Non-invasive Detection of Driveline Infections in Patients with a Left Ventricular Assist Device

• Conditions: LVAD (Left Ventricular Assist Device) Driveline Infection

• Registration Number: NCT06867887
• Lead Sponsor: Erasmus Medical Center

Brief Summary

The aim of this single center observational study is to determine the feasibility of using non-invasive imaging methods, including smartphone photography and infrared thermography, for detecting of DLIs in LVAD patients in terms of severity, extent and natural healing process.

Detailed Description

Observational data of the driveline exit of LVAD patients will be collected during a follow-up period of 26 weeks. Two non-invasive imaging methods will be used.

Smartphone photos will be taken weekly by the patient during routine wound care in the home environment.

In case the patient is admitted for driveline infection, infrared thermographic (IRT) photography will be used to make thermographic photos of the driveline exit and the abdominal area of the subcutaneous driveline.

Furthermore, existing smartphone images and diagnostic data regarding prior DLI status will be obtained from the electronic patient records.

Imaging data will additionally be retrospectively analyzed using artificial intelligence (AI) and machine learning for the development of a predictive AI model.

Study Timeline

• Study Start: 2024-02-12
• Status Verified: 2024-09
• Study First Submitted: 2024-09-05
• Study First Submitted QC: 2025-03-05
• Last Update Submitted: 2025-03-05
• Study First Posted: 2025-03-10
• Last Update Posted: 2025-03-10
• Primary Completion: 2026-12-31
• Study Completion: 2026-12-31

Recruitment & Eligibility

• Status: ENROLLING_BY_INVITATION
• Sex: All
• Target Recruitment: 70

Inclusion Criteria

Patients age 16 years or older, implanted with an LVAD, followed at Erasmus MC, with access to a smartphone with a built-in camera, who have signed an informed consent for data collection.

Exclusion Criteria

Known cognitive problems, like dementia etc., non-cardiac disease or cardiac diseases resulting in a life expectancy less than 1 years, inability to read or sign the informed consent form.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Extent and severity of driveline infections in LVAD patients using non-invasive imaging	26 weeks	Assess the extent, severity, and healing process of LVAD driveline infections in patients on LVAD support
Driveline exit healing process and risk of infection of the LVAD driveline	26	Assess the healing process of the driveline exit using non-invasive imaging (smartphone and thermographic)

Secondary Outcome Measures

Name	Time	Method
Machine learning model for predicting DLIs.	26 weeks	Assess whether a machine learning model can be developed and validated based on smartphone photography and IRT to predict the occurrence of DLIs.
Sceptic complications	26 weeks	Occurance of systemic infection, positive blood cultures, and VAD-related infections.

Trial Locations

Locations (1)

Erasmus MC; 🇳🇱 Rotterdam, Netherlands