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 3.5, 4, and 4 Visual (4 V) with 12 multiple-choice questions related to six kidney transplant cases from 2013 to 2015 American Society of Nephrology (ASN) fellowship program quizzes. We compared the performance of ChatGPT with US nephrology fellowship program directors, nephrology fellows, and the audience of the ASN's annual Kidney Week meeting. RESULTS: Overall, ChatGPT 4 V correctly answered 10 out of 12 questions, showing a performance level comparable to nephrology fellows (group majority correctly answered 9 of 12 questions) and training program directors (11 of 12). This surpassed ChatGPT 4 (7 of 12 correct) and 3.5 (5 of 12). All three ChatGPT versions failed to correctly answer questions where the consensus among human respondents was low. CONCLUSION: Each iterative version of ChatGPT performed better than the prior version, with version 4 V achieving performance on par with nephrology fellows and training program directors. While it shows promise in understanding and answering kidney transplantation questions, ChatGPT should be seen as a complementary tool to human expertise rather than a replacement.

Single center utilization and post-transplant outcomes of thoracoabdominal normothermic regional perfusion deceased cardiac donor organs.

INTRODUCTION: Thoracoabdominal normothermic regional perfusion (TA-NRP) following cardiac death is an emerging multivisceral organ procurement technique. Recent national studies on outcomes of presumptive TA-NRP-procured organs are limited by potential misclassification since TA-NRP is not differentiated from donation after cardiac death (DCD) in registry data. METHODS: We studied 22 donors whose designees consented to TA-NRP and organ procurement performed at our institution between January 20, 2020 and July 3, 2022. We identified these donors in SRTR to describe organ utilization and recipient outcomes and compared them to recipients of traditional DCD (tDCD) and donation after brain death (DBD) organs during the same timeframe. RESULTS: All 22 donors progressed to cardiac arrest and underwent TA-NRP followed by heart, lung, kidney, and/or liver procurement. Median donor age was 41 years, 55% had anoxic brain injury, 45% were hypertensive, 0% were diabetic, and median kidney donor profile index was 40%. TA-NRP utilization was high across all organ types (88%-100%), with a higher percentage of kidneys procured via TA-NRP compared to tDCD (88% vs. 72%, p = .02). Recipient and graft survival ranged from 89% to 100% and were comparable to tDCD and DBD recipients (p ≥ .2). Delayed graft function was lower for kidneys procured from TA-NRP compared to tDCD donors (27% vs. 44%, p = .045). CONCLUSION: Procurement from TA-NRP donors yielded high organ utilization, with outcomes comparable to tDCD and DBD recipients across organ types. Further large-scale study of TA-NRP donors, facilitated by its capture in the national registry, will be critical to fully understand its impact as an organ procurement technique.

Improving long-term kidney allograft survival by rethinking HLA compatibility: from molecular matching to non-HLA genes.

Optimizing immunologic compatibility in organ transplantation extends beyond the conventional approach of Human Leukocyte Antigen (HLA) antigen matching, which exhibits significant limitations. A broader comprehension of the roles of classical and non-classical HLA genes in transplantation is imperative for enhancing long-term graft survival. High-resolution molecular HLA genotyping, despite its inherent challenges, has emerged as the cornerstone for precise patient-donor compatibility assessment. Leveraging understanding of eplet biology and indirect immune activation, eplet mismatch calculators and the PIRCHE-II algorithm surpass traditional methods in predicting allograft rejection. Understanding minor histocompatibility antigens may also present an opportunity to personalize the compatibility process. While the application of molecular matching in deceased donor organ allocation presents multiple technical, logistical, and conceptual barriers, rendering it premature for mainstream use, several other areas of donor-recipient matching and post-transplant management are ready to incorporate molecular matching. Provision of molecular mismatch scores to physicians during potential organ offer evaluations could potentially amplify long-term outcomes. The implementation of molecular matching in living organ donation and kidney paired exchange programs is similarly viable. This article will explore the current understanding of immunologic matching in transplantation and the potential applications of epitope and non-epitope molecular biology and genetics in clinical transplantation.

Evaluating Large Language Models in Extracting Cognitive Exam Dates and Scores.

