Tag: Medication

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FDA Clears First AI Algorithm to Diagnose Cardiac Amyloidosis

Anumana has received FDA approval for its ECG-AI algorithm designed to support the diagnosis of cardiac amyloidosis at the point of care. This makes it the first and only AI algorithm cleared by the FDA for this severe heart condition, which is often missed by the human eye when looking at electrocardiogram (ECG) data.  

“Cardiac amyloidosis can be challenging to detect early, especially when its signs overlap with more common heart conditions,” said Martha Grogan, MD, consultant in cardiovascular medicine at Mayo Clinic and co-principal investigator of the clinical study that supported the approval. “A tool that helps clinicians recognize suspicion of amyloidosis from a routine ECG could support earlier diagnosis and more timely next steps in care.”

Caused by abnormal protein deposits in the heart, cardiac amyloidosis is a life-threatening condition that can lead to heart failure if missed. Early diagnosis is critical to ensure a timely intervention, which can significantly improve patient outcomes, but the condition is often underdiagnosed due to unspecific symptoms that can be easily mistaken for other, more common heart conditions. 

Symptoms of cardiac amyloidosis are evaluated using a routine ECG. However, diagnosis requires identifying a combination of subtle features found in ECG data, meaning human interpretation can often miss the condition. 

Anumana’s ECG-AI algorithm can analyze ECG waveform to detect these subtle patterns in the data and support the diagnosis process. In a validation study involving more than 15,000 adults presenting signs, symptoms, or comorbidities of cardiac amyloidosis, the AI model detected the condition with 78.9% sensitivity and 91.2% specificity. 

“What makes this work especially meaningful is the rigor of the validation,” said Angela Dispenzieri, MD, hematologist at Mayo Clinic and co-principal investigator of the clinical study. “This ECG-AI algorithm was validated in a large multicenter study that included both ATTR and AL cardiac amyloidosis at major referral centers with deep expertise in amyloidosis diagnosis, supporting its potential to help identify patients earlier.”

Because the algorithm leverages ECGs obtained in routine clinical practice, it can be directly integrated into existing workflows without requiring clinicians to conduct any additional testing, helping them identify patients at risk and informing treatment decisions. 

Anumana previously received FDA clearance for two other ECG-AI algorithms, one for the diagnosis of low ejection fraction and another for pulmonary hypertension. All of these heart conditions are characterized by complex diagnoses that are often delayed or missed; for these patients, early diagnosis and treatment can significantly increase their outcomes and life expectancy.

“Each of our FDA-cleared algorithms addresses a specific and frequently missed cardiovascular condition, and cardiac amyloidosis represents an important addition to that portfolio,” said Maulik Nanavaty, CEO of Anumana. “The more conditions we can identify from a single ECG, the more valuable the test becomes in clinical practice. That’s what Anumana is working toward with each new clearance as we continue to advance our rigorous clinical evidence approach.”

The post FDA Clears First AI Algorithm to Diagnose Cardiac Amyloidosis appeared first on Inside Precision Medicine.

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Metabolic Driver of Radiation Resistance in Lung Cancer Identified

Radiation therapy remains a cornerstone of lung cancer treatment, yet its long-term effectiveness is often undermined by a persistent challenge: tumors adapt and become resistant. Understanding, and overcoming, this resistance is a major priority in oncology.

A new study from researchers at The University of Texas MD Anderson Cancer Center, published in Cancer Research, identifies a metabolic mechanism that allows lung cancer cells to evade radiation-induced death and proposes a clinically actionable strategy to counter it.

A hidden driver of resistance

Radiotherapy works by damaging cancer cells in multiple ways, including triggering ferroptosis—an iron-dependent form of cell death driven by oxidative stress. However, many tumors develop the ability to suppress this process, allowing them to survive treatment.

The new study pinpoints a key player in this resistance: the mitochondrial enzyme dihydroorotate dehydrogenase (DHODH). Researchers found that radiation exposure increases DHODH activity in lung cancer cells, enabling them to withstand ferroptosis and continue growing.

