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Early detection is a key strategy to prevent kidney disease, its progression and related complications, but numerous studies show that awareness of kidney disease at the population level is low. Therefore, increasing knowledge and implementing sustainable solutions for early detection of kidney disease are public health priorities. Economic and epidemiological data underscore why kidney disease should be placed on the global public health agenda — kidney disease prevalence is increasing globally and it is now the seventh leading risk factor for mortality worldwide. Moreover, demographic trends, the obesity epidemic and the sequelae of climate change are all likely to increase kidney disease prevalence further, with serious implications for survival, quality of life and health care spending worldwide. Importantly, the burden of kidney disease is highest among historically disadvantaged populations that often have limited access to optimal kidney disease therapies, which greatly contributes to current socioeconomic disparities in health outcomes. This joint statement from the International Society of Nephrology, European Renal Association and American Society of Nephrology, supported by three other regional nephrology societies, advocates for the inclusion of kidney disease in the current WHO statement on major non-communicable disease drivers of premature mortality.Addressing the burden of non-communicable diseases is a global public health priority. In this joint Consensus Statement, the American Society of Nephrology, the European Renal Association and the International Society of Nephrology highlight the need to recognize kidney disease as a key driver of premature mortality, in addition to other non-communicable diseases already prioritized by the World Health Organization.

Clinical decision-making is one of the most impactful parts of a physician’s responsibilities and stands to benefit greatly from artificial intelligence solutions and large language models (LLMs) in particular. However, while LLMs have achieved excellent performance on medical licensing exams, these tests fail to assess many skills necessary for deployment in a realistic clinical decision-making environment, including gathering information, adhering to guidelines, and integrating into clinical workflows. Here we have created a curated dataset based on the Medical Information Mart for Intensive Care database spanning 2,400 real patient cases and four common abdominal pathologies as well as a framework to simulate a realistic clinical setting. We show that current state-of-the-art LLMs do not accurately diagnose patients across all pathologies (performing significantly worse than physicians), follow neither diagnostic nor treatment guidelines, and cannot interpret laboratory results, thus posing a serious risk to the health of patients. Furthermore, we move beyond diagnostic accuracy and demonstrate that they cannot be easily integrated into existing workflows because they often fail to follow instructions and are sensitive to both the quantity and order of information. Overall, our analysis reveals that LLMs are currently not ready for autonomous clinical decision-making while providing a dataset and framework to guide future studies. Using a curated dataset of 2,400 cases and a framework to simulate a realistic clinical setting, current large language models are shown to incur substantial pitfalls when used for autonomous clinical decision-making.

As the burgeoning field of Artificial Intelligence (AI) continues to permeate the fabric of healthcare, particularly in the realms of patient surveillance and telemedicine, a transformative era beckons. This manuscript endeavors to unravel the intricacies of recent AI advancements and their profound implications for reconceptualizing the delivery of medical care. Through the introduction of innovative instruments such as virtual assistant chatbots, wearable monitoring devices, predictive analytic models, personalized treatment regimens, and automated appointment systems, AI is not only amplifying the quality of care but also empowering patients and fostering a more interactive dynamic between the patient and the healthcare provider. Yet, this progressive infiltration of AI into the healthcare sphere grapples with a plethora of challenges hitherto unseen. The exigent issues of data security and privacy, the specter of algorithmic bias, the requisite adaptability of regulatory frameworks, and the matter of patient acceptance and trust in AI solutions demand immediate and thoughtful resolution .The importance of establishing stringent and far-reaching policies, ensuring technological impartiality, and cultivating patient confidence is paramount to ensure that AI-driven enhancements in healthcare service provision remain both ethically sound and efficient. In conclusion, we advocate for an expansion of research efforts aimed at navigating the ethical complexities inherent to a technology-evolving landscape, catalyzing policy innovation, and devising AI applications that are not only clinically effective but also earn the trust of the patient populace. By melding expertise across disciplines, we stand at the threshold of an era wherein AI's role in healthcare is both ethically unimpeachable and conducive to elevating the global health quotient.

