The landmark review, published in JAMA Internal Medicine, provides general practitioners and physiotherapists with an updated roadmap for managing shoulder pain.

It suggests that simple supportive care delivers better patient outcomes in most cases, rather than unnecessary scans and invasive procedures.

Shoulder pain affects nearly one in six adults each year, making it the third most common musculoskeletal complaint in primary care, trailing only behind back and knee conditions.

For most of these patients, the review emphasises that routine scans (X-rays, ultrasounds or MRIs) are not recommended because what appears on a scan often does not explain a person’s pain.

Instead, clinicians should focus on understanding the patient’s symptoms and history, conducting a physical examination, providing reassurance about their expected recovery, and recommending activity modifications, symptom relief or a wait-and-see approach where appropriate.

Lead author Dr Romi Haas, Research Fellow at the Monash School of Public Health and Preventive Medicine, said initial assessments should focus on ruling out serious underlying causes, such as infections, tumours or broken bones, and distinguishing localised shoulder pain from referred pain, such as pain originating from the neck or heart.

“The traditional approach has been to look for a structural flaw by scanning the shoulder, assuming that if you can identify the source of the pain, you can fix it,” Dr Haas said.

“However, global evidence shows these findings are often just normal signs of ageing, akin to grey hair or wrinkles.

“Unwarranted imaging can wrongly attribute a person’s pain to these normal age-related changes, causing undue worry, overdiagnosis and treatments they don’t need. Importantly, early scans don’t improve long-term recovery.”

Subacromial pain is the most common presentation of shoulder pain. It’s usually felt around the top and outside of the shoulder, and can worsen when lifting or reaching with the arm, or when sleeping on that side.

“Structural labels like ‘bursitis’ or ‘tendon tears’ make people think their shoulder is damaged and needs fixing,” Dr Haas said.

“Shifting to location-based labels, such as ‘subacromial pain’, helps reassure patients that it’s safe to keep moving while they manage their symptoms and recover.”

Co-author Dr Thomas Ibounig, a shoulder and elbow surgeon at Helsinki University Hospital in Finland, said the evidence is just as relevant for surgeons as it is for other clinicians.

“High-quality evidence has found that a common shoulder operation, which removes bone and tissue to create more space for the tendons, provides no meaningful benefit over a dummy procedure, where incisions are still cut into a patient, but nothing has been repaired,” Dr Ibounig said.

“It’s a reminder that pain isn’t always caused by an anatomical or structural problem we can simply fix with surgery.

“This guidance helps clinicians explain that clearly, so patients aren’t unnecessarily worried or pushed toward treatments they don’t need.”

Dr Haas said the same principle applies to corticosteroid injections.

“They can provide short-term pain relief, but they don’t routinely need to be guided by imaging,” Dr Haas said.

“Evidence shows an injection given by a doctor using the patient’s physical anatomy as a guide works just as well, without the additional cost or inconvenience of imaging.”

Senior author, Professor Rachelle Buchbinder, a rheumatologist and clinical epidemiologist from the Monash School of Public Health and Preventive Medicine, said most people recover from shoulder pain within one year, although often much sooner.

“Based on a long-term study of 526 adults with new shoulder concerns, followed for more than 10 years, almost 80 per cent experienced satisfactory improvement, through watchful waiting or anti-inflammatory medication,” Professor Buchbinder said.

“Our new guidance is a practical tool and a reassuring reminder for clinicians.

“It gives GPs, physios and surgeons the evidence base they need to reassure patients that self-management, time, and targeted advice are usually the safest and most effective path to recovery.”

Read the research paper: https://doi.org/10.1001/jamainternmed.2026.3135

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Researchers found that rates of gestational diabetes – a condition that develops during pregnancy and can cause serious complications for both mother and baby – increased from around eight per cent of pregnancies in 2018 to more than 12 per cent in 2022.

The sharpest rises were seen among some ethnic minority groups and women living in deprived areas.

Experts say the findings highlight an urgent need to strengthen maternity services and improve support for women at highest risk.

Gestational diabetes mellitus (GDM) is the most common complication arising during pregnancy. The condition occurs when the body cannot produce enough insulin to regulate blood sugar levels during pregnancy.

GDM is associated with an increased risk of complications including preterm birth, emergency Caesarean section and babies being born either larger or smaller than expected for their gestational age. It is also linked to long-term health risks for both mothers and their children.

Researchers analysed routinely collected NHS maternity data covering over 2.3 million mothers and around 2.8 million births across 184 hospitals in England between 2018 and 2022.

The highest increases in gestational diabetes were seen among Asian women, where rates reached around 23 per cent, and among women living in the most deprived areas, where they reached around 14 per cent.

The study also found marked inequalities in pregnancy outcomes across ethnic and socioeconomic groups. Black mothers were more likely to experience an emergency Caesarean birth, women living in deprived areas were more likely to give birth preterm, and Asian mothers were more likely to have babies born small for gestational age.

Among these higher-risk groups, a diagnosis of gestational diabetes was associated with a further increase in the risk of preterm birth.

