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Machine Learning Assisted Electrochemical Profiling to Provide Early Identification of Bloodstream Infections Pathogens

Study acronym: E-MOC
StatusRecruiting
PhaseNot applicable
Started
View on ClinicalTrials.gov ↗

Record History

  1. Trial status: Not Yet Recruiting to Recruitingv3 Show 4 more changesShow less
    • Primary completion date: Apr 2025 to Jan 2028
    • Start date changed from estimate of Apr 2025 to Jul 13, 2026
    • Study completion date: Aug 2026 to Jan 2028
    • Site details revised at 2 of 2 sites
  2. Start date: Feb 2025 to Apr 2025
    • Primary completion date: Feb 2025 to Apr 2025
    v2
  3. Study First Submitted
  • Stopped: an ongoing trial was terminated, suspended or withdrawn.
  • Notable: the trial’s plan changed such as a big move in its timeline or size, a new primary endpoint, sponsor or phase, or recruiting opened or resumed.
  • Minor: routine progress and housekeeping, such as sites added or enrollment closed.
In the context of a bacteremia, although significant progress has been made in speeding up pathogen identification once a blood culture bottle turns positive, few cost-effective solutions have been proposed to improve the earlier stages of the process-specifically, from blood collection to bottle positivity. The investigators propose that transport time could be leveraged to grow and identify bacteria, enabling faster access to actionable results through innovative technologies. This project aims to develop a bacterial identification database by analyzing the electrochemical profile of bacteria growing within the blood culture bottle, using machine learning.
Trial Details
NCT Number NCT06853301
Lead Sponsor University Hospital, Grenoble
Collaborators: CEA - Leti
Conditions
(from sponsor)		 Bacteremia Sepsis
Related terms Bacteremia
Enrollment 200 participants
Start Date
Primary Completion (estimated)
Study Completion (estimated)
Updated on ClinicalTrials.gov