Importance: Large language models (LLMs) are crucial for medical tasks. Ensuring their reliability is vital to avoid false results. Our study assesses two state-of-the-art LLMs (ChatGPT and LlaMA-2) for extracting clinical information, focusing on cognitive tests like MMSE and CDR. Objective: Evaluate ChatGPT and LlaMA-2 performance in extracting MMSE and CDR scores, including their associated dates. Methods: Our data consisted of 135,307 clinical notes (Jan 12th, 2010 to May 24th, 2023) mentioning MMSE, CDR, or MoCA. After applying inclusion criteria 34,465 notes remained, of which 765 underwent ChatGPT (GPT-4) and LlaMA-2, and 22 experts reviewed the responses. ChatGPT successfully extracted MMSE and CDR instances with dates from 742 notes. We used 20 notes for fine-tuning and training the reviewers. The remaining 722 were assigned to reviewers, with 309 each assigned to two reviewers simultaneously. Inter-rater-agreement (Fleiss' Kappa), precision, recall, true/false negative rates, and accuracy were calculated. Our study follows TRIPOD reporting guidelines for model validation. Results: For MMSE information extraction, ChatGPT (vs. LlaMA-2) achieved accuracy of 83% (vs. 66.4%), sensitivity of 89.7% (vs. 69.9%), true-negative rates of 96% (vs 60.0%), and precision of 82.7% (vs 62.2%). For CDR the results were lower overall, with accuracy of 87.1% (vs. 74.5%), sensitivity of 84.3% (vs. 39.7%), true-negative rates of 99.8% (98.4%), and precision of 48.3% (vs. 16.1%). We qualitatively evaluated the MMSE errors of ChatGPT and LlaMA-2 on double-reviewed notes. LlaMA-2 errors included 27 cases of total hallucination, 19 cases of reporting other scores instead of MMSE, 25 missed scores, and 23 cases of reporting only the wrong date. In comparison, ChatGPT's errors included only 3 cases of total hallucination, 17 cases of wrong test reported instead of MMSE, and 19 cases of reporting a wrong date. Conclusions: In this diagnostic/prognostic study of ChatGPT and LlaMA-2 for extracting cognitive exam dates and scores from clinical notes, ChatGPT exhibited high accuracy, with better performance compared to LlaMA-2. The use of LLMs could benefit dementia research and clinical care, by identifying eligible patients for treatments initialization or clinical trial enrollments. Rigorous evaluation of LLMs is crucial to understanding their capabilities and limitations.

Integrative multi-omics profiling in human decedents receiving pig heart xenografts.

In a previous study, heart xenografts from 10-gene-edited pigs transplanted into two human decedents did not show evidence of acute-onset cellular- or antibody-mediated rejection. Here, to better understand the detailed molecular landscape following xenotransplantation, we carried out bulk and single-cell transcriptomics, lipidomics, proteomics and metabolomics on blood samples obtained from the transplanted decedents every 6 h, as well as histological and transcriptomic tissue profiling. We observed substantial early immune responses in peripheral blood mononuclear cells and xenograft tissue obtained from decedent 1 (male), associated with downstream T cell and natural killer cell activity. Longitudinal analyses indicated the presence of ischemia reperfusion injury, exacerbated by inadequate immunosuppression of T cells, consistent with previous findings of perioperative cardiac xenograft dysfunction in pig-to-nonhuman primate studies. Moreover, at 42 h after transplantation, substantial alterations in cellular metabolism and liver-damage pathways occurred, correlating with profound organ-wide physiological dysfunction. By contrast, relatively minor changes in RNA, protein, lipid and metabolism profiles were observed in decedent 2 (female) as compared to decedent 1. Overall, these multi-omics analyses delineate distinct responses to cardiac xenotransplantation in the two human decedents and reveal new insights into early molecular and immune responses after xenotransplantation. These findings may aid in the development of targeted therapeutic approaches to limit ischemia reperfusion injury-related phenotypes and improve outcomes.

Pig-to-human heart xenotransplantation in two recently deceased human recipients.

