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Septic Shock clinical trials at UCSF
4 in progress, 2 open to new patients

  • An Algorithm Driven Sepsis Prediction Biomarker

    open to eligible people ages 18 years and up

    A sepsis early warning predictive algorithm, InSight, has been developed and validated on a large, diverse patient cohort. In this prospective study, the ability of InSight to predict severe sepsis patients is investigated. Specifically, InSight is compared with a well established severe sepsis detector in the UCSF electronic health record (EHR).

    San Francisco, California

  • Crystalloid Liberal or Vasopressors Early Resuscitation in 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.

    Fresno, California and other locations

  • Stress Hydrocortisone In Pediatric Septic Shock

    Sorry, not yet accepting patients

    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).

    Oakland, California and other locations

  • 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.