“This is an important finding because of the immediate translational opportunity,” said Boyi Gan, PhD, senior author of the study. “By understanding how DHODH is preventing cell death in radioresistant cancer cells, we were able to develop a strategy to overcome radiation therapy resistance in tumor models.”

A metabolic shield against cell death

DHODH is best known for its role in nucleotide synthesis, helping cells produce the building blocks needed for DNA repair and replication. But the study highlights an additional function that is particularly relevant in cancer.

The enzyme also supports the production of ubiquinol, a molecule that protects cells from oxidative damage. In the context of radiation therapy, this acts as a shield, preventing the lipid damage required to trigger ferroptosis.

By simultaneously promoting DNA repair and suppressing ferroptosis, DHODH enables cancer cells to survive what would otherwise be lethal radiation-induced stress.

Repurposing an existing drug

Rather than developing a new inhibitor from scratch, the researchers turned to leflunomide—an FDA-approved drug currently used to treat rheumatoid arthritis, which is known to inhibit DHODH.

In preclinical models, blocking DHODH alone modestly increased sensitivity to radiation. However, the most striking results emerged when the team combined three treatment modalities: radiation therapy, immune checkpoint blockade, and DHODH inhibition.

Radiation plus immunotherapy alone was insufficient to control tumor growth. But when leflunomide was added, the combination restored ferroptosis and led to a marked reduction in tumor progression.

“DHODH inhibition alone had some effect on sensitization to radiation therapy, but it was really this triple combination that had a marked effect,” Gan said.

Leveraging the immune response

A key aspect of the strategy lies in its interaction with the immune system. Immunotherapy, specifically anti–PD-1 checkpoint blockade, stimulates the production of interferon-gamma (IFN-γ), a signaling molecule that can enhance ferroptosis.

However, in resistant tumors, this signal alone is not enough to overcome the protective effects of DHODH. By inhibiting the enzyme, the researchers effectively remove this metabolic barrier, allowing IFN-γ–driven ferroptosis to proceed.

The result is a coordinated therapeutic effect in which radiation induces stress, immunotherapy amplifies cell death signals, and DHODH inhibition prevents tumor cells from escaping.

Toward clinical translation

One of the most compelling aspects of the study is its translational potential. Leflunomide is already widely used in clinical practice, with a well-characterized safety profile, potentially accelerating its evaluation in oncology settings.

“These findings provide a good rationale for testing this combination in clinical studies,” Gan said in a press release.

If validated in patients, this approach could offer a new strategy for overcoming resistance not only in lung cancer but potentially in other solid tumors treated with radiotherapy.

A broader shift in cancer therapy

The findings also reflect a broader trend in cancer research: targeting metabolic pathways that enable tumor survival under stress. While traditional therapies focus on directly damaging cancer cells, emerging approaches aim to disrupt the adaptive mechanisms that allow tumors to recover.

By linking metabolism, immune signaling, and cell death pathways, the study provides a more integrated view of how resistance develops—and how it can be reversed.

Although the results are based on preclinical models, they offer a clear path forward. Future clinical trials will be needed to determine whether the triple combination strategy can improve outcomes in patients with radioresistant lung cancer.

More broadly, the work highlights the importance of identifying “druggable” vulnerabilities within resistance pathways, especially those that can be targeted with existing therapies.

In this case, a drug originally developed for autoimmune disease may help solve one of the most persistent challenges in cancer treatment: restoring the effectiveness of radiation therapy when it begins to fail.

The post Metabolic Driver of Radiation Resistance in Lung Cancer Identified appeared first on Inside Precision Medicine.

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Therapeutic Potential of GLP-1 Receptor Agonists for Smoking Cessation

Glucagon-like peptide-1 (GLP-1) therapies are under investigation for a growing number of neuropsychiatric conditions, including substance use disorders. Cigarette smoking accounts for the largest proportion of substance use-related morbidity and mortality, in part reflecting increased risk for cardiometabolic disease among people who smoke. Given modest quit rates with approved smoking cessation therapies, medications with novel mechanisms of action are needed to expand the available monotherapy and combination treatment options.

