WATCH-DM Risk Score Predicts Heart Failure Risk in Diabetes Patients

Senior woman with glucometer checking blood sugar level at home. Diabetes, health care conceptIn September 2019, results from the DAPA-HF trial revealed that SGLT2 inhibitors may be helpful for patients with heart failure. These therapies may also be used to prevent heart failure in patients with diabetes*. However, a way of accurately identifying which diabetes patients are most at risk for heart failure has been elusive.

A new study led by investigators from Brigham and Women’s Hospital and UT Southwestern Medical Center has unveiled a new, machine-learning derived model that can predict, with a high degree of accuracy, future heart failure among patients living with diabetes. The team’s findings were presented at the 2019 Heart Failure Society of America Annual Scientific Meeting in Philadelphia and published in Diabetes Care.

“We hope that this risk score can be useful to clinicians on the ground—primary care physicians, endocrinologists, nephrologists and cardiologists—who are caring for patients with diabetes and thinking about what strategies can be used to help them,” says co-first author Muthiah Vaduganathan, MD, MPH, a cardiologist at the Brigham.

The risk score, known as WATCH-DM, provides a novel prediction tool to identify patients who may face a heart failure risk in the next five years. By not requiring specific clinical cardiovascular biomarkers or advanced imaging, WATCH-DM can be integrated into bedside practice or electronic health record systems and may help identify patients who would benefit from therapeutic interventions.

To develop WATCH-DM, the teams leveraged data from 8,756 patients with diabetes enrolled in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. These data included 147 variables, such as demographics, clinical information, laboratory data and more. The investigators used machine-learning methods capable of handling multidimensional data to determine the top-performing predictors of heart failure.

Over the course of five years, 319 patients (3.6 percent) developed heart failure. The team identified the 10 top-performing predictors of heart failure, which make up the WATCH-DM risk score: weight (BMI), age, hypertension, creatinine, HDL-C, diabetes control (fasting plasma glucose), QRS duration, myocardial infarction and coronary artery bypass grafting. Patients with the highest WATCH-DM scores faced a five-year risk of heart failure approaching 20 percent.

The WATCH-DM risk score is now available as a free online tool for clinicians to use. As a next step, the teams are working to integrate the risk score into electronic health record systems at both Brigham Health and UT Southwestern to facilitate its practical use.

In addition to the tool’s usefulness for clinicians, Dr. Vaduganathan also sees a key message from the study for patients with diabetes who are concerned about their risk of heart failure.

“It’s important to look at these ten variables and reflect on them. For patients, these are important messages to think about when assessing personal risk. BMI was one of the top predictors of heart failure risk, which reinforces the idea that long-term excess weight may increase future risk for heart failure. We hope this work highlights ways to intervene—both through lifestyle changes and through the use of SGLT2 inhibitors—to delay or even entirely prevent heart failure,” says Dr. Vaduganathan.

*Canagliflozin is now approved to reduce risk of heart failure in patients with diabetic kidney disease. Dapagliflozin is also now approved to reduce risk of heart failure in patients with type 2 diabetes at high cardiovascular risk.  
WATCH-DM score card

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