Study Warns of High-Risk Group for Fatal Liver Disease

 

• An estimated 9% of U.S. adults said they had obesity and drank heavily in 2023, according to nationally representative survey data.
• Age and insurance were linked to prevalence of concurrent heavy drinking and obesity.
• GLP-1 agents could be a potential treatment option to address both obesity and alcohol use disorder, the researchers suggested.

An estimated 1 in 10 U.S. adults had overlapping heavy drinking and obesity conditions in 2023, a cross-sectional study found.

In a survey of roughly 45,000 U.S. adults representing more than 257 million people, 9% said they had obesity and drank heavily over the past month, while 3.8% said they had both obesity and met criteria for alcohol use disorder (AUD) over the past year, reported researchers led by Bryant Shuey, MD, MPH, of the University of Pittsburgh.

Overlapping heavy drinking and obesity was most common among men ages 35 to 49 (13.6%), women ages 26 to 34 (11.9%), and Black individuals (11.9%). AUD and obesity overlap was highest for men and women ages 26 to 34 (6.2% and 5.1%), people without insurance, and those on Medicaid, the findings in JAMA Internal Medicine showed.

Shuey and colleagues said the findings on this high-risk population call for public health and clinical interventions tailored to younger and middle-age adults, especially the uninsured and those on Medicaid, to prevent liver disease and liver-associated deaths.

Insurance coverage of evidence-based therapies for the two preventable risk factors, which "contribute synergistically" to rising rates of liver disease and death, is also needed, according to the researchers.

"While evidence is limited on concurrent treatment of risky alcohol use and obesity, clinicians should offer interventions that are effective for both conditions, including motivational interviewing, cognitive behavior therapy, and pharmacotherapy," wrote Shuey and colleagues.

Given the effectiveness of GLP-1 drugs "for weight loss and metabolic dysfunction–associated steatohepatitis, expanding access for patients with co-occurring risky alcohol use and obesity may reduce liver disease burden," they argued.

Real-world data have also shown lower AUD-related hospitalization rates for people on GLP-1 drugs, and the researchers pointed to early trial data showing these drugs can help people with AUD reduce their drinking.

"If this finding is confirmed in larger studies, GLP-1 receptor agonists could become a dual therapeutic for risky alcohol use and obesity," the authors suggested.

In their introduction, Shuey and co-authors noted that heavy drinking in people with obesity has become more common in recent decades, but that the prevalence has not been evaluated since the COVID-19 pandemic, a time when multiple reports indicated increases in alcohol abuse and associated complications. Furthermore, the prevalence of obesity and AUD together has not been looked at.

Their study utilized 2023 National Survey on Drug Use and Health data from 45,133 respondents, representing a total weighted population of 257.5 million adults. About half of the survey respondents were women (51.3%), and 61.2% were white, 17.6% were Hispanic, 12.1% were Black, 6.2% were Asian, 2% were multiracial, and 0.4% were Native Hawaiian or Pacific Islander.

Obesity was defined as a body mass index (BMI) of 30 or higher. Past-month heavy drinking was evaluated by the National Institute on Alcohol Abuse and Alcoholism definition (for men: ≥15 drinks per week or ≥5 drinks per day; for women: ≥8 drinks per week or ≥4 drinks per day). Past-year AUD was defined using DSM-5 criteria.

Nearly 100 million adults were estimated to have obesity, around 60 million to drink heavily, and about 30 million to have AUD.

Men and women with obesity ages 65 and older had the lowest rates of heavy drinking (6% and 3%, respectively) and AUD (2.8% and 0.8%).

Stratified by race and ethnicity, Native Hawaiian and Pacific Islanders had the highest overlap with AUD (7.3%). Conversely, Asian adults reported the lowest prevalence for both obesity and heavy drinking (2.1%) and obesity and AUD (1%).

Uninsured adults had a higher prevalence of overlapping obesity and heavy drinking (9.7%) and AUD (4.5%) than insured adults. Adults covered by Medicaid or the Children's Health Insurance Program (CHIP) had the same 4.5% rate of overlapping AUD and obesity. Higher income correlated with higher prevalence of overlapping heavy drinking and obesity but not overlapping AUD and obesity.

The study findings might have been limited by self-reporting bias, and underreporting of AUD may have overestimated rates of heavy drinking, the researchers acknowledged.

Disclosures

The study was supported by NIH grants.

