Patient sequentially receives a left ventricular assist device and a porcine kidney transplant.

As a second porcine kidney xenotransplant case in a human recipient to date, this breakthrough technology offers an option even to patients with complex multiorgan failures, who may not be candidates for a conventional organ transplant.

Classification of Documented Goals of Care Among Hospitalized Patients with High Mortality Risk: a Mixed-Methods Feasibility Study.

BACKGROUND: The ability to classify patients' goals of care (GOC) from clinical documentation would facilitate serious illness communication quality improvement efforts and pragmatic measurement of goal-concordant care. Feasibility of this approach remains unknown. OBJECTIVE: To evaluate the feasibility of classifying patients' GOC from clinical documentation in the electronic health record (EHR), describe the frequency and patterns of changes in patients' goals over time, and identify barriers to reliable goal classification. DESIGN: Retrospective, mixed-methods chart review study. PARTICIPANTS: Adults with high (50-74%) and very high (≥ 75%) 6-month mortality risk admitted to three urban hospitals. MAIN MEASURES: Two physician coders independently reviewed EHR notes from 6 months before through 6 months after admission to identify documented GOC discussions and classify GOC. GOC were classified into one of four prespecified categories: (1) comfort-focused, (2) maintain or improve function, (3) life extension, or (4) unclear. Coder interrater reliability was assessed using kappa statistics. Barriers to classifying GOC were assessed using qualitative content analysis. KEY RESULTS: Among 85 of 109 (78%) patients, 338 GOC discussions were documented. Inter-rater reliability was substantial (75% interrater agreement; Cohen's kappa = 0.67; 95% CI, 0.60-0.73). Patients' initial documented goal was most frequently "life extension" (N = 37, 44%), followed by "maintain or improve function" (N = 28, 33%), "unclear" (N = 17, 20%), and "comfort-focused" (N = 3, 4%). Among the 66 patients whose goals' classification changed over time, most changed to "comfort-focused" goals (N = 49, 74%). Primary reasons for unclear goals were the observation of concurrently held or conditional goals, patient and family uncertainty, and limited documentation. CONCLUSIONS: Clinical notes in the EHR can be used to reliably classify patients' GOC into discrete, clinically germane categories. This work motivates future research to use natural language models to promote scalability of the approach in clinical care and serious illness research.

How to edit a surgical case video.

A video can help highlight the real-time steps, anatomy and the technical aspects of a case that may be difficult to convey with text or static images alone. Editing with a regimented workflow allows for the transmission of only essential information to the viewer while maximizing efficiency by going through the editing process. This video tutorial breaks down the fundamentals of surgical video editing with tips and pointers to simplify the workflow.

Heart Transplantation for Uhl Anomaly in an Adult.

Uhl anomaly is characterized by the morphologic absence of right ventricular myocardium and is an exceedingly rare cause of nonischemic cardiomyopathy. We report the first case of a successful heart transplantation in a 41-year-old patient who presented in cardiogenic shock from Uhl anomaly causing decompensated right ventricular failure.

Researchers propose ice 3D printing as a method to create internal channels in artificial organs.

By freezing water droplets into smooth, even columns, researchers from Carnegie Mellon University created complex internal channels that may eventually render viable complex artificial tissue.

Engineers use a porcine heart scaffold to create a bio-robotic model of the right ventricle.

The simulator can provide a dynamic and sophisticated platform to further aid in the study of the right heart in an era where numerous technologies are rapidly emerging in this space.

Can Artificial Intelligence Improve the Readability of Patient Education Materials on Aortic Stenosis? A Pilot Study.

