Citations

Abstract Purpose Validate the semiquantitative (SQ)-MRI score for chronic pancreatitis (CP) diagnosis in an independent, multicenter cohort. Methods We analyzed MRIs performed at baseline in 337 participants with acute (AP) or recurrent AP (RAP) and 67 with non-calcific chronic pancreatitis (NCCP) enrolled in the PROCEED study from 6/2017 to 3/2023. MRIs were performed at multiple clinical centers using site-specific clinical protocols and a variety of MRI vendors to evaluate the SQ-MRI score in a real-world setting. The SQ-MRI score was calculated using the T1 signal intensity ratio of the pancreas to the spleen (T1 score), arteriovenous enhancement ratio (AVR), and pancreatic body diameter (PBD). We adjusted for confounding by participant characteristics via propensity score weighting. Results Median AVR was higher in AP/RAP (1.18, IQR: 0.97–1.44) than in the NCCP group (1.03, IQR: 0.78–1.22, p = 0.007). Pancreatic body diameters were larger in AP/RAP than in the NCCP group − 7–14 mm (10% vs 25%), 14–20 mm (40% vs 54%), and > 20 mm (50% vs 21%), respectively ( p < 0.01). Median T1 score was higher in AP/RAP (1.18, IQR: 0.96–1.40) than in the NCCP group (1.04, IQR: 0.86–1.32, p = 0.10). Median SQ-MRI score in the AP/RAP group was significantly lower, 1.91 (IQR: 0.97, 2.95), than in the NCCP group, 2.74 (IQR: 2.04–4.03) ( p < 0.001). The propensity score-adjusted AUC for SQ-MRI to distinguish AP/RAP from NCCP was 0.64, which was higher than for individual parameters. Conclusion We have validated the SQ-MRI score in a multicenter cohort using an independent, real-world MRI dataset.

Importance Elevated low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for cardiovascular disease, the leading cause of premature death worldwide. Assessing the LDL-C–related burden is critical for guiding prevention and treatment strategies. Objectives To estimate the global, regional, and national burden of ischemic heart disease and ischemic stroke attributable to elevated LDL-C (relative to 35-54 mg/dL) from 1990 to 2023 and to quantify the contributions of population growth, aging, risk-deleted burden, and exposure changes to burden trends. Design, Setting, and Population This comparative risk assessment, part of the Global Burden of Disease Study 2023, estimated population-level LDL-C exposure and associated health loss in 204 countries and territories. Mean LDL-C levels were estimated using spatiotemporal gaussian process regression based on 806 studies across 161 countries. Relative risks were derived from meta-analyses of 38 randomized clinical trials. Population-attributable fractions for deaths and disability-adjusted life-years (DALYs) were estimated by age and sex for adults aged 25 years or older from 1990 to 2023, with 95% uncertainty intervals. Exposure Population-level LDL-C concentrations. Main Outcomes and Measures Population-attributable fractions, counts, and rates (all ages and age standardized per 100 000) of LDL-C–attributable deaths and DALYs from ischemic heart disease and ischemic stroke, with uncertainty intervals. Results In 2023, elevated LDL-C accounted for 3.6 million deaths (95% uncertainty interval, 2.2-5.4 million; 6.0% of global mortality) and 90.7 million DALYs (95% uncertainty interval, 58.9-123.3 million; 3.2% of DALYs). Although global all-ages rates remained stable, age-standardized death and DALY rates decreased by 45.6% and 39.5%, respectively, since 1990. In 2023, age-standardized LDL-C–attributable DALY rates were highest in Eastern Europe and lowest in high-income Asia-Pacific. One-third of the global LDL-C burden occurred in India and China. Population growth and aging drove the increasing burden, with notable regional disparities in LDL-C exposure and risk-deleted DALY rates shifting toward middle-sociodemographic settings. Conclusions and Relevance Despite declining age-standardized rates, the absolute LDL-C burden has increased since 1990 due to demographic changes and has shifted toward middle-sociodemographic countries. Measurement and surveillance gaps persist. Strengthened prevention, diagnosis, and treatment access strategies are essential to mitigate the health burden of LDL-C.

