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Explainable AI for Predicting Hospital Admissions in Heart Failure: ExplAIn-HF

NCT07689760 · Status: ENROLLING_BY_INVITATION · Type: OBSERVATIONAL · Enrollment: 95

Last updated 2026-08-03

No results posted yet for this study

Summary

The goal of this observational study is to develop and validate an XAI based model that predicts HF events and identifies modifiable con-tributing factors, and to evaluate the added value of integrating high frequency smartwatch data compared to usual care in patients with heart failure. The main objectives of the study are:

1. To develop and validate an XAI based model that predicts HF events and identifies modifiable contributing factors, and to evaluate the added value of integrating high frequency smartwatch data compared to usual care. In the Netherlands usual care includes remote monitoring of heartrate, blood pressure, weight and symptoms.
2. To include insights of the smartwatch into activity patterns, impact on quality of life (KCCQ-12), and patient satisfaction with net promoter score (NPS).

Participants will wear a smartwatch for six months and perform an I-lead ecg with the smartwatch weekly.

Conditions

Sponsors & Collaborators

  • Saxion University of Applied Sciences

    collaborator OTHER

  • Deventer Ziekenhuis

    collaborator OTHER

  • University of Twente

    collaborator OTHER

  • Ziekenhuisgroep Twente

    collaborator OTHER

  • Medisch Spectrum Twente

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-07-31
Primary Completion
2027-12-31
Completion
2027-12-31

Countries

  • Netherlands

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07689760 on ClinicalTrials.gov