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Following the Metabolic Clues in Obesity and MASLD

Slideset

Although evidence indicates that common pathophysiological factors contribute to obesity, metabolic dysfunction–associated steatotic liver disease (MASLD), and increased cardiovascular risk, MASLD and its more serious form, metabolic dysfunction–associated steatohepatitis (MASH), are often underrecognized and undertreated in the context of comprehensive, integrated cardiometabolic care. This downloadable slideset provides expert perspectives on the pathophysiology connecting obesity, liver health, and cardiovascular risk; current recommendations for identifying and assessing patients at risk for developing hepatic fibrosis; and current insights regarding available therapies for MASLD/MASH. The slides also explore emerging investigational agents and introduce strategies for incorporating MASLD/MASH into multidisciplinary cardiometabolic care.

Released: November 15, 2026

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Provided by

Provided by Clinical Care Options, LLC dba Decera Clinical Education

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Supporters

This activity is supported by Boehringer Ingelheim Pharmaceuticals, Inc.

Boehringer Ingelheim Pharmaceuticals, Inc.

Target Audience

This activity is intended for endocrinologists, primary care physicians, hepatologists, nurse practitioners, physician associates, pharmacists, and other healthcare providers interested in improving the care of patients living with obesity and MASLD/MASH. 

Learning Objectives

Upon completion of this activity, participants should be able to:

  • Apply current evidence on the interconnected metabolic pathways linking obesity, liver health, and cardiovascular risk to clinical assessment and management decisions

  • Employ recommended screening and risk assessments to improve timely detection of MASLD/MASH in patients at risk

  • Incorporate the latest efficacy and safety data for new and emerging treatments into integrated management decisions for patients with obesity and MASLD/MASH

Additional Disclosures

Generative artificial intelligence (AI) tools were used for drafting educational content, revising or refining educational content, generating clinical case(s) or scenario(s), and drafting assessment question(s) and/or rationale(s). All AI-assisted content underwent human review, editing, and validation by qualified faculty and accredited education staff to ensure scientific accuracy, balance, and compliance with the ACCME Standards for Integrity and Independence in Accredited Continuing Education.