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Medscape
23 minutes ago
- Medscape
The Hidden Hazards of Generative AI in Medicine
The idiosyncrasies and inadequacies of NHS IT systems — past and present — have driven many a doctor to frustration and despair, as they grapple with yet another new software package whilst trying to manage patient demand. There is an understandable reluctance to embrace change, given that change has rarely delivered the promised efficiencies. It is perhaps unsurprising, therefore, that some healthcare professionals view artificial intelligence (AI) with suspicion. Dr Sara Jamieson Even those who have embraced it and are optimistic about its benefits admit they're unsure about the risks. AI, though, is different from anything that has come before. It is something we should consider embracing and incorporating into our practice as it develops. If we don't, we risk being left behind. Imagine how life might look if we had ignored the introduction of the World Wide Web back in the mid-90s. Similarly, think back to the rapid introduction of telemedicine at the start of the COVID-19 pandemic. This method of consulting with patients, previously frowned upon as too inherently risky, continued even after infection levels subsided. Any new way of practising will bring with it new medicolegal risks, and steps will need to be considered to mitigate these. Whilst beyond the scope of this article, a true understanding of the medicolegal implications of using AI in healthcare requires an understanding of what AI is and how its outputs are generated. This is particularly true for generative AI tools such as ChatGPT. Dr Lucy Hanington According to a survey of over 1000 GPs in the UK, published in BMJ Health & Care Informatics, a fifth of GPs are using generative AI tools such as ChatGPT to help with day-to-day tasks such as writing letters. One in five said they had used these tools in their clinical practice, and of these, nearly a third (28%) said they had used them to suggest a different diagnosis, and a quarter said they had used them to suggest treatment options. Consider this scenario: Dr C, a GP, was running behind schedule and still had three more patients to see. During her next consultation, a 50-year-old patient, Mr B, came in with a set of vague symptoms. Dr C considered a range of possible conditions. Feeling under pressure, she discreetly opened ChatGPT and entered an anonymised summary of the patient's symptoms, requesting a differential diagnosis and possible lab tests. The AI quickly returned a detailed summary of plausible possibilities, including some that Dr C hadn't considered herself. She was impressed and used the suggestions to help her decide on the next steps for Mr B, which included arranging further tests. That night, however, the consultation weighed on her mind, and she couldn't sleep. She knew she hadn't disclosed her use of AI to the patient. She also worried whether she had inadvertently input details that could make Mr B identifiable. She also questioned whether the AI's suggested diagnoses might have influenced her clinical judgement. By morning, Dr C was feeling anxious and uneasy, and decided to call Medical Protection Society (MPS) for advice. A medicolegal consultant advised her to consider whether, objectively, she still agreed with the management plan and could justify it clinically. The GP was also advised to rectify any omissions immediately and to discuss the case with a colleague if helpful. The medicolegal consultant also explained the consent and confidentiality principles around AI use. Benefits Generative AI tools offer many potential benefits for both doctors and patients. Patients may use these tools to understand medical terminology or a diagnosis they have been given. Doctors may find that, when used safely, generative AI can aid diagnosis or identify potential drug interactions. However, generative AI is not always correct. As well as errors or omissions, it can sometimes produce 'hallucinations,' confidently presenting incorrect information as fact. It is incumbent on the clinicians using these tools to ensure that information shared with a patient is reliable and accurate. Bias, whilst not unique to AI, also deserves consideration. The data used by AI tools may be biased due to the inclusion or exclusion of certain information. Outputs may also fail to account for the demographics of a particular patient population. The use of generative AI does not permit doctors to work outside the limits of their competence. There should be no overreliance on the software, and doctors remain ultimately responsible for the decisions they make. Data Protection and Confidentiality Data protection and confidentiality, as highlighted in the earlier scenario, are key considerations. Compliance with General Data Protection Regulation is essential when using generative AI. These tools, by their nature, store, share, and learn from the information entered into them and can be accessed by anyone. Care must be taken not to input any personal patient data. Simply removing a patient's name may not be sufficient to anonymise their information, as other details could make them identifiable. To ensure compliance with data protection legislation, we recommend seeking guidance from: Hospital Data Protection Officers, who may be able to advise on this in a secondary care setting Integrated Care Boards, who may have policies that would be applicable The Information Commissioners Office (ICO) Consent The earlier scenario also highlights the issue of consent. Consent remains a key cornerstone of all doctor-patient interactions. The ICO advises that, for consent to be a lawful basis for processing data when using AI, it must be freely given, specific, and clear. The individual must agree to it, and they must be able to withdraw their consent at any time. AI as an Aid It is important to hold in mind that AI is a tool to assist, rather than replace, the clinician. When it comes to decision-making, AI software can't readily consider the individual wishes and circumstances of the patient. The 'black box' problem — a lack of transparency in how an AI system reaches conclusions — can make it difficult to challenge outputs or detect errors. Ultimately, AI should not replace clinical reasoning, evidence-based medicine, or consultation with colleagues, peers, multidisciplinary teams, specialists, seniors, and supervisors. Training and Continued Learning Clinicians should aim to be literate in AI, understand its basis and governance, and know how to use it safely. We would encourage all clinicians to incorporate learning on the topic as part of their annual development plans. A multitude of resources on AI are available across medical colleges and institutions. We would also recommend watching the recordings of the recent MPS Foundation AI symposia. A white paper, published by the MPS Foundation, the Centre for Assuring Autonomy at the University of York, and the Improvement Academy hosted at the Bradford Institute for Health Research, offers further useful guidance for doctors to consider on AI use. Conclusion Like it or not, AI is here to stay. Readers should consider its potential benefits while remaining alive to its limitations and risks. Doctors should also ensure they continue to work in a manner consistent with General Medical Council guidance and relevant legislation. If in doubt about using AI tools and their medicolegal implications, doctors can contact MPS or their medical defence organisation to request advice. This article is published as part of an editorial collaboration between Medscape UK and MPS that aims to deliver medicolegal content to help healthcare professionals navigate the many challenges they face in their clinical practice. Dr Sara Jamieson, MBBS, trained in psychiatry before joining MPS in 2016 as a medicolegal consultant. She has disclosed no relevant financial relationships. Dr Lucy Hanington, BMBCh, MRCPCH, has worked as a medicolegal consultant at MPS since 2016. She has disclosed no relevant financial relationships.