Shuey reported grants from the National Institute on Drug Abuse during the conduct of the study. Co-authors reported grants from or other relationships with various NIH institutes, the CDC, Helmsley Charitable Trust, the Commonwealth of Pennsylvania, the Donaghue Foundation, the Agency for Healthcare Research and Quality, the U.S. Department of Veterans Affairs, the American Medical Association, and the International Alliance for Diabetes Action.

Primary Source

JAMA Internal Medicine

Source Reference: Shuey B, et al "Heavy drinking, alcohol use disorder, and obesity" JAMA Intern Med 2026; DOI: 10.1001/jamainternmed.2026.0428.

https://www.medpagetoday.com/psychiatry/addictions/120871

'New Kink in the Link Between GLP-1 Drugs and Cognition'

 Adults whose type 2 diabetes was treated with GLP-1 receptor agonists were more likely to develop cognitive impairment over 10 years than their counterparts not treated with GLP-1 agents, a propensity-matched retrospective study of nearly 65,000 patients suggested.

Durable cognitive impairment -- defined as vascular dementia, Alzheimer's disease, or mild cognitive impairment -- occurred twice as frequently in diabetes patients who used GLP-1 drugs (2.6% vs 1.3%, HR 2.74, P<0.0001), but mortality risk was lower with the drugs (3.9% vs 8.2%, HR 0.68, P<0.0001), according to Isaac Thorman, ScM, an epidemiology researcher at the Johns Hopkins University School of Medicine and a third-year medical student at New York Medical College in Valhalla, and colleagues.

On a compound outcome that assessed both cognitive impairment and mortality, there was no significant difference between GLP-1 receptor agonist users and non-users (6.1% vs 9.1%, HR 0.98, P=0.39), Thorman reported at a late-breaking science session at the American Academy of Neurology annual meeting in Chicago.

Overall, GLP-1 analogs were associated with an increased risk of cognitive impairment, secondary to a larger, protective effect against mortality, Thorman noted.

"We interpret this to mean that GLP-1 analog recipients lived significantly longer than non-recipients, and that they lived long enough for them to develop cognitive impairment," he said.

The findings come on the heels of two phase III trials showing that Alzheimer's patients treated with the GLP-1 agent semaglutide (Rybelsus) had no significant improvement in cognitive or functional decline over 2 years compared with placebo, Thorman noted.

"The apparent survival paradox demonstrated here, plus our unprecedented sample size and long-term follow-up, may explain the non-significance found in the randomized controlled trials," he said.

The idea of repurposing semaglutide to treat Alzheimer's was driven by real-world data and preclinical research. In observational analyses, GLP-1 receptor agonists were tied to a reduced risk of cognitive impairment and dementia, including a lower risk of Alzheimer's diagnoses. The drug class also demonstrated neuroprotective and anti-inflammatory effects in animal models of Alzheimer's disease.

"Our objective was to assess the long-term risk of cognitive impairment associated with GLP-1 analog use in older adults with type 2 diabetes," Thorman said.

Thorman and co-authors studied people ages 50 and older with type 2 diabetes in the TriNetX dataset of patients from 115 healthcare organizations in five countries. People with pre-existing cerebrovascular disease or durable cognitive impairment were excluded from the study. Patients were followed for up to 10 years.

From a sample of 404,084 middle-age and older adults, the researchers matched 64,530 diabetes patients on more than 170 variables, including demographics, vital statistics, comorbidities, and medications prescribed.

A critical distinction between this study and other observational data "is likely in how we accounted for overall patient health," Thorman told MedPage Today. "At baseline and prior to matching, patients receiving GLP-1 analogs were in significantly worse health, with significant elevations in almost every lab value, diagnosis, and medication. After matching, there were few statistically significant differences, and almost all of these differences were devoid of clinical significance."

In women, the mortality protection of GLP-1 agents balanced cognitive impairment risk; whereas in men, it outweighed the risk of cognitive impairment. The researchers also found no overall protective effect of GLP-1 drugs in diabetes patients ages 80 and older.

When patients are in their 80s and are being followed up for another 10 years into their 90s, other comorbidities may influence cognitive deterioration, observed Paul Edison, MD, PhD, of Imperial College London, who wasn't involved with the study.

Whether robust measurements were used to assess cognitive function also is a question, Edison pointed out. "A thorough investigation into these factors is important before reaching a conclusion," he told MedPage Today.

Long-term, prospective surveillance and results from randomized trials remain critical in assessing the risk-benefit ratio of these drugs, Thorman noted. "Caution is advised when interpreting these findings, as causality cannot be inferred from this retrospective analysis," he said.

Disclosures

Thorman reported no conflicts of interest.