Researchers say rising maternal age, increasing rates of obesity and improvements in data capture are likely contributors to the growing prevalence of gestational diabetes.

The study also found that changes to gestational diabetes screening introduced during the COVID-19 pandemic did not meaningfully affect overall trends in diagnosis. Experts say the rise in cases reflects broader underlying changes rather than changes in testing practice.

Rebecca Reynolds, Professor of Metabolic Medicine at the University of Edinburgh, said: “This the first time we have managed to estimate the number of women with gestational diabetes in the UK. The rising number of women being diagnosed is concerning and impacts on maternity services delivery which are already challenged. Importantly, gestational diabetes also increases risk of future type 2 diabetes and cardiovascular disease, so better preventative measures are needed to help support these women post partum.”

Dr Sonya Babu-Narayan, Clinical Director at the British Heart Foundation, said: “Big data research studies like this, which can now analyse millions of healthcare records, are uncovering a concerning rise in conditions which raise people’s chances of having a future heart attack or stroke. Gestational diabetes often goes away after pregnancy, but it can increase women’s risk of future cardiovascular disease. Healthcare professionals who want to fully understand people’s risk of heart attack and stroke should routinely ask women about risk factors unique to them, such as diabetes or high blood pressure in pregnancy – even if that pregnancy was decades earlier. If you are a woman who has had diabetes or high blood pressure during pregnancy, it is especially important to attend health checks when invited.”

The study is published in the journal BMJ Medicine: https://bmjmedicine.bmj.com/lookup/doi/10.1136/bmjmed-2025-002412 [URL will become active after embargo lifts]. It involved researchers from King’s College London, University of Glasgow, University of Warwick and researchers within the HDRUK Diabetes Data Catalyst, a partnership between British Heart Foundation Data Science Centre, Diabetes UK and Health Data Research UK. It was funded by the British Heart Foundation.

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The strongest increase in consultations for anxiety and depression was observed for symptoms, such as feeling depressed or anxious, rather than anxiety or depressive disorders, the findings indicate.

Mental health problems have reportedly increased in many high-income countries, particularly among teens and young adults, raising concerns about deteriorating population mental health, note the researchers.

But it’s not clear if rising service use might reflect greater underlying mental ill health or changes in help seeking behaviour and diagnostic practice, they add.

In a bid to find out, the researchers studied all 10–46 year olds in Norway between 2010 and 2024—a total of 3,728,002 people.

They analysed administrative registers of general practitioner (GP) data to estimate the annual sex- and age-specific prevalence of any mental health consultation.

In the Norwegian primary care reimbursement system doctors code the reasons for contact as either symptoms or disorders.

Analysis of the data showed that the proportion of 10–46 year olds with any mental health consultation recorded by a GP rose from just under 10% in 2010 to 16% in 2024.

Among girls and women, it rose from nearly 12% to just over 19.5%, and from just over 8% to just over 12.5% among boys and men.

The steepest increases occurred among 21–30 year olds, with relative increases of 69% for women—from 13% to 22%—and 52% for men—from just under 9% to nearly 14%.

Among the youngest age group (10–15 year olds), the proportion of those with any mental health consultation rose from 3.5% of girls and just over 5% of boys in 2010 to around 9% for both sexes in 2024.

When consultations for anxiety and depression—two of the most common reasons for mental health consultations—were disaggregated, symptom codes showed notably steeper increases than disorder codes across all age groups.

The proportion of primary care consultations for anxiety or depressive symptoms increased substantially over the study period: 286% relative rise in those coded as anxiety symptoms (from 0.44% to 1.7%); 147% relative rise in those coded as depressive symptoms (from 0.73% to 1.8%).

By comparison, the proportion of consultations coded as anxiety or depressive disorders rose only slightly or remained stable: 46% relative increase for those coded as anxiety disorder (from 0.95% to 1.4%); 4% decrease for those coded as depressive disorder (from 2.8% to 2.7%).

The steepest increase in recorded anxiety symptoms was among 16–20 year old women, rising from 0.4% to 2.3%—a 475% relative increase—while the proportion recorded as anxiety disorder rose by a relative increase of 64%–from just under 1.5% to just over 2%.

The steepest increases in depressive symptom consultations were among 21–46 year old women, particularly after 2020, and particularly among 21-30 year olds.

By comparison, there was no comparable increase in the proportion of depressive disorder consultations in either sex at any age.

The researchers caution that their study relied only on primary care data, which didn’t include symptom severity, so can’t be used to provide conclusive evidence on the mechanisms underlying the changes in primary healthcare service use for mental health problems.

“The observed increases could reflect changes in underlying distress, but also changes in recognition, willingness to disclose symptoms, help-seeking and clinical recording practices,” they note.

“While the observed over-proportional increase in symptoms is consistent with changes in norms for help-seeking, it cannot exclude alternative explanations, such as an actual increase in lighter mental health problems among young people, for example, due to increased social media use, the pandemic experience, or other factors,” they add.

