Muthiah Vaduganathan, MD, MPH, is a cardiologist specializing in cardiorenal metabolism at Brigham and Women's Hospital in Boston, MA. Vaduganathan is a member of Practical Cardiology's advisory board and co-host of Don't Miss a Beat, a podcast presented by Inside Cardiology.

Evaluating Clinical Gaps in Combining uACR and eGFR Testing in CKD Diagnosis

This episode, titled, ‘Evaluating Clinical Gaps in Combining uACR and eGFR Testing in CKD Diagnosis,’ features panelists discussing the following critical questions:

Do gaps persist in combining uACR and eGFR testing among patients with CKD-related comorbidities beyond T2D, and where are these gaps most evident across primary care, cardiology, nephrology, and endocrinology?

What recommendations would you make to improve testing uptake?

The discussion highlights that while routine panels often include eGFR, lipid panels, and hemoglobin A1c, these tests alone do not capture the full scope of kidney risk, making uACR an essential complement. Panelists explain the practicalities of uACR testing, including using a quantitative lab measurement rather than a simple urine dip, and addressing factors like hydration, exercise, and timing to ensure accuracy. They stress repeating a positive uACR within three months to confirm a CKD diagnosis, paralleling the complementary roles of eGFR and uACR in assessing both kidney function and damage. The conversation also touches on barriers to implementation, such as clinician unfamiliarity and workflow challenges, while emphasizing that comprehensive testing is inexpensive, straightforward, and critical for identifying patients at latent risk. Overall, the panel underscores that missing uACR testing is akin to checking only part of a vital sign—it leaves the clinician with an incomplete picture and potentially misses opportunities for early intervention.

In the next episode, ‘uACR and eGFR Testing in CKD: Addressing Barriers and Patient Communication,’ panelists will continue their discussion on chronic kidney disease and highlight operational and behavioral hurdles to CKD screening, ranging from a "not my lane" mentality to the common misconception that a standard urine dipstick is a sufficient substitute for uACR testing. They advocate for overcoming clinical inertia by integrating eGFR and uACR into comprehensive cardiovascular risk assessments, specifically utilizing the KDIGO heat map as a tool to communicate systemic vascular health to patients.

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Combined Role of Estimated Glomerular Filtration Rate (eGFR) and Urine Albumin-Creatinine Ratio (uACR) Testing in CKD

In ‘Combined Role of Estimated Glomerular Filtration Rate (eGFR) and Urine Albumin-Creatinine Ratio (uACR) Testing in CKD,’ our experts delve into the following critical question:

How do you explain estimated glomerular filtration rate (eGFR) and urine albumin-creatinine ratio (uACR) to patients and their combined role in CKD diagnosis and staging?

Led by the moderator, the experts explore the practical steps clinicians should take after ordering a uACR, including how to interpret results and communicate their significance to patients. They emphasize that uACR and eGFR are complementary measures, with eGFR reflecting kidney function and uACR serving as a marker of endothelial and vascular damage that informs both kidney and cardiovascular risk. The discussion highlights the KDIGO heat map as a practical tool that integrates these measures to stratify risk, guide follow-up testing, and inform referral decisions. The experts underscore that uACR is critical for uncovering latent CKD in patients with normal or mildly reduced eGFR, and that failing to test for albuminuria results in missed diagnoses and unrecognized cardiovascular risk across all care settings.

Our next episode, ‘Evaluating Clinical Gaps in Combining uACR and eGFR Testing in CKD Diagnosis,’ further explores chronic kidney disease, highlighting the importance of pairing uACR with eGFR in routine renal screening to get a complete picture of kidney health. The panel emphasizes proper ordering, testing techniques, and follow-up to ensure accurate diagnosis and management of chronic kidney disease.

Learn how UACR testing complements eGFR, reveals hidden kidney and cardiovascular risk, and uses a color-coded heat map to guide patient communication and referrals.

Emphasizing Multidisciplinary Collaboration for Early CKD Diagnosis

In this episode, ‘Emphasizing Multidisciplinary Collaboration for Early CKD Diagnosis,’ the panelists explore the following question:

How does research in this area emphasize the need for proactive detection strategies across specialties?

