Independent Associations of Aortic Calcification with Cirrhosis and Liver Related Mortality in Veterans with Chronic Liver Disease.

INTRODUCTION: Abdominal aortic calcifications (AAC) are incidentally found on medical imaging and useful cardiovascular burden approximations. The Morphomic Aortic Calcification Score (MAC) leverages automated deep learning methods to quantify and score AACs. While associations of AAC and non-alcoholic fatty liver disease (NAFLD) have been described, relationships of AAC with other liver diseases and clinical outcome are sparse. This study's purpose was to evaluate AAC and liver-related death in a cohort of Veterans with chronic liver disease (CLD). METHODS: We utilized the VISN 10 CLD cohort, a regional cohort of Veterans with the three forms of CLD: NAFLD, hepatitis C (HCV), alcohol-associated (ETOH), seen between 2008 and 2014, with abdominal CT scans (n = 3604). Associations between MAC and cirrhosis development, liver decompensation, liver-related death, and overall death were evaluated with Cox proportional hazard models. RESULTS: The full cohort demonstrated strong associations of MAC and cirrhosis after adjustment: HR 2.13 (95% CI 1.63, 2.78), decompensation HR 2.19 (95% CI 1.60, 3.02), liver-related death HR 2.13 (95% CI 1.46, 3.11), and overall death HR 1.47 (95% CI 1.27, 1.71). These associations seemed to be driven by the non-NAFLD groups for decompensation and liver-related death [HR 2.80 (95% CI 1.52, 5.17; HR 2.34 (95% CI 1.14, 4.83), respectively]. DISCUSSION: MAC was strongly and independently associated with cirrhosis, liver decompensation, liver-related death, and overall death. Surprisingly, stratification results demonstrated comparable or stronger associations among those with non-NAFLD etiology. These findings suggest abdominal aortic calcification may predict liver disease severity and clinical outcomes in patients with CLD.

Incorporation of quantitative imaging data using artificial intelligence improves risk prediction in veterans with liver disease.

BACKGROUND AND AIMS: Utilization of electronic health records data to derive predictive indexes such as the electronic Child-Turcotte-Pugh (eCTP) Score can have significant utility in health care delivery. Within the records, CT scans contain phenotypic data which have significant prognostic value. However, data extractions have not traditionally been applied to imaging data. In this study, we used artificial intelligence to automate biomarker extraction from CT scans and examined the value of these features in improving risk prediction in patients with liver disease. APPROACH AND RESULTS: Using a regional liver disease cohort from the Veterans Health System, we retrieved administrative, laboratory, and clinical data for Veterans who had CT scans performed for any clinical indication between 2008 and 2014. Imaging biomarkers were automatically derived using the analytic morphomics platform. In all, 4614 patients were included. We found that the eCTP Score had a Concordance index of 0.64 for the prediction of overall mortality while the imaging-based model alone or with eCTP Score performed significantly better [Concordance index of 0.72 and 0.73 ( p <0.001)]. For the subset of patients without hepatic decompensation at baseline (n=4452), the Concordance index for predicting future decompensation was 0.67, 0.79, and 0.80 for eCTP Score, imaging alone, or combined, respectively. CONCLUSIONS: This proof of concept demonstrates that the potential of utilizing automated extraction of imaging features within CT scans either alone or in conjunction with classic health data can improve risk prediction in patients with chronic liver disease.

Self-administered acupressure for veterans with chronic back pain: Study design and methodology of a type 1 hybrid effectiveness implementation randomized controlled trial.

BACKGROUND: Chronic low back pain is prevalent and disabling in Veterans, but effective pain management is challenging. Clinical practice guidelines emphasize multimodal pain management including evidence-based complementary and integrative health treatments such as acupressure as a first line of care. Unfortunately, the ability to replicate interventions, cost, resources, and limited access are implementation barriers. Self-administered acupressure has shown positive effects on pain and can be practiced anywhere with little to no side effects. METHODS/DESIGN: The aims of this Type 1 hybrid effectiveness implementation randomized controlled trial are 1) to determine effectiveness of a self-administered acupressure protocol at improving pain interference and secondary outcomes of fatigue, sleep quality, and disability in 300 Veterans with chronic low back pain, and 2) evaluate implementation barriers and facilitators to scale-up acupressure utilization within Veterans Health Administration (VHA). Participants randomized to the intervention will receive instruction on acupressure application using an app that facilitates daily practice for 6 weeks. During weeks 6 through 10, participants will discontinue acupressure to determine sustainability of effects. Participants randomized to waitlist control will continue their usual care for pain management and receive study materials at the end of the study period. Outcomes will be collected at baseline and at 6- and 10-weeks post baseline. The primary outcome is pain interference, measured by the PROMIS pain interference scale. Using established frameworks and a mixed methods approach, we will evaluate intervention implementation. DISCUSSION: If acupressure is effective, we will tailor strategies to support implementation in the VHA based on study findings. TRIAL REGISTRATION NUMBER: NCT05423145.

Properties of laser-produced GaAs plasmas measured from highly resolved X-ray line shapes and ratios.

The properties of hot, dense plasmas generated by the irradiation of GaAs targets by the Titan laser at Lawrence Livermore National Laboratory were determined by the analysis of high resolution K shell spectra in the 9 keV to 11 keV range. The laser parameters, such as relatively long pulse duration and large focal spot, were chosen to produce a steady-state plasma with minimal edge gradients, and the time-integrated spectra were compared to non-LTE steady state spectrum simulations using the FLYCHK and NOMAD codes. The bulk plasma streaming velocity was measured from the energy shifts of the Ga He-like transitions and Li-like dielectronic satellites. The electron density and the electron energy distribution, both the thermal and the hot non-thermal components, were determined from the spectral line ratios. After accounting for the spectral line broadening contributions, the plasma turbulent motion was measured from the residual line widths. The ionization balance was determined from the ratios of the He-like through F-like spectral features. The detailed comparison of the experimental Ga spectrum and the spectrum simulated by the FLYCHK code indicates two significant discrepancies, the transition energy of a Li-like dielectronic satellite (designated t) and the calculated intensity of a He-like line (x), that should lead to improvements in the kinetics codes used to simulate the X-ray spectra from highly-charged ions.

Demonstration of imaging X-ray Thomson scattering on OMEGA EP.

Foams are a common material for high-energy-density physics experiments because of low, tunable densities, and being machinable. Simulating these experiments can be difficult because the equation of state is largely unknown for shocked foams. The focus of this experiment was to develop an x-ray scattering platform for measuring the equation of state of shocked foams on OMEGA EP. The foam used in this experiment is resorcinol formaldehyde with an initial density of 0.34 g/cm3. One long-pulse (10 ns) beam drives a shock into the foam, while the remaining three UV beams with a 2 ns square pulse irradiate a nickel foil to create the x-ray backlighter. The primary diagnostic for this platform, the imaging x-ray Thomson spectrometer, spectrally resolves the scattered x-ray beam while imaging in one spatial dimension. Ray tracing analysis of the density profile gives a compression of 3 ± 1 with a shock speed of 39 ± 6 km/s. Analysis of the scattered x-ray spectra gives an upper bound temperature of 20 eV.