Nevertheless they conclude: “The findings suggest that changes in help-seeking behaviour and/or diagnostic recording, rather than worsening underlying morbidity, are key drivers of rising primary care mental health contacts.”

The findings also have implications for primary care, they point out.

“The growing volume of symptom-level presentations poses an organisational challenge for GPs, who face increasing demand that may be more appropriately managed through psychoeducation or brief digital interventions rather than traditional clinical pathways,” they suggest.

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Fortunately, we are not quite there yet, but digitalization is advancing rapidly in the healthcare sector as well. AI chatbots and digital symptom checkers are playing an increasingly important role and are more and more serving as the first point of contact for so-called “self-triage”—that is, the initial assessment of the urgency of treatment by the patients themselves.

But while the technical capabilities of these systems are constantly growing, another factor is coming into the focus of research: how humans communicate with the machine. This is an important topic because even the best technology, especially in medical diagnostics, relies on precise information that users do not always provide in full.

Human reluctance limits the potential of AI

This is the central finding of a study now published in the journal Nature Health. The study was led by Professor Wilfried Kunde, holder of the Chair of Psychology III at the University of Würzburg, and Moritz Reis, a research associate in that department. It involved scientists from Charité – Universitätsmedizin Berlin, the University of Cambridge, as well as Helios Klinikum Emil von Behring and Vivantes Klinikum Neukölln in Berlin.

“The 500 study participants were tasked with writing simulated symptom reports for two common conditions – unusual headaches and flu-like symptoms” describes lead author Moritz Reis the study design. They were led to believe that their reports would be read either by an AI chatbot or a human doctor. The goal was to examine the quality of these reports in terms of their suitability for a medical urgency assessment.

Loss of quality is evident in reduced level of detail

The key finding: When participants believed they were communicating with artificial intelligence, the suitability of their descriptions for an initial medical assessment deteriorated measurably compared to interactions with supposed medical professionals. This effect was even observed among participants who were actually experiencing the relevant symptoms at the time of the survey.

This loss of quality is directly reflected in the level of detail in the reports. While descriptions provided to medical professionals averaged 255.6 characters, those provided to chatbots averaged only 228.7 characters.

Even though a difference of 28 characters may sound small, the research team states that this effect is practically relevant and can result in even high-performance AI models ultimately providing incorrect medical advice. After all, these models also fail to make an accurate medical assessment if patients do not provide all essential information. The success of digital initial assessments depends less on computational power than on the patient’s willingness to provide a detailed description.

Psychological Barriers: Concerns About a “One-Size-Fits-All Diagnosis”

But why are people so hesitant when it comes to machines? A key reason is likely what’s known as “uniqueness neglect.” “Many people assume that AI cannot grasp the individual nuances of their personal situation and instead merely matches standardized patterns,” explains Wilfried Kunde.

In addition, skepticism about algorithms’ diagnostic capabilities, as well as privacy concerns, may lead people to provide abbreviated or vague information. Moritz Reis sums up the human component this way: “If we don’t trust a machine to understand our uniqueness, we may unconsciously withhold the information it would need to provide precise assistance.” This psychological filter can have the effect that medically relevant details never even reach the system, thereby lowering the quality of the diagnosis.

Improving the dialogue with the machine

In the research team’s view, the findings clearly show that the technical advancement of AI alone is not sufficient. They therefore see a potential solution in the intelligent design of user interfaces.

To improve the quality of symptom reports, developers should provide concrete examples of high-quality descriptions and program the AI to actively request missing details. Only when users are encouraged to provide detailed information misdiagnoses can be avoided and the burden on the healthcare system could be effectively reduced.

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The paper published online today highlights that ^99mTc-maraciclatide has potential as:

• A novel non-invasive diagnostic test, particularly for superficial peritoneal endometriosis (SPE), which cannot be reliably detected by conventional imaging techniques and currently requires laparoscopic surgery for definitive diagnosis
• A tool to enable disease monitoring, eliminating uncertainty around disease recurrence
• A marker of treatment response, empowering the development of novel therapies

^99mTc-maraciclatide is a gamma-emitting radiotracer that binds to αvβ3 integrin, which is upregulated during angiogenesis (new blood vessel formation), a cardinal feature of inflammatory diseases. The DETECT study describes, for the first time, the use of ^99mTc-maraciclatide as a potential tool for the visualisation and diagnosis of endometriosis.

Key findings:

• The DETECT study demonstrated a high correlation between locations of maraciclatide uptake and laparoscopy across all types of endometriotic lesions, including superficial peritoneal endometriosis (SPE). SPE is the earliest stage of endometriosis, which is found in 80 per cent of all laparoscopically diagnosed disease
• Imaging with ^99mTc-maraciclatide visualised endometriosis, detecting disease missed by conventional imaging methods
• Imaging results were concordant with the surgical presence or absence of endometriosis in 16/19 cases, with endometriosis imaged in 14/17 surgically positive participants, including two cases of thoracic endometriosis
• No false positives were reported in this study
• ^99mTc-maraciclatide imaging was able to detect lesions across all endometriosis subtypes supporting the applicability of the scan to various patient groups
• ^99mTc-maraciclatide was well tolerated and patient acceptability was high

Dr Tatjana Gibbons, lead author on the paper and investigator on the study from the Nuffield Department of Women’s and Reproductive Health, University of Oxford added, 

“These exciting findings indicate that maraciclatide offers a highly promising diagnostic and monitoring tool, particularly for superficial peritoneal endometriosis, which is the most common and yet the hardest type of endometriosis to identify.

