Emily Lau, MD, is a professor of cardiology at Harvard University

Emily Lau, MD

Broadening Access to Cardiovascular Care for Female Patients, With Emily Lau, MD

Virtual shared medical appointments (SMAs) are a feasible solution for closing care gaps for female patients with elevated cardiometabolic risk and/or established 

Cardiovascular disease is the leading cause of death among women in the US. An increasing amount of evidence regarding sex- and gender-based differences in cardiovascular disease outcomes has indicated the necessity of more efficient approaches to screening.

American Heart Association’s Scientific Sessions 2025

 in New Orleans, Louisiana, by Emily Lau, MD, cardiologist at Massachusetts General Hospital and Assistant Professor of Medicine at Harvard Medical School, and colleagues. The team collaborated with Systole Health, a group virtual care organization, to design the study.

 sat down with Lau to discuss the importance of enhancing access to cardiovascular care for women. Lau discussed the factors she sees as driving these treatment gaps.

“I think it’s largely due to a number of reasons. I think that, as physicians, we often see an implicit bias to be less aggressive with our prevention goals in female patients,” Lau told 

. “There is also an access issue; many of our female patients are caregivers themselves, and what is often least prioritized is their own health. And finally, I think there’s a public health education messaging issue, which is to say that despite decades of research demonstrating the opposite, women still think of heart disease as a man’s disease.”

Systole Health enrolled 13 individual cohorts, each consisting of 3 to 5 women, into a 6-week cardiovascular prevention program across 16 US states. Patients were eligible for inclusion if they had documented or self-reported overweight or obesity, hypertension, dyslipidemia, prediabetes, and/or established cardiovascular disease. Patients were excluded if they had unstable cardiovascular disease or were pregnant.

The program included weekly physician-led SMAs, lifestyle health coaching, and peer support. A subset of patients was offered medication management, depending on clinical need. Investigators assessed outcomes, which included self-reported body mass index (BMI), blood pressure, and LDL-C, at baseline and at completion of the program.

Ultimately, 45 women enrolled, collectively contributing 247 patient visits. The mean age across all cohorts was 52 +/- 12 years, and 87% of the population was White. Mean systolic blood pressure at baseline was 124 +/- 15 mmHg, diastolic blood pressure was 78 +/- 11 mmHg, LDL-C was 117 +/- 38 mg/dL, and BMI was 33.4 +/- 7.5 kg/m2. The majority of patients had ≥3 unoptimized cardiovascular risk factors (blood pressure ≥130/80, LDL-C above guideline-recommended thresholds, BMI ≥27, and/or A1c ≥5.7%).

Patients with complete data contributed to a mean change in LDL-C of -35.4% (

 = .001), systolic blood pressure of -7% (

 < .001), diastolic blood pressure of -3% (

 <.001). Investigators also noted that, among patients receiving medication management (N = 20), 36 titrations were performed (mean 1.8 +/- 1.5 per patient) with a median intensification time of 8 days.

This alternative and simplified method of accessing critical features of care for cardiovascular disease may enable clinicians to close care gaps with female patients. Lau also spoke on the value of multiple care models.

“I’ll say this as a cardiologist: we really have an access issue,” Lau said. “There are many more patients who need to see us than we can possibly see. We really need to be thinking about different care models. The traditional care model of people coming in for one-on-one visit into the office or hospital is not meeting their expectations or needs.”

Editor's Note: Lau reports disclosures with Roon, SystoleHealth Inc, and Amissa Health.

Parmar S, Lee S, Lau E. Closing Prevention Gaps in Women’s Heart Health: Real-World Impact of a Scalable Group Virtual Care Model. Presented at the American Heart Association’s Scientific Sessions 2025. New Orleans, Louisiana. November 8-10, 2025.

Adedinsewo DA, Pollak AW, Phillips SD, et al. Cardiovascular Disease Screening in Women: Leveraging Artificial Intelligence and Digital Tools. Circ Res. 2022;130(4):673-690. 