Edison reported relationships with Medical Research Council, the Higher Education Funding Council for England, Alzheimer's Research U.K., Alzheimer's Drug Discovery Foundation, Alzheimer's Society U.K., Alzheimer's Association, the Van-Geest Foundation, the European Union, Roche, Pfizer, Novo Nordisk, GE Healthcare, Piramal Life Science/Life Molecular Imaging, Avid Radiopharmaceuticals, and Eli Lilly.

Primary Source

American Academy of Neurology

Source Reference: Thorman I, et al "Long-term risk of cognitive impairment with GLP-1 analogues in older adults with type 2 diabetes mellitus" AAN 2026.

https://www.medpagetoday.com/meetingcoverage/aan/120862

'If It's COVID, Paxlovid? Studies Suggest a Rethink'

 

• Two multicenter trials found no change in hospitalization and death rates when antiviral nirmatrelvir-ritonavir (Paxlovid) was given to COVID-19 patients already mostly vaccinated.
• However, nirmatrelvir-ritonavir was linked to more early sustained recovery when taken within the first 5 days of illness in both trials.
• Additionally, there was evidence of more nirmatrelvir-ritonavir recipients reaching a viral load below detection level at day 5 following treatment.

Oral nirmatrelvir-ritonavir (Paxlovid) failed to spare COVID-19-vaccinated individuals from the worst outcomes if they got sick, though it may have helped speed recovery time and cut viral loads, according to two community-based clinical trials.

In the U.K.-based PANORAMIC trial, the incidence of all-cause hospitalization or death after 28 days was 0.8% among those receiving the antiviral combination plus usual care, which was comparable to the 0.7% of peers receiving only usual care (adjusted OR 1.18, 95% Bayesian credible interval [CrI] 0.55-2.62).

With an estimated 33% chance of superiority over usual care, nirmatrelvir-ritonavir fell well short of the superiority threshold of 97.5% in this trial of over 3,000 higher-risk people.

In the smaller Canadian CanTreatCOVID trial, the same outcome of hospitalization or death reached 0.6% in the nirmatrelvir-ritonavir group and 1.2% with usual care. The between-arm difference was again not significant (adjusted OR 0.48, 95% CrI 0.08-2.23), and the antiviral treatment's 83% probability of superiority over usual care once more fell short of the 97.5% threshold.

The two studies were reported together by Christopher Butler, MD, of the University of Oxford, England, and colleagues in the New England Journal of Medicine.

"We found no evidence that early treatment with nirmatrelvir-ritonavir reduced the already-low incidence of hospitalization or death in either trial and were unable to identify any prespecified subgroup with compelling evidence of treatment effect," Butler and colleagues wrote.

Nirmatrelvir-ritonavir was first made available under emergency use authorization by the FDA in late 2021, and was FDA approved in 2023 as a 5-day regimen for treating adult outpatients with mild to moderate COVID-19 at risk for severe disease. Approval was based on efficacy data in symptomatic, unvaccinated adults testing positive for SARS-CoV-2 infection in the EPIC-HR trial.

Now, the PANORAMIC and CanTreatCOVID results reflect a COVID-19 landscape that's shifted since the pandemic's early period, said H. Clifford Lane, MD, former deputy director for clinical research and special projects at the National Institute of Allergy and Infectious Diseases (NIAID), and Anthony Fauci, MD, the former NIAID director.

"These new data indicate that the 89% relative risk reduction seen in the analysis of hospitalizations or death associated with the use of nirmatrelvir-ritonavir in the EPIC-HR trial does not apply to the current circumstances, in which most adults have varying degrees of preexisting immunity and the circulating variants are different," Lane and Fauci wrote in an accompanying editorial.

That doesn't mean nirmatrelvir-ritonavir's therapeutic time has come and gone, they cautioned. PANORAMIC and CanTreatCOVID participants who took the combination drug saw enhanced recovery and faster viral load reductions, they noted, which points to both clinical efficacy and antiviral activity.

Indeed, Butler's group reported that early sustained recovery, defined as recovery by day 14 of treatment that was sustained to day 28, reached 33% and 22.1% in PANORAMIC's treatment and control arms, respectively (adjusted OR 1.74, 95% CrI 1.48-2.04), and 69% and 53.1% in CanTreatCOVID (adjusted OR 1.99, 95% CrI 1.40-2.87). Median time to recovery with the antiviral was 3 to 7 days shorter in the two studies.

