Dr. Martin is an assistant professor at the Ciccarone Center for the Prevention of Heart Disease at the Johns Hopkins University School of Medicine.

Seth Martin, MD, MHS

New Martin-Hopkins LDL-C-Estimating Equation Simplifies Implementation for Comparable Results

A new investigation into the Martin-Hopkins equation has produced a simplified version of the 

 calculation to streamline care and broaden implementation.

The original Martin-Hopkins Equation was developed in response to the rising importance of LDL-C calculation and the continuous risk of underestimating LDL-C levels. However, the equation, first drafted in 2013, requires some laboratories to undertake extra steps in implementing it for patients. To this end, investigators at Johns Hopkins University aimed to streamline the system into something universally applicable and accessible.

“The equation itself is a bit complex, but it can be coded into the lab IT system as a single line of code, so clinicians never need to deal with that complexity,” Seth Martin, MD, MHS, a professor in the division of cardiology at Johns Hopkins University and an investigator in the study, told 

 in an exclusive interview. “It makes it easier for lab directors to implement this, because they can take the line of code that currently is offered with the Friedewald equation to calculate LDL cholesterol, replace it with this new line of code, and get substantially enhanced LDL cholesterol accuracy.”

Martin and colleagues included patients from the second harvest of the Very Large Database of Lipids (VLDBL), which was collected from several US clinics from October 2015 to June 2019. These patients exhibit similar lipid distributions to those of the broader US population. Patients with missing values for total cholesterol, HDL-C, triglycerides, or LDL-C concentration were excluded. The primary analysis focused on patients with triglyceride concentrations <400 mg/dL.

The team measured patients’ total cholesterol, LDL-C, VLDL-C, and HDL-C concentrations using the Vertical Auto Profile (VAP) test. Triglyceride measurements utilized the Abbott ARCHITECT C-8000 system. Additionally, the team implemented the Friedewald equation, the Martin-Hopkins equation, the extended Martin-Hopkins equation, the Sampson-National Institutes of Health equation, and the modified Sampson-National Institutes of Health equation.

Machine-learning methods were also employed – Martin and colleagues estimated VLDL-C using total cholesterol, triglyceride, and HDL-C concentrations as independent variables, followed by calculating LDL-C concentration by subtracting VLDL-C from non-HDL-C. Of the 3 machine learning algorithms implemented in the study, MARS created a new equation for the estimation of VLDL-C.

Martin and colleagues then conducted a statistical analysis of the new equation, randomly assigning patients in a 2:1 ratio to either a training or test dataset. Of the initial 5,081,680 patients in the dataset, 10,856 were excluded for incomplete data, and 131,296 were removed for having triglyceride concentrations ≥400 mg/dL. Of the remaining patients, 3,292,889 were assigned to the training dataset and 1,646,639 to the test dataset. Median LDL-C concentration was 114 mg/dL (interquartile ratio [IQR], 90-141), and the median triglyceride/VLDL-C ratio was 5.1 (IQR, 4.4 to 5.9) for both groups.

During the test, the MARS equation showed minimal bias in estimating LDL-C concentration (median [IQR], -0.1; -2.1 to 1.8 mg/dL), comparable with the existing Martin-Hopkins equation. The median difference between the 2 was -0.5 (-1.2 to 0) mg/dL, indicating the methods’ potential comparability. Additionally, the proportion of patients correctly classified to each clinical category was almost identical for the MARS equation and the Martin-Hopkins equation, with 89.7% and 89.6% of patients correctly assigned, respectively.

Ultimately, the team determined that this newer version of the Martin-Hopkins equation, developed by the MARS machine learning algorithm, may provide the same quality of results while simplifying its implementation.

“We have extensive external validation with the original equation – this one performs similarly, and we have additional external validation included in this paper,” Martin said. “I think this is an equation that’s ready for implementation and really has robust science behind it.”

Editors’ Note: Martin reports disclosures with Amgen, Merck, Arrowhead, Verve Therapeutics, Novartis, Regeneron, and others.

Park J, Fan L, Marzinke MA, et al. Development and validation of a simplified Martin-Hopkins LDL-C equation using machine learning. JAMA Cardiology. Published online July 15, 2026. 

Johns Hopkins Medicine. Machine Learning Method Enables Easier and Wider Use of Martin-Hopkins Equation to Accurately Assess LDL Cholesterol Risk. July 15, 2026. Accessed July 16, 2026. 

https://www.hopkinsmedicine.org/news/newsroom/news-releases/2026/07/machine-learning-method-enables-easier-and-wider-use-of-martin-hopkins-equation-to-accurately-assess-ldl-cholesterol-risk

Videos

Seth Martin, MD, MHS, discusses his recent study, which produced an AI-optimized equation that only requires 1 line of code.

Counting down the biggest news from major medical meetings, it's the HCPLive Five!

HCPLive Five at Heart in Diabetes 2025

 is a medical conference bringing together world-renowned clinical leaders in 

. Designed to evaluate state-of-the-art clinical data and research while focusing on the management of the heart and 

 in diabetes, the meeting’s goal is to align cardiologists, endocrinologists, diabetologists, 

, nephrologists, and all other interested clinicians in their understanding and development of appropriate comprehensive clinical management plans for high-risk patients.

’s on-site coverage, the editorial team conducted expert interviews and reported on timely topics across implementation science, cardiometabolic health, combination therapy, and more. In this edition of the HCPLive Five, the team highlights key conversations on barriers to evidence-based cardiometabolic care, recognizing 

 as a chronic disease, data on cardiovascular disease trends, the CONFIDENCE trial of combined finerenone plus empagliflozin in patients with both 

 and type 2 diabetes, and data accessibility issues in an era of unprecedented technological innovation.

