Citations

Alcohol-associated liver disease (ALD) is a growing global health concern, with alcohol-associated hepatitis (AH) leading to the highest morbidity and mortality. Available therapies are limited and often inadequate. Platelets contribute in a variety of ways to liver disease pathogenesis, but their role in AH remains largely unexplored. In this study, we addressed the hypothesis that platelets contribute to pathological inflammation in AH. Using patient samples and a multiomics approach, we found that platelets undergo proinflammatory transcriptomic and proteomic changes in AH, with 2 alarmins, S100A8 and S100A9, being among the top upregulated genes/proteins. Additionally, the abundance of platelet-derived microparticles containing S100A8 and S100A9 in AH patient plasma was increased and correlated with disease severity (assessed by model for end-stage liver disease sodium [MELD-Na]) and endotheliopathy (assessed by ICAM1, CXCL8, and vWF). We mechanistically linked S100A9 with endotheliopathy via crosstalk between primary human liver sinusoidal endothelial cells and primary human monocytes. We also demonstrated that IL-6 upregulates S100A9 in megakaryocytic cells in a JAK/STAT-dependent manner, modeling changes occurring in the bone marrow in patients with AH. Our studies establish proinflammatory platelets as important contributors to AH pathology. Moreover, antiplatelet agents — or, more specifically, S100A9 targeted drugs — are potential therapeutic strategies in AH.

Background New antiamyloid therapies (AAT) for treating patients with early Alzheimer disease (AD) have become available in the past 3 years. Although AAT can be beneficial in slowing progression of AD, they also come with potentially serious side effects, particularly for patients requiring anticoagulation or thrombolysis for cardiovascular conditions. Given that most patients with AD are older and likely to have cardiovascular risk factors, there is urgent need for additional guidance for clinicians about potential risks and benefits associated with AAT for patients with cardiovascular comorbidities, best practices for management of these patients, and special considerations with respect to emergency evaluation and treatment of patients on AAT who develop acute neurological symptoms. Methods The American Heart Association convened 75 multidisciplinary experts for the Amyloid‐Related Imaging Abnormalities Summit: Cardiovascular and Stroke Considerations for β‐Amyloid Immunotherapy in AD in July 2025. These experts were divided into 8 work groups to evaluate the current evidence related to AAT usage in patients with cardiovascular risk factors and conditions and develop consensus‐based guidance for clinicians. Results This statement outlines the outcomes of the Summit, including considerations for prescribers, primary care professionals, emergency personnel, and health care system stakeholders. These considerations are intended to improve identification of patients as appropriate candidates for AAT, management of patients with co‐occurring AD and cardiovascular conditions, and their emergency evaluation and treatment. The statement also includes guidance for shared decision‐making, implementation of system changes for improving dementia care, and recommendations for future research and data collection to add to the body of evidence for treating patients with concomitant AD and cardiovascular conditions. Conclusions Building on lessons learned from the establishment of stroke systems of care, the consensus‐based considerations outlined in this document can serve as a foundation for AD systems of care aimed at ensuring optimal use of these ground‐breaking therapies.

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.