Emerging evidence links veno-venous extracorporeal membrane oxygenation (VV-ECMO) to right ventricular (RV) dysfunction, but the relative contribution of ECMO versus underlying disease progression remains unclear. We conducted a multicenter, retrospective, propensity-matched study including 408 intubated acute respiratory distress syndrome (ARDS) patients who were admitted between January 2020 and October 2024 in a quaternary referral hospital network within the United States and underwent at least two transthoracic echocardiograms (TTEs) after intubation. Using 1:2 propensity score matching, we adjusted for baseline comorbidities, baseline hemoglobin, lactate, and worst PaO 2 /FiO 2 ratio (P/F). Longitudinal echocardiographic changes were analyzed with a cumulative link mixed model (CLMM), evaluating RV size and function as ordinal outcomes. Within 408 patients (112 received ECMO support), propensity matching identified 55 ECMO and 110 non-ECMO patients with balanced baseline characteristics. Among 469 serial echocardiograms, RV size and function worsened more frequently in ECMO patients. In longitudinal modeling, ECMO use alone was not associated with RV dilation ( p = 0.23) or dysfunction ( p = 0.43). However, longer ECMO duration was associated with RV dilation (OR: 1.04 per day, p = 0.004) and dysfunction (odds ratio [OR]: 1.04 per day, p < 0.001). Higher ECMO circuit flow had a trend toward progressive RV dilation and dysfunction but did not reach statistical significance. These findings highlight the need for vigilant RV monitoring during ECMO support.

21 Background: Large language models (LLMs) are becoming an increasing source of medical information for both patients and providers. Clinical decision making is occasionally complex and may use factors outside of traditional guidelines. We conducted a comparative performance evaluation of frontier models on standardized genitourinary (GU) oncology knowledge assessments derived from the American Society of Clinical Oncology Self-Evaluation Program 2025 (ASCO SEP 2025) in addition to challenging questions developed by GU oncology experts. Methods: Three frontier LLMs were selected: ChatGPT-5.2 (OpenAI, San Francisco, CA, USA), Claude Opus 4.6 (Anthropic, San Francisco, CA, USA), and Gemini 3 Pro (Google DeepMind, Mountain View, CA, USA). Model selection was based on publicly reported performance on “Humanity’s Last Exam,” a benchmark of advanced scientific reasoning (Scale AI leaderboard Jan-Feb 2026). The OpenEvidence (OpenEvidence Inc., MA, USA) search engine was also selected for evaluation. All models were asked 145 ASCO SEP 2025 GU oncology questions and 12 real world challenging scenarios using an uniform prompt. Subject matter experts peer reviewed LLM generated responses to challenging questions and credit was given only for correct rationale and option selection. Results: All models demonstrated high and comparable accuracy on Standardized knowledge assessment, with Gemini 3 Pro leading numerically at 97.24% (95% CI, 93.1% – 99.0%), OpenEvidence followed with an accuracy of 94.48% (95% CI, 89.5% – 97.3%), while Chat GPT -5.2 and Claude OPUS 4.6 scored 92.41% (95%, CI 86.9% – 95.7%) and 79.31% (95% CI, 71.9% – 85.1%) respectively. On challenging real world scenarios, ChatGPT-5.2 demonstrated the highest numerical accuracy at 100% (95% CI, 75.8% – 100%), Gemini 3 Pro and Open Evidence scored 75.0% (95% CI, 46.8%–91.1%) each, followed by Claude Opus 4.6 at 66.7% (39.1–86.3). Conclusions: All current frontier AI models appear to provide accurate medical information and rationale on a large majority of guideline based medical knowledge assessments for GU oncology. Frontier AI models also appear to have emerging competence in highly challenging real-world scenarios. AI based tools may become a valuable and reliable tool for patients and providers. Comparative LLM performance. Model ASCO SEP 2025 % (95% CI) Real World Scenarios % (95% CI) Gemini 3 Pro 97.24% (93.1–99.0) 75.0% (46.8–91.1) OpenEvidence 94.48% (89.5–97.3) 75.0% (46.8–91.1) ChatGPT-5.2 92.41% (86.9–95.7) 100% (75.8–100) Claude Opus 4.6 79.31% (71.9–85.1) 66.67% (39.1–86.3)

Abstract Hematoxylin and eosin (H&E) slides are routinely available in cancer care, but molecular profiling often requires additional tissue processing and turnaround time. We introduce HistoMethyl, a DNA methylation-aware pathology foundation model that aligns whole-slide histopathology with matched genome-scale methylation beta-value profiles during pre-training while requiring only an H&E slide at inference. We evaluated HistoMethyl across four task groups: gene mutation prediction, morphology-associated classification, overall survival prediction, and direct DNA methylation beta-value recovery. Evaluation spanned TCGA cross-validation, a disease-held-out lower-grade glioma cohort, and external cohort validation in CPTAC glioblastoma and SurGen rectal adenocarcinoma, totaling 14 cancer cohorts and 81 gene mutation tasks. The best-performing configuration improved mean mutation AUROC by 5.03 percentage points. By converting DNA methylation supervision into an H&E-only representation, His-toMethyl could support an early molecular triage layer that helps prioritize cases for confirmatory sequencing, methylation profiling, immunohistochemistry, and molecular tumor board review. These image-only predictions are intended to accelerate downstream molecular testing and tissue allocation while leaving final diagnosis and treatment selection anchored in validated molecular assays.