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AI Finds Unreported Side Effects of GLP-1 Drugs in Reddit Posts

A study of more than 400,000 posts in the social media platform Reddit has identified previously unreported side effects from the increasingly popular GLP-1 weight loss and diabetes drugs. Users reported symptoms affecting menstrual cycles and body temperature, which have not yet been described in clinical trials or included in drug labels.  

Published today in Nature Health, the study covers over five years of public online posts from nearly 70,000 Reddit users discussing their personal experience taking the GLP-1 drugs semaglutide and tirzepatide.

“Some of the side effects we found, like nausea, are well known, and that shows that the method is picking up a real signal,” says Sharath Chandra Guntuku, PhD, research associate professor in computer and information science at Penn Engineering and the study’s senior author. “The underreported symptoms are leads that came from patients themselves, unprompted, and clinicians could potentially pay attention to them.”  

Although the study is not representative of the broader population—Reddit users are generally younger, more likely male and based in the U.S.—the symptoms reported collectively match known side effects of semaglutide and tirzepatide. About 44% of users described at least one known side effect, most commonly symptoms of gastrointestinal distress. 

“Clinical trials generally identify the most dangerous side effects of drugs, but they can fail to find what symptoms patients are most concerned about,” says Lyle H. Ungar, PhD, professor in computer and information science at Penn Engineering. “Online patient communities work a lot like a neighborhood grapevine. People who are living with these medications are swapping notes with each other in real time, sharing experiences that rarely make it into a doctor’s office visit or an official report. Even though social media is not necessarily representative, a large collection of posts may reflect additional concerns.” 

The study uncovered a series of side effects that were previously unreported for these drugs. This included discussions of menstrual cycle changes, such as intermenstrual bleeding, heavy bleeding, and irregular cycles. Other users reported chills, hot flashes, fever, and other temperature-related symptoms. In addition, fatigue symptoms ranked as the second most common complaint in these online posts despite rarely being reported in clinical trials. 

“We can’t say that GLP-1s are actually causing these symptoms,” says Neil K. R. Sehgal, doctoral student at the University of Pennsylvania and the study’s lead author. “But nearly 4% of the Reddit users in our sample reported menstrual irregularities, which would be even higher in a female-only sample. We think that’s a signal worth investigating.” 

While efforts to scour the internet for self-reported drug side effects have been ongoing for more than a decade, screening through social media posts at scale remained challenging until the arrival of large language models such as ChatGPT or Gemini. In particular, these tools can prove instrumental in mapping the language users use to describe their symptoms to clinical terminology defined in the Medical Dictionary for Regulatory Activities (MedDRA), used to officially report symptoms in clinical trials. 

“Large language models have made it possible to do this kind of analysis much faster with a level of standardization that could be difficult to achieve before,” says Sehgal. 

The researchers hope these findings will encourage researchers and drug developers to investigate the side effects discussed by users online. In future work, the team plans to expand beyond Reddit and English-language discussions to confirm whether the same symptoms appear across different social media platforms and populations. 

While this approach is not intended as a replacement for clinical trials, screening social media posts for clues on unreported side effects can make a significant difference in terms of speed. This can be especially relevant for drugs like semaglutide and tirzepatide, originally diabetes drugs that quickly became mainstream when the FDA granted them approval as weight loss drugs. 

“Clinical trials are the gold standard, but by design, they are slow,” says Guntuku. “The whole point of this kind of approach is that it can move quickly, and that’s exactly when it’s most valuable.”

The post AI Finds Unreported Side Effects of GLP-1 Drugs in Reddit Posts appeared first on Inside Precision Medicine.

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Artificial Sweeteners Could Alter Metabolism over Generations

Popular low-calorie sugar substitutes can negatively affect both the balance of microbes in the gut and gene expression in a heritable way, preclinical research suggests.