Medscape
an hour ago
- Medscape
Talk Therapy Less Effective in Young vs Middle-Aged Adults
TOPLINE: NHS Talking Therapies for anxiety and depression (TTad) were less effective for adults aged 16-24 years than for those aged 25-65 years, a cohort study of over 1.5 million people revealed. METHODOLOGY: Researchers conducted a retrospective cohort study using the data of 309,758 young adults (aged 16-24 years; 69.4% women; 82.5% White) and 1,290,130 working-age adults (aged 25-65 years; 65.2% women; 83.6% White) who received psychological treatment through England's NHS TTad services between 2015 and 2019. The primary outcome was the change in symptom severity scores on the Patient Health Questionnaire nine-item (PHQ-9) and Generalised Anxiety Disorder Scale seven-item (GAD-7) between age groups. Secondary outcomes were rates of recovery, reliable recovery, reliable improvement, and reliable deterioration. The analysis was adjusted for gender, ethnicity, local area deprivation, clinical factors, treatment intensity, and the number of sessions. Sensitivity analyses included geographical and temporal variation in age-related differences and adults older than 65 years in the working-age group. TAKEAWAY: Differences in pre-post symptom severity scores on the PHQ-9 and GAD-7 increased with age. In the unadjusted analysis, young adults experienced smaller improvements in PHQ-9 and GAD-7 scores than working-age adults (PHQ-9: b, -0.98; GAD-7: b, -0.77; P < .001 for both). The magnitude of difference was smaller in the adjusted analysis. Young adults had lower rates of reliable recovery (41.5% vs 48.2%; adjusted odds ratio [aOR], 0.76), reliable improvement (68.6% vs 72.6%; aOR, 0.83), and recovery (43.7% vs 51.1%; aOR, 0.74) but higher rates of reliable deterioration (5.9% vs 5.2%; aOR, 1.15) than working-age adults. Age-related differences were consistent across regions and treatment years, with London having the smallest difference (3.0%) and the South West having the largest difference (~6.5%), and unchanged when including adults older than 65 years. IN PRACTICE: "Getting young adults into treatment more quickly, offering them treatment in a convenient and desired format, and working hard to ensure they stay in treatment have the potential to improve outcomes for this group. Addressing social factors that are of particular concern to emerging adults — eg, job and housing insecurity — might also be required to improve outcomes in young adults," the authors wrote. "Considering and trialling adaptions tailored to specific requirements of this age group, the management of information on mental health and mental illness, as well as expectations of treatment, might also be necessary," they added. SOURCE: This study was led by Rob Saunders, PhD, and Jae Won Suh, DPhil, University College London, London, England. It was published online on August 6 in The Lancet Psychiatry. LIMITATIONS: The use of routinely recorded health service data limited the availability of measures on general well-being and personal sense of improvement. Although the analysis was adjusted for neurodevelopmental conditions such as autism, attention-deficit/hyperactivity disorder, and intellectual disability, the severity of these conditions and other potential confounders, such as gender identity, sexual orientation, and social support, were not captured. Moreover, unmeasured differences in treatment delivery and other common disorders in young adults may have influenced the results, and the findings were not generalisable to non-binary individuals due to limited data availability. DISCLOSURES: This study was funded by the UK National Institute for Health and Care Research. The authors reported having no conflicts of interest. This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.
