As a left ventricular assist device is designed to pump against the systemic vascular resistance (SVR), pulmonary congestion may occur when using such device for right ventricular support. The present study evaluates the efficacy of using a fixed right outflow banding in patients receiving biventricular assist device support under various circulatory conditions, including variations in the SVR, pulmonary vascular resistance (PVR), total blood volume (BV), as well as ventricular contractility. Effect of speed variation on the hemodynamics was also evaluated at varying degrees of PVR. Pulmonary congestion was observed at high SVR and BV. A reduction in right ventricular assist device (RVAD) speed was required to restore pulmonary pressures. Meanwhile, at a high PVR, the risk of ventricular suction was prevalent during systemic hypotension due to low SVR and BV. This could be compensated by increasing RVAD speed. Isolated right heart recovery may aggravate pulmonary congestion, as the failing left ventricle cannot accommodate the resultant increase in the right-sided flow. Compared to partial assistance, the sensitivity of the hemodynamics to changes in VAD speed increased during full assistance. In conclusion, our results demonstrated that the introduction of a banding graft with a 5 mm diameter guaranteed sufficient reserve of the pump speed spectrum for the regulation of acceptable hemodynamics over different clinical scenarios, except under critical conditions where drug administration or volume management is required.
Fatigue assessment of the trabecular bone has been developed to give a better understanding of bone properties. While most fatigue studies are relying on uniaxial compressive load as the method of assessment, in various cases details are missing, or the uniaxial results are not very realistic. In this paper, the effect of three different load histories from physiological loading applied on the trabecular bone were studied in order to predict the first failure surface and the fatigue lifetime. The fatigue behaviour of the trabecular bone under uniaxial load was compared to that of multiaxial load using a finite element simulation. The plastic strain was found localized at the trabecular structure under multiaxial load. On average, applying multiaxial loads reduced more than five times the fatigue life of the trabecular bone. The results provide evidence that multiaxial loading is dominated in the low cycle fatigue in contrast to the uniaxial one. Both bone volume fraction and structural model index were best predictors of failure (p
We examine the low-frequency limit of hearing of the mammalian ear through the analytical modelling of the natural frequency of the tympanic membrane. The resulting equation of the natural frequency of the modelled tympanic membrane is numerically verified against previous theoretical studies, and is statistically validated against the experimental data on the low-frequency limit of hearing. By utilizing the Wilcoxon signed-rank test; W-values of 29 (p value = 0.25014) and 23 (p value = 0.11642) are respectively obtained for the 0.2% and 0.3% prestrain (at 5% significance level for sample size of 13). We fail to reject the null hypothesis as the W-values are within the critical values of the test statistics, and therefore conclude that the tympanic membrane acts as a low-frequency limiter of acoustic stimulus. Based on our study, we can predict the low-frequency limit of hearing in mammals (e.g., for the whale as 3.6 Hz and for the zebra as 44.0 Hz).
As drilling generates substantial bone thermomechanical damage due to inappropriate cutting tool selection, researchers have proposed various approaches to mitigate this problem. Among these, improving the drill bit design is one of the most feasible and economical solutions. The theory and applications in drill design have been progressing, and research has been published in various fields. However, pieces of information on drill design are dispersed, and no comprehensive review paper focusing on this topic. Systemizing this information is crucial and, therefore, the impetus of this review. Here, we review not only the state-of-the-art in drill bit designs-advances in surgical drill bit design-but also the influences of each drill bit geometries on bone damage. Also, this work provides future directions for this topic and guidelines for designing an improved surgical drill bit. The information in this paper would be useful as a one-stop document for clinicians, engineers, and researchers who require information related to the tool design in bone drilling surgery.