The findings in mice, published in Frontiers in Nutrition, challenge long-standing assumptions that non-nutritive sweeteners (NNS) are metabolically inert and underscore their potential to influence health across generations through microbial and molecular pathways.

Both sugar alternatives studied had an impact: sucralose, a popular artificial sweetener that is around 600 times sweeter than sugar, and stevia, a no-calorie natural alternative extracted from the leaves of a South American plant.

Lead researcher Francisca Concha Celume, PhD, from the University of Chile, said the changes seen in glucose tolerance and gene expression could be interpreted as early biological signals related to metabolic or inflammatory diseases.

“For example, the animals did not develop diabetes. Instead, what we observed were subtle changes in how the body regulates glucose and in the activity of genes associated with inflammation and metabolic regulation,” she explained.

“It is possible that such changes could increase susceptibility to metabolic disturbances under certain conditions, such as a high-fat diet.”

Celume and team divided 47 male and female mice into three groups receiving either plain water, or water with sucralose or stevia added over 16 weeks at levels comparable to those seen in a usual human diet.

These mice were then bred, with each of the two subsequent generations just receiving plain water.

The team found there were no differences in glycemic response in the initial group, but that it had mildly altered in the male offspring of those fed sucralose in both successive generations. By the second generation, female mice with stevia-consuming grandparents had elevated fasting blood sugar.

Fecal microbiomes in both sets of animals receiving sweeteners were more diverse than in those given plain water. But sweetener-fed mice also had lower levels of short-chain fatty acids, which could signal epigenetic changes and could indicate that bacteria may be generating less beneficial metabolites and that this was passed on to subsequent generations.

Mice that had consumed sucralose were particularly affected and had more pathogenic bacteria and fewer beneficial species in their fecal microbiomes. The impact of this sweetener tended to be more consistent and persistent across generations.

The researchers also examined the impact of five genes relating to inflammation, gut barrier function, and metabolism in the liver and intestines.

Overexpression in the inflammation-linked toll-like receptor-4 (tlr4) and tumor necrosis factor (tnf) genes was seen both in animals that consumed sucralose and stevia. This was also seen in the immediate offspring of the former but not the latter.

The expression of sterol regulatory element-binding protein 1 (Srepb1), which is linked with regulation of lipid and carbohydrate metabolism, was decreased in the liver of sucralose-fed animals and subsequent generations.

“In summary, our findings demonstrate that parental consumption of sucralose or stevia induces persistent, intergenerational changes in host metabolism, intestinal and hepatic gene expression, gut microbiota composition, and microbial metabolite production in unexposed offspring,” the researchers concluded.

They added: “Given the widespread use of NNS during critical developmental periods, these findings raise important questions about their safety and long-term impact.”

The post Artificial Sweeteners Could Alter Metabolism over Generations appeared first on Inside Precision Medicine.

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A Text Messaging–Based Program to Transition From Basal Insulin to Glucagon-Like Peptide-1 Receptor Agonists in Safety-Net Diabetes Care: Pilot Quality Improvement Intervention Study