“We are hugely grateful to the patients who have participated in the DETECT study without whom investigating this diagnostic approach would not have been possible.”

Professor Christian Becker, Co-Director of the Endometriosis CaRe Centre in Oxford, co-lead on the study and joint senior co-author on the paper, added:

“Novel, non-invasive diagnostic tests for endometriosis are a global research priority. The diagnostic challenge of endometriosis, which presents with varied and non-specific symptoms, is exacerbated by an absence of clinically validated biomarkers and the limitations of currently available imaging techniques. If these Phase II results are reproduced in the Phase III studies, maraciclatide has the potential to be an extremely valuable tool, as it could both reduce diagnostic delays and provide a validated endpoint for the development of new therapeutics.”

David Hail, CEO of Serac Healthcare, commented:

“The completion and publication of this clinical study marks a pivotal achievement for Serac Healthcare. These data, from a representative patient population, including women receiving hormone therapy, provide  evidence of maraciclatide’s anticipated real-world performance.

“With FDA Fast Track Designation and agreed Phase III study designs, we are now advancing to validate these findings in larger trials and progress to regulatory submission.”

Professor Krina Zondervan, Co-Director of the Endometriosis CaRe Centre, Head of Department at the Nuffield Department of Women’s and Reproductive Health, Co-theme Lead for the NIHR Oxford Biomedical Research Centre’s Surgical Innovation Theme, co-lead on the study and joint senior co-author on the paper, said:

“Superficial peritoneal endometriosis, the most prevalent subtype of endometriosis, currently evades reliable detection, leaving women no choice for diagnosis other than invasive surgery. If these results are confirmed in larger Phase III studies, imaging with maraciclatide could transform clinical research and practice and potentially empower the development of treatments for women across the globe.”

The study was co-led by Professor Christian Becker, Co-Director of the Endometriosis CaRe Centre in Oxford, together with Professor Krina Zondervan, Co-Director of the Endometriosis CaRe Centre and Head of Department at the Nuffield Department of Women’s and Reproductive Health at the University of Oxford. The study was funded by the  NIHR Oxford Biomedical Research Centre and Serac Healthcare. Scans were performed at the Royal United Hospital, Bath.

About the Phase 2 trial:

This was an exploratory, open-label, single-centre, phase 2 study evaluating preoperative imaging in 20 individuals with suspected or confirmed pelvic or thoracic endometriosis using a SPECT-CT, with intravenous ^99mTc-maraciclatide. The primary outcome was alignment of radiological and surgical findings in those patients completing both imaging and surgery. The surgical report on lesion type and location was compared to images for alignment.

Ten of the participants with SPE had prior imaging with traditional modalities (transvaginal (TV) ultrasound and/or MRI) in the last 12 months, none of which had detected SPE.

Phase III multi-centre international studies are due to start later this year.

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In a paper, published today in the British Journal of Psychiatry, a group of experts led by Professor Samuele Cortese from the University of Southampton say there is no robust evidence that ADHD is over-diagnosed in the UK.

The new paper refutes the view that ‘nowadays everyone has ADHD’ which is gaining traction in public discourse and has been amplified by some leading politicians, as demand rises for NHS assessments and services.

Bringing together academics, clinicians, people with lived experience and carers, the group say this narrative risks misleading the public and policymakers and overshadows a more pressing concern – unmet need.

Professor Cortese said: “Rather than focusing on increases or decreases in diagnostic rates, attention should be directed toward the extent to which those with ADHD are being adequately diagnosed and treated.

“While misdiagnosis and inappropriate diagnosis do occur, the available evidence indicates that under diagnosis and under treatment remain the predominant challenges.”

When standardised diagnostic criteria are applied, the prevalence of ADHD internationally is around 5 per cent in children and 3 per cent in adults.

While prevalence has increased over time, NHS administrative data in England remains substantially below these expected levels, suggesting that many people with ADHD are living without a diagnosis and adequate support.

The group acknowledge that misdiagnosis can occur in some cases, particularly where assessments rely heavily on self-reporting or where alternative conditions are not fully considered.

Professor Tamsin Ford, Head of the Department of Psychiatry at the University of Cambridge, a coauthor on the paper, commented: “While many more people with ADHD are being recognised and treated, we are failing to support many more. Overdiagnosis is not a problem, but misdiagnosis may be as people are driven into the private sector by long waits; and sadly, missed diagnoses remain common.”

The researchers stress that the absence of biological diagnostic markers means that thorough, multidisciplinary clinical assessment is essential. Field trials show that when clinicians are properly trained, an ADHD diagnosis is among the most reliable for a mental health condition.