Acute cholecystitis affects ∼200,000 individuals annually in the United States, with laparoscopic cholecystectomy as the gold standard treatment. However, in high-risk surgical candidates, alternative drainage methods are necessary. Percutaneous transhepatic gallbladder drainage (PT-GBD) has traditionally served as the primary alternative intervention, offering rapid decompression, but is limited by a negative impact on the patient’s quality of life, the risk of long-term or even permanent tube placement, adverse events, and high recurrence rates. Endoscopic approaches, such as endoscopic transpapillary gallbladder drainage (ET-GBD) and, more recently, endoscopic ultrasound-guided gallbladder drainage (EUS-GBD), have emerged as viable alternatives to PT-GBD. EUS-GBD, first introduced in 2007, offers technical and clinical outcomes comparable to PT-GBD with fewer adverse events, shorter hospital stays, and lower rates of recurrence. The introduction of lumen-apposing metal stents (LAMS) has revolutionized EUS-GBD, simplifying deployment and enabling subsequent internal gallbladder access, which allows additional interventions such as cholecystoscopy and stone removal. EUS-GBD is now supported by international guidelines, and 1 device has achieved FDA approval for the management of acute cholecystitis in nonsurgical candidates. Proper patient selection is essential, guided by multidisciplinary evaluation, with EUS-GBD contraindicated in specific scenarios such as gallbladder perforation, coagulopathy, and large-volume ascites. Technical considerations include choice of access site (transgastric versus transduodenal), stent type, and procedural route [direct (freehand) or wire-guided]. Postprocedural care and stent management remain variable and nonstandardized. Emerging data suggest that interval cholecystectomy can still be performed safely after EUS-GBD. As adoption of EUS-GBD with LAMS expands, structured training and standardization of practice are crucial to optimizing outcomes.

At a time when there was no unifying hypothesis and no broadly effective treatments for heart failure with a preserved ejection fraction (HFpEF), it was proposed that HFpEF represented a multitude of different disorders. Accordingly, characterization of phenotypic heterogeneity was envisioned as a means of identifying novel causal pathways that could lead to new treatments while simultaneously discerning patients who would selectively benefit from a specific therapy. However, efforts over the past decade to characterize phenotypic diversity in diverse and complex ways have not achieved these goals. Subgroup analyses of neutral HFpEF trials have failed to reliably identify responders to treatments. Neither proteomics nor unsupervised cluster analysis across multiple phenotypic domains has yielded reproducible results (even in the same dataset), elucidated novel mechanistic pathways for new drug development, or identified patients most likely to benefit from treatment. In marked contrast to these efforts to characterize phenotypic heterogeneity, large-scale trials in HFpEF enrolled patients using broad eligibility criteria, and they established the benefits of sodium-glucose cotransporter 2 inhibitors and mineralocorticoid receptor antagonists without evidence for subgroup effects. However, it is noteworthy that patients enrolled in recent large-scale HFpEF trials were characterized by general uniformity with respect to the presence of excess adiposity, with central obesity being a feature of the vast majority of enrolled participants. Of note, patients with obesity showed particularly large benefits when treated with effective drugs for HFpEF. These observations raise the possibility that, if these trials had permitted the participation of patients with class III obesity or with lower natriuretic peptide levels, the magnitude of the observed treatment effects might have been greater than originally reported. These findings are consistent with a central role for visceral adiposity (and the secretion of an altered suite of adipokines) in the pathogenesis of HFpEF. Therefore, because the field of HFpEF has a unifying hypothesis (applicable to the large majority of patients), enrolled a broad population of patients in large-scale trials without subgroup interactions, and has several broadly applicable effective treatments (as is true for heart failure with a reduced ejection fraction), the motivation to characterize phenotypic heterogeneity in HFpEF in complex ways may no longer be supported or needed.

Abstract Background Cardiovascular inflammation is thought to play a central role in the pathogenesis of heart failure (HF) with preserved ejection fraction (HFpEF) and heart failure with mildly reduced ejection fraction (HFmrEF), but no therapies specifically targeting inflammation in this setting are currently available. Purpose Here we describe the rationale and design of two clinical trials (ATHENA and HERMES) investigating ziltivekimab, a human monoclonal antibody directed against the IL-6 ligand, in patients with HFpEF/HFmrEF and cardiovascular inflammation. Methods ATHENA and HERMES are international, multicenter, double-blind, placebo-controlled trials randomizing adults with HFpEF/HFmrEF and cardiovascular inflammation to ziltivekimab 15 mg or placebo, both administered subcutaneously once-monthly on top of standard of care. Eligible participants have a left ventricular ejection fraction >40%, elevated NTproBNP and serum high sensitivity C reactive protein ≥2 mg/L. The primary endpoint in ATHENA (n=680) is the change in Kansas City Cardiomyopathy Questionnaire–Clinical Summary Score at 12 months. The primary endpoint in HERMES (n=4900) is the composite of CV death, hospitalization for HF or urgent HF visit. The study is event-driven and will target 845 primary events (Figure 1). Conclusions ATHENA and HERMES will investigate the effect of ziltivekimab in HFpEF/HFmrEF and cardiovascular inflammation. ATHENA will determine the effect of ziltivekimab on health status. HERMES will determine the efficacy and safety of ziltivekimab on morbidity and mortality.Fig 1.ATHENA and HERMES trial designsFor image description, please refer to the figure legend and surrounding text.

