Citations

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, impacting approximately 6.1 million adults in the United States, with projections to increase two-fold by 2030. AF significantly increases the risk of stroke and other adverse cardiovascular events, leading to increased morbidity and mortality. The 2023 ACC/AHA/ACCP/HRS guidelines present a paradigm shift in AF management, moving from a duration-based classification to a more comprehensive, patient-centered approach. This includes a novel AF classification system that emphasizes early detection and intervention, including risk factors and lifestyle modification tailored to each patient’s risk profile. Moreover, the recommendations advocate for a multidisciplinary care model, ensuring coordinated management involving primary care providers and specialists. Primary care providers play a crucial role in initiating risk factor management and lifestyle interventions, even before the development of AF. This review aims to thoroughly examine the guidelines for the diagnosis and management of AF and equip general internists with the necessary insights to navigate the evolving landscape of AF care effectively.

The gut–brain axis plays an integral role in maintaining overall health, with growing evidence suggesting its impact on the development of various neuropsychiatric disorders, including depression. This review explores the complex relationship between gut microbiota and glutamate (Glu) regulation, highlighting its effect on brain health, particularly in the context of depression following certain neurological insults. We discuss how microbial populations can either facilitate or limit Glu uptake, influencing its bioavailability and predisposing to neuroinflammation and neurotoxicity. Additionally, we examine the role of gut metabolites and their influence on the blood–brain barrier and neurotransmitter systems involved in mood regulation. The therapeutic potential of microbiome-targeted interventions, such as fecal microbiota transplantation, is also highlighted. While much research has explored the role of Glu in major depressive disorders and other neurological diseases, the contribution of gut microbiota in post-neurological depression remains underexplored. Future research should focus on explaining the mechanisms linking the gut microbiota to neuropsychiatric outcomes, particularly in conditions such as post-stroke depression, post-traumatic brain-injury depression, and epilepsy-associated depression. Systematic reviews and human clinical studies are needed to establish causal relationships and assess the efficacy of microbiome-targeted therapies in improving the neuropsychiatric sequalae after neurological insults.

Pancreatic cystic lesions (PCLs) represent a spectrum of non-neoplasms and neoplasms with varying malignant potential, posing significant challenges in diagnosis and management. While some PCLs are precursors to pancreatic cancer, others remain benign, necessitating accurate differentiation for optimal patient care. Conventional approaches to PCL management rely heavily on radiographic imaging, and endoscopic ultrasound (EUS) guided fine-needle aspiration (FNA), coupled with clinical and biochemical data. However, the observer-dependent nature of image interpretation and the complex morphology of PCLs can lead to diagnostic uncertainty and variability in patient management strategies. This review critically evaluates current PCL diagnosis and surveillance practices, showing features of the different lesions and highlighting the potential limitations of conventional methods. We then explore the potential of artificial intelligence (AI) to transform PCL management. AI-driven strategies, including deep learning algorithms for automated pancreas and lesion segmentation, and radiomics for analyzing heterogeneity, can improve diagnostic accuracy and risk stratification. These advanced techniques can provide more objective and reproducible assessments, aiding clinicians in decision-making regarding follow-up intervals and surgical interventions. Early results suggest that AI-driven methods can significantly improve patient outcomes by enabling earlier detection of high-risk lesions and reducing unnecessary procedures for benign cysts. Finally, this review emphasizes that AI-driven approaches could potentially reshape the landscape of PCL management, ultimately leading to improved pancreatic cancer prevention.

Abstract Genome-wide DNA methylation signatures correlate with and distinguish central nervous system (CNS) tumor types. Since the publication of the initial CNS tumor DNA methylation classifier in 2018, this platform has been increasingly used as a diagnostic tool for CNS tumors, with multiple studies showing the value and utility of DNA methylation-based classification of CNS tumors. A Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT-NOW) Working Group was therefore convened to describe the current state of the field and to provide advice based on lessons learned to date. Here, we provide recommendations for the use of DNA methylation-based classification in CNS tumor diagnostics, emphasizing the attributes and limitations of the modality. We emphasize that the methylation classifier is one diagnostic tool to be used alongside previously established diagnostic tools in a fully integrated fashion. In addition, we provide examples of the inclusion of DNA methylation data within the layered diagnostic reporting format endorsed by the World Health Organization (WHO) and the International Collaboration on Cancer Reporting. We emphasize the need for backward compatibility of future platforms to enable accumulated data to be compatible with new versions of the array. Finally, we outline the specific connections between methylation classes and CNS WHO tumor types to aid in the interpretation of classifier results. It is hoped that this update will assist the neuro-oncology community in the interpretation of DNA methylation classifier results to facilitate the accurate diagnosis of CNS tumors and thereby help guide patient management.