High rates of failure, exorbitant costs, and the sluggish pace of new drug discovery and development have led to a growing interest in repurposing “old” drugs to treat both common and rare diseases, particularly cancer. Cancer, a complex and heterogeneous disease, often necessitates a combination of different treatment modalities to achieve optimal outcomes. The intrinsic polygenicity of cancer, intricate biological signalling networks, and feedback loops make the inhibition of a single target frequently insufficient for achieving the desired therapeutic impact. As a result, addressing these complex or “smart” malignancies demands equally sophisticated treatment strategies. Combinatory treatments that target the multifaceted oncogenic signalling network hold immense promise. Repurposed drugs offer a potential solution to this challenge, harnessing known compounds for new indications. By avoiding the prohibitive costs and long development timelines associated with novel cancer drugs, this approach holds the potential to usher in more effective, efficient, and cost-effective cancer treatments. The pursuit of combinatory therapies through drug repurposing may hold the key to achieving superior outcomes for cancer patients. However, drug repurposing faces significant commercial, technological and regulatory challenges that need to be addressed. This review explores the diverse approaches employed in drug repurposing, delves into the challenges faced by the drug repurposing community, and presents innovative solutions to overcome these obstacles. By emphasising the significance of combinatory treatments within the context of drug repurposing, we aim to unlock the full potential of this approach for enhancing cancer therapy. The positive aspects of drug repurposing in oncology are underscored here; encompassing personalized treatment, accelerated development, market opportunities for shelved drugs, cancer prevention, expanded patient reach, improved patient access, multi-partner collaborations, increased likelihood of approval, reduced costs, and enhanced combination therapy.

During the COVID-19 global pandemic, the cancer community faces many difficult questions. We will first discuss safety considerations for patients with cancer requiring treatment in SARS-CoV-2 endemic areas. We will then discuss a general framework for prioritizing cancer care, emphasizing the precautionary principle in decision making.

Parkinson’s disease (PD) is one of the world’s fastest growing neurological disorders. Much is unknown about PD-associated economic burdens in the United States (U.S.) and other high-income nations. This study provides a comprehensive analysis of the economic burdens of PD in the U.S. (2017) and projections for the next two decades. Multiple data sources were used to estimate the costs of PD, including public and private administrative claims data, Medicare Current Beneficiary Survey, Medical Expenditure Panel Survey, and a primary survey (n = 4,548) designed for this study. We estimated a U.S. prevalence of approximately one million individuals with diagnosed Parkinson’s disease in 2017 and a total economic burden of$51.9 billion. The total burden of PD includes direct medical costs of $ 25.4 billion and$26.5 billion in indirect and non-medical costs, including an indirect cost of $ 14.2 billion (PWP and caregiver burden combined), non-medical costs of$7.5 billion, and $ 4.8 billion due to disability income received by PWPs. The Medicare program bears the largest share of excess medical costs, as most PD patients are over age 65. Projected PD prevalence will be more than 1.6 million with projected total economic burden surpassing $79 billion by 2037. The economic burden of PD was previously underestimated. Our findings underscore the substantial burden of PD to society, payers, patients, and caregivers. Interventions to reduce PD incidence, delay disease progression, and alleviate symptom burden may reduce the future economic burden of PD.

Medical and long-term care for Alzheimer’s disease and related dementias (ADRDs) can impose a large economic burden on individuals and societies. We estimated the per capita cost of ADRDs care in the in the United States in 2016 and projected future aggregate care costs during 2020–2060. Based on a previously published methodology, we used U.S. Health and Retirement Survey (2010–2016) longitudinal data to estimate formal and informal care costs. In 2016, the estimated per patient cost of formal care was$28,078 (95% confidence interval [CI]: $ 25,893– $30,433), and informal care cost valued in terms of replacement cost and forgone wages was $ 36,667 ( $34,025–$ 39,473) and$15,792 ($ 12,980– $18,713), respectively. Aggregate formal care cost and formal plus informal care cost using replacement cost and forgone wage methods were $ 196 billion (95% uncertainty range [UR]:$179–$ 213 billion),$450 billion ($ 424– $478 billion), and $ 305 billion ( $278–$ 333 billion), respectively, in 2020. These were projected to increase to$1.4 trillion ($ 837 billion– $2.2 trillion), $ 3.3 trillion ( $1.9–$ 5.1 trillion), and$2.2 trillion ($ 1.3–$3.5 trillion), respectively, in 2060.