Furthermore, in a PANORAMIC virology substudy of 485 participants, 29.2% of nirmatrelvir-ritonavir recipients reached a viral load below detection level at day 5, a significant improvement over the 16.5% of controls (adjusted OR 2.15, 95% CrI 1.37-3.44). Day 5 geometric mean viral load was 3,587 in the nirmatrelvir-ritonavir group and 30,267 among controls (adjusted geometric mean ratio 0.13, 95% CrI 0.08-0.21).

"Clinicians may become more selective regarding which patients to refer for treatment," Lane and Fauci wrote. "But it still would seem prudent to consider antivirals on a case-by-case basis, particularly in older adults, persons with a compromised immune system, and persons for whom more-rapid recovery is a priority."

The open-label, prospective PANORAMIC and CanTreatCOVID trials enrolled adults in the community at higher risk of COVID-19, which included either those age 50 years or older and younger adults with relevant coexisting conditions. Participants had to have SARS-CoV-2 infection symptoms for 5 days or less and a positive COVID test.

Patients were randomized to receive either usual care plus daily oral nirmatrelvir-ritonavir for 5 days, or usual care alone. The PANORAMIC primary analysis included 1,698 people who received nirmatrelvir-ritonavir and 1,673 who received usual care. CanTreatCOVID included 343 people in the nirmatrelvir-ritonavir group and 324 in the usual-care group.

PANORAMIC evaluated nirmatrelvir-ritonavir from April 2022 to March 2024, while CanTreatCOVID evaluated the intervention from January 2023 to September 2024. Nearly everyone in PANORAMIC and CanTreatCOVID was vaccinated, with rates reaching at least 97.8% among all participants.

Most of PANORAMIC's nirmatrelvir-ritonavir group had adverse events (90.4%), while 0.5% had serious adverse events. The rate of serious adverse events in CanTreatCOVID was higher in the usual-care only group (3.4%) than in the nirmatrelvir–ritonavir group (1.3%).

Butler's group acknowledged that the two studies had an open-label design that precluded estimation of placebo or nocebo effects.

Additionally, the CanTreatCOVID trial was stopped early due to slow recruitment and because the supply of nirmatrelvir-ritonavir was discontinued.

Disclosures

The two studies were supported by the U.K. National Institute for Health and Care Research, the Canadian Institutes of Health Research, and Health Canada.

Butler, Lane, and Fauci had no relevant disclosures. Study coauthors disclosed relationships with multiple companies.

Primary Source

New England Journal of Medicine

Source Reference: Butler CC, et al "Oral nirmatrelvir-ritonavir for Covid-19 in higher-risk outpatients" N Engl J Med 2026; DOI: 10.1056/NEJMoa2502457.

Secondary Source

New England Journal of Medicine

Source Reference: Lane HC, Fauci AS "Same pill, different impact -- reassessing the efficacy of nirmatrelvir-ritonavir" N Engl J Med 2026; DOI: 10.1056/NEJMe2603127.

https://www.medpagetoday.com/infectiousdisease/covid19/120915

'Machine Analyzes Joint X-Rays About as Well as Humans'

 

• The Sharp/van der Heijde (SvdH) method for analyzing X-ray images is the standard way to measure joint space narrowing and bone erosions in rheumatoid arthritis, requiring well-trained readers.
• Recent advances in machine learning and artificial intelligence carry the potential to automate SvdH scoring.
• In this early study, a machine-learning system called autoscoRA produced SvdH scores with good to excellent concordance with experienced human readers.

A machine-learning system for analyzing rheumatoid arthritis (RA) patients' X-rays was able to produce Sharp/van der Heijde (SvdH) scores, the standard way to quantify joint space narrowing and bone erosions, with good accuracy when compared with human readers, researchers said.

Called autoscoRA, the system matched the human reader's scores for joint space narrowing in more than 95% of hand and foot images, according to Thomas Deimel, MD, of the Medical University of Vienna in Austria, and colleagues.

Performance in scoring erosions was more variable, the group reported in Arthritis & Rheumatology, but the level of agreement was still considered good. Scoring differences greater than 1 point in the SvdH method were seen for only 6.3% of hand images and 11.0% of foot X-rays.

Another finding in favor of autoscoRA came from a test in which images were scored by the first human reader, autoscoRA, and a second human reader. AutoscoRA agreed with the first reader for summed scores with an intraclass correlation of 0.94, whereas the second human reader's scores agreed with the first's with a correlation of 0.86. When scoring individual joints, autoscoRA readouts for joint space narrowing differed from the first reader's by more than 1 point in fewer than 3% of instances, whereas for the second reader, about 10% of images had these differences.