INTRODUCTION: The advent of generative artificial intelligence (AI) dialogue platforms and large language models (LLMs) may help facilitate ongoing efforts to improve health literacy. Additionally, recent studies have highlighted inadequate health literacy among patients with cardiac disease. The aim of the present study was to ascertain whether two freely available generative AI dialogue platforms could rewrite online aortic stenosis (AS) patient education materials (PEMs) to meet recommended reading skill levels for the public. METHODS: Online PEMs were gathered from a professional cardiothoracic surgical society and academic institutions in the USA. PEMs were then inputted into two AI-powered LLMs, ChatGPT-3.5 and Bard, with the prompt "translate to 5th-grade reading level". Readability of PEMs before and after AI conversion was measured using the validated Flesch Reading Ease (FRE), Flesch-Kincaid Grade Level (FKGL), Simple Measure of Gobbledygook Index (SMOGI), and Gunning-Fog Index (GFI) scores. RESULTS: Overall, 21 PEMs on AS were gathered. Original readability measures indicated difficult readability at the 10th-12th grade reading level. ChatGPT-3.5 successfully improved readability across all four measures (p < 0.001) to the approximately 6th-7th grade reading level. Bard successfully improved readability across all measures (p < 0.001) except for SMOGI (p = 0.729) to the approximately 8th-9th grade level. Neither platform generated PEMs written below the recommended 6th-grade reading level. ChatGPT-3.5 demonstrated significantly more favorable post-conversion readability scores, percentage change in readability scores, and conversion time compared to Bard (all p < 0.001). CONCLUSION: AI dialogue platforms can enhance the readability of PEMs for patients with AS but may not fully meet recommended reading skill levels, highlighting potential tools to help strengthen cardiac health literacy in the future.

An early artificial implantable kidney prototype demonstrates short-term viability in a porcine model without immunosuppression.

Dialysis remains an imperfect treatment for over two million patients with renal failure worldwide. This bioreactor may lead to the completely implantable, continuous filtration system they need.

"Choose Your Own Threat"-A Modern Paradigm for Academic Surgery.

This Viewpoint discusses a potential shift from academic surgery's triple-threat paradigm (provide high-quality clinical care, perform primary research, and train residents and students) to defining success in ways that allow individual surgeons to focus on their own path based on intrinsic motivation and curiosity.

D2H2: diabetes data and hypothesis hub.

Motivation: There is a rapid growth in the production of omics datasets collected by the diabetes research community. However, such published data are underutilized for knowledge discovery. To make bioinformatics tools and published omics datasets from the diabetes field more accessible to biomedical researchers, we developed the Diabetes Data and Hypothesis Hub (D2H2). Results: D2H2 contains hundreds of high-quality curated transcriptomics datasets relevant to diabetes, accessible via a user-friendly web-based portal. The collected and processed datasets are curated from the Gene Expression Omnibus (GEO). Each curated study has a dedicated page that provides data visualization, differential gene expression analysis, and single-gene queries. To enable the investigation of these curated datasets and to provide easy access to bioinformatics tools that serve gene and gene set-related knowledge, we developed the D2H2 chatbot. Utilizing GPT, we prompt users to enter free text about their data analysis needs. Parsing the user prompt, together with specifying information about all D2H2 available tools and workflows, we answer user queries by invoking the most relevant tools via the tools' API. D2H2 also has a hypotheses generation module where gene sets are randomly selected from the bulk RNA-seq precomputed signatures. We then find highly overlapping gene sets extracted from publications listed in PubMed Central with abstract dissimilarity. With the help of GPT, we speculate about a possible explanation of the high overlap between the gene sets. Overall, D2H2 is a platform that provides a suite of bioinformatics tools and curated transcriptomics datasets for hypothesis generation. Availability and implementation: D2H2 is available at: https://d2h2.maayanlab.cloud/ and the source code is available from GitHub at https://github.com/MaayanLab/D2H2-site under the CC BY-NC 4.0 license.

Researchers successfully engineer endovascular probes for brain recording at a microscopic scale.

A neural probe capable of recording single-cell resolution was implanted using an endovascular approach through micrometer-scale vasculature. Overall, this, among other developments, are enabling safer and more specific targeting of neurologic conditions, but their overall ethical implications remain to be further discussed.

The convergence between artificial organ technology and simulation in surgery.

Scientists are creating high-fidelity, physiologic simulation platforms that enable the testing of various artificial organs, which may offer a valuable alternative to animal testing in the future.

Three-dimensional bioprinting of artificial organs: How close are we to its clinical application?

A patient recently received a 3D-printed outer ear made out of her own cells. An endoscopic 3D bioprinter was able to print biomaterials in situ. In this decade, we may at last see the application of 3D bioprinters in the creation of complex, clinically viable artificial organs.

A multimillion-dollar DARPA grant awarded to a team developing artificial whole blood product.

Each year, countless individual die from not having immediate access to life-saving blood products. A multi-institutional team was awarded a $46.4 million grant to create an artificial alternative.