The discussion emphasizes that early diagnosis and management of CKD is a shared responsibility across specialties, not the sole domain of nephrology or primary care, given the numerous clinical touchpoints for patients with diabetes, obesity, and cardiovascular disease. Panelists highlight how diffusion of responsibility and workflow barriers—such as uncertainty about urine testing, confusion around uACR and eGFR interpretation, and lack of follow-up processes—often lead to missed screening and delayed action. They stress that relying on “someone else” to address CKD allows patients to fall through the cracks, underscoring the need for every clinician to become comfortable with screening, communication, and early treatment. Drawing parallels to cardiology’s evolution in owning cholesterol and SGLT2 inhibitor use, the panel calls for a cultural shift in which all specialties step forward, supported by decision tools and updated care models, to deliver timely, evidence-based CKD care.

The next episode in this series, ‘Combined Role of Estimated Glomerular Filtration Rate (eGFR) and Urine Albumin-Creatinine Ratio (uACR) Testing in CKD,’ features the panelists advancing their conversation on chronic kidney disease and focusing on the practical steps clinicians can take after ordering a uACR, including how to interpret the result and communicate its significance to patients. It emphasizes using uACR alongside eGFR and the KDIGO heat map to reveal hidden kidney and cardiovascular risk that might otherwise go undetected.

Clinicians across specialties share responsibility for early kidney disease screening—use UACR and eGFR at every touchpoint to prevent patients slipping through cracks.

SUMMIT: Bezuclastinib Delivers Durable, Deepening Symptom Relief in NonAdvSM, With Cem Akin, MD

Bezuclastinib, an oral, highly selective type 1 KIT inhibitor, has demonstrated that clinically meaningful symptom improvement not only holds but continues to deepen out to 48 weeks of treatment in patients with nonadvanced systemic mastocytosis (NonAdvSM), with every assessed symptom domain showing progressive gains over the treatment course.

These data were from the pivotal, multicenter, randomized, double-blind, placebo-controlled phase 2 SUMMIT trial and were presented at the 

American Academy of Allergy, Asthma & Immunology (AAAAI)

 2026 Annual Meeting held in Philadelphia, Pennsylvania.

The trial is evaluating bezuclastinib 100 mg once daily versus placebo in patients with NonAdvSM (n = 179; bezuclastinib, n = 119; placebo, n = 60). To discuss the findings and what they mean for a patient population with limited established options, 

 spoke with Cem Akin, MD, Professor of Medicine at the University of Michigan Division of Allergy and Immunology, a leading authority in mast cell disorders and a principal investigator on the trial, during the meeting. Akin also discussed the importance of prioritizing the symptom burden in patients with NonAdvSM, as visualized with SUMMIT trial entry interviews, which were highlighted in the poster he presented at the meeting.

Across the MS2D2 Total Symptom Score, bezuclastinib produced broad, sustained reductions from a mean baseline score of 8.1. At 48 weeks, mean changes from baseline were observed across all symptom domains: itching (–5.2), flushing (–5.1), skin papules (–5.2), fatigue (–6.0), cognitive concentration (–7.3), memory (–5.7), nausea (–5.5), abdominal pain (–3.3), headache (–4.3), bone pain (–4.0), diarrhea (–5.6), brain fog (–3.0), and dizziness (–3.4) — with all symptoms showing deepening improvement from the 24-week timepoint. In total, 86% of bezuclastinib-treated patients achieved a ≥30% reduction in MS2D2 TSS (81/94), and 56.4% achieved ≥50% reduction (53/94) at 48 weeks.

“These interviews were conducted before they were enrolled in the trial, and they focused on different domains, like skin, gastrointestinal, neurocognitive domains and there are some sentences taken directly from the patient interview that kind of tells you the impact of these patients are experiencing. And some of them are really very severe. And I think for somebody who is new to the field, it is absolutely eye opening to recognize what the patient's going through,” Akin said.

On biomarker endpoints, 98.9% of patients (88/89) in the bezuclastinib arm achieved ≥50% reduction in serum tryptase at week 48, compared to 96.1% (49/51) among placebo crossover patients — with median serum tryptase of 4.7 ng/mL (range 1.0–128.0) versus 5.8 ng/mL (range 1.1–143.0), respectively. Patients achieving tryptase below 20 ng/mL reached 91.7% (66/72), and 83.3% (70/84) fell below 11.4 ng/mL. KIT p.D816V variant allele fraction in peripheral blood was reduced to a median of 0.04% (range, 0–10.5) in the bezuclastinib arm versus 0.07% (range 0–12.1) in placebo crossovers, with 98.4% (61/62) of the ITT population achieving ≥50% VAF reduction. The tolerability profile remained favorable through 48 weeks, with serious TEAEs occurring in just 1.7% of bezuclastinib-treated patients and discontinuations due to TEAEs in 9.2% (11/119 in the double-blind period).