Ziftomenib - a potent, selective, oral menin inhibitor - is approved as monotherapy for adults with relapsed/refractory (R/R) NPM1-mutated acute myeloid leukemia (NPM1-m AML). The KOMET-007 phase 1 trial investigated clinical activity and tolerability of ziftomenib in combination with standard therapies for R/R and newly diagnosed AML. Here, we report outcomes of adults with R/R NPM1-m AML treated with ziftomenib plus venetoclax/azacitidine. In phase 1a, patients received ziftomenib 200, 400, or 600 mg once daily with standard doses of venetoclax/azacitidine. In phase 1b, ziftomenib 600 mg was selected for expansion. Sixty-seven patients were treated (27 phase 1a; 40 phase 1b). Median age was 66 years, and 55% were men. Median number of prior therapies was 1 (range 1-8); 55% received prior venetoclax and 22% had prior transplantation. Most common (≥20%) grade ≥3 treatment-emergent adverse events were leukopenia (34%), thrombocytopenia (28%), febrile neutropenia and neutropenia (25% each). Six patients developed QTc prolongation (1 ziftomenib-related; grade 1), and 2 experienced differentiation syndrome (grade 3); all events were successfully managed. In patients receiving ziftomenib 600 mg, composite complete remission (CRc) rate was 46% (22/48), with 67% (12/18) achieving central measurable residual disease (MRD) negativity (&lt;0.01% threshold). In venetoclax-naïve and -exposed patients, CRc rates were 70% (16/23) and 24% (6/25), with MRD-negativity rates of 75% (9/12) and 50% (3/6), respectively. Median duration of response was 8.6 months, and median overall survival was not reached. The combination of ziftomenib 600 mg with venetoclax/azacitidine was well tolerated with deep and durable clinical activity in R/R NPM1-m AML. This trial was registered at www.ClinicalTrials.gov as #NCT05735184.

Abstract Background Lung transplantation remains the accepted treatment modality of choice for life-threatening advanced lung disease due to established benefits of improving survival and functional status of the patients. However, the annual mortality of lung waitlist candidates remains high, reflecting ongoing donor-recipient mismatches and prolonged wait times. Modalities such as extracorporeal membrane oxygenation (ECMO) have been effectively used as a “bridge to transplant” (BTT) in high-risk patients on waitlist. Objective To evaluate trends in ECMO utilization, waitlist dynamics, and outcomes among lung transplant candidates between 2018 and 2024, with emphasis on the use of ECMO as a bridge to transplantation. Methods We conducted a retrospective chart review of all ECMO runs performed between 2018 to 2024 at the Mayo Clinic Florida Hospital. Among these, patients who underwent evaluation for lung transplantation were identified, and their waitlisting patterns, transplant outcomes, and peri-transplant ECMO status were described. Results Between 2018 and 2024, a total of 348 ECMO runs were recorded among 293 patients. Annual ECMO runs increased steadily from 17 in 2018 to 83 in 2024 (2019: 33, 2020: 30, 2021: 61, 2022: 56, 2023: 68, 2024: 83). Out of these patients, 142 underwent evaluation for lung transplantation and 133 (93.67%) were placed on the waitlist. Among waitlisted patients, 105 (78.9%) were listed before ECMO initiation, 23 (17.3%) during ECMO, and 5 (3.8%) after decannulation. Waitlist outcomes included 116 (87.2%) transplanted, 16 (12.0%) deaths before transplant, and 1 (0.8%) clinical improvement precluding transplant. Among 116 transplanted patients, 36 patients (31.03%) received ECMO as a bridge to lung transplantation. The annual patients bridged with ECMO demonstrated a progressive rise: 1 (2019), 3 (2020), 9 (2021), 6 (2022), 9 (2023), and 8 (2024). Among these 36 patients, 29 (80.56%) remained on ECMO support in the immediate post-transplant period. At the latest follow-up, mortality among BTT recipients was 9 (25%). Conclusion ECMO utilization has expanded substantially over the past several years reflecting its expanding role in supporting critically ill patients. There has been increased utilization of ECMO as a bridge to lung transplantation in order to support high risk candidates awaiting donor organs. The post-transplant mortality among BTT recipients was 25%, which highlights the importance of peri-transplant management to optimize long-term outcomes in this high-risk cohort. This abstract is funded by: None