indwelling sensor but an air pressure cuff sensor. Performing this test does not require any interruption of regular rotary VAD operation or cardiac care facility. Successful development of this algorithm would allow more frequent monitoring for patients with less concerns of safety or examination cost, which could potentially improve the outcome of weaning patients from VAD support.

Oscillometric measurement of arterial pulse pressure for patients supported by a rotary blood pump.

A computer model has been developed to evaluate the accuracy of an oscillometric method to measure the arterial pulse pressure from a patient with a rotary ventricular assist device (VAD). This computer model consists of three major components: the cardiovascular system, the HeartMate II VAD, and the operation of an automated cuff. Simulation was performed to mimic failure, recovery, and normal cardiac functions of a patient, supported by the HeartMate II VAD at different levels from minimum to maximum. The oscillating cuff pressure, simulating the air pressure of a deflecting cuff, was obtained from simulation under different conditions to test the accuracy of an oscillometric algorithm in determining the arterial pulse pressure. The algorithm was able to detect the systolic and diastolic arterial pressure with the error within ±2 mmHg in most cases, except the cases when ventricular suction, induced by the VAD, occurred. The results from this study suggested that the oscillometric algorithm is capable to accurately detect the arterial pulse pressure for a rotary VAD patient if the algorithm is properly tuned.

In vitro hemodynamic evaluation of ventricular suction conditions of the EVAHEART ventricular assist pump.

PURPOSE: Mismatches between pump output and venous return in a continuous-flow ventricular assist device may elicit episodes of ventricular suction. This research describes a series of in vitro experiments to characterize the operating conditions under which the EVAHEART centrifugal blood pump (Sun Medical Technology Research Corp., Nagano, Japan) can be operated with minimal concern regarding left ventricular (LV) suction. METHODS: The pump was interposed into a pneumatically driven pulsatile mock circulatory system (MCS) in the ventricular apex to aorta configuration. Under varying conditions of preload, afterload, and systolic pressure, the speed of the pump was increased step-wise until suction was observed. Identification of suction was based on pump inlet pressure. RESULTS: In the case of reduced LV systolic pressure, reduced preload (=10 mmHg), and afterload (=60 mmHg), suction was observed for speeds=2,200 rpm. However, suction did not occur at any speed (up to a maximum speed of 2,400 rpm) when preload was kept within 10-14 mmHg and afterload=80 mmHg. Although in vitro experiments cannot replace in vivo models, the results indicated that ventricular suction can be avoided if sufficient preload and afterload are maintained. CONCLUSION: Conditions of hypovolemia and/or hypotension may increase the risk of suction at the highest speeds, irrespective of the native ventricular systolic pressure. However, in vitro guidelines are not directly transferrable to the clinical situation; therefore, patient-specific evaluation is recommended, which can be aided by ultrasonography at various points in the course of support.

Performance prediction of a percutaneous ventricular assist system using nonlinear circuit analysis techniques.

A percutaneous ventricular assist device (pVAD) is an extracorporeal cardiac assist system that supports the failing ventricle in advanced stage heart failure by bypassing blood from the venous to the arterial circulation through a blood pump. The system can be implanted in a Cath lab using standard interventional techniques, and typically consists of a venous or atrial drainage cannula, the VAD (or blood pump), and an arterial perfusion cannula. Because the device allows clinicians the freedom of choosing the configuration and size of the cannulae based on the patient's body size and the size of the artery, it is extremely difficult but important to be able to predict the amount of blood flow that the device can provide before it is implanted to support the patient. In this paper, we develop a novel method that can be used to accurately predict the mean flow rate that the device can provide to the patient based on the size and configuration of the arterial cannula, the pump speed, and the patient's left atrial and mean arterial pressures. To do this, we first develop a nonlinear electric circuit model for the pVAD. This model includes a speed dependent voltage source and flow dependent resistors to simulate the pressure-flow relationship in the various cannulae in the device. We show that the flow rate through the device can be determined by solving a quadratic equation whose coefficients are scaled depending on the size and configuration of the arterial cannula. The model and prediction method were tested experimentally on a test loop supported by the TandemHeart pVAD (Cardiacassist, Inc., Pittsburgh, PA). A comparison of the predicted flow rates obtained from our method with experimental data shows that our method can predict the flow rates accurately with error indices less than 6% for all test conditions over the entire range of intended use of the device. Computer simulations of the pVAD model coupled to a cardiovascular model showed that the accuracy- of the method in estimating the mean flow rate is consistent over the normal range of operation of the device regardless of the pulsatility introduced by the cardiovascular system. This method can be used as an additional too to assist cardiologists in choosing a proper arterial cannulae configurations and sizes for pVAD patients. It can also be used as a tool to train clinical personnel to operate the device under different physiological conditions.