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Lau discusses the use of virtual shared medical appointments for increasing access to cardiovascular care in a traditionally underserved population.

Cardiorespiratory Fitness May Predict Pregnancy-Related Cardiovascular Complications, With Emily Lau, MD

 has been associated with higher risks of pregnancy-related cardiovascular complications, according to a recent study.1

 in New Orleans, Louisiana, by Emily Lau, MD, Massachusetts General Hospital and professor of cardiology at Harvard University, and colleagues, these data also indicate the predictive power of artificial intelligence-enabled electrocardiograms (ECG), which were utilized during the trial.

Cardiovascular disease is the leading cause of indirect maternal mortality; it accounts for >33% of all pregnancy-related maternal deaths. Additionally, ≥50% of maternal deaths happen post-partum. However, other research has indicated up to 68% of pregnancy-related deaths through cardiovascular conditions are preventable.

 sat down with Lau to discuss the study and its implications. Lau discussed the methods used to collect and analyze the data used in the study, noting the artificial intelligence model they utilized to filter through screening pregnancies at the Massachusetts General Brigham system.

“One of the things we wanted to do is to develop tools that can help us identify women who are at high risk for developing a cardiovascular complication, so that we might be able to help target preventive therapies and identify which women need greater screening during their pregnancy” Lau told 

. “We are using a really novel model; we had previously developed an EKG deep learning model to estimate cardiorespiratory fitness from the 12-lead ECG.”

Lau and colleagues had previously developed a deep learning model to accurately estimate peak oxygen uptake (VO2) using a resting 12-lead ECG. The team examined ECG-estimated VO2 among patients who underwent clinical 12-lead ECG testing between 1 year before pregnancy and 13 weeks of gestation. Investigators used age-adjusted logistic regression models to examine the association between estimated peak VO2 and subsequent pregnancy-related cardiovascular complications ≤1 year postpartum, which included maternal death, severe hypertensive disorders of pregnancy, and major adverse cardiac events.

A total of 3437 women were included in the study, resulting in a total of 3650 pregnancies. Mean age at delivery was 33 +/- 6 years, and the median ECG-estimated VO2 was 26.5 mL/kg/min. Investigators noted that 26% of patients experienced a pregnancy-related cardiovascular complication.

Lower ECG-estimated peak VO2 was associated with greater risk of a pregnancy-related complication (odds ratio [OR], 1.18 per 1-unit lower metabolic equivalent [MET = 3.5 kg/m2]; 95% CI, 1.15-1.23; 

 <.001). Women in the lowest quartile of ECG-estimated peak VO2 had almost 2 times the odds of developing a complication compared to the highest quartile (OR, 2.36; 95% CI, 1.91-2.93; 

Ultimately, investigators noted the strong and independent association between lower estimated cardiorespiratory fitness and pregnancy-related cardiovascular complications. They also highlighted the effectiveness of a routinely-performed AI-enabled analysis of ECGs in antepartum care, which they believe may enable scalable risk assessment for identifying high-risk pregnancies.

“Now the next step after the study is really to think about a prospective study where we actually perform ECGs in all women, including women who would not have qualified for getting an ECG under a current obstetrical practice,” Lau said. “We need to identify how ECG-estimated cardiorespiratory fitness captures risk of pregnancy-related cardiovascular complications across an entire sample of individuals who are less sick.”

Brown L, Zhao Y, Dsouza V, et al. Prediction of Pregnancy-related Cardiovascular Outcomes Using Electrocardiogram-Derived Cardiorespiratory Fitness. Presented at the American Heart Association’s Scientific Sessions 2025. New Orleans, Louisiana. November 8-10, 2025.

Kotit S, Yacoub M. Cardiovascular adverse events in pregnancy: A global perspective. Glob Cardiol Sci Pract. 2021;2021(1):e202105. Published 2021 Apr 30. 

Lau discusses the importance of developing and applying technology to predict potential adverse cardiovascular outcomes in pregnant patients.

Emily Lau, MD

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