“Similar to physiological traits, such as blood pressure or weight, ADHD symptoms are distributed along a continuum,” says coauthor Professor Chris Hollis from the University of Nottingham. “But as with hypertension or obesity, there are diagnostic severity thresholds that determine health risks and what interventions should be used. Similarly, in ADHD a risk-stratified stepped-care approach may be useful.”

Professor Cortese and colleagues highlight significant pressure on UK services, with long waiting times and growing demand, especially among adults who were not diagnosed in childhood.

They point to figures showing that around 27 per cent of children and young people diagnosed with ADHD reported waiting one to two years, while 14 per cent waited two to three years.

Evidence shows that untreated ADHD is associated with serious long-term risks, while effective treatments are available, backed by strong evidence, and generally well tolerated.

“The costs of untreated ADHD are often overlooked,” says Professor Cortese. “They include increased risk of academic failure, suicidal behaviour, substance abuse, criminality, injury and death. The failure to provide treatments which have been shown to reduce these risks represents a major ethical issue that needs to be urgently addressed.”

The authors call for improved funding, workforce training and a more balanced, evidence-based conversation to ensure accurate diagnosis while expanding access to care for those who need it.

The researchers are supported by the National Institute for Health and Care Research (NIHR), UK Research and Innovation (UKRI) and the Office for Life Sciences.

ADHD (over) diagnosis: fiction, fashion, and failure is published in the British Journal of Psychiatry and is available online.

Contact

Steve Williams, Media Manager, University of Southampton, press@soton.ac.uk or 023 8059 3212.

1. In 2018, the administrative prevalence was 2.5% in boys and 0.7% in girls, and 0.7% in men and 0.2% in women, respectively. Current post-pandemic administrative prevalence data are unavailable.
2. Figures on wait list times come from an online survey of 7,340 people, conducted by the House of Commons Petitions Committee between 2021 and 2022.
3. ADHD (over) diagnosis: fiction, fashion, and failure is published in the British Journal of Psychiatry here:ADHD (over) diagnosis: fiction, fashion and failure | The British Journal of Psychiatry | Cambridge Core
4. For interviews, please contact press@soton.ac.uk or 023 8059 3212.

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Depression is the most severely impacted, with almost a third fewer diagnoses than expected compared with pre-pandemic trends.

The King’s College London study is the first to evaluate whether diagnosis rates have recovered after emerging from the pandemic. Published today in the British Medical Journal (BMJ), it uses anonymised data from over 29 million people in England.

The pandemic had an unprecedented impact on healthcare systems around the world, leading to abrupt decreases in diagnosis rates for a wide range of diseases.

Of the 19 major conditions analysed, diagnoses of depression were 27.7% lower than expected compared with pre-pandemic trends. Diagnoses were also lower than expected for asthma (16.4%), chronic obstructive pulmonary disease (COPD, 15.8%) and osteoporosis (11.5%).

The study also identified differences in how diagnosis rates recovered across ethnic and socioeconomic groups. While dementia diagnoses recovered to pre-pandemic levels for individuals of white ethnicity and those living in less deprived areas, they remained lower than expected among other ethnic groups and in more deprived communities.

Co-author Professor Sam Norton, Professor of Medical Statistics at King’s College London, said: “The deficits in depression diagnoses were particularly striking and somewhat puzzling. After an initial decrease during the early pandemic, diagnosis rates partially recovered by late 2021, but have declined markedly since 2022. This pattern was most evident among younger adults aged 20 to 39 years, and among individuals of white or mixed ethnicity.

“This is difficult to reconcile with other indicators of mental health need. Disability benefit claims for mental health conditions have increased substantially over the same period, suggesting these declining diagnosis rates may not reflect improving mental health.”

Diagnosis rates may be influenced by increasing pressures on the NHS, meaning it is taking longer for people to be formally diagnosed. It is also possible that more people are accessing mental health support without receiving a formal diagnosis of depression. Following a national drive to expand access to psychological therapies, referrals to NHS Talking Therapies services increased by nearly two-thirds between 2013 and 2024, with self-referrals accounting for almost 70% of all referrals.

The team also suggest that pandemic-related disruption could be behind the fall in diagnoses for asthma, COPD and osteoporosis. Backlogs in diagnostic testing for these conditions during the pandemic is likely to be a key factor, and the NHS has identified this as a priority area for improvement.

Further analysis revealed that chronic kidney disease (CKD) diagnoses have increased by 34.8% compared to expected levels.

Lead author Dr Mark Russell, consultant rheumatologist and epidemiologist at King’s College London, said: “The rise in CKD diagnoses may reflect increased testing and greater awareness following guideline changes and the introduction of new treatments.

“It is also possible that the pandemic itself has contributed to an increase in CKD, either through the direct effects of Covid-19 infection or through delays in diagnosing related conditions such as diabetes.”

The research team used OpenSAFELY, a highly secure and anonymised NHS data platform, to analyse disease trends for 29 million people between April 2016 and November 2024.