Abstract US clinical practice guidelines for the diagnostic evaluation of cognitive impairment due to Alzheimer's disease (AD) or AD and related dementias (ADRD) are decades old and aimed at specialists. This evidence‐based guideline was developed to empower all—including primary care—clinicians to implement a structured approach for evaluating a patient with symptoms that may represent clinical AD/ADRD. Through a modified‐Delphi approach and guideline‐development process (7374 publications were reviewed; 133 met inclusion criteria) an expert workgroup developed recommendations as steps in a patient‐centered evaluation process. This summary focuses on recommendations, appropriate for any practice setting, forming core elements of a high‐quality, evidence‐supported evaluation process aimed at characterizing, diagnosing, and disclosing the patient's cognitive functional status, cognitive–behavioral syndrome, and likely underlying brain disease so that optimal care plans to maximize patient/care partner dyad quality of life can be developed; a companion article summarizes specialist recommendations. If clinicians use this guideline and health‐care systems provide adequate resources, outcomes should improve in most patients in most practice settings. Highlights US clinical practice guidelines for the diagnostic evaluation of cognitive impairment due to Alzheimer's disease (AD) or AD and related dementias (ADRD) are decades old and aimed at specialists. This evidence‐based guideline was developed to empower all—including primary care—clinicians to implement a structured approach for evaluating a patient with symptoms that may represent clinical AD/ADRD. This summary focuses on recommendations, appropriate for any practice setting, forming core elements of a high‐quality, evidence‐supported evaluation process aimed at characterizing, diagnosing, and disclosing the patient's cognitive functional status, cognitive–behavioral syndrome, and likely underlying brain disease so that optimal care plans to maximize patient/care partner dyad quality of life can be developed; a companion article summarizes specialist recommendations. If clinicians use this guideline and health‐care systems provide adequate resources, outcomes should improve in most patients in most practice settings.

Abstract US clinical practice guidelines for the diagnostic evaluation of cognitive impairment due to Alzheimer's disease (AD) or a related dementia (ADRD) are two decades old. This evidence‐based guideline was developed to empower all clinicians to implement a structured approach for evaluating a patient with symptoms that may represent clinical AD/ADRD. An expert workgroup conducted a review of 7374 publications (133 met inclusion criteria) and developed recommendations as steps in an evaluation process. This summary briefly reviews core recommendations and details specialist recommendations of a high‐quality, evidence‐supported evaluation process aimed at characterizing, diagnosing, and disclosing the patient's cognitive functional status, cognitive–behavioral syndrome, and likely underlying brain disease so that optimal care plans to maximize patient/care partner dyad quality of life can be developed; a companion article summarizes primary care recommendations. If clinicians use the recommendations in this guideline and health‐care systems provide adequate resources, outcomes should improve in most patients in most practice settings. Highlights US clinical practice guidelines for the diagnostic evaluation of cognitive impairment due to Alzheimer's disease (AD) or related dementias (ADRD) are decades old and aimed at specialists. This evidence‐based guideline was developed to empower all—including primary care—clinicians to implement a structured approach for evaluating a patient with symptoms that may represent clinical AD/ADRD. This summary focuses on recommendations appropriate for specialty practice settings, forming key elements of a high‐quality, evidence‐supported evaluation process aimed at characterizing, diagnosing, and disclosing the patient's cognitive functional status, cognitive–behavioral syndrome, and likely underlying brain disease so that optimal care plans to maximize patient/care partner dyad quality of life can be developed; a companion article summarizes primary care recommendations. If clinicians use this guideline and health‐care systems provide adequate resources, outcomes should improve in most patients in most practice settings.

Abstract US clinical practice guidelines for the diagnostic evaluation of cognitive impairment due to Alzheimer's Disease (AD) or AD and related dementias (ADRD) are decades old and aimed at specialists. This evidence‐based guideline was developed to empower all—including primary care—clinicians to implement a structured approach for evaluating a patient with symptoms that may represent clinical AD/ADRD. As part of the modified Delphi approach and guideline development process (7374 publications were reviewed; 133 met inclusion criteria) an expert workgroup developed recommendations as steps in a patient‐centered evaluation process. The workgroup provided a summary of validated instruments to measure symptoms in daily life (including cognition, mood and behavior, and daily function) and to test for signs of cognitive impairment in the office. This article distills this information to provide a resource to support clinicians in the implementation of this approach in clinical practice. The companion articles provide context for primary care and specialty clinicians with regard to how to fit these instruments into the workflow and actions to take when integration of performance on these instruments with clinical profile and clinician judgment support potential cognitive impairment.

Abstract INTRODUCTION Psychotropic medication (PM) use in behavioral‐variant frontotemporal dementia (bvFTD) is higher than in other dementias. However, no information exists on whether PM use differs between sporadic and genetic bvFTD. METHODS We analyzed data from sporadic and genetic bvFTD participants with PM prescriptions in the Advancing Research and Treatment in Frontotemporal Lobar Degeneration/Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects study. We estimated ordinal odds ratio (OOR) of having more PM comparing sporadic and genetic bvFTD. Finally, we explored the neuropsychiatric symptom (NPS) combinations using classification and regression trees (CART). RESULTS We included 263 with sporadic and 193 with genetic bvFTD. The OOR for sporadic bvFTD to be on PM was 1.75 (95% confidence interval: 1.21 to 2.53) for the fully adjusted model. CART revealed the most common NPS combination was apathy + personality changes in 18% of participants. DISCUSSION Participants with sporadic bvFTD were twice as likely to be on PM compared to genetic bvFTD. The reason for increased PM usage in sporadic bvFTD participants should be further investigated. Highlights We report on patients with behavioral variant frontotemporal dementia (bvFTD). We evaluated the psychotropic medication (PM) prescription at baseline in the cohort. Patients with sporadic bvFTD had more prescriptions for PM than genetic patients. The frequency of symptoms combination was different in sporadic and genetic bvFTD.