Improving Evidence-Based Cardiometabolic Care, with Neha Pagidipati, MD, MPH

While innovation in cardiovascular, kidney, and metabolic care often centers around emerging therapies, the underuse of established, evidence-based treatments in clinical practice remains a major and under-discussed challenge. In this interview with 

 at HiD, Neha Pagidipati, MD, MPH, an assistant professor of medicine and cardiovascular disease prevention specialist at Duke University School of Medicine, reviews different barriers to implementing guideline-directed medical therapy as well as facilitators and potential avenues for improvement moving forward.

Classifying Obesity as a Chronic Disease with W. Timothy Garvey, MD

Given the limitations surrounding BMI measurement of obesity, a recent Lancet Commission aimed to better define obesity as a condition of illness that comes as a direct result of excess adiposity and its effect on the function of tissues and organs. In this interview with 

 at HiD, Timothy Garvey, MD, breaks down some of the key points from the paper and how they will influence the treatment of obesity and its complications moving forward.

Moving the Needle on Cardiovascular Disease, with Seth Martin, MD, MHS

Despite decades of progress and innovation in cardiovascular care, recent data from the American Heart Association (AHA) suggest that the momentum has stalled—and in some cases, reversed. At HiD, Seth Martin, MD, MHS, a professor of medicine in the division of cardiology at Johns Hopkins Hospital and co-founder at Corrie Health, offered a data-driven overview of the current state of cardiovascular disease (CVD) in the United States and globally, based on the AHA’s 2024 statistical update. In this interview with 

, he reviews key trends and calls for urgent action to improve implementation of prevention and treatment strategies at scale.

Don’t Miss a Beat: CONFIDENCE Trial and Combination T2D, CKD Therapy at Heart in Diabetes 2025

, hosts Muthiah Vaduganathan, MD, MPH, a cardiologist and codirector of the Center for Cardiometabolic Implementation Science at Brigham and Women’s Hospital, and Steve Greene, MD, an advanced heart failure specialist at Duke University School of Medicine, review key findings and clinical implications of the CONFIDENCE trial. The data, which were also presented at the 

62nd European Renal Association (ERA 2025) Congress

 in Vienna, Austria, suggest the potential benefits of combination initial therapy with finerenone plus empagliflozin in patients with both CKD and type 2 diabetes.

Confronting Cardiology's Data Accessibility Problem, with Robert Califf, MD

, Robert Califf, MD, an instructor of medicine at Duke University School of Medicine and former commissioner of the US Food and Drug Administration, provided his perspective on the ongoing difficulties in implementation of digital technologies and preventative measures for cardiovascular diseases and diabetes. He points to shortcomings of the cardiology field and the medical industry at large in adapting technological advances to practical, clinical usability, citing the high number of new programs and mechanisms for tracking individual risk factors and their failure to collate this data meaningfully for patients.

These 5 represent only some of the data the 

 team covered at this year's meeting! Check out more KOL insight and our full conference coverage on our 

From barriers to implementing evidence-based care to innovations in combination therapy, here are 5 key updates from the annual meeting.

Despite decades of progress and innovation in 

 care, recent data from the American Heart Association (AHA) suggest that the momentum has stalled—and in some cases, reversed.

, Seth Martin, MD, MHS, a professor of medicine in the division of cardiology at Johns Hopkins Hospital and co-founder at Corrie Health, offered a data-driven overview of the current state of cardiovascular disease (CVD) in the United States and globally, based on the AHA’s 2024 statistical update. Framing the atherosclerotic cardiovascular disease (ASCVD) session, he presented key trends and calls for urgent action to improve implementation of prevention and treatment strategies at scale.

, Martin describes the latest trends in cardiovascular disease and contributing underlying risk factors, discussing how those serve as a call to action for innovation and in the way that we improve on those numbers. Specifically, he highlights how although CVD mortality declined steadily from 2000 to 2010, both the total number of deaths and age-adjusted death rates have plateaued or worsened since then. As of 2024, the U.S. age-adjusted cardiovascular death rate is 224.3 per 100,000—virtually unchanged from 2012.

“Whether you look at overall counts or the age-adjusted rate, either we've gone up or we're stagnant based on those two different metrics, whereas we really should be going down with all the innovation that we have in cardiovascular care,” Martin explained. “Clearly, we need to find a way for all the treatments that we know work and the prevention strategies that we know work to penetrate at very high levels across the population.”

Underlying this issue are large increases and high prevalence of key cardiovascular risk factors, including obesity, prediabetes, diabetes, and chronic kidney disease.

“There have been periods of reduction in cardiovascular disease deaths, but in the last decade, we have not had the progress that we'd like to see,” Martin said. “It's really a call to action, these statistics that we're seeing, and it's going to take tremendous scale and multidisciplinary teamwork to really move the needle in the right direction.”

Looking ahead, Martin emphasizes the importance of multidisciplinary collaboration and implementation science and their potential role as catalysts for change.

Editors’ note: Martin has relevant disclosures with Amgen, Arrowhead Pharmaceuticals, Chroma, Heartflow, Kaneka, Merck, New Amsterdam, Novartis, Premier, Sanofi, and Verve Therapeutics.

Martin SS, Aday AW, Almarzooq ZI, et al. 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association. Circulation. 

Martin reviews recent trends in cardiovascular disease and contributing underlying risk factors, describing them as a “call to action” for cardiovascular care. 

Seth Martin, MD, MHS

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