Citations

Percutaneous ventricular assist devices (pVAD) decrease mortality in cardiogenic shock (CS) patients, but at a high adverse event rate. Novel pVADs need to improve cardiac power output (CPO) to improve efficacy and reduce profile to reduce adverse events. Venstramedical has developed an impeller with nitinol and polymer which can collapse for low-profile insertion and expand in the body to provide optimal CPO. We have also developed a unique 9 French (9Fr) delivery system. In vitro and in vivo testing have been performed to develop this device. Head-flow (HQ) tests generate 5.0 L/min with a pressure differential of 80 mm Hg and 7.0 L/min against 60 mm Hg. Durability testing demonstrated continuous operation of up to 20 days. In the acute healthy ovine model, we demonstrated full flow (7–9 L against 60–80 mm Hg), transcatheter 9Fr delivery, retrieval of the device, and resting of the native heart during pumping. In a CS animal, we demonstrated survival and resting of the native heart during the acute study with decreased stroke work (SW), decreased stroke volume (SV), while total cardiac output was up to 7 L/min and maintaining adequate pressure with low hemolysis. We also demonstrated multiday functioning of the device in a healthy ovine model with good CO and low hemolysis.

ABSTRACT Light chain multiple myeloma (LCMM) is a subtype of multiple myeloma (MM) characterized by the exclusive production of immunoglobulin light chains and accounts for 15%–20% of newly diagnosed MM. A comprehensive comparison of LCMM with MM producing intact immunoglobulin (non‐LCMM) remains limited. In this retrospective study, we described distinct clinical and cytogenetic features and assessed long‐term outcomes in 852 LCMM patients diagnosed between 01/01/2004 and 12/31/2022, compared with non‐LCMM controls matched for age, sex, and year of diagnosis. On univariable analysis, LCMM patients were more likely to present with elevated creatinine (> 2 mg/dL), beta‐2‐microglobulin ≥ 5.5 mg/L, elevated LDH, hypercalcemia, t(11;14), del(13q), and t(6;14). Conversely, IMS‐IMWG high‐risk disease, hyperdiploidy, t(4;14), and serum albumin < 3.5 g/dL were less common. On multivariable analysis, elevated creatinine (OR: 5.1, 95% CI: 1.2–27, p = 0.04), t(11;14) (OR: 2.6, 95% CI: 1.3–5.2, p = 0.006), and del(13q) (OR: 4.1, 95% CI: 2.1–8.2, p < 0.001) were independently associated with LCMM, while IMS‐IMWG high‐risk disease (OR: 0.3, 95% CI: 0.1–0.8, p = 0.02) and hyperdiploidy (OR: 0.3, 95% CI: 0.1–0.7, p = 0.002) were less frequent. Despite these differences, progression‐free survival with frontline treatment (HR: 0.97, 95% CI: 0.84–1.11, p = 0.63) and overall survival (HR: 0.99, 95% CI: 0.87–1.13, p = 0.94) were similar between LCMM and non‐LCMM patients. This study highlights the distinct clinical and cytogenetic features of LCMM, marked by higher rates of renal failure, t(11;14), and del(13q), lower prevalence of IMS‐IMWG high‐risk disease, and comparable survival outcomes.

Abstract Medical imaging is undergoing a transformation driven by the advent of new, highly effective, machine learning techniques paired with increases in computational capabilities (Cheng et al. 2021; Gilson et al. 2023; Almeida et al. 2024; Krishna et al. 2024). These advanced algorithms have the potential to improve disease detection, diagnosis, prognosis, and treatment outcomes. However, the complexity of machine learning models, the large amounts of curated and annotated data required by some methods, and the potential for bias and error make it challenging for individuals to safely and effectively leverage these methods (Lin et al. 2024; Guo et al. 2024; Xu et al. 2024; Linguraru et al. 2024; Wood et al. 2019). To address these challenges, the American Association of Physicists in Medicine (AAPM), American College of Radiology (ACR), Radiological Society of North America (RSNA), and Society for Imaging Informatics in Medicine (SIIM) have worked together to develop a syllabus detailing a recommended set of competencies for medical imaging professionals interacting with these systems. This guide is aimed at four different personas: users of AI systems, purchasers of AI systems, individuals who provide clinical expertise during the development of AI systems (“clinical collaborators”), and developers of AI systems.1 This is a syllabus, not a curriculum, and is intentional in this scope. Recognizing that individuals may benefit from different presentations of the same material, this work enumerates a series of relevant competencies but does not prescribe, nor offer, a method of instruction (Schuur, Rezazade Mehrizi, and Ranschaert 2021; Garin et al. 2023). By addressing the task‐specific demands of each role, this guide will enable medical imaging professionals to utilize machine learning systems more safely and effectively, ultimately improving patient care and outcomes.

Background: Lyme disease is the most common vector-borne disease in United States children. It was traditionally thought to be limited to the Northeast and upper Midwest due to the prevalence of tick and deer vectors in these regions. We hypothesize that as Lyme disease cases in children continue to increase throughout the country, nontraditional regions such as the Midwest and South may have an increased rate of Lyme disease compared with the Northeast region. Methods: The Pediatric Health Information System (PHIS) database was queried for patients 19.0 years or younger who were treated for Lyme disease between 2004 and 2019 through Emergency Department and in-patient records using ICD coding. Data from 49 pediatric hospitals was included and the centers were split into 4 regions based on geographic location. The data was separated into 2 time periods: 2004 to 2014 and 2015 to 2019. Slopes were compared using a general linear model with interaction to determine if annual rates of Lyme disease were statistically different between the 2 time periods. The data was then split by geographic region and again the annual rate of Lyme disease was compared between the 4 regions. A P -value <0.008 was considered significant to adjust for multiple comparisons. Results: Between 2004 and 2019, 7,572 cases of Lyme disease were reported with a mean age of 9.5 years (range: 0.08 to 19.00 y) and 58% male. From 2004 to 2019, there was an annual increase of 46.5 cases. When separated by region from 2004 to 2019, the Midwest had a higher increased annual rate of Lyme disease (30.7 additional cases/year) compared with the Northeast (10.0 additional cases/y), the South (3.6 additional cases/y), and the West (2.2 additional cases/y). Conclusions: Lyme disease continues to show an increased rate across the United States. The annual increase in cases in the Midwest was significantly higher than the other regions from 2004 to 2019. There does appear to be a significant regional spread, particularly in the Midwest. Awareness of the increased rate and spread of Lyme disease across the US is crucial in helping to identify national and regional strategies to diagnose and treat this disease in children. Level of Evidence: Level IV.