Background: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and basal insulin both lower blood sugar, but while insulin puts people at risk of hypoglycemia and weight gain, GLP-1 RAs do not. In addition, GLP-1 RAs have added cardiometabolic and renal benefits. For these reasons, when possible, many primary care providers prefer their patients with type 2 diabetes to be from basal insulin to a GLP-1 RA. This transition process can be labor intensive, requiring multiple dosing adjustments and a watchful eye for hypoglycemia and hyperglycemia. The Mobile Insulin Titration Intervention (MITI)–GLP1 program uses SMS text messaging–based technology to support a streamlined and supervised transition process from basal insulin to a GLP-1 RA. This program takes place at a multilingual safety-net clinic. Objective: Our objectives were to assess program feasibility and acceptability to determine whether the intervention was doable, practical, and worthy of further investigation via a larger controlled trial. Preliminary clinical outcomes are also discussed in this paper. Methods: Patients were enrolled on a secure web platform that sent them a daily SMS text message asking the following: “What was your fasting blood sugar this morning?” Each weekday, texted responses containing patients’ fasting blood sugar levels were checked for alarm values, and once weekly, patients were called and advised on whether and how to lower their basal insulin and increase their GLP-1 RA dose. The program was co-run by general internal medicine physicians and nurses and continued until the patient had their insulin stopped completely and/or their GLP-1 RA dose reached the maximum, or 16 weeks elapsed. All enrolled patients were included in the analyses. Results: A total of 72 patients completed the pilot program. Feasibility and acceptability were high. Of 3671 SMS text messages sent by the program, 3520 (95.89%) received a response from patients. Of 719 cumulative weeks in which Thursday titration phone calls were attempted, successful connections with patients were made in 649 (90.26%) instances. Preliminary clinical outcomes were promising. Insulin doses were meaningfully reduced (55/72, 76.39% had their basal insulin reduced by at least 50%; 45/72, 62.5% had their insulin stopped completely). GLP-1 RA doses were meaningfully increased (64/72, 88.89% had their GLP-1 RA dose increased by ≥1 level; 45/72, 62.5% were discharged on the maximum dose of their GLP-1 RA). There was minimal hypoglycemia (5/3520, 0.14% of the SMS text messages reported a value of <80 mg/dL) and hyperglycemia (1/3520, 0.03% of the SMS text messages reported a value of >400 mg/dL). Conclusions: A general internal medicine–run MITI-GLP1 pilot program using SMS text messaging and interdisciplinary teamwork between internists and nurses is a feasible and acceptable intervention for safely and effectively transitioning people with well-controlled type 2 diabetes away from basal insulin and toward a GLP-1 RA.
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STAT+: A new health care blueprint from a key Democratic think tank

You’re reading the web edition of D.C. Diagnosis, STAT’s twice-weekly newsletter about the politics and policy of health and medicine. Sign up here to receive it in your inbox on Tuesdays and Thursdays.

In which RFK Jr. says the “government lies to us” while sitting in front of an HHS seal. Send news tips and podcast recommendations to John.Wilkerson@statnews.com or John_Wilkerson.07 on Signal.

First, control health care costs

Last month, a group of 12 Senate Democrats proposed a framework for rebuilding the health care system. The idea was to spur input from others ahead of when Democrats might get a chance to act on those plans.

Continue to STAT+ to read the full story…

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CAR T Cells Drive Recovery in Severe Autoimmune Disease Case

A single infusion of zorpocabt agene-autoleucel (Zorpo-cel), an autologous CAR T-cell therapy, has led to a rapid and sustained remission in a patient with multiple life-threatening autoimmune disorders, according to a newly reported case published in Med. 

Researchers from the University Hospital of Erlangen at Friedrich-Alexander-Universitat Erlangen-Nürnberg in Germany describe how a CD19-targeting CAR T-cell therapy successfully treated a 47-year-old woman suffering from severe autoimmune hemolytic anemia (AIHA), along with immune thrombocytopenia (ITP) and antiphospholipid antibody syndrome (APLAS). All three conditions are driven by malfunctioning B cells that produce harmful autoantibodies attacking the body’s own tissues.

The patient’s condition had proven exceptionally difficult to manage. Over nearly a decade, she had undergone nine different treatment regimens, including steroids, immunosuppressants, and antibody-based therapies, without lasting success. Her AIHA was particularly severe, leaving her dependent on daily blood transfusions and at risk of organ damage due to chronic anemia and iron overload.

With no effective options remaining, the clinicians, under compassionate use, turned to the CAR T-cell therapy developed by Miltenyi Biomedicine. This technique involves collecting a patient’s own T cells, genetically modifying them to target the B cell marker CD19 and reinfusing them to eliminate the dysfunctional immune cells.

The results were striking. Within just seven days of treatment, the patient no longer required blood transfusions. By day 25, her hemoglobin levels had returned to normal, indicating a complete resolution of the hemolytic anemia. Laboratory markers of red blood cell destruction also normalized rapidly.

