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AI may predict patient decline at home before it happens

NCT ID NCT05045742

Completed Knowledge-focused Sponsor: Brigham and Women's Hospital Source: ClinicalTrials.gov ↗

First seen Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This study tested a machine learning algorithm to predict if a patient being cared for at home would deteriorate. Researchers used data from over 500 patients to train the algorithm and compared its alerts to traditional vital sign alarms. The goal is to catch problems earlier and reduce emergencies.

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 better early warning systems for patients being cared for at home, potentially reducing hospital readmissions and emergencies.
What could go wrong
This is a retrospective observational study, not a clinical trial testing a treatment. The algorithm may not work as well in real-time or in different patient populations.

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.

asthma atrial fibrillation chronic kidney disease chronic obstructive pulmonary disease chronic renal failure syndrome gout heart failure Hypertensive Crisis hypertensive urgency Infections infectious disease

As listed by the trial registrant

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

ANTICOAGULANTS; INCREASED ASTHMA ATRIAL FIBRILLATION RAPID CHRONIC KIDNEY DISEASES CHRONIC OBSTRUCTIVE PULMONARY DISEASE GOUT FLARE HEART FAILURE HYPERTENSIVE URGENCY INFECTION

Contacts and locations

Locations

  • Brigham and Women's Faulkner Hospital

    Boston, Massachusetts, 02130, United States

  • Brigham and Women's Hospital

    Boston, Massachusetts, 02115, United States

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