Citations

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.

Abstract Glioblastoma (GBM) remains the most lethal primary brain cancer due to its remarkable metabolic plasticity and therapeutic resistance. Here, we identify cholesterol dependency as a therapeutically exploitable vulnerability in GBM using two FDA-approved drugs: the H1 histamine antagonist clemastine and the retinoid X receptor agonist bexarotene. Combined treatment induces potent synergistic anti-tumor activity across patient-derived glioma models, suppressing proliferation, stemness, and survival at sub-IC50 concentrations. Mechanistically, this therapy disrupts cholesterol biosynthesis, transport, and homeostasis, triggering endoplasmic reticulum stress and activation of the unfolded protein response, ultimately leading to autophagy and apoptotic cell death. Orthotopic patient-derived glioma models recapitulate these mechanisms in vivo, where local intracranial administration significantly reduces tumor progression and prolongs survival using fourfold lower doses than systemic intraperitoneal delivery. Single-cell RNA sequencing revealed activation of regeneration and plasticity programs, accompanied by immune microenvironment remodeling and enhanced inflammatory signaling. Importantly, syngeneic models preserved immune cell composition, supporting future integration with immunotherapeutic strategies. Together, these findings establish cholesterol dysregulation–induced metabolic collapse as a promising therapeutic approach for GBM.

Abstract Background Online hemodiafiltration (HDF) enhances the removal of middle molecules, including large-middle molecules, through the combined action of diffusion and convection. Randomized controlled trials (RCTs) and individual participant data (IPD) meta-analyses demonstrate improved cardiovascular outcomes and, importantly, a reduction in all-cause mortality when HDF is delivered with sufficiently high convective volumes in post-dilution mode. These findings underscore that an adequate convective dose is a critical determinant of clinical benefits compared to high-flux hemodialysis (HD). However, translation into consistent clinical practice remains heterogeneous. Therefore, the Italian Society of Nephrology convened an international, multidisciplinary panel to synthesize randomized evidence comparing online post-dilution HDF with high-flux HD in adults receiving maintenance hemodialysis. Methods The critical outcomes included all-cause and cardiovascular mortality, whereas the important outcomes included selected patient-reported health domains, including physical function, patient-perceived cognitive function, pain interference, social participation, and health-related quality of life. The certainty of the evidence was appraised using the GRADE methodology. Structured guidance recommendations and best practice statements were developed through a consensus. Sensitivity analyses were performed to assess the robustness of the observed mortality effect. Results High-volume post-dilution HDF reduces all-cause mortality (hazard ratio 0.84; 95% CI 0 74–0.95; moderate-certainty evidence) and cardiovascular mortality (hazard ratio 0.78, 95% CI 0.64–0.96; moderate-certainty evidence; data from an individual participant data analysis of trials of high volume HDF versus high-flux HD). Emerging evidence suggests slower deterioration in selected patient-reported domains, including physical function, patient-perceived cognitive function, pain interference, and social participation (low-certainty evidence). Safety with on-line post-dilution HDF has been demonstrated to be similar to that of high-flux HD. Conclusions Online post-dilution HDF should be regarded as a dose-dependent therapy. We recommend its use to reduce cardiovascular mortality and suggest high-volume HDF to reduce all-cause mortality and slow deterioration in selected patient-reported health domains. Effective implementation in clinical practice requires a targeted and individualized approach with careful optimization and monitoring of convective volume, along with appropriate treatment time, blood-flow rate, supporting infrastructure, and consideration of patient preferences. This guidance provides evidence-based recommendations and best practice statements for its use.

Abstract Aim To confirm or refute recent pilot studies showing unexpectedly high rates of undetected heart failure (HF) in cardiology patients. Methods We assessed the prevalence, characteristics, and outcome of undetected HF in a large prospective cohort study of patients referred for non-invasive coronary artery disease (CAD) work-up with cardiac positron emission tomography computed tomography. HF presence and phenotype were centrally adjudicated by an independent cardiologist according to clinical practice guidelines requiring three mandatory criteria: symptoms, elevated natriuretic peptides, and structural/functional cardiac abnormalities. The endpoint was a composite of cardiovascular death and acute HF (AHF) hospitalization through 2-year of follow-up. Results Among 1738 eligible patients (median age 67 years, 30% women), 138 patients (7.9%) had known HF, and 534 of 1600 patients (33.4%) without known HF had adjudicated undetected HF, resulting in a ratio of undetected HF to known HF of 3.9 (95%CI, 3.2–4.7)-to-1 and a number needed to screen to detect one patient with undetected HF of 3.0 (95%CI, 2.9-3.1). In undetected HF, left ventricular ejection fraction (LVEF) was preserved in 72.3%, mildly reduced in 16%, and reduced in 11.7%. Older age, known CAD, atrial fibrillation, previous pacemaker implantation, and ECG abnormalities were associated with a higher likelihood for undetected HF. Undetected HF was associated with an increased cumulative incidence of the composite endpoint (adjusted subdistribution hazard ratio 7.37 [95%CI, 3.87-14.06], p<0.001, versus no HF). Conclusion One-out-of three patients referred for CAD work-up had undetected HF, which was associated with cardiovascular death and AHF hospitalization.