Cogent Biosciences submitted a new drug application (NDA) for a broad NonAdvSM indication in December 2025.

Akin’s disclosures include Blueprint Medicines, Cogent, Telios, GSK, and Novartis.

Boggs NA, Rein L, Bose P, et al. Expanded Results From the Phase 2 Summit Trial: Bezuclastinib in Adults With Nonadvanced Systemic Mastocytosis. Presented at: AAAAI 2026 Annual Meeting, February 27-March 2, Philadelphia, Pennsylvania. Abstract #519

Akin C, Boggs NA, Rein L, et al. Results From the Phase 2 Summit Trial of Bezuclastinib in Adults With Nonadvanced Systemic Mastocytosis (NonAdvSM): Patient Experience of Living With NonAdvSM. Presented at: AAAAI 2026 Annual Meeting, February 27-March 2, Philadelphia, Pennsylvania. Abstract #510

Cogent Biosciences announces submission of new drug application for bezuclastinib in nonadvanced systemic mastocytosis. News release. Cogent Biosciences, Inc. December 30, 2025. Accessed January 2, 2025. https://investors.cogentbio.com/news-releases/news-release-details/cogent-biosciences-announces-submission-new-drug-application

Cogent Biosciences previously submitted an NDA for bezuclastinib at the end of 2025.

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Girish Nadkarni, MD, MPH, is the Irene and Dr. Arthur M. Fishberg Professor of Medicine, System Chief of the Division of Data Driven and Digital Medicine , Co-Director of the Mount Sinai Clinical Intelligence Center, and the Director of Charles Bronfman Institute for Personalized Medicine.

The Hidden Dangers of AI-Generated Medical Advice, With Girish Nadkarni, MD, MPH

As large language models (LLMs) become increasingly embedded in everyday life, more patients are turning to consumer-facing AI tools for health information and advice, raising critical questions about what happens when misinformation enters these systems.

That concern is at the heart of a new study from researchers at the Icahn School of Medicine at Mount Sinai, who conducted a large-scale evaluation of how LLMs handle medical misinformation. In an interview with HCPLive, Girish Nadkarni, MD, MPH, the Irene and Dr. Arthur M. Fishberg Professor of Medicine, System Chief of the Division of Data Driven and Digital Medicine , Co-Director of the Mount Sinai Clinical Intelligence Center and the Director of Charles Bronfman Institute for Personalized Medicine, emphasized that today’s AI models are trained broadly on internet data rather than exclusively on vetted medical sources, raising important concerns about patient safety.

To stress test these systems, he and a team of investigators exposed multiple widely used LLMs, including ChatGPT and Gemini, as well as health-specific AI models, to 3 types of content: authentic hospital discharge summaries altered to include a single piece of misinformation, common health myths drawn from social media platforms such as Reddit, and 300 short clinical vignettes embedded with misleading claims. Each scenario was presented in both neutral and emotionally charged language to mirror how misinformation often appears online.

Across platforms, the researchers observed that LLMs frequently passed along misinformation rather than correcting it, with LLMs found to be susceptible to fabricated data in 50,108 (31.7%) of 158,000 base prompts. Of note, 8 of 10 fallacy framings significantly reduced or did not change that rate, led by appeal to popularity (susceptibility 11.9%; difference of –19.8 percentage points; 

<.0001). Real hospital notes with fabricated inserted elements produced the highest susceptibility to the base prompt (46.1%), whereas social media misinformation showed lower base prompt susceptibility (8.9%).

Results showed performance varied by model: GPT models were the least susceptible and most accurate at fallacy detection, whereas others, such as Gemma-3–4B-it, showed 63.6% susceptibility.

“We had a discharge note which advised patients with bleeding in the GI tract to drink cold milk to suit the symptoms. It sounds reasonably easy enough to do, but if you just drink cold milk to soothe the symptoms and you actually have bleeding in a GI tract, as opposed to going to the emergency room, that can actually be really dangerous and really fatal,” Nadkarni said. “Several models accepted the statement rather than flagging it as unsafe, and they treated it like ordinary medical guidance.”