Equally notable was the therapy’s broader impact. The patient’s elevated antiphospholipid antibodies—responsible for dangerous blood clots in APLAS—fell to normal levels and remained undetectable through 11 months of follow-up. Meanwhile, her platelet counts stabilized, indicating improvement in ITP without the need for additional treatment.

Researchers attribute this success to a “reset” of the patient’s B cell population. Unlike conventional therapies such as rituximab, which partially deplete B cells, CAR T cells appear to achieve deeper and more durable elimination. When B cells eventually returned months later, they were predominantly naïve, suggesting a reprogrammed and healthier immune profile.

Importantly, the treatment was well tolerated. The patient experienced none of the serious side effects commonly associated with CAR T therapy in cancer patients, such as cytokine release syndrome or neurotoxicity. Some mild liver enzyme elevations and blood count abnormalities were observed, likely related to prior treatments and iron overload rather than the therapy itself.

This is the second clinical win for Zorpo-cel in the treatment of autoimmune diseases this year. In January, the Phase I/II basket trial known as the CASTLE trial reported encouraging early results of Zorpo-cel administration in 24 patients with treatment-resistant autoimmune diseases, including systemic lupus erythematosus (SLE), systemic sclerosis (SSc), and idiopathic inflammatory myopathies (IIM). The therapy showed a favorable safety profile, with no cases of severe cytokine release syndrome or neurotoxicity observed. Efficacy outcomes were strong: 22 of 24 patients met predefined endpoints, including remission in most SLE patients, halted disease progression in all SSc patients, and meaningful clinical responses in the majority of IIM cases.

The case highlights the growing potential of CAR T therapy beyond oncology. Previous studies have shown promising results in systemic autoimmune diseases like lupus, but evidence in hematologic autoimmune disorders such as AIHA has been limited. While the findings are encouraging, researchers caution that this is a single case report. Larger, controlled clinical trials will be necessary to confirm safety, effectiveness, and long-term outcomes across diverse patient populations.

The post CAR T Cells Drive Recovery in Severe Autoimmune Disease Case appeared first on Inside Precision Medicine.

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Targeting the microbiota-gut-brain axis in post-stroke insomnia: a phase-dependent therapeutic framework

Post-stroke insomnia (PSI) is a critical biological barrier to neurorehabilitation afflicting over half of all stroke survivors. Traditional sedatives often force clinicians into a therapeutic dilemma between sleep efficacy and cognitive suppression. The microbiota-gut-brain (MGB) axis has recently emerged as a transformative target to resolve this impasse. Acute stroke triggers profound autonomic dysfunction, causing immediate intestinal barrier collapse. This “leaky gut” facilitates the systemic translocation of lipopolysaccharides (LPS) and activates the NLRP3 inflammasome. The resulting inflammatory storm hijacks central tryptophan metabolism via the indoleamine 2,3-dioxygenase (IDO) enzyme. This “tryptophan steal” diverts serotonin precursors toward neurotoxic kynurenine pathways, driving severe cortical hyperarousal. Sleep fragmentation then prevents the glymphatic system from clearing metabolic waste, further exacerbating neuroinflammation. To break this vicious cycle of neurotoxicity, we propose a phase-dependent therapeutic framework. During the highly vulnerable acute phase, interventions must prioritize gut barrier protection using postbiotics to mitigate infection risks under CNS injury-induced immunodepression (CIDS), often discussed as stroke-induced immunosuppression. As patients enter the chronic phase, therapy shifts toward metabolic restoration using live therapeutics, such as washed microbiota transplantation (WMT) and next-generation psychobiotics like Akkermansia muciniphila. Targeting the MGB axis offers a mechanism-based strategy to achieve precision sleep medicine, restoring the biological foundation necessary for optimal neuroplasticity and recovery.
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C-section rate in 2025 highest in a decade 

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A First Opinion essay today argues that “tastiness is not why people overeat.” But I may beg to differ — and so may a friend of mine who recently gave me a stuffed scolding after I convinced her to order pad thai for the table in addition to our meals.

Read the rest…