Dr Russell added: “This study highlights the incredible health data resources available within the NHS and demonstrates how real-time, anonymised data could be used safely and securely, without any individual patient data ever leaving the NHS system, to transform disease monitoring, enabling earlier identification of inequities and informing how care is delivered.”

Notes to Editors

The OpenSAFELY platform is principally funded by grants from NHS England, the Wellcome Trust, and the Medical Research Council.

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Bladder cancer remains a major clinical challenge as it is one of the most common and deadliest urological cancers with a high recurrence rate. Yet its diagnosis still relies heavily on invasive and costly procedures like cystoscopy (inserting a thin, tube-like instrument through the urethra) or cytology, a noninvasive test that can identify tumor cells shed in urine but has limited sensitivity.

Investigators of the current study were motivated to find a simpler, more comfortable way to detect and monitor bladder cancer. They analyzed urine samples from 156 patients with bladder cancer and 79 matched controls and using real-time PCR, measured the concentration and integrity (long-short size distribution) of cfDNA fragments from five genes (ACTB, AR, MYC, BCAS1, and STOX1).

“Our most significant finding was that the small fragment of the MYC gene may represent a valuable tool to diagnose bladder cancer, as it exhibited excellent specificity (97%) and predictive value (88%) for identifying muscle-invasive bladder cancer,“ explains lead investigator Pilar Medina, PhD, Haemostasis, Thrombosis, Arteriosclerosis and Vascular Biology Research Group, Health Research Institute Hospital La Fe (IIS La Fe), Valencia, Spain.

MYC produces a transcription factor crucial for regulating cell growth, proliferation, and metabolism.

Additionally, researchers found that the ratio of large to small fragments of the housekeeping gene ACTB and the small fragment of the AR gene increased with disease severity, suggesting these could be reliable staging biomarkers. The integrity of these genes may be useful to identify bladder cancer relapse.

Lead author Raquel Herranz, MS, Haemostasis, Thrombosis, Arteriosclerosis and Vascular Biology Research Group, Health Research Institute Hospital La Fe (IIS La Fe), Valencia, Spain, notes, “With growing interest in liquid biopsies and personalized medicine, our study offers a timely and practical alternative to invasive diagnostics. This study is one of the first to comprehensively evaluate urine cfDNA fragmentation and integrity across most bladder cancer stages, bringing us closer to a future in which bladder cancer can be diagnosed and monitored through a simple urine test, improving patient comfort and care.”

Dr. Medina concludes, “Our findings show that urine can tell us much more than we thought; it holds the potential to transform how we detect and manage bladder cancer.”

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To diagnose a mental illness, medical practitioners rely on a variety of factors, including the symptoms reported by patients and recorded on clinical questionnaires. The precise wording of individual questions on these questionnaires is often crucial for making the correct diagnosis. However, standard questionnaires often vary considerably. Researchers have found evidence of overlaps and deviations in the content of questions used to identify depression, bipolar disorder, and the risk of psychosis, which makes accurate diagnosis difficult.

In addition, doctors rely on their clinical experience. This means that they associate individual symptoms with a specific illness that corresponds to their experience. However, as different illnesses can produce the same or similar symptoms, this can also increase the risk of misdiagnosis. “We know surprisingly little about whether – and how – the wording of clinical questionnaires triggers certain associations in doctors,” says Professor Joseph Kambeitz. Inconsistent findings could also result from differences among patients in the same diagnostic group or, alternatively, from differences between questionnaires.

Using large language models (LLMs) is one approach to analysing language-mediated illness descriptions. The team used the LLMs GPT-3, Llama and BERT to analyse both the structure and content of four clinical questionnaires. The study was based on data from over 50,000 questionnaires on depression, anxiety, psychosis risk, and autism.

In clinical practice, symptoms often occur simultaneously, such as the empirical association between a lack of drive and a loss of pleasure. The analysis showed that the LLMs ‘recognize’ which symptoms commonly occur together. Even without access to specific empirical data, the same symptom associations are evident in LLMs based purely on the questionnaire formulations.

This suggests new ways in which artificial intelligence could improve psychological questionnaires in future, by avoiding redundant items and making diagnosis and understanding of mental illnesses more efficient. LLMs can be used to develop questionnaires that are both precise (i.e. that reliably recognize psychological symptoms) and efficient, asking only as many questions as necessary in order to simplify the process for patients and practitioners.

“AI can map both medical knowledge and the structures of mental illnesses. This is an important step in bringing digital methods and neuroscience closer together, and in advancing the development of diagnostics and research in psychiatry,” says Professor Kai Vogeley.

Professor Joseph Kambeitz concludes: “In psychiatry, the ‘spoken word’ plays an important role in diagnosis and therapy. There are currently many promising projects that are investigating how we can use LLMs in psychiatry, from diagnostics via the writing and amending of reports to the simulation of therapy sessions. We can expect many more exciting research results in this field.”

