Citations

Abstract Purpose: Polatuzumab vedotin (polatuzumab) was approved for up-front treatment of diffuse large B-cell lymphoma in combination with chemoimmunotherapy (Pola-R-CHP) based on the POLARIX trial. However, when stratified by cell of origin (COO), polatuzumab seems to have greater efficacy in activated B-cell than germinal center B-cell (GCB) subtype disease. Most studies of polatuzumab used RNA expression to assess COO, whereas in routine clinical practice, the immunohistochemistry-based Hans algorithm is used. Experimental Design: To assess the impact of COO by immunohistochemistry on polatuzumab efficacy, we conducted a multicenter real-world study of adults with large B-cell lymphoma (LBCL) receiving polatuzumab from 2015 to 2024, split by receipt of polatuzumab in first-line versus relapsed/refractory settings. The primary endpoint was overall response rate (ORR) to polatuzumab-based treatment in GCB versus non-GCB relapsed/refractory LBCL. Results: Of 740 patients, 305 received polatuzumab in the first-line setting and 435 in the relapsed/refractory setting. In the relapsed/refractory cohort, the ORR in non-GCB versus GCB LBCL was 59.7% versus 36.3% [OR, 2.6; 95% confidence interval (CI), 1.77–3.84; P < 0.0001], with a complete response rate of 35.7% versus 17.7% (OR, 2.6; 95% CI, 1.66–4.02; P < 0.0001). Progression-free survival was longer for patients with non-GCB versus GCB COO (HR, 0.64; 95% CI, 0.5–0.83; P = 0.0006). In the first-line cohort, ORR, complete response rate, and progression-free survival were similar in non-GCB versus GCB LBCL, as hypothesized based on outcomes in the Pola-R-CHP arm of POLARIX, suggesting that the addition of polatuzumab overcomes the adverse risk of non-GCB COO in patients receiving R-CHOP. Conclusions: Based on these data, COO classification by the Hans algorithm is a strong predictor of polatuzumab efficacy in LBCL, informing real-world treatment decisions.

ABSTRACT As artificial intelligence (AI) continues to rapidly reshape health care, there is a critical need for clear frameworks for clinicians to ensure ethical, equitable, and effective integration and use of AI in patient care. Key integrations of AI include enhancing health communications, patient engagement, clinicians' training, pharmaceutical advertising, clinical decision‐making, and automation of clinical operations and workflow. However, there are growing concerns related to regulatory gaps, the spread of misinformation, security threats, patient and data privacy leaks, and widening health disparities gaps. These concerns are exacerbated by limited institutional infrastructure and limited AI literacy of clinicians and patients. Recent policy developments reflect efforts to guide responsible AI development and use. While progress has been made, the lack of standardized human oversight remains a critical gap, particularly as policies may not fully consider the challenges and complexities at institutional, societal, technical, and individual levels. Thus, herein, the Drug Information Practice and Research Network (DI PRN) of the American College of Clinical Pharmacy (ACCP) : (1) explores current and emerging multifaceted challenges, a call to action, and opportunities of AI integration in health care including examination of the regulatory, ethical, operational, and health equity implications; and (2) provides practical recommendations for responsible use of AI through DI PRN‐developed example case‐based approaches and best practices infographics to enhance AI literacy for diverse learners including clinicians, trainees, and patients. This DI PRN opinion paper highlights the importance of proactive governance frameworks and equips and empowers diverse learners with practical AI literacy tools to confidently engage with AI technologies in patient care.

