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An Algorithm Driven Sepsis Prediction Biomarker

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ClinicalTrials.gov Identifier: NCT03015454
Recruitment Status : Recruiting
First Posted : January 10, 2017
Last Update Posted : January 10, 2017
Sponsor:
Collaborator:
Information provided by (Responsible Party):

Study Description
Brief Summary:
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).

Condition or disease Intervention/treatment
Sepsis Septic Shock Severe Sepsis Other: Severe Sepsis Prediction Other: Severe Sepsis Detection

Study Design

Study Type : Interventional  (Clinical Trial)
Estimated Enrollment : 150 participants
Allocation: Randomized
Intervention Model: Factorial Assignment
Masking: None (Open Label)
Primary Purpose: Screening
Official Title: A Randomized Controlled Clinical Trial of an Algorithm Driven Sepsis Prediction Biomarker
Study Start Date : December 2016
Estimated Primary Completion Date : February 2017

Resource links provided by the National Library of Medicine

MedlinePlus related topics: Sepsis
U.S. FDA Resources

Arms and Interventions

Arm Intervention/treatment
Experimental: With InSight
Healthcare provider receives an alert from InSight for patients trending towards severe sepsis. Healthcare provider also receives information from the severe sepsis detector in the UCSF electronic health record.
Other: Severe Sepsis Prediction
Upon receiving an InSight alert, healthcare provider follows standard practices in assessing possible (severe) sepsis and intervening accordingly.
Other: Severe Sepsis Detection
Upon receiving information from the severe sepsis detector in the UCSF electronic health record, healthcare provider follows standard practices in assessing possible (severe) sepsis and intervening accordingly.
Active Comparator: Without InSight
Healthcare provider does not receive any alerts from InSight. Healthcare provider receives information from the severe sepsis detector in the UCSF electronic health record.
Other: Severe Sepsis Detection
Upon receiving information from the severe sepsis detector in the UCSF electronic health record, healthcare provider follows standard practices in assessing possible (severe) sepsis and intervening accordingly.


Outcome Measures

Primary Outcome Measures :
  1. Hospital length of stay [ Time Frame: Through study completion, an average of 45 days ]

Secondary Outcome Measures :
  1. In-hospital mortality [ Time Frame: Through study completion, an average of 45 days ]

Other Outcome Measures:
  1. ICU length of stay [ Time Frame: Through study completion, an average of 45 days ]

Eligibility Criteria

Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years and older   (Adult, Senior)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Criteria

Inclusion Criteria:

  • All adult patients admitted to the participating units will be eligible.

Exclusion Criteria:

  • All patients younger than 18 years of age will be excluded.
Contacts and Locations

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03015454


Contacts
Contact: Ritankar Das 872 228 5332 ritankar@dascena.com

Locations
United States, California
UCSF Moffit-Long Hospital Recruiting
San Francisco, California, United States, 94143
Contact: David W Shimabukuro, MDCM         
Sponsors and Collaborators
Dascena
University of California, San Francisco
Investigators
Principal Investigator: Ritankar Das Dascena
More Information