Seasonal influenza is a contagious viral respiratory illness that causes yearly epidemics.

There is limited evidence of the strategies to mitigate burnout among all health care professionals (HCPs).

Sepsis is the leading cause of death worldwide. Mortality has improved in the past few decades but remains high, and survivors frequently have long-term complications. Initial diagnostic evaluation focuses on risk stratification and source and pathogen identification. Treatment includes intravenous fluids, vasopressors, steroids if shock is present, antimicrobial therapy targeting the most likely source of infection, and source control. Patients with shock or high-risk organ failure syndromes should be admitted early to an intensive care unit. After initial antimicrobials and resuscitation, care should focus on antimicrobial deescalation, volume management, and high-quality supportive care. Shared decision making about goals of care and transitions is important to support survivors after discharge.

Health care systems are investing significant resources in social needs screening and intervention programs.

Perinatal depression can have a deleterious impact on mothers and infants.

Cardiac implantable electronic devices (CIEDs) have increased the quality and duration of life for millions of patients. As their utilization continues to grow exponentially, clinicians need to diagnose and manage several device-associated complications that may arise during the CIED life cycle. This primer is tailored for the general internal medicine physician or hospitalist, who will inevitably take care of patients with CIEDs, to provide a contemporary update on the incidence and clinical manifestations of the 4 most common CIED complications, with the latest evidence to guide clinical management and expected outcomes. Specifically, this review focuses on: 1) generator/lead failure, which has decreased to less than 1% per year due to continuous advances in manufacturing and programming and is mostly managed conservatively with close monitoring; 2) CIED infections, which, while also rare at approximately 1% per year, carry a short-term mortality of 10% to 20%, thus requiring immediate diagnosis and often urgent treatment with lead extraction because antibiotic treatment is rarely effective; and 3) lead-related venous obstruction, which has highly variable incidence (5% to 30%) and manifestations, ranging from arm swelling to superior vena cava syndrome. Management options range from anticoagulation to balloon venoplasty, often with unsatisfying results. This review will also focus on 4) lead-related tricuspid regurgitation, which affects 20% to 30% of CIEDs and has become an area of intense interest with the development of percutaneous tricuspid treatments-where evidence is urgently needed to inform the need for lead extraction versus jailing during tricuspid interventions. The progressive adoption of leadless devices may significantly reduce many of these complications. Nonetheless, optimal management requires input from a multidisciplinary team of electrophysiologists and imaging, heart failure, and structural interventional specialists-who should be able to recognize and treat each complication promptly based on a rapidly evolving evidence base.

Chronic coronary artery disease (CCAD) is a leading cause of death in the United States and many other countries. The defining pathobiology is an imbalance between the metabolic demands of the myocardium and oxygen supply, which most often results from coronary artery atherosclerosis. The classic presenting symptom of CCAD is angina, but clinical presentation varies greatly among patients. Since the last In the Clinic on CCAD (previously termed "stable ischemic heart disease") in 2019, several new medications have been approved to reduce ischemic complications.

Screening for multiple types of cancer with a single blood test is potentially transformative.

Electronic health record (EHR) data are increasingly used to develop prediction models that guide clinical decision making at the point of care. These include algorithms that use high-frequency data, like in sepsis prediction, as well as simpler equations, such as the Pooled Cohort Equations for cardiovascular outcome prediction. Although EHR data used in prediction models are often highly granular and more current than other data, there is systematic and nonsystematic missingness in EHR data as there is with most data. Despite growing use for clinical decisions, algorithms implemented in EHRs are mostly unregulated and are often opaque to the user. Guidelines about the development, validation, implementation, and reporting on clinical prediction models are sparse in their recommendations regarding missing data. This article characterizes missingness in EHR data, summarizes methods for attending to missing data when developing prediction models, makes recommendations about validation and implementation of models in practice when data are missing, and identifies research needs in this field.

Nearly 14% of Americans have chronic kidney disease (CKD), which includes persistent decrements in glomerular filtration rate or the presence of albuminuria. Although CKD is commonly attributed to diabetes or hypertension, there is growing awareness of the interplay among cardiovascular, kidney, and metabolic health. Progression of CKD can result in metabolic abnormalities and end-stage kidney disease, but cardiovascular events are even more common. The main goals of CKD treatment include slowing the decline in kidney function, preventing cardiovascular disease, and treating metabolic complications. Recent pharmacologic advancements have yielded effective therapeutic agents capable of concurrently addressing all of these objectives.

Rapid changes in the legalized cannabis market have led to the predominance of high-concentration delta-9-tetrahydrocannabinol (THC) cannabis products.

Accurate blood pressure measurement (BPM) is essential for managing hypertension, but previous studies have not systematically compared different monitoring methods across varying BP levels. To address this gap, a comprehensive analysis using network meta-analysis (NMA) and meta-regression was done to evaluate their agreement and clinical implications.

Irritable bowel syndrome (IBS) is a common gastrointestinal disorder, with a prevalence of 4% to 10%. It is a chronic condition characterized by abdominal pain in conjunction with altered bowel habits, abdominal distention, or bloating. IBS can present with 3 different defecation patterns: IBS with constipation, IBS with diarrhea, or mixed IBS. Recent advances in IBS include a positive diagnosis based on symptom-based criteria and a treatment plan based on IBS subtype and bothersome symptoms. In addition to diet and lifestyle modifications, this article discusses the role of new pharmacologic and nonpharmacologic treatment options for the management of IBS.