The successful clinical applicability of rotary left ventricular assist devices (LVADs) has led to research interest in devising a total artificial heart (TAH) using two rotary blood pumps (RBPs). The major challenge when using two separately controlled LVADs for TAH support is the difficulty in maintaining the balance between pulmonary and systemic blood flows. In this study, a starling-like controller (SLC) hybridized with an adaptive mechanism was developed for a dual rotary LVAD TAH. The incorporation of the adaptive mechanism was intended not only to minimize the risk of pulmonary congestion and atrial suction but also to match cardiac demand. A comparative assessment was performed between the proposed adaptive starling-like controller (A-SLC) and a conventional SLC as well as a constant speed controller. The performance of all controllers was evaluated by subjecting them to three simulated scenarios [rest, exercise, head up tilt (HUT)] using a mock circulation loop. The overall results showed that A-SLC was superior in matching pump flow to cardiac demand without causing hemodynamic instabilities. In contrast, improper flow regulation by the SLC resulted in pulmonary congestion during exercise. From resting supine to HUT, overpumping of the RBPs at fixed speed (FS) caused atrial suction, whereas implementation of SLC resulted in insufficient flow. The comparative study signified the potential of the proposed A-SLC for future TAH implementation particularly among outpatients, who are susceptible to variety of clinical scenarios.
While lung protective mechanical ventilation (MV) guidelines have been developed to avoid ventilator-induced lung injury (VILI), a one-size-fits-all approach cannot benefit every individual patient. Hence, there is significant need for the ability to provide patient-specific MV settings to ensure safety, and optimise patient care. Model-based approaches enable patient-specific care by identifying time-varying patient-specific parameters, such as respiratory elastance, Ers, to capture inter- and intra-patient variability. However, patient-specific parameters evolve with time, as a function of disease progression and patient condition, making predicting their future values crucial for recommending patient-specific MV settings. This study employs stochastic modelling to predict future Ers values using retrospective patient data to develop and validate a model indicating future intra-patient variability of Ers. Cross validation results show stochastic modelling can predict future elastance ranges with 92.59 and 68.56% of predicted values within the 5-95% and the 25-75% range, respectively. This range can be used to ensure patients receive adequate minute ventilation should elastance rise and minimise the risk of VILI should elastance fall. The results show the potential for model-based protocols using stochastic model prediction of future Ers values to provide safe and patient-specific MV. These results warrant further investigation to validate its clinical utility.
At the fascinating intersection of artificial intelligence and medicine, ChatGPT morphs into a compact, personal digital physician. With a simple click, it furnishes an abundance of health-related information, initial medical consultations, and a plethora of disease management recommendations. Moreover, it stands at the ready to provide immediate mental health assistance in times of psychological distress. Yet, each innovation carries inherent challenges. As we embrace the conveniences proffered by ChatGPT, it is imperative that we grapple with associated issues such as data privacy, risk of misdiagnosis, complexities in human-machine interaction, and particular situations that elude its understanding. Let's probe further into this intriguing world, brimming with contention and prospects, and observe how ChatGPT traverses the landscape of digital health, uncovering the potential it holds for the future evolution of medical practice.
Additive Manufacturing is noted for ease of product customization and short production run cost-effectiveness. As our global population approaches 8 billion, additive manufacturing has a future in maintaining and improving average human life expectancy for the same reasons that it has advantaged general manufacturing. In recent years, additive manufacturing has been applied to tissue engineering, regenerative medicine, and drug delivery. Additive Manufacturing combined with tissue engineering and biocompatibility studies offers future opportunities for various complex cardiovascular implants and surgeries. This paper is a comprehensive overview of current technological advancements in additive manufacturing with potential for cardiovascular application. The current limitations and prospects of the technology for cardiovascular applications are explored and evaluated.
ChatGPT, an advanced language generation model developed by OpenAI, has the potential to revolutionize healthcare delivery and support for individuals with various conditions, including Down syndrome. This article explores the applications of ChatGPT in assisting children with Down syndrome, highlighting the benefits it can bring to their education, social interaction, and overall well-being. While acknowledging the challenges and limitations, we examine how ChatGPT can be utilized as a valuable tool in enhancing the lives of these children, promoting their cognitive development, and supporting their unique needs.