Li, Yanming

Abstract Background Prosthetic valves are considered a risk factor for endocarditis however diagnosing prosthetic valve endocarditis (PVE) is complicated by acoustic shadowing on echocardiography. In 2023, the ISCVID published an update to the Duke Criteria (Duke 2023) which intended to increase the sensitivity in diagnosing PVE. The purpose of this study was to examine how TAVR infective endocarditis (TAVR-IE) was diagnosed at our institution 90 Day Mortality Kaplan Meier Curve Methods HERON was utilized to match cases between ACC/STS databases and the EMR at The University of Kansas Health System (TUKHS). Patients with bacteremia occurring after a TAVR were reviewed. Each case was evaluated if they met rejected/possible/definitive endocarditis criteria in the Modified Duke Criteria (Duke 2005) and the Duke 2023 Criteria. To adjudicate the diagnosis, an expert panel reviewed all cases that met definitive endocarditis criteria in any edition of the Duke Criteria. Results A total of 2371 TAVRs were conducted at TUKHS from 2012 to 2023. We identified 146 cases of post procedure bacteremia. We excluded 53 cases leaving 93 in the cohort. Transeophageal echocardiography was utilized in about half of the cases (TTE 73, TEE 45). F-FDG positron emission tomography/CT was done in six patients and Cardiac CT in one patient. Cultures returning with Enterococcus spp (16). viridans group streptococci (15), and Staphylococcus spp. (15) had similar incidence. About half had either atypical organisms (40) on 2005 Duke criteria or polymicrobial growth (7). Definitive criteria were met in 18 and 21 patients for the Duke 2005 and Duke 2023 Criteria respectively. Two cases had minor microbiological criteria upgraded to major in Duke 2023. One case was promoted to definitive endocarditis based on Cardiac CT. Upon adjudication the panel agreed with Duke 2023 Criteria classification. Sensitivity was calculated 85%/100% for Duke 2005 and Duke 2023 Criteria respectively. Kaplan Meier curves calculated no significant difference of 3 month mortality between TAVR patients who had met definitive criteria and those who did not. (Figure #1) Conclusion The 2023 ISCVID Duke Criteria in this study appeared to have superior sensitivity for TAVR-IE when compared to the older Modified Duke Criteria published in 2005. Disclosures Larry M. Baddour, MD, UpToDate, Inc.: Royalty payments (authorship duties). Wissam El Atrouni, MD, ViiV Healthcare: Advisor/Consultant

Background and Aims: Alcohol-associated hepatitis (AH) poses significant short-term mortality. Existing prognostic models lack precision for 90-day mortality. Utilizing artificial intelligence in a global cohort, we sought to derive and validate an enhanced prognostic model. Approach and Results: The Global AlcHep initiative, a retrospective study across 23 centers in 12 countries, enrolled patients with AH per National Institute for Alcohol Abuse and Alcoholism criteria. Centers were partitioned into derivation (11 centers, 860 patients) and validation cohorts (12 centers, 859 patients). Focusing on 30 and 90-day postadmission mortality, 3 artificial intelligence algorithms (Random Forest, Gradient Boosting Machines, and eXtreme Gradient Boosting) informed an ensemble model, subsequently refined through Bayesian updating, integrating the derivation cohort’s average 90-day mortality with each center’s approximate mortality rate to produce posttest probabilities. The ALCoholic Hepatitis Artificial INtelligence Ensemble score integrated age, gender, cirrhosis, and 9 laboratory values, with center-specific mortality rates. Mortality was 18.7% (30 d) and 27.9% (90 d) in the derivation cohort versus 21.7% and 32.5% in the validation cohort. Validation cohort 30 and 90-day AUCs were 0.811 (0.779–0.844) and 0.799 (0.769–0.830), significantly surpassing legacy models like Maddrey’s Discriminant Function, Model for End-Stage Liver Disease variations, age-serum bilirubin-international normalized ratio-serum Creatinine score, Glasgow, and modified Glasgow Scores (p < 0.001). ALCoholic Hepatitis Artificial INtelligence Ensemble score also showcased superior calibration against MELD and its variants. Steroid use improved 30-day survival for those with an ALCoholic Hepatitis Artificial INtelligence Ensemble score > 0.20 in both derivation and validation cohorts. Conclusions: Harnessing artificial intelligence within a global consortium, we pioneered a scoring system excelling over traditional models for 30 and 90-day AH mortality predictions. Beneficial for clinical trials, steroid therapy, and transplant indications, it’s accessible at: https://aihepatology.shinyapps.io/ALCHAIN/.

We executed a genome-wide association scan for age-related macular degeneration (AMD) in 2,157 cases and 1,150 controls. Our results validate AMD susceptibility loci near CFH ( P < 10 −75 ), ARMS2 ( P < 10 −59 ), C2/CFB ( P < 10 −20 ), C3 ( P < 10 −9 ), and CFI ( P < 10 −6 ). We compared our top findings with the Tufts/Massachusetts General Hospital genome-wide association study of advanced AMD (821 cases, 1,709 controls) and genotyped 30 promising markers in additional individuals (up to 7,749 cases and 4,625 controls). With these data, we identified a susceptibility locus near TIMP3 (overall P = 1.1 × 10 −11 ), a metalloproteinase involved in degradation of the extracellular matrix and previously implicated in early-onset maculopathy. In addition, our data revealed strong association signals with alleles at two loci ( LIPC , P = 1.3 × 10 −7 ; CETP , P = 7.4 × 10 −7 ) that were previously associated with high-density lipoprotein cholesterol (HDL-c) levels in blood. Consistent with the hypothesis that HDL metabolism is associated with AMD pathogenesis, we also observed association with AMD of HDL-c—associated alleles near LPL ( P = 3.0 × 10 −3 ) and ABCA1 ( P = 5.6 × 10 −4 ). Multilocus analysis including all susceptibility loci showed that 329 of 331 individuals (99%) with the highest-risk genotypes were cases, and 85% of these had advanced AMD. Our studies extend the catalog of AMD associated loci, help identify individuals at high risk of disease, and provide clues about underlying cellular pathways that should eventually lead to new therapies.