Citations

Acute myeloid leukemia (AML) is a heterogeneous hematologic malignancy characterized by the clonal expansion of myeloid blasts in the peripheral blood, bone marrow, and/or other tissues. It is the most common form of acute leukemia among adults and accounts for the largest number of annual deaths from leukemias in the United States. 1 The NCCN Guidelines Panel for AML convenes annually to update recommendations for the diagnosis and treatment of AML in adults. These recommendations are based on a review of recently published clinical trials that have led to significant improvements in treatment or have yielded new information regarding biologic factors that may have prognostic importance. These NCCN Guidelines Insights summarize the panel’s most recent recommendations regarding the monitoring and management of measurable (minimal) residual disease.

The International Academy for Clinical Hematology (IACH) is a global, non-profit educational organization dedicated to advancing excellence, equity, and innovation in clinical hematology. Since its creation, the IACH has built an international community spanning more than 130 countries, leveraging digital-first education, scientific collaboration, and professional networking to improve patient care worldwide. This document presents the IACH Strategic Vision for 2026–2030, outlining a structured roadmap for the Academy’s next phase of growth and international leadership. The strategy is built upon six interdependent pillars: scientific excellence and credibility; digital leadership and intelligent learning; academic alliances and global footprint; innovation, visibility, and advocacy; transparency and sustainability; and brand positioning with global impact. By reinforcing scientific rigor, embracing digital transformation, and promoting innovation, the IACH aims to become the most trusted global reference for clinical hematology education and collaboration. This strategic vision positions the IACH as a unifying platform to unite the world hematology community under one banner of knowledge, collaboration, and compassion, for the benefit of every patient, everywhere.

ABSTRACT Objective This study assessed the impact of sex and age on weight loss outcomes in patients receiving tirzepatide in real‐world clinical practice. Methods We conducted a retrospective cohort study of adults with overweight or obesity who initiated tirzepatide at Mayo Clinic between June 2022 and May 2024 and completed ≥ 12 months of continuous therapy. Primary outcome was total body weight loss percentage (TBWL%) at 15 months, stratified by sex and age groups (≤ 45, 46–59, ≥ 60 years). Results Among 1039 patients (57% women; mean age 56 ± 11 years), women achieved significantly greater TBWL% than men after 15 months of treatment (15.1% vs. 10.7%, p < 0.001). Patients aged ≤ 45 years had greater weight loss than those ≥ 60 years (15.1% vs. 12.3%, p = 0.024). In multivariable analyses, greater weight loss was independently associated with female sex, absence of type 2 diabetes, no prior obesity medication use, no concomitant weight gain‐promoting medications, and higher tirzepatide dosage. Age was not an independent predictor. Conclusions Sex, but not age, predicted weight loss with tirzepatide among individuals using the medication continuously for ≥ 12 months. These findings underscore the importance of incorporating sex‐specific considerations into personalized obesity treatment strategies.

ABSTRACT HLA‐C*01:155 is characterised by a single nucleotide substitution in codon 225 in exon 4.

Coronary artery disease (CAD) remains a leading cause of global morbidity and mortality. Accurate diagnosis of ischemia-causing coronary stenoses is essential for guiding revascularization and improving outcomes. Although invasive fractional flow reserve (FFR) remains the gold standard for functional lesion assessment, its use is limited by procedural invasiveness, cost, and complexity. CT-derived FFR (FFRct), based on computational fluid dynamics (CFD), was the first major advance in noninvasive physiological assessment, but its adoption has been hindered by intensive off-site computation and dependence on high-quality imaging. This review summarizes the evolution from invasive FFR to AI-driven functional assessment of coronary lesions. We examine the principles and validation of CFD-based FFRct and then focus on the shift toward artificial intelligence, including both machine learning (ML) and deep learning (DL) approaches. These methods range from models using engineered geometric and plaque features trained on large synthetic datasets to end-to-end systems that learn directly from imaging data. We discuss key validation studies evaluating diagnostic accuracy, prognostic value, and clinical utility, with attention to performance in challenging settings such as intermediate stenoses, heavy calcification, and patients with comorbidities. We also highlight major barriers to widespread adoption, including dependence on input data quality, limited explainability, regulatory hurdles, and integration into clinical workflows. Finally, we outline future directions, including AI-enabled virtual PCI planning, multimodal risk stratification, and broader access to functional cardiac assessment. AI has the potential to transform noninvasive coronary imaging by enabling a single CCTA scan to provide rapid, integrated evaluation of anatomy, plaque characteristics, and physiological significance, supporting more personalized care and better clinical outcomes.