Abstract Triple-Negative Breast Cancer (TNBC) presents a significant clinical challenge due to its heterogeneity and lack of targeted treatment options, with chemotherapy and immunotherapy combinations currently serving as the main therapeutic strategy. Efforts to address TNBC heterogeneity have largely focused on classifying intrinsic cancer subtypes based on differential tumor mRNA expression, a strategy that has proven effective in hormone receptor-positive breast cancers but has yet to yield a clinically useful predictor of survival or treatment response in TNBC. We hypothesize that both the intrinsic characteristics of TNBC and the surrounding immune microenvironment influence treatment outcomes and that immune cell infiltration affects TNBC subtype classification and response variability. To explore this hypothesis, we compared the predictive and prognostic capabilities of cancer subtype-based (TNBC-type) gene signatures and immune cell deconvolution methods (CIBERSORT) within the same TNBC datasets. We found that immune cell abundance outperformed TNBC subtype-signatures and multicellular immune cell aggregates showed the highest performance of all. More specifically, aggregate immune cells associated with tertiary lymphoid structures and tumor associated macrophages/monocytes demonstrated statistically significant predictive value. These findings were confirmed in an independent cohort of 67 TNBC patients treated with neoadjuvant chemotherapy. Further, single-cell RNA sequencing analysis revealed that the predictive power of cancer-subtype could be partially explained by immune- and stromal features. Examination of single-cell resolution spatial transcriptomic data confirmed presence of TLS-like, TAM- and cancer-stromal niches within TNBC biopsy samples that were associated with treatment response. Overall, our results highlight that immune cell aggregates, which capture the spatial organization of the TME, outperform cell-type specific gene signatures in predicting TNBC outcomes. Our novel approach provides a robust framework for interpreting spatial relationships in bulk RNA-seq data, offering a pathway for reconciling past data with current advancements in spatial profiling technologies. This work paves the way for future studies to leverage the multi-cellular complexity of TNBC, enhancing diagnostic precision and facilitating the development of therapies that strategically modulate the tumor microenvironment for improved anti-cancer responses.

ABSTRACT Many real‐world patients with advanced biliary tract cancer (BTC) are excluded by TOPAZ‐1 criteria; this study assessed cisplatin and gemcitabine plus durvalumab (CGD) efficacy and safety in these patients. Data from 1358 patients with advanced BTC treated with first‐line CGD across 55 international centers were retrospectively analyzed. Patients were classified as TOPAZ‐1‐in (meeting all inclusion criteria) or TOPAZ‐1‐out (meeting ≥ 1 exclusion criterion). Primary endpoints were overall survival (OS) and progression‐free survival (PFS); secondary endpoints included objective response rate (ORR), disease control rate (DCR), and safety. Furthermore, OS and PFS of the TOPAZ‐1‐out cohort were compared with reconstructed survival data from the phase III trial. 912 (67.1%) patients were classified as TOPAZ‐1‐in , and 446 (32.9%) as TOPAZ‐1‐out . After a median follow‐up of 14.5 months (95% CI: 13.7–36.5), OS was 16.1 months in TOPAZ‐1‐in and 12.5 months in TOPAZ‐1‐out (HR 0.69, 95% CI: 14.6–16.5, p = 0.0001); PFS was 8.2 versus 6.5 months (HR 0.73, 95% CI: 7.1–8.1, p < 0.0001). Median OS in the TOPAZ‐1‐out cohort (12.5 months) was nearly identical to the phase III trial experimental arm (12.9 months; HR 1.15, p = 0.13); for PFS the HR was 1.12 (95% CI 0.93–1.42; p = 0.09). Among TOPAZ‐1‐out patients, active infection, elevated bilirubin, and ECOG PS > 1 were linked to poorer OS, while no detrimental impact emerged for ALT/AST abnormalities, corticosteroid use, renal or hematologic parameters, or prior surgery within 6 months, suggesting treatment effectiveness was broadly maintained across clinical subgroups. Furthermore, TOPAZ‐1‐out patients experienced no significant increase in adverse events compared with the TOPAZ‐1‐in group. Real‐world data suggest CGD may be effective in TOPAZ‐1‐out patients, with no evident increase in toxicity, supporting the potential expanded use of the regimen in clinical practice.

Background Intensive care units are high-acuity environments characterized by time pressure, medical complexity, and organizational demands. These conditions may influence clinicians’ ability to provide patient-centered care and contribute to forms of care perceived as fragmented or dehumanizing. Objective To examine how ICU clinicians describe and make sense of the pressures shaping everyday critical care practice, and how these pressures give rise to interacting patterns of care, including those described as hurry, blur, burden, and cruelty. Methods We conducted a qualitative study using focus groups with ICU clinicians from a large academic health system. Discussions were informed by the concept of the pathologies of care as sensitizing concepts. Four focus groups were held with physicians, nurses, advanced practice nurses, and a social worker ( N = 14). Transcripts were analyzed using directed content analysis with both deductive and inductive coding. Results Clinicians described these patterns not as discrete phenomena but as interrelated, context-dependent processes shaped by shared operational pressures such as time constraints, workload, and information demands. These dynamics were often viewed as inherent to the structure and culture of ICU care and were described as co-occurring and compounding. Communication emerged as both a contributor to and a potential mechanism for mitigation, alongside system-level strategies such as reducing documentation burden and leveraging artificial intelligence to support care delivery. Conclusions Patterns reflected in hurry, blur, burden, and cruelty are best understood as emergent properties of complex care systems. Addressing these dynamics may require system-level approaches to improve communication, reduce workload pressures, and support more patient-centered, humanizing care.

Abstract Artificial intelligence is spreading through public health agencies and healthcare systems faster than workforces are trained to govern it. We describe RHAMI (Responsible Health AI Readiness and Maturity Index), the first human-centered automated composite index for health organizations to score AI readiness and maturity as one measurable system of science, economics and ethics, and the physician certification-to-Master’s pathway built to teach what it measures—both designed jointly by frontline public health professionals, clinicians, ethicists, engineers, leaders, and policy-makers in low- and middle-income countries and high-income countries.