Medical large language models are vulnerable to data-poisoning attacks.

The adoption of large language models (LLMs) in healthcare demands a careful analysis of their potential to spread false medical knowledge. Because LLMs ingest massive volumes of data from the open Internet during training, they are potentially exposed to unverified medical knowledge that may include deliberately planted misinformation. Here, we perform a threat assessment that simulates a data-poisoning attack against The Pile, a popular dataset used for LLM development.

Balancing equity and human leukocyte antigen matching in deceased-donor kidney allocation with eplet mismatch.

Human leukocyte antigen-level matching in US kidney allocation has been deemphasized due to its role in elevating racial disparities. Molecular matching based on eplets might improve risk stratification compared to antigen matching, but the magnitude of racial disparities in molecular matching is not known. To assign eplets unambiguously, we utilized a cohort of 5193 individuals with high-resolution allele-level human leukocyte antigen genotypes from the National Kidney Registry.

Generalizability of kidney transplant data in electronic health records - The Epic Cosmos database vs the Scientific Registry of Transplant Recipients.

Developing real-world evidence from electronic health records (EHR) is vital to advancing kidney transplantation (KT). We assessed the feasibility of studying KT using the Epic Cosmos aggregated EHR data set, which includes 274 million unique individuals cared for in 238 US health systems, by comparing it with the Scientific Registry of Transplant Recipients (SRTR). We identified 69 418 KT recipients who underwent transplants between January 2014 and December 2022 in Cosmos (39.

ChatGPT Solving Complex Kidney Transplant Cases: A Comparative Study With Human Respondents.

Introduction: ChatGPT has shown the ability to answer clinical questions in general medicine but may be constrained by the specialized nature of kidney transplantation. Thus, it is important to explore how ChatGPT can be used in kidney transplantation and how its knowledge compares to human respondents.

Methods: We prompted ChatGPT versions 3.

Targeted Broader Sharing for Liver Continuous Distribution.

Background: In recent years, changes to US organ allocation have aimed to improve equity and accessibility across regions. The Organ Procurement and Transplantation Network plans to adopt continuous liver distribution, prioritizing candidates based on a weighted composite allocation score (CAS) incorporating proximity, ABO types, medical urgency, and pediatric priority. The Liver Committee has requested research on CAS variations that account for geographical heterogenicity.

Balancing Equity and HLA Matching in Deceased-Donor Kidney Allocation with Eplet Mismatch.

Background: Prioritization of HLA antigen-level matching in the US kidney allocation system intends to improve post-transplant survival but causes racial disparities and thus has been substantially de-emphasized. Recently, molecular matching based on eplets has been found to improve risk stratification compared to antigen matching.

Methods: To assign eplets unambiguously, we utilized a cohort of 5193 individuals with high resolution allele-level HLA genotypes from the National Kidney Registry.

Removing geographic boundaries from liver allocation: A method for designing continuous distribution scores.

Background: The Organ Procurement and Transplantation Network (OPTN) is eliminating geographic boundaries in liver allocation, in favor of continuous distribution. Continuous distribution allocates organs via a composite allocation score (CAS): a weighted sum of attributes like medical urgency, candidate biology, and placement efficiency. The opportunity this change represents, to include new variables and features for prioritizing candidates, will require lengthy and contentious discussions to establish community consensus.

Kidney Exchange Program Reporting Standards: Evidence-Based Consensus From Europe.

Kidney Exchange Programs can play an important role to increase access to the life saving and most cost-effective treatment for End Stage Renal Disease. The rise of national KEPs in Europe brings a need for standardized performance reporting to facilitate the development of an international evidence base on program practices. We systematically searched and reviewed the literature to extract kidney exchange program performance measures.

Accelerating kidney allocation: Simultaneously expiring offers.

Using nonideal kidneys for transplant quickly might reduce the discard rate of kidney transplants. We studied changing kidney allocation to eliminate sequential offers, instead making offers to multiple centers for all nonlocally allocated kidneys, so that multiple centers must accept or decline within the same 1 hour. If more than 1 center accepted an offer, the kidney would go to the highest-priority accepting candidate.