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	<title>early detection of cardiometabolic vulnerability &#8211; Science</title>
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	<title>early detection of cardiometabolic vulnerability &#8211; Science</title>
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		<title>Rethinking Cardiometabolic Treatment Thresholds for People Living With Obesity</title>
		<link>https://scienmag.com/rethinking-cardiometabolic-treatment-thresholds-for-people-living-with-obesity/</link>
		
		<dc:creator><![CDATA[Daisy Hatcher]]></dc:creator>
		<pubDate>Fri, 17 Jul 2026 13:40:18 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[cardiovascular prevention guidelines]]></category>
		<category><![CDATA[early detection of cardiometabolic vulnerability]]></category>
		<category><![CDATA[inadequacy of traditional risk calculators for obesity]]></category>
		<category><![CDATA[limitations of LDL-cholesterol and blood pressure markers]]></category>
		<category><![CDATA[obesity as a chronic disease]]></category>
		<category><![CDATA[obesity-related cardiometabolic risk]]></category>
		<category><![CDATA[outcome-based therapy for obesity]]></category>
		<category><![CDATA[rethinking treatment thresholds for people living with obesity]]></category>
		<category><![CDATA[risk assessment in obesity]]></category>
		<category><![CDATA[role of visceral fat and hepatic steatosis in cardiometabolic risk]]></category>
		<category><![CDATA[use of SGLT2 inhibitors and GLP-1 receptor agonists in cardiovascular prevention]]></category>
		<guid isPermaLink="false">https://scienmag.com/rethinking-cardiometabolic-treatment-thresholds-for-people-living-with-obesity/</guid>

					<description><![CDATA[The American Heart Association, the American College of Cardiology, and the European Society of Cardiology now recognize obesity as a chronic disease—yet their cardiovascular prevention playbooks largely still rely on thresholds built in leaner study populations. In everyday practice, risk estimates are often anchored to LDL-cholesterol, blood pressure, and HbA1c, even though obesity biology frequently [&#8230;]]]></description>
										<content:encoded><![CDATA[<p>The American Heart Association, the American College of Cardiology, and the European Society of Cardiology now recognize obesity as a chronic disease—yet their cardiovascular prevention playbooks largely still rely on thresholds built in leaner study populations. In everyday practice, risk estimates are often anchored to LDL-cholesterol, blood pressure, and HbA1c, even though obesity biology frequently operates through pathways that those markers fail to fully capture.</p>
<p>That mismatch has consequences. BMI, visceral fat distribution, and hepatic steatosis—signals closely tied to inflammation, insulin resistance, and adverse metabolic remodeling—remain underused or excluded in most cardiovascular risk calculators. As a result, many people living with obesity are categorized as “moderate risk,” despite evidence of cardiometabolic vulnerability that can begin decades before overt diabetes or frank dyslipidemia.</p>
<p>A new discussion in <em>International Journal of Obesity</em> argues that prevention guidelines may be lagging behind therapeutic science. The authors note that contemporary diabetes recommendations already apply cardio-protective medications such as SGLT2 inhibitors and GLP-1 receptor agonists based on cardiovascular outcomes, not solely on whether a patient’s glucose levels meet a specific target.</p>
<p>“Carving therapy decisions strictly from glycaemic thresholds” may therefore be an overly narrow approach when the goal is cardiovascular prevention. Extending the same outcome-based logic to obesity could align treatment algorithms with the underlying mechanisms that generate cardiometabolic risk, including ectopic fat accumulation and metabolic inflammation.</p>
<p>The paper also highlights a shift toward more precise risk stratification. AI-derived imaging biomarkers could quantify phenotypes—such as visceral fat burden and liver fat—that correlate with atherosclerotic processes. Meanwhile, metabolomics may reveal composite metabolic signatures reflecting early vascular stress.</p>
<p>Additionally, polygenic risk scores offer another layer, combining inherited susceptibility with modifiable drivers. Together, these tools could identify high-risk individuals within the “moderate” category and enable earlier, mechanism-informed intervention.</p>
<p>The authors’ overarching point is straightforward: when risk tools ignore obesity-specific physiology, clinicians may miss windows for prevention. Updating thresholds and incorporating modern biomarker technologies could help turn recognition of obesity as a chronic disease into earlier cardiovascular action.</p>
<p><strong>Subject of Research</strong>: Cardiometabolic therapy thresholds and cardiovascular risk estimation in obesity</p>
<p><strong>Article Title</strong>: Rethinking cardiometabolic therapy thresholds in individuals with obesity</p>
<p><strong>Article References</strong>: Khanna, S., Nerlekar, N. &amp; Bhat, A. Rethinking cardiometabolic therapy thresholds in individuals with obesity. <em>Int J Obes</em> (2026). <a href="https://doi.org/10.1038/s41366-026-02160-w">https://doi.org/10.1038/s41366-026-02160-w</a></p>
<p><strong>Image Credits</strong>: AI Generated</p>
<p><strong>DOI</strong>: 10.1038/s41366-026-02160-w</p>
<p><strong>Keywords</strong>: Obesity; cardiovascular risk; LDL-C; blood pressure; HbA1c; visceral fat; hepatic steatosis; SGLT2 inhibitors; GLP-1 receptor agonists; AI imaging biomarkers; metabolomics; polygenic risk scores</p>
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