Pulsatile Pressure Delivery of Continuous-Flow Left Ventricular Assist Devices Is Markedly Reduced Relative to Heart Failure Patients.

Although continuous-flow left ventricular assist devices (CF-LVADs) provide an augmentation in systemic perfusion, there is a scarcity of in vivo data regarding systemic pulsatility on support. Patients supported on CF-LVAD therapy (n = 71) who underwent combined left/right catheterization ramp study were included. Aortic pulsatility was defined by the pulsatile power index (PPI), which was also calculated in a cohort of high-output heart failure (HOHF, n = 66) and standard HF cohort (n = 44). PPI was drastically lower in CF-LVAD-supported patients with median PPI of 0.006 (interquartile range [IQR], 0.002-0.012) compared with PPI in the HF population at 0.09 (IQR, 0.06-0.17) or HOHF population at 0.25 (IQR, 0.13-0.37; p < 0.0001 among groups). With speed augmentation during ramp, PPI values fell quickly in patients with higher PPI at baseline. PPI correlated poorly with left ventricular ejection fraction (LVEF) in all groups. In CF-LVAD patients, there was a stronger correlation with LV dP/dt (r = 0.41; p = 0.001) than LVEF (r = 0.21; p = 0.08; pint < 0.001). CF-LVAD support is associated with a dramatic reduction in arterial pulsatility as measured by PPI relative to HOHF and HF cohorts and decreases with speed. Further work is needed to determine the applicability to the next generation of device therapy.

Evidence-based aerosol clearance times in a healthcare environment.

BACKGROUND: As researchers race to understand the nature of COVID-19 transmission, healthcare institutions must treat COVID-19 patients while also safeguarding the health of staff and other patients. One aspect of this process involves mitigating aerosol transmission of the SARS-CoV2 virus. The U.S. Centers for Disease Control and Prevention (CDC) provides general guidance on airborne contaminant removal, but directly measuring aerosol clearance in clinical rooms provides empirical evidence to guide clinical procedure. AIM: We present a risk-assessment approach to empirically measuring and certifying the aerosol clearance time (ACT) in operating and procedure rooms to improve hospital efficiency while also mitigating the risk of nosocomial infection. METHODS: Rooms were clustered based on physical and procedural parameters. Sample rooms from each cluster were randomly selected and tested by challenging the room with aerosol and monitoring aerosolized particle concentration until 99.9% clearance was achieved. Data quality was analysed and aerosol clearance times for each cluster were determined. FINDINGS: Of the 521 operating and procedure rooms considered, 449 (86%) were issued a decrease in clearance time relative to CDC guidance, 32 (6%) had their clearance times increased, and 40 (8%) remained at guidance. The average clearance time change of all rooms assessed was a net reduction of 27.8%. CONCLUSION: The process described here balances the need for high-quality, repeatable data with the burden of testing in a functioning clinical setting. Implementation of this approach resulted in a reduction in clearance times for most clinical rooms, thereby improving hospital efficiency while also safeguarding patients and staff.

Factors associated with proximal femur fracture determined in a large cadaveric cohort.

Many researchers have used cadaveric fracture tests to determine the relationship between proximal femur (hip) fracture strength and a multitude of possible explanatory variables, typically considered one or two at a time. These variables include subject-specific proximal femur variables such as femoral neck areal bone mineral density (aBMD), sex, age, and geometry, as well as physiological hip fracture event variables such as fall speed and angle of impact. However, to our knowledge, no study has included all of these variables simultaneously in the same experimental dataset. To address this gap, the present study simultaneously included all of these subject-specific and fracture event variables in multivariate models to understand their contributions to femoral strength and fracture type. The primary aim of this study was to determine not only whether each of these variables contributed to the prediction of femoral strength, but also to determine the relative importance of each variable in strength prediction. A secondary aim was to similarly characterize the importance of these variables for the prediction of fracture type. To accomplish these aims, we characterized 197 proximal femurs (covering a wide range of subject-specific variables) with DXA and CT scans, and then tested the femurs to fracture in a sideways fall on the hip configuration. Each femur was tested using one of three fall speed conditions and one of four angles of impact (bone orientations). During each test, we acquired measurements of relevant force and displacement data. We then reduced the test data to determine femoral strength, and we used post-fracture CT scans to classify the fracture type (e.g., trochanteric, cervical). Using these results, the explanatory variables were analyzed with mixed statistical models to explain variations in hip fracture strength and fracture type, respectively. Five explanatory variables were statistically significant in explaining the variability in femoral strength: aBMD, sex, age, fall speed, and neck-shaft angle (P ≤ 0.0135). These five variables, including significant interactions, explained 80% of the variability in hip fracture strength. Additionally, when only aBMD, sex, and age (P < 0.0001) were considered in the model, again including significant interactions, these three variables alone explained 79% of the variability in hip fracture strength. So while fall speed (P = 0.0135) and neck-shaft angle (P = 0.0041) were statistically significant, the inclusion of these variables did not appreciably improve the prediction of hip fracture strength compared to the model that considered only aBMD, sex and age. For the variables we included in this study, in the ranges we considered, our findings indicate that the clinically-available information of patient age, sex and aBMD are sufficient for femoral strength assessment. These findings also suggest that there is little value in the extra effort required to characterize the effect of femoral geometry on strength, or to account for the probabilistic nature of fall-related factors such as fall speed and angle of impact. For fracture type, the only explanatory variable found to be significant was aBMD (P ≤ 0.0099). We found that the odds of having intertrochanteric fractures increased by 47% when aBMD decreased by one standard deviation (0.2 g/cm2).

Intra-aneurysmal flow rates are reduced by two flow diverters: an experiment using tomographic particle image velocimetry in an aneurysm model.

BACKGROUND: Limitations on treating large, giant, and wide-necked aneurysms with coiling have made flow diverters a promising alternative to current practice by supporting reconstruction of the parent artery. OBJECTIVE: To assess the changes to fluid dynamics within an aneurysm by studying two different endoluminal flow diverters on a simple aneurysm model, using tomographic particle image velocimetry to determine which device would better minimize fluid flow into an aneurysm and observe any significant changes in aneurysm fluid structures. METHODS: Steady velocity fields of the model's aneurysm dome and neck were measured at three inlet velocities (18, 39, and 59 cm/s) for two flow diverter diameters with different porosities and compared against a baseline case with no flow diverter. RESULTS: In the baseline case a large vortex was present inside the dome for all flow rates. However, both devices eliminated this main vortex at all flow rates and reduced the peak aneurysmal velocities by about 90%. A strong correlation between flow diverter porosity and flow reduction was found. In each case the inflow to the aneurysm shifted from the distal neck to the mid- or proximal neck after flow diverter placement. CONCLUSIONS: Even with this relatively simple experimental setup, we were able to observe the major flow field changes, which occurred immediately after the deployment of each flow diverter. Limitations of the study included a simplified geometry and steady-state flow. Constraints included model making and limited availability of flow diverters.