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In a new study, the researchers show the test can detect the virus that causes COVID-19 with pinpoint accuracy, clearly distinguishing it from other infections.

The new diagnostic device, called NasRED (Nanoparticle-Supported Rapid Electronic Detection), is simple and portable enough to be used almost anywhere — from remote rural clinics to busy urban hospitals. The tool provides lab-quality accuracy without expensive equipment and does not require specialized training, giving it the potential to become a public health game changer.

“We have the speed and ease of use of a rapid antigen test with sensitivity that’s even better than lab-based tests,” says Chao Wang, lead author of the new study. “This is very difficult to achieve.”

Wang is an associate professor with the Biodesign Center for Molecular Design and Biomimetics and ASU’s School of Electrical, Computer and Energy Engineering. He is joined by ASU researchers Yeji Choi, Seyedsina Mirjalili, Ashif Ikbal, Sean McClure, Maziyar Kalateh Mohammadi, Scott Clemens, Jose Solano, John Heggland, Tingting Zhang and Jiawei Zuo.

The research appears in the current issue of the journal ACS Nano.

Halting the spread of infectious diseases

Infectious diseases are one of humanity’s deadliest threats, causing immense suffering and economic damage worldwide. Collectively, infectious diseases cause over 10 million deaths around the world each year, and they are the leading cause of death in low-income countries.

Nearly 800,000 Americans die or are permanently disabled every year due to diagnostic errors, according to a study published in BMJ Quality & Safety. Many of these cases involve infections or vascular events that might have been treatable if caught early.

In many low- and middle-income countries, access to reliable diagnostic testing is limited or nonexistent. Expensive equipment, shortages of trained personnel and long turnaround times all contribute to delayed or missed diagnoses — often with deadly consequences.

A fast, affordable and portable test like NasRED would enable frontline health workers globally to detect infections early and respond before outbreaks spiral out of control.

“In many parts of the world, including the U.S., diseases are spreading, but people often don’t get tested — even for something like HIV. Ideally, you’d want to test them regularly, to catch infections early,” Wang says. “For example, people who use injection drugs are at higher risk for HIV or HCV, but they may be living in the streets and hard to reach. If we don’t test them consistently over time, we may miss the chance to intervene — until they develop serious complications like cancer or liver disease, when it’s much harder to treat.”

Striking diagnostic gold

At the core of the new test are tiny gold nanoparticles, engineered to detect extremely small amounts of disease-related proteins. Researchers coat these nanoparticles with special molecules designed to detect specific diseases.

Some nanoparticles carry antibodies, tiny molecules that act like magnets. Antibodies stick to proteins released by viruses or bacteria when they infect the body. Other nanoparticles carry antigens, fragments of proteins taken directly from viruses or bacteria themselves. These naturally attract antibodies produced by the body to fight infections.

Once coated, these nanoparticles are combined with a tiny sample of bodily fluid, such as a drop of blood, saliva or nasal fluid. If a disease is present, most nanoparticles will sink to the bottom of the tube. If there is no disease, they will remain suspended throughout the liquid.

The NasRED device shines a small beam of LED light through the liquid at the top of the tube. The team built a custom electronic detector that senses how much light gets through the tube. More light means the nanoparticles have sunk to the bottom, leaving the top fluid clearer, meaning that the disease is present.

Accurate, accessible and affordable

The device is so sensitive it can detect disease even when only a few hundred molecules are present in a tiny fluid sample — just a fraction of a single drop. This is a concentration nearly 100,000 times lower than what standard laboratory tests require.

Adding to its promise is NasRED’s portability and affordability. The current gold standards for testing, like PCR or ELISA, require expensive equipment and trained technicians. NasRED is compact and user-friendly. The researchers estimate each test costs $2, making it ideal for use in low-resource or remote locations.

NasRED has the potential to fill a critical diagnostic gap, especially for diseases that are difficult to detect early, such as hepatitis C, HIV or Lyme disease. It is also promising for emerging outbreaks with low prevalence but high risk. Such diseases often go undiagnosed because running a lab test for just one or two patients isn’t cost effective. NasRED bridges that gap by offering a highly sensitive test that works immediately and economically at the point of care.

While NasRED currently requires small, benchtop machines for spinning and mixing samples, the researchers are working to further miniaturize and automate the process. With continued development, the technology might one day become a convenient home test, similar to existing rapid COVID-19 tests. However, it would have vastly superior sensitivity and broader applications.

Significant leap forward in diagnostics

NasRED dramatically surpasses existing diagnostic standards. The new study shows that NasRED is roughly 3,000 times more sensitive than ELISA, requires 16 times less sample volume, and delivers results approximately 30 times faster.

An earlier version of the technology detected Ebola in a tiny sample of blood. “For the new technology, we pushed the sensitivity down to the attomolar range,” Wang says. That’s like detecting a single drop of ink in 20 Olympic swimming pools.

The technology holds promise for detecting viral loads directly from bodily fluids without the complicated sample preparation used in PCR-based methods. In preliminary tests with actual coronavirus particles, NasRED achieved sensitivities comparable to Abbott ID NOW, a popular molecular test for many diseases such as COVID-19.