Abstract Background Approximately 12,000 adolescents and young adults (ages 15-39, AYAs) are diagnosed with a primary central nervous system (CNS) tumor each year. DNA methylation profiling has transformed CNS tumor classification by refining diagnostic accuracy and identifying biologically distinct subtypes, but its application has not been systematically evaluated in the AYA population. In this study, we examined the spectrum of CNS tumor types across age groups, with a focus on the AYA population. Methods We assembled a large dataset of CNS tumor samples with age annotations and methylation profiles matching with high confidence to a CNS tumor type using the NCI/Bethesda classifier. Prevalence of tumor type, methylation class and DNA copy number aberrations were compared across age strata (pediatric, AYA and adult). Results The cohort of 21,099 CNS tumors included 5139 tumors from AYAs (24%), which showed a mixed pattern, with tumors typical of childhood (e.g. medulloblastoma) as well as those common in older adults (e.g. glioblastoma). Several tumor types were specifically enriched in the AYA, including IDH-mutant astrocytoma, pleomorphic xanthoastrocytoma, posterior fossa group B ependymoma, and diffuse hemispheric glioma, H3 G34-mutant, among others. Distinct methylation subclasses of multiple tumor types were observed in the AYA, and patterns of genomic aberrations showed age-specific distributions. Conclusion Large-scale methylation profiling revealed unique classification patterns of CNS tumors in AYAs, with specific tumor types, subclasses, and genomic alterations enriched in this population. These data may serve as a valuable reference resource for better understanding the spectrum of CNS tumors affecting AYA patients.

Introduction The introduction of the purpose‐built single‐port (SP) robotic platform has allowed for the advent of regionalized minimally invasive surgical approaches for robotic radical prostatectomy (RARP), including the extraperitoneal and transvesical techniques. This study sought to develop a best practice consensus on the key principles, patient selection, surgical techniques, expected clinical outcomes, and learning curves pertaining to SP‐RARP. Methods A modified Delphi consensus was developed by a panel of experts, consisting of a 33‐item questionnaire, with each statement rated using a binary Likert scale (‘agree’ or ‘disagree’). The survey was distributed via email to all practicing SP‐RARP surgeons across the USA and Europe. Consensus was defined as ≥75% agreement on a given statement. Results A total of 53 surgeons participated in the Delphi Consensus across the two rounds. Of 33 statements, 28 (84.8%) reached agreement in the first round. The remaining consensus was achieved in the second round, involving 35 surgeons, and with one additional statement. The panel agreed that, although are no absolute contraindications to SP‐RARP, the preference towards specific SP‐RARP techniques should remain guided by the individual patients and surgical expertise. Although the SP extraperitoneal technique is recommended to pursue pelvic lymph node dissections, the panel agreed that transvesical SP‐RARP showed promise in promoting shorter hospital stay, faster recovery of urinary continence, and utility in patients with extensive prior abdominal surgery. Consensus was also reached on the need for a structured training pathway, with most recommending beginning with extraperitoneal SP‐RARP before advancing to the transvesical approach. Conclusion This Delphi consensus demonstrates broad agreement among experienced SP surgeons in the USA and Europe, forming the foundation for future research on the clinical utility and necessary training pathways for SP‐RARP. Nevertheless, empirical validation based on clinical data from large cohort studies remains important.

