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Septic Shock clinical trials at UC Health
5 in progress, 1 open to eligible people

  • A Study of Different Ways to Use Intravenous Fluids (given through a vein) and Vasopressors (blood pressure medicine) for Sepsis

    open to eligible people ages 18 years and up

    Multicenter, prospective, phase 3 randomized non-blinded interventional trial of fluid treatment strategies in the first 24 hours for patients with sepsis-induced hypotension. The aim of the study is to determine the impact of a restrictive fluids strategy (vasopressors first followed by rescue fluids) as compared to a liberal fluid strategy (fluids first followed by rescue vasopressors) on 90-day in-hospital mortality in patients with sepsis-induced hypotension.

    at UCLA UCSF

  • HindSight Phase II

    Sorry, not yet accepting patients

    Machine learning is a powerful method for creating clinical decision support (CDS) tools, but it requires training labels which reflect the desired alert behavior. In the Phase I work for this project, investigators have developed an encoding software called HindSight that examines discharged patients' electronic health records (EHR), identifies clinicians' sepsis treatment decisions and patient outcomes, and passes these labeled examples to an online algorithm for retraining InSight, a machine-learning-based CDS tool for real-time sepsis prediction. Although HindSight has been shown to be successful in improving the performance of InSight in retrospective work, it has yet to be validated in prospective settings; therefore, in this project, the clinical utility of HindSight will be assessed through a multicenter randomized controlled trial (RCT).

    at UCSF

  • RCT of Sepsis Machine Learning Algorithm

    Sorry, not yet accepting patients

    The focus of this study will be to conduct a prospective, multi-center randomized controlled trial (RCT) at Cape Regional Medical Center (CRMC), Oroville Hospital (OH), and UCSF Medical Center (UCSF) in which a machine-learning algorithm will be applied to EHR data for the detection of sepsis. For patients determined to have a high risk of sepsis, the algorithm will generate automated voice, telephone notification to nursing staff at CRMC, OH, and UCSF. The algorithm's performance will be measured by analysis of the primary endpoint, in-hospital SIRS-based mortality.

    at UCSF

  • Stress Hydrocortisone In Pediatric Septic Shock

    Sorry, not currently recruiting here

    SHIPSS is a multi-institutional, prospective, controlled, randomized, double-blinded interventional trial that will examine the potential benefits and risks of adjunctive hydrocortisone prescribed for children with fluid and vasoactive-inotropic refractory septic shock. It is hypothesized that adjunctive hydrocortisone will significantly reduce the proportion of children with poor outcomes, defined as death or severely impaired health-related quality of life (HRQL), as assessed at 28 days following study enrollment (randomization).

    at UCSF

  • Subpopulation-Specific Sepsis Identification Using Machine Learning

    Sorry, not yet accepting patients

    The focus of this study will be to conduct a prospective, randomized controlled trial (RCT) at Cape Regional Medical Center (CRMC), Oroville Hospital (OH), and UCSF Medical Center (UCSF) in which a subpopulation-optimized algorithm will be applied to EHR data for the detection of severe sepsis. For patients determined to have a high risk of severe sepsis, the algorithm will generate automated voice, telephone notification to nursing staff at CRMC, OH, and UCSF. The algorithm's performance will be measured by analysis of the primary endpoint, in-hospital SIRS-based mortality. The secondary endpoints will be in-hospital severe sepsis/shock-coded mortality, SIRS-based hospital length of stay, and severe sepsis/shock-coded hospital length of stay.

    at UCSF

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