Yahoo
2 hours ago
- Yahoo
Understanding tick immunity may be key to preventing killer viruses from spreading
A tiny tick crawls across your skin, potentially carrying a virus so lethal it kills up to four out of every ten people it infects. Yet that same tick shows no signs of illness whatsoever – it feeds, moves and reproduces as if nothing is wrong. Scientists studying severe fever with thrombocytopenia syndrome virus (SFTSV) have long wondered why this happens. The pathogen, first identified in China in 2009, causes high fevers, bleeding and organ failure in humans, but leaves ticks completely unharmed. Alongside colleagues, I conducted research into how ticks can carry deadly viruses without becoming ill themselves. Understanding these resistance mechanisms could help scientists develop new ways to block or weaken tick-borne diseases before they spill over into humans or animals. The findings come as climate change pushes ticks into new territories around the world. The Asian longhorned tick that carries SFTSV has been identified in Australia, New Zealand and the eastern US, raising concerns the disease could spread to regions that have never seen it before. Unlike mice, humans or even mosquitoes, ticks pose a unique scientific challenge: most of the molecular tools researchers use to study infection simply don't work in ticks. Instead, we turned to data analysis. We captured detailed molecular snapshots of infected tick cells, tracking thousands of genes and more than 17,000 proteins simultaneously. This allowed the team to study the cellular response comprehensively, at different time post-infection. We found that while human cells respond to viral invasion by mounting aggressive immune responses, mobilising multiple defence systems to fight the infection, tick cells take a fundamentally different approach. Survival strategy Ticks do have immune systems but they operate very differently from ours. Like humans, ticks have cellular signalling pathways that help detect and respond to infection. Known as Toll, IMD and JAK-STAT, these pathways coordinate defensive responses and trigger the production of antimicrobial proteins. But when infected with SFTSV, the tick's immune system showed only minimal activity. Instead of launching full-scale defensive responses, these pathways remained largely quiet. The virus appears to have evolved ways to avoid triggering the tick's immune alarm bells. Instead, the tick cells made major changes to their stress response systems, their production of RNA and proteins, and the pathways that control cell death. (RNA is a molecule that carries genetic instructions – like a working copy of DNA – used by cells to make proteins.) Rather than attacking the virus head-on, tick cells seem to tolerate the infection, reorganising their internal machinery to manage the damage while continuing to function. This approach makes evolutionary sense when you consider the constraints these tiny creatures face. Mounting a full-blown immune response is energetically expensive – it requires lots of resources and can harm the host's own tissues. For ticks, which feed only a few times in their life and live off limited energy reserves, a gentler response may be more sustainable. And because this virus has likely been infecting ticks for millions of years, the two have had time to adapt to each other. Rather than killing the host, the virus may have evolved to fly under the radar, while the tick evolved ways to tolerate it – allowing both to survive and reproduce. Unexpected antiviral guardians We identified two key proteins that act as molecular RNA quality controllers. These proteins, called UPF1 and DHX9, are ancient guardians found in all complex life forms, from plants to humans. One of their normal functions involves monitoring and controlling the quality of RNA, the molecular messenger that carries genetic instructions around cells. Think of them as cellular proofreaders, constantly checking that genetic messages are accurate and functional. My research team first identified these proteins when they appeared as cellular partners that directly interact with viral proteins inside infected cells. This discovery intrigued us because UPF1 and DHX9 were unexpected candidates – they aren't typically associated with antiviral defence – yet they seemed perfectly positioned to detect or process viral RNA, likely because these proteins normally scan RNA for errors, making them well-suited to spot the unusual structures often found in viral genetic material. To test whether these proteins fight the virus, we used genetic techniques to silence the expression of UPF1 and DHX9 in tick cells, essentially removing these molecular guardians. We found that SFTSV viral growth increased significantly when these proteins were absent, demonstrating their antiviral function. This suggests that ticks may have evolved a different kind of immune defence known as non-canonical immunity. Instead of attacking viruses head-on using traditional immune systems, ticks seem to use more subtle strategies. In this case, their RNA quality-control proteins act as internal monitors. Because viral RNA often looks different from normal cellular RNA, these proteins may recognise it as unusual. Once detected, they can trigger internal control systems that slow down or block the virus from multiplying – helping the tick stay healthy without a full-blown immune response. Our research has important implications because UPF1 and DHX9 proteins exist in human cells too. Understanding how they work in ticks could reveal new ways to strengthen human antiviral defences or develop treatments that enhance these natural quality-control mechanisms. The research also opens possibilities for using these tolerance mechanisms to stop disease – either by strengthening similar defences in humans and animals, or by targeting them in ticks to break the chain of transmission. Future strategies might involve boosting antiviral proteins in wild tick populations or developing treatments that specifically target virus-tick interactions. Traditional approaches to disease control are struggling to keep up, especially as climate change helps ticks expand into new regions. To prevent future outbreaks, we need a deeper understanding of how ticks, and the viruses they carry, interact with both humans and animals. Learning how these tiny creatures tolerate deadly pathogens could be key to developing new tools that make people and animals less vulnerable to these diseases – or prevent ticks from passing them on in the first place. This article is republished from The Conversation under a Creative Commons license. Read the original article. Marine J. Petit receives funding from European Union's Horizon 2020 Research and Innovation Program under the Marie Skłodowska-Curie grant agreement No 890970.