It is unclear whether weight loss before in vitro fertilization (IVF) improves reproductive outcomes in women with obesity.

Engineering infection controls include a wide range of interventions used indoors to reduce occupants' exposure to respiratory pathogens.

Ablation of atrial fibrillation can restore normal heart rhythm, but its effect on clinical outcomes is uncertain.

Risk adjustment is a critical component of health care reimbursement aimed at ensuring fair compensation on the basis of the characteristics of patients receiving care. Optimizing risk adjustment is not just a matter of improving efficiency or predictive accuracy; it is a crucial step toward achieving health equity by ensuring that resources are directed toward patients who need them most and reducing incentives to exclude or neglect high-risk patients. The authors reviewed available publications from PubMed and Google Scholar published between 2000 and 2025, as well as relevant news articles, policy documents, websites, and other sources related to risk adjustment and application areas. This process yielded 8 recommendations related to standardizing risk adjustment methods, promoting data interoperability, implementing strategies to enable more accurate and continuous reflections of patients' health status, integrating valid and reliable metrics into regular evaluation and feedback mechanisms, limiting "gaming" opportunities and incentives, creating valid ways to measure costs of caring for patients who are experiencing health care disparities and inequities and/or are disproportionately affected by social drivers of health, evaluating and leveraging advanced analytics and machine learning when able to improve risk adjustment models, and promoting research and implementation methods that combine elements of both prospective and concurrent risk adjustment. Implementation of these risk adjustment recommendations has broad implications for various entities in the health care ecosystem.

Climate change is anticipated to continue to adversely affect public health, with heat stress the predominant threat. Accordingly, heat-related illness is predicted to increase as extremely hot days become more frequent. Heat stroke, the most serious heat-related illness, is a medical emergency that may be fatal if it is not promptly recognized, addressed with early and rapid cooling, and accompanied by multidisciplinary supportive care as clinically indicated. Heat stroke is a preventable illness that occurs in 2 distinct forms-classic and exertional-that have distinct demographic profiles and clinical courses but similar management paradigms.

Large language models (LLMs) offer substantial promise for improving health care; however, some risks warrant evaluation and discussion. This study assessed the effectiveness of safeguards in foundational LLMs against malicious instruction into health disinformation chatbots. Five foundational LLMs-OpenAI's GPT-4o, Google's Gemini 1.5 Pro, Anthropic's Claude 3.5 Sonnet, Meta's Llama 3.2-90B Vision, and xAI's Grok Beta-were evaluated via their application programming interfaces (APIs). Each API received system-level instructions to produce incorrect responses to health queries, delivered in a formal, authoritative, convincing, and scientific tone. Ten health questions were posed to each customized chatbot in duplicate. Exploratory analyses assessed the feasibility of creating a customized generative pretrained transformer (GPT) within the OpenAI GPT Store and searched to identify if any publicly accessible GPTs in the store seemed to respond with disinformation. Of the 100 health queries posed across the 5 customized LLM API chatbots, 88 (88%) responses were health disinformation. Four of the 5 chatbots (GPT-4o, Gemini 1.5 Pro, Llama 3.2-90B Vision, and Grok Beta) generated disinformation in 100% (20 of 20) of their responses, whereas Claude 3.5 Sonnet responded with disinformation in 40% (8 of 20). The disinformation included claimed vaccine-autism links, HIV being airborne, cancer-curing diets, sunscreen risks, genetically modified organism conspiracies, attention deficit-hyperactivity disorder and depression myths, garlic replacing antibiotics, and 5G causing infertility. Exploratory analyses further showed that the OpenAI GPT Store could currently be instructed to generate similar disinformation. Overall, LLM APIs and the OpenAI GPT Store were shown to be vulnerable to malicious system-level instructions to covertly create health disinformation chatbots. These findings highlight the urgent need for robust output screening safeguards to ensure public health safety in an era of rapidly evolving technologies.

In January 2025, the Republican majority in the House of Representatives' Budget Committee offered a list of possible spending reductions to offset revenue losses from proposed tax cuts. In May, the Committee advanced a bill incorporating several reductions on the list. The Committee estimated that the 6 largest potential Medicaid cuts (for example, work requirements for some Medicaid enrollees) would each reduce the federal government's Medicaid outlays by at least $100 billion over 10 years. On the basis of the Committee's estimates of savings; Congressional Budget Office analyses; and peer-reviewed studies of the coverage, financial, and health impacts of past Medicaid expansions and contractions, the authors project the likely effects of each option and of the House bill advanced by the Budget Committee in May. Each option individually would reduce federal Medicaid outlays by between $100 billion and $900 billion over a decade, increase the ranks of the uninsured by between 600 000 and 3 900 000 and the annual number of persons forgoing needed medical care by 129 060 to 838 890, and result in 651 to 12 626 medically preventable deaths annually. Enactment of the House bill advanced in May would increase the number of uninsured persons by 7.6 million and the number of deaths by 16 642 annually, according to a mid-range estimate. These figures exclude harms from lowering provider payments and shrinking benefits, as well as possible repercussions from states increasing taxes or shifting expenditures from other needs to make up for shortfalls in federal Medicaid funding. Policy makers should weigh the likely health and financial harms to patients and providers of reducing Medicaid expenditures against the desirability of tax reductions, which would accrue mostly to wealthy Americans.