"For the erosion score, the performance of the automated system roughly matched that of the second human reader numerically, although visual inspection indicated potentially more consistent predictions by the former," Deimel and colleagues added.

One of the problems with standard SvdH scoring is that inter-reader (and even intra-reader) reliability is only so-so. Consistency, therefore, is a desirable goal for any method of radiograph analysis. For one thing, errors are more likely to be systematic and therefore more easily recognized and rectified than if they occur randomly.

Another reason to favor an automated system is cost and efficiency. SvdH scoring requires considerable training and experienced readers are therefore scarce, especially outside major referral centers. The reading itself is also time-consuming and, with the requirement for specialized staff to do it, expensive. "An automated system such as autoscoRA directly addresses the feasibility gap, offering a scalable and reproducible solution that transforms imaging into reliable, structured outcome data," Deimel and colleagues wrote.

AutoscoRA has been under development for some time; Deimel gave a preliminary presentation on it at a 2020 rheumatology conference. This new study included many more images and additional analyses to better define the system's potential.

The researchers drew on a large archive of hand and foot X-rays from 769 RA patients seen at the Medical University of Vienna, who had a total of 3,437 clinic visits and more than 12,000 radiographs. Some 60% of images were used for training, 20% for validation, and 20% as a "test set." The comparative testing with autoscoRA and human readers was performed on this latter set.

Besides scoring individual radiographs, the study also looked at serial images from 54 patients with a total of 237 visits over time. This allowed an examination of how autoscoRA could quantify disease progression. Agreement with the human reader averaged 70% over a range of progression definitions (i.e., the degree of change in erosion and joint space scores over time). "Overall performance appeared to be relatively stable across the range of cutoffs," the researchers wrote.

Deimel and colleagues stressed that autoscoRA needs additional "external validation" with images from other institutions, as well as more focus on the system's ability to assess progression over time, before it could be considered for routine clinical use. In the meantime, however, the researchers suggested that it could find near-term application in clinical trials and for analyzing large image collections such as those in registries and other observational patient cohorts.

Disclosures

The study was funded by the Innovative Health Initiative Joint Undertaking, which is supported by the European Union, Swiss and Austrian national governments, and a variety of nonprofit organizations and commercial enterprises involved in healthcare technology.

Co-authors reported relationships with numerous pharmaceutical companies.

Primary Source

Arthritis & Rheumatology

Source Reference: Deimel T, et al "autoscoRA: deep learning to automate Sharp/van der Heijde scoring of radiographic damage in rheumatoid arthritis" Arthritis Rheumatol 2026; DOI: 10.1002/art.70196.

https://www.medpagetoday.com/radiology/diagnosticradiology/120923

IBM beats Q1 2026 estimates with EPS $1.91, revenue $15.9B as J.P. Morgan cuts price target

 

IBM beats Q1 2026 estimates with EPS $1.91, revenue $15.9B as J.P. Morgan cuts price target to $270 from $283

• J.P. Morgan Securities cut IBM price target to $270 from $283 after it maintained full-year guidance despite slowing revenue growth.
• Q1 2026 revenue was $15.92B, up 9% YoY, supported by AI-driven hybrid cloud and mainframe growth.
• Q1 revenue grew 6% at constant currency, with broad-based strength in software and infrastructure.
• Software revenue rose 8%, driven by 16% growth in Data and 10% growth in Red Hat.
• Infrastructure revenue increased 12%, including 48% growth in IBM Z and double-digit distributed infrastructure.
• Consulting grew 1%, with signings up 6% and generative AI now ~30% of backlog.
• Consulting revenue slightly missed estimates despite overall Q1 earnings and revenue outperformance.
• Margins expanded strongly: operating pretax margin +140 bps, infrastructure margin +720 bps, software +60 bps.
• Free cash flow was $2.2 billion, up 13% YoY, the strongest Q1 in a decade.
• Full-year 2026 guidance maintained: 5%+ constant-currency revenue growth and ~$1 billion free cash flow increase.
• Management now expects software to grow 10%+ in 2026, data segment low-20%+, consulting low-to-mid single digits.
• IBM increased its quarterly dividend to $1.69, raising its regular payout to shareholders.
• Key risks: macro/geopolitics, infrastructure and mainframe cycle dependence, despite unchanged guidance and no reported demand deterioration.
• Strong quarter, driven by accelerating software and infrastructure growth, expanding margins, and robust free cash flow.

https://finviz.com/quote.ashx?t=IBM&p=d