According to Nadkarni, these findings are particularly concerning because these AI systems are highly fluent and persuasive. Patients may bring AI-generated recommendations to clinicians as if they are established fact, adding to clinical burden and potentially introducing risk.

“Large language models are extremely good at sounding convincing and presenting information to patients that they want to hear,” he said. “Anything that's generated by large language models, I think there should be some amount of human oversight, particularly clinician oversight, on top of this.”

The findings underscore the need for stronger evaluation frameworks for medical AI. Nadkarni argues that assessment must extend beyond single-use testing to include ongoing monitoring. Because LLMs are continuously retrained and updated, performance can shift over time. Identifying failure modes, implementing engineering safeguards or human oversight, and regularly reassessing models are critical steps toward safer deployment.

While no technology can be made entirely risk-free, the goal, Nadkarni noted, is risk mitigation. For clinicians and patients alike, he says this means approaching AI-generated medical information with caution, prioritizing trusted sources, and recognizing that convincing language does not guarantee clinical accuracy.

Editors’ note: Nadkarni reports no relevant disclosures.

Mount Sinai. Can Medical AI Lie? Large Study Maps How LLMs Handle Health Misinformation. February 9, 2026. Accessed March 3, 2026. 

https://www.mountsinai.org/about/newsroom/2026/can-medical-ai-lie-large-study-maps-how-llms-handle-health-misinformation

Omar M, Sorin V, Wieler LH, et al. Mapping the susceptibility of large language models to medical misinformation across clinical notes and social media: a cross-sectional benchmarking analysis. Lancet. doi:

Nadkarni’s research suggests LLMs often pass along medical misinformation, underscoring the need for oversight, evaluation, and stronger AI guardrails.

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Mapping Medical Misinformation Risks in the Age of Generative AI, With Girish Nadkarni, MD, MPH

Nada Elbuluk, MD, MSc, is a dermatologist in California. 

In this segment of the recent Skin of Color Savvy podcast, the value of advocacy and meaningful change in skin health equity is highlighted.

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Ryan Livingston joined the MJH Life Sciences team in March of 2025, shortly after graduating from TCNJ with a bachelor’s degree in English. He enjoys creative writing, reading, and scuba diving. He can be reached at rlivingston@mjhlifesciences.com.

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Iben Lyskjær, PhD, is an associate professor and leader of the Lyskjær Group at the Department of Molecular Medicine (MOMA) at Aarhus University.

Lyskjaer walks clinicians through 10-year data from a nationwide cohort study comparing ablation and surgery for renal cancer.

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This segment of the February episode of The Medical Sisterhood podcast highlights burdens faced by those balancing motherhood with being a physician.

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Abigail Brooks is an assistant managing editor for 

She joined MJH Life Sciences in August 2023 shortly after graduating from Monmouth University where she earned her BA in Communication with a concentration in Public Relations/Journalism and later an MA in Interactive Digital Media. She enjoys traveling, running, and reading books. She can be reached at abrooks@mjhlifesciences.com.

Catch up on durability data and real-world insight from trials across inflammatory bowel disease and short bowel syndrome.

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Akin discussed how avapritinib continues to demonstrate its benefit in indolent systematic mastocytosis.

Long-Term PIONEER Data Reinforce Avapritinib’s Benefit–Risk Profile in ISM, with Cem Akin, MD

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In February 2026, rusfertide garnered priority review, ASH published new guidelines, and luspatercept mets its primary endpoint in a phase 2a trial.  


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Norouzi discusses a recent review where 11 clinicians described C3G pathology and diagnosis.  

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Latest News

Evaluating Clinical Gaps in Combining uACR and eGFR Testing in CKD Diagnosis

Combined Role of Estimated Glomerular Filtration Rate (eGFR) and Urine Albumin-Creatinine Ratio (uACR) Testing in CKD

Emphasizing Multidisciplinary Collaboration for Early CKD Diagnosis

SUMMIT: Bezuclastinib Delivers Durable, Deepening Symptom Relief in NonAdvSM, With Cem Akin, MD

Mapping Medical Misinformation Risks in the Age of Generative AI, With Girish Nadkarni, MD, MPH