New Calculator Predicts Heart Failure Treatment Effects on Blood Pressure and Kidney Function
- A new digital health tool introduced on August 31, 2026, aims to predict how comprehensive heart failure treatments will impact patient blood pressure, kidney function, and potassium levels.
- Heart failure affects roughly 64 million people worldwide, carrying a one-year mortality risk of up to 30 percent.
- The web-based tool at hfmodel.org generates personalized estimates based on specific patient characteristics.
A new digital health tool introduced on August 31, 2026, aims to predict how comprehensive heart failure treatments will impact patient blood pressure, kidney function, and potassium levels. According to research published in Nature Medicine and presented at the European Society of Cardiology Congress, the Heart Failure Treatment Effect Calculator uses individual data from 38,753 participants across nine major clinical trials to guide safer therapy initiation.
Addressing Barriers to Effective Heart Failure Care
Heart failure affects roughly 64 million people worldwide, carrying a one-year mortality risk of up to 30 percent. Despite decades of pharmacological advancements, adoption rates for guideline-recommended therapies remain low. Registry studies indicate that only two percent of eligible patients receive a recommended four-pillar treatment approach.
Clinicians frequently hesitate to prescribe these multi-drug regimens due to anticipated adverse events. Fear of adverse effects, particularly low blood pressure, worsening kidney function or high potassium levels are the major reasons clinicians do not start treatment,
said Dr. Nelson Wang, a cardiologist and Senior Research Fellow at The George Institute for Global Health.
How the Treatment Calculator Operates
The web-based tool at hfmodel.org generates personalized estimates based on specific patient characteristics. These inputs include age, sex, body mass index, baseline blood pressure, kidney function measured by estimated glomerular filtration rate, serum potassium levels, and prior heart failure hospitalization status. The model evaluates combinations across five major classes of heart failure therapy:
- Angiotensin receptor blocker–neprilysin inhibitors (ARNI)
- Angiotensin converting enzyme inhibitors or angiotensin receptor blockers (ACEI/ARB)
- Sodium-glucose cotransporter 2 inhibitors (SGLT2i)
- Steroidal mineralocorticoid receptor antagonists (sMRA)
- Non-steroidal mineralocorticoid receptor antagonists (nsMRA)
Researchers found that utilizing these recommended combination therapies produces modest reductions in blood pressure and early declines in kidney function, alongside small to modest increases in serum potassium. However, these physiological shifts contrast with substantial risk reductions for worsening heart failure events, ranging from 31 percent to 61 percent compared to standard care.
Validation and Clinical Outlook
The predictive model was validated against data drawn from 1,016 participants across four additional trials. The estimated treatment effects aligned closely with observed patient outcomes, confirming the reliability of the software. The project was conducted through a collaboration between The George Institute for Global Health and Brigham and Women’s Hospital, Harvard Medical School. Developers note that because the tool relies on clinical trial populations, estimates may not be fully generalizable to broader populations. Dr. Wang indicated that providing personalized visibility into short-term physiological shifts should give physicians greater confidence to prescribe combination therapies simultaneously, improving long-term outcomes for vulnerable populations.