Objective: The specialty of critical care in the United States currently lacks a single, broad, unified database. We conducted a scoping review of existing established national ICU databases, describing national and international patterns of critical care delivery. Data Sources: A systematic literature search was undertaken using MEDLINE, Embase, and Web of Science search engines. Study Selection: Projects describing national critical care delivery (including any subspecialty) published in any language were included. Titles, abstracts, and full-text manuscripts were reviewed in duplicate for inclusion. Data Extraction: National database characteristics were collected, including the number and subspecialty of ICUs, the inaugural year, data entry methodology, the number of episodes of care included, and captured clinical data elements. Data Synthesis: Of 24,003 abstracts screened, 185 manuscripts were eligible for inclusion. Thirty countries were identified as having established national ICU registries: Argentina, Australia/New Zealand, Austria, Belgium, Brazil, Canada, Denmark, Ecuador, Finland, Germany, Iceland, India, Ireland, Italy, Japan, Kenya, Malaysia, Mexico, Nepal, Netherlands, Norway, Pakistan, Paraguay, Spain, Sri Lanka, Sweden, Switzerland, United Kingdom, United States and Uruguay. Data entry commonly incorporates a combination of automated data abstraction from electronic healthcare systems and manual data entry, followed by independent validation. Frequently recorded variables include patient demographics; admission vital signs and laboratory data; comorbidities; admission source and diagnoses; ICU diagnoses, treatments, and complications; illness severity scores; and clinically relevant outcomes including discharge disposition, functional status, lengths of stay, and mortality. Conclusions: Insights and experience gained from the study of mature national ICU registries may be used to guide an equivalent U.S. multidisciplinary program aimed at benchmarking, needs assessment, quality improvement, and research facilitation

ABSTRACT Suicidality contributes substantially to global morbidity and mortality, yet despite its heritability, its biological etiology remains largely elusive. We conducted multi-ancestry genome-wide association study meta-analyses of suicidal ideation (259,747 cases), suicide attempt (64,993 cases), suicide death (9,197 cases), and suicidal behavior (suicide attempt/ death, 75,300 cases), across 54 cohorts (e.g., the Psychiatric Genomics Consortium, Million Veteran Program, UK Biobank). We identified 77 significant loci across meta-analyses, including 59 previously unreported for suicidality. SNP-based heritability ranged from 2.0-6.7% and there were strong, yet incomplete, genetic correlations between suicidality phenotypes (0.70-0.88). Fine-mapping prioritized putative causal SNPs and 20 credible genes. Enrichment analyses implicated synaptic pathways and neuronal populations predominantly in subcortical brain regions (e.g., amygdala excitatory, medium spiny, hippocampal CA1-3). Together, these findings establish suicidality as a polygenic set of traits with both shared and distinct genetic influences, providing a foundation for future studies of suicide biology and etiology.

Abstract The sections in this article are: Basic Concepts—Review of Muscle Mechanics Muscle Fiber Types Mechanics of Muscle Electrical Properties of Skeletal Muscle Individual Respiratory Muscles and Their Properties General Considerations Diaphragm Intercostal Muscles Sternocleidomastoid and Scalenus Muscles Abdominal Muscles Other Respiratory Muscles Altered Respiratory Muscle Mechanical Properties in Disease Obstructive Lung Disease Diseases Characterized by Stiff Lungs Neuromuscular Diseases Severe Obesity

Abstract The sections in this article are: Basal Vascular Resistance and Autoregulation Role of Myogenic Mechanism in Reactive Hyperemia Role of Myogenic Mechanism in Exercise Hyperemia Types of Skeletal Muscle Fibers Muscle Blood Flow During Exercise Oxygen Lack Lactic Acid, pH, and CO 2 Potassium Inorganic Phosphate Osmolarity Prostaglandins Adenosine and Adenine Nucleotides Intrinsic Neurons and Exercise Dilatation General Conclusions Mechanical Hindrance to Blood Flow in Skeletal Muscle Reactive Hyperemia Are Exercise and Reactive Hyperemia Due to the Same Mechanism(s)? Propagated Vasodilatation Sympathetic Vasomotor Outflow Noradrenergic Innervation of Resistance Vessels in Muscles Neuroeffector Junction α‐Adrenergic Activation Factors that Modulate Transmitter Output From Sympathetic Nerve Endings Metabolic Action Neurohumoral Action Reflex Regulation of Skeletal Muscle Resistance Vessels by Sympathetic Noradrenergic Nerves Carotid and Aortic Baroreflex Carotid and Aortic Chemoreflex Reflexes From the Heart and Lungs Diving Reflex Reflex From Receptors in Skeletal Muscles Rhythmic Exercise Isometric Exercise Influence of Sympathetic Noradrenergic Fibers on the Blood Flow to Active Muscles β 2 ‐Adrenergic Activation Cholinergic Vasodilator Nerves Role of Cholinergic Nerves in the Carotid Baroreflex Cholinergic Vasodilatation in Humans Histaminergic Vasodilatation Role of Histamine in the Vasodilatation Resulting From Reflex Inhibition of Sympathetic Outflow Conclusions