AI tool aims to tailor diuretic doses for heart failure patients

NCT ID NCT07470554

Ongoing Knowledge-focused Sponsor: IRCCS Azienda Ospedaliero-Universitaria di Bologna Source: ClinicalTrials.gov ↗

First seen Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This study analyzes data from over 4,200 heart failure patients to create a tool that uses biomarkers to guide diuretic dosing. Researchers aim to develop a machine-learning algorithm that could personalize treatment and improve outcomes. The study is observational and does not test a new drug or intervention.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

What this could lead to: If successful, this could lead to a machine-learning algorithm that helps doctors choose the right diuretic dose for each heart failure patient, potentially reducing hospitalizations and deaths.
What could go wrong: This is a retrospective study using existing data, not a new treatment trial. The algorithm needs to be tested in future prospective studies before it can be used in practice.

This is an AI summary of the original study and may miss details. Read our disclaimer.

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Conditions

The condition(s) this trial relates to.

congestive heart failure heart failure systolic heart failure

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

CONGESTIVE HEART FAILURE(CHF) HEART FAILURE WITH REDUCED EJECTION FRACTION (HFREF)

Contacts and locations

Locations

Heart Failure and Transplant Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna

Bologna, Emilia-Romagna, 40138, Italy

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