Erasmus MC
Rotterdam, Netherlands
NCT Number: NCT06867887
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.
Interested in participating?
Request Info16 year–99 year
All sexes
Observational
Rotterdam, Netherlands
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.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
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.
Time frame: 26 weeks
Assess the extent, severity, and healing process of LVAD driveline infections in patients on LVAD support
Time frame: 26
Assess the healing process of the driveline exit using non-invasive imaging (smartphone and thermographic)
Time frame: 26 weeks
Occurance of systemic infection, positive blood cultures, and VAD-related infections.
Time frame: 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.
Erasmus Medical Center
Other
Acronym: DRIVE-ID
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View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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