This article uses novel data collected on a weekly basis covering more than 35,000 individuals in the EU to analyze the relationship between trust in various dimensions and COVID-19 vaccine hesitancy. We found that trust in science is negatively correlated, while trust in social media and the use of social media as the main source of information are positively associated with vaccine hesitancy. High trust in social media is found among adults aged 65+, financially distressed and unemployed individuals, and hesitancy is largely explained by conspiracy beliefs among them. Finally, we found that the temporary suspension of the AstraZeneca vaccine in March 2021 significantly increased vaccine hesitancy and especially among people with low trust in science, living in rural areas, females, and financially distressed. Our findings suggest that trust is a key determinant of vaccine hesitancy and that pro-vaccine campaigns could be successfully targeted toward groups at high risk of hesitancy.

The development of dialysis by early pioneers such as Willem Kolff and Belding Scribner set in motion several dramatic changes in the epidemiology, economics and ethical frameworks for the treatment of kidney failure. However, despite a rapid expansion in the provision of dialysis — particularly haemodialysis and most notably in high-income countries (HICs) — the rate of true patient-centred innovation has slowed. Current trends are particularly concerning from a global perspective: current costs are not sustainable, even for HICs, and globally, most people who develop kidney failure forego treatment, resulting in millions of deaths every year. Thus, there is an urgent need to develop new approaches and dialysis modalities that are cost-effective, accessible and offer improved patient outcomes. Nephrology researchers are increasingly engaging with patients to determine their priorities for meaningful outcomes that should be used to measure progress. The overarching message from this engagement is that while patients value longevity, reducing symptom burden and achieving maximal functional and social rehabilitation are prioritized more highly. In response, patients, payors, regulators and health-care systems are increasingly demanding improved value, which can only come about through true patient-centred innovation that supports high-quality, high-value care. Substantial efforts are now underway to support requisite transformative changes. These efforts need to be catalysed, promoted and fostered through international collaboration and harmonization.Dialysis is a life-saving therapy; however, costs of dialysis are high, access is inequitable and outcomes are inadequate. This Review describes the current landscape of dialysis therapy from an epidemiological, economic, ethical and patient-centred framework, and describes initiatives that are aimed at stimulating innovations in the field to one that supports high-quality, high-value care.

Neurological disorders are the leading cause of global disability. However, for most people around the world, current neurological care is poor. In low-income countries, most individuals lack access to proper neurological care, and in high-income countries, distance and disability limit access. With the global proliferation of smartphones, teleneurology -- the use of technology to provide neurological care and education remotely -- has the potential to improve and increase access to care for billions of people. Telestroke has already fulfilled this promise, but teleneurology applications for chronic conditions are still in their infancy. Similarly, few studies have explored the capabilities of mobile technologies such as smartphones and wearable sensors, which can guide care by providing objective, frequent, real-world assessments of patients. In low-income settings, teleneurology can increase the capacity of local care systems through professional development, diagnostic support and consultative services. In high-income settings, teleneurology is likely to promote the expansion and migration of neurological care away from institutions, incorporate systems of asynchronous communication (such as e-mail), integrate clinicians with diverse skill sets and reach new populations. Inertia, outdated policies and social barriers -- especially the digital divide -- will slow this progress at considerable cost. However, a future increasingly will be possible in which neurological care can be accessed by anyone, anywhere. Here, we examine the emerging evidence regarding the benefits of teleneurology for chronic conditions, its role and risks in low-income countries and the promise of mobile technologies to measure disease status and deliver care. We conclude by discussing the future trends, barriers and timing for the adoption of teleneurology.