“One of the strengths of our sensor is that it’s highly modular,” Wang says. “The nanoparticles are designed so that we can easily swap in different proteins, allowing the same platform to be adapted for many different diseases. We’ve already demonstrated this approach in our research on Shiga toxin-producing E. coli, as well as cancer biomarkers, Alzheimer’s-related proteins, Lyme disease and African swine fever.”

Wang recently received the Bay Area Lyme Foundation Emerging Leader Award and will make use of the high sensitivity and portability of this new technology to detect early Lyme infection.

As the technology evolves, its range of applications may extend beyond infectious diseases. Early detection of cancers, real-time monitoring of chronic illnesses and improved surveillance of public health threats are all within reach.

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Their new research compares ChatGPT, Gemini, and DXplain at diagnosing patient cases, revealing that DXplain performed somewhat better, but the LLMs also performed well. The investigators envision pairing DXplain with an LLM as the optimal way forward, as it would improve both systems and enhance their clinical efficacy. The results are published in JAMA Network Open.

“Amid all the interest in large language models, it’s easy to forget that the first AI systems used successfully in medicine were expert systems like DXplain,” said co-author Edward Hoffer, MD, of the LCS at MGH.

“These systems can enhance and expand clinicians’ diagnoses, recalling information that physicians may forget in the heat of the moment and isn’t biased by common flaws in human reasoning. And now, we think combining the powerful explanatory capabilities of existing diagnostic systems with the linguistic capabilities of large language models will enable better automated diagnostic decision support and patient outcomes,” said corresponding author Mitchell Feldman, MD, also of MGH’s LCS.

The investigators tested the diagnostic capabilities of DXplain, ChatGPT, and Gemini using 36 patient cases spanning racial, ethnic, age, and gender categories. For each case, the systems had a chance to suggest potential case diagnoses both with and without lab data. With lab data, all three systems listed the correct diagnosis most of the time: 72% for DXplain, 64% for ChatGPT, and 58% for Gemini. Without lab data, DXplain listed the correct diagnosis 56% of the time, outperforming ChatGPT (42%) and Gemini (39%), though the results were not statistically significant.

The researchers observed that the DDSS and LLMs caught certain diseases the others missed, suggesting there may be promise in combining the approaches. Preliminary work building off these findings reveals that LLMs could be used to pull clinical findings from narrative text, which could then be plugged into DDSSs—in turn synergistically improving both systems and their diagnostic conclusions.

Authorship: Additional Mass General Brigham authors include Jared Conley, Jaime Chang, Jeanhee Chung, Michael Jernigan, William Lester, Zachary Strasser, and Henry Chueh.

Disclosures: None.

Funding: This work was supported by the National Center for Advancing Translational Sciences of the NIH (UM1TR004408), awarded through Harvard Catalyst.

Paper cited: Feldman, Met al. “Dedicated AI Expert System vs Generative AI With Large Language Model for Clinical Diagnoses” JAMA Network Open DOI: 10.1001/jamanetworkopen.2025.12994

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Bacterial meningitis is a life-threatening condition in which one in six patients die and half of the survivors have residual symptoms. Thus, prompt diagnosis and treatment are crucial. “The distinction between bacterial meningitis and similar conditions is often difficult for doctors. Until now, reliable diagnostic tests that could quickly distinguish were lacking,” says last author and Amsterdam UMC neurologist, Matthijs Brouwer.

Reliable indicator  

Researchers at Amsterdam UMC have discovered that the CRP protein in cerebrospinal fluid is a very reliable indicator of bacterial meningitis. CRP is already frequently tested in blood to detect bacterial infections, but the value of this test in cerebrospinal fluid had not been well researched until now. After previous successful laboratory tests, the researchers now showed that the device that measures CRP in blood is also sensitive enough to measure CRP in cerebrospinal fluid.

“It is a huge gain that the existing infrastructure of the laboratory can be used for the CRP measurements in cerebrospinal fluid. As a result, the test result is already known half an hour after the epidural and the correct treatment of the patient can therefore be started quickly,” says Brouwer.

Daily practice  

Since June 2024, the new test has been used in the daily practice of the Amsterdam UMC. In the study published today, researchers describe how the test was introduced and how effective it is in practice.

“Our results show that all patients with bacterial meningitis had an elevated CRP in their cerebrospinal fluid. This was the case in only a few patients without bacterial meningitis, ” adds Brouwer. The test also proved reliable in additional studies in children and patients from at Aalborg University Hospital in Denmark.

Broad application in hospitals 

It is expected that more hospitals will adopt the test, because it can easily be performed in laboratories with existing equipment. The test only costs between three and five euros, providing an affordable and accessible solution to diagnose and treat bacterial meningitis faster.

“Any laboratory in which CRP is measured in blood can introduce this test for cerebrospinal fluid tomorrow. We could not have predicted in advance that a new diagnostic test would be used in patients within a year of its discovery,” concludes Brouwer.

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