Abstract Background Machine perfusion represents the most significant breakthrough in liver transplantation (LT) since the discovery of cyclosporin. Yet, the optimal perfusion strategy remains unsettled. Randomized trials demonstrate that hypothermic oxygenated perfusion (HOPE) improves graft survival and function and reduces ischemic cholangiopathy, whereas normothermic machine perfusion (NMP) decreases post-transplant injury. Real-world comparisons are lacking and challenging due to heterogeneity in donor-recipient risk profiles and regional differences. Aims To compare real-world outcomes of HOPE and NMP in LT. Methods We analyzed consecutive NMP-preserved LTs from seven North American centers between 2021 and 2024. We compared NMP to the European HOPE-REAL cohort, comprising HOPE-treated LTs from 22 centers between 2012 and 2021. Analyses were stratifyied by graft type and risk category and adjusted for donor age, donor risk index, and balance of risk score using entropy balancing. Results A total of 470 NMP and 1202 HOPE-treated grafts were analyzed, revealing major differences in risk profiles (Figure 1). In NMP, death-censored graft survivals at 1, 2, and 3 years were >95% in donation after brain death (DBD) and >94% in donation after circulatory death (DCD) grafts. Comparable outcomes were observed in the HOPE cohort with >93%, in DBD, and >87% in DCD after up to 3 years, despite significantly higher donor age and longer functional warm ischemia in the HOPE DCD cohort (Figure 2). After risk adjustment, death-censored graft survival remained similar between both modalities (Table 1). Non-anastomotic biliary stricture rates after DCD-LT were comparable (8.5% vs. 12.4%), independent of whether continuous or end-ischemic NMP was performed. Conclusion This first transatlantic real-world report demonstrates excellent outcomes with both NMP and HOPE despite higher graft risk in Europe. Machine perfusion is the new standard of care in LT, while further understanding is needed regarding the distinct benefits of each modality across risk profiles.Figure 1.Graft risk in NMP and HOPE stratified by graft type. Benchmark case was defined as primary transplant with MELD <20 and BAR score <9, extended criteria as either BMI >30kg/m2, donor age >65 years, CIT >12h. DCD grafts were categorized as definedFor image description, please refer to the figure legend and surrounding text. Figure 2.Death-censored graft survival in liver transplantation following NMP and HOPE stratified by graft type. Abbreviations: NMP (Normothermic Machine Perfusion), HOPE (Hypothermic Oxygenated Perfusion), DBD (Donation after Brain Death), DCD (Donation after circulatory death)For image description, please refer to the figure legend and surrounding text. Table 1.Risk-adjusted comparison of death-censored graft survival between NMP and HOPE.For image description, please refer to the figure legend and surrounding text.

As machine learning (ML)-based decision support tools proliferate in clinical practice, understanding how clinicians integrate personalized ML predictions alongside randomized controlled trial (RCT) evidence is critical. We designed a web-based clinical decision support system (CDSS) presenting survival and adverse event data from a simulated RCT and ML model across 12 synthetic multiple myeloma scenarios. In a within-subjects study with 32 physicians, we evaluated how clinicians synthesize competing evidence sources to make treatment decisions. When ML and RCT outputs were concordant, physicians reported greater confidence than with RCT data alone. When results were discordant, most physicians shifted toward the ML-supported treatment, often before reviewing any information about model training or validation, suggesting a tendency toward automation bias rather than algorithm avoidance. Despite reporting higher perceived reliability after viewing model quality disclosures, physicians were largely unable to describe the validation procedures they had reviewed. Taken together, these findings reveal that clinicians may over-rely on ML recommendations even when equipped with tools designed to support critical appraisal. We discuss implications for CDSS design, clinician training, and the institutional safeguards needed before ML-based systems are deployed in high-stakes oncology settings.