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Background: The role played by large-scale repetitive SARS-CoV-2 screening programs within university populations interacting continuously with an urban environment, is unknown. Our objective was to develop a model capable of predicting the dispersion of viral contamination among university populations dividing their time between social and academic environments., Methods: Data was collected through real, large-scale testing developed at the University of Liège, Belgium, during the period Sept. 28th-Oct. 29th 2020. The screening, offered to students and staff (n = 30,000), began 2 weeks after the re-opening of the campus but had to be halted after 5 weeks due to an imposed general lockdown. The data was then used to feed a two-population model (University + surrounding environment) implementing a generalized susceptible-exposed-infected-removed compartmental modeling framework., Results: The considered two-population model was sufficiently versatile to capture the known dynamics of the pandemic. The reproduction number was estimated to be significantly larger on campus than in the urban population, with a net difference of 0.5 in the most severe conditions. The low adhesion rate for screening (22.6% on average) and the large reproduction number meant the pandemic could not be contained. However, the weekly screening could have prevented 1393 cases (i.e. 4.6% of the university population; 95% CI: 4.4-4.8%) compared to a modeled situation without testing., Conclusion: In a real life setting in a University campus, periodic screening could contribute to limiting the SARS-CoV-2 pandemic cycle but is highly dependent on its environment., (© 2022. The Author(s).)

Background: Peak first derivative of femoral artery pressure (arterial dP/dtmax) derived from fluid-filled catheter remains questionable to assess left ventricular (LV) contractility during shock. The aim of this study was to test if arterial dP/dtmax is reliable for assessing LV contractility during various hemodynamic conditions such as endotoxin-induced shock and catecholamine infusion., Methods: Ventricular pressure-volume data obtained with a conductance catheter and invasive arterial pressure obtained with a fluid-filled catheter were continuously recorded in 6 anaesthetized and mechanically ventilated pigs. After a stabilization period, endotoxin was infused to induce shock. Catecholamines were transiently administrated during shock. Arterial dP/dtmax was compared to end-systolic elastance (Ees), the gold standard method for assessing LV contractility., Results: Endotoxin-induced shock and catecholamine infusion lead to significant variations in LV contractility. Overall, significant correlation (r=0.51; p<0.001) but low agreement between the two methods were observed. However, a far better correlation with a good agreement were observed when positive-pressure ventilation induced an arterial pulse pressure variation (PPV)≤11% (r=0.77; p<0.001)., Conclusion: While arterial dP/dtmax and Ees were significantly correlated during various hemodynamic conditions, arterial dP/dtmax was more accurate for assessing LV contractility when adequate vascular filling, defined as PPV≤11%, was achieved.

Background: Valve dysfunction is a common cardiovascular pathology. Despite significant clinical research, there is little formal study of how valve dysfunction affects overall circulatory dynamics. Validated models would offer the ability to better understand these dynamics and thus optimize diagnosis, as well as surgical and other interventions., Methods: A cardiovascular and circulatory system (CVS) model has already been validated in silico, and in several animal model studies. It accounts for valve dynamics using Heaviside functions to simulate a physiologically accurate "open on pressure, close on flow" law. However, it does not consider real-time valve opening dynamics and therefore does not fully capture valve dysfunction, particularly where the dysfunction involves partial closure. This research describes an updated version of this previous closed-loop CVS model that includes the progressive opening of the mitral valve, and is defined over the full cardiac cycle., Results: Simulations of the cardiovascular system with healthy mitral valve are performed, and, the global hemodynamic behaviour is studied compared with previously validated results. The error between resulting pressure-volume (PV) loops of already validated CVS model and the new CVS model that includes the progressive opening of the mitral valve is assessed and remains within typical measurement error and variability. Simulations of ischemic mitral insufficiency are also performed. Pressure-Volume loops, transmitral flow evolution and mitral valve aperture area evolution follow reported measurements in shape, amplitude and trends., Conclusions: The resulting cardiovascular system model including mitral valve dynamics provides a foundation for clinical validation and the study of valvular dysfunction in vivo. The overall models and results could readily be generalised to other cardiac valves.