Genetically modified xenografts are one of the most promising solutions to the discrepancy between the numbers of available human organs for transplantation and potential recipients. To date, a porcine heart has been implanted into only one human recipient. Here, using 10-gene-edited pigs, we transplanted porcine hearts into two brain-dead human recipients and monitored xenograft function, hemodynamics and systemic responses over the course of 66 hours. Although both xenografts demonstrated excellent cardiac function immediately after transplantation and continued to function for the duration of the study, cardiac function declined postoperatively in one case, attributed to a size mismatch between the donor pig and the recipient. For both hearts, we confirmed transgene expression and found no evidence of cellular or antibody-mediated rejection, as assessed using histology, flow cytometry and a cytotoxic crossmatch assay. Moreover, we found no evidence of zoonotic transmission from the donor pigs to the human recipients. While substantial additional work will be needed to advance this technology to human trials, these results indicate that pig-to-human heart xenotransplantation can be performed successfully without hyperacute rejection or zoonosis.

Comparing the Diagnostic Accuracy of Clinician Judgment to a Novel Host Response Diagnostic for Acute Respiratory Illness.

BACKGROUND: Difficulty discriminating bacterial from viral infections drives antibacterial misuse. Host gene expression tests discriminate bacterial and viral etiologies, but their clinical utility has not been evaluated. METHODS: Host gene expression and procalcitonin levels were measured in 582 emergency department participants with suspected infection. We also recorded clinician diagnosis and clinician-recommended treatment. These 4 diagnostic strategies were compared with clinical adjudication as the reference. To estimate the clinical impact of host gene expression, we calculated the change in overall Net Benefit (∆NB; the difference in Net Benefit comparing 1 diagnostic strategy with a reference) across a range of prevalence estimates while factoring in the clinical significance of false-positive and -negative errors. RESULTS: Gene expression correctly classified bacterial, viral, or noninfectious illness in 74.1% of subjects, similar to the other strategies. Clinical diagnosis and clinician-recommended treatment revealed a bias toward overdiagnosis of bacterial infection resulting in high sensitivity (92.6% and 94.5%, respectively) but poor specificity (67.2% and 58.8%, respectively), resulting in a 33.3% rate of inappropriate antibacterial use. Gene expression offered a more balanced sensitivity (79.0%) and specificity (80.7%), which corresponded to a statistically significant improvement in average weighted accuracy (79.9% vs 71.5% for procalcitonin and 76.3% for clinician-recommended treatment; P<.0001 for both). Consequently, host gene expression had greater Net Benefit in diagnosing bacterial infection than clinician-recommended treatment (∆NB=6.4%) and procalcitonin (∆NB=17.4%). CONCLUSIONS: Host gene expression-based tests to distinguish bacterial and viral infection can facilitate appropriate treatment, improving patient outcomes and mitigating the antibacterial resistance crisis.

A Decade On: Systematic Review of ClinicalTrials.gov Infectious Disease Trials, 2007-2017.

BACKGROUND: Registration of interventional trials of Food and Drug Administration-regulated drug and biological products and devices became a legal requirement in 2007; the vast majority of these trials are registered in ClinicalTrials.gov. An analysis of ClinicalTrials.gov offers an opportunity to define the clinical research landscape; here we analyze 10 years of infectious disease (ID) clinical trial research. METHODS: Beginning with 166 415 interventional trials registered in ClinicalTrials.gov from 2007-2017, ID trials were selected by study conditions and interventions. Relevance to ID was confirmed through manual review, resulting in 13 707 ID trials and 152 708 non-ID trials. RESULTS: ID-related trials represented 6.9%-9.9% of all trials with no significant trend over time. ID trials tended to be more focused on treatment and prevention, with a focus on testing drugs, biologics, and vaccines. ID trials tended to be large, randomized, and nonblinded with a greater degree of international enrollment. Industry was the primary funding source for 45.2% of ID trials. Compared with the global burden of disease, human immunodeficiency virus/AIDS and hepatitis C trials were overrepresented, and lower respiratory tract infection trials were underrepresented. Hepatitis C trials fluctuated, keeping with a wave of new drug development. Influenza vaccine trials peaked during the 2009 H1N1 swine influenza outbreak. CONCLUSIONS: This study presents the most comprehensive characterization of ID clinical trials over the past decade. These results help define how clinical research aligns with clinical need. Temporal trends reflect changes in disease epidemiology and the impact of scientific discovery and market forces. Periodic review of ID clinical trials can help identify gaps and serve as a mechanism to realign resources.