Background and Objective: This study aimed to characterize clinical characteristics and visual outcomes of patients with hemorrhagic choroidal detachments. Patients and Methods: Single-center retrospective case series of patients with hemorrhagic choroidal detachments from January 1, 2003, to December 31, 2020 at Mayo Clinic. Patients were categorized as appositional or non-appositional based on ultra-sonography. Results: Among 39 cases with hemorrhagic choroidal detachments, 15 (38%) were appositional and 24 (62%) were non-appositional. There was a significant difference between the appositional and non-appositional groups in mean initial logMAR visual acuity (VA) (2.8 [ SD = 0.20] vs 2.2 [ SD = 0.78], P < .001). However, no difference was observed in final logMAR VA (1.9 [ SD = 1.2] vs 1.5 [ SD = 1.1], P = .30). Comparison between surgical ( N = 9) versus non-surgical ( N = 5) hemorrhagic appositional choroidal detachments cases revealed no differences in outcomes. Comparison between anticoagulated ( N = 21) versus nonanticoagulated ( N = 18) patients with hemorrhagic choroidal detachments also revealed no differences in outcomes. Conclusion: Patients with appositional and nonappositional hemorrhagic choroidal detachments did not differ significantly with regards to visual outcome. Surgical intervention was not associated with improved final vision in this cohort.

Accurate assessment of renal function is fundamental to dosing renally eliminated drugs. For decades, serum creatinine–based estimating equations have been used to approximate glomerular filtration rate (GFR) for this purpose. While these equations perform reasonably well at the population level, they exhibit substantial individual‐level imprecision and inaccuracy. Simultaneously, recent efforts to remove race from estimating equations addressed important ethical concerns but did not resolve the core limitation of population‐based estimation for individual drug dosing. In this perspective, we argue that personalized dosing requires a shift away from demographic surrogates toward direct measurement of renal clearance and clarify when incremental therapeutic complexity is warranted. We review the limitations of endogenous biomarkers, discuss the role of cystatin C, and propose exogenously measured GFR using iohexol integrated within a Bayesian pharmacometric framework as a clinically actionable approach to individualized drug dosing. Practically, this framework can be implemented by administering a small iohexol dose, collecting sparse timed samples, estimating absolute mGFR and its uncertainty with Bayesian software, and using that posterior estimate to refine renal dose selection.

Abstract BACKGROUND Remote, smartphone‐based cognitive testing may improve access to cognitive assessments for Alzheimer's disease and related dementias. We evaluated the feasibility, reliability, and validity of unsupervised smartphone‐based cognitive tests in a registry‐based cohort. METHODS Adults without a record of cognitive impairment ( N = 1815; ages 18–92) were recruited from the University of California, San Francisco (UCSF) Brain Health Registry to complete three unsupervised smartphone cognitive testing sessions within 2 weeks. Reliability was assessed with correlations between sessions. Linear regression models tested associations of smartphone tasks with demographics, self‐ and informant‐rated cognitive concerns, and web‐based cognitive testing (Cogstate Brief Battery). RESULTS Adherence was high (82.2%) and usability favorable. Test–retest reliability was moderate to strong ( ρ ’s = 0.61–0.85, all p ’s < 0.001). Lower smartphone scores were associated with older age, lower education, cognitive concerns, and worse Cogstate performance. DISCUSSION Findings support the feasibility, reliability, and validity of remote digital assessments in adults without a record of cognitive impairment.