RCT of Sepsis Machine Learning Algorithm
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|ClinicalTrials.gov Identifier: NCT03882476|
Recruitment Status : Unknown
Verified March 2019 by Dascena.
Recruitment status was: Not yet recruiting
First Posted : March 20, 2019
Last Update Posted : March 25, 2019
|Condition or disease||Intervention/treatment||Phase|
|Sepsis Severe Sepsis Septic Shock||Diagnostic Test: InSight||Phase 2|
|Study Type :||Interventional (Clinical Trial)|
|Estimated Enrollment :||51645 participants|
|Intervention Model:||Parallel Assignment|
|Masking:||Triple (Participant, Care Provider, Investigator)|
|Official Title:||Randomized Controlled Trial of a Machine Learning Algorithm for Early Sepsis Detection|
|Estimated Study Start Date :||January 1, 2020|
|Estimated Primary Completion Date :||February 28, 2021|
|Estimated Study Completion Date :||February 28, 2021|
The experimental arm will involve patients monitored by InSight.
Diagnostic Test: InSight
Clinical decision support (CDS) system for sepsis detection
No Intervention: Control
The control arm will have no intervention and will involve patients with the usual standard of care.
- In-hospital SIRS-based mortality [ Time Frame: Through study completion, an average of eight months ]Rate of mortality attributed to patients meeting two or more SIRS criteria at some point during their stay
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): NCT03882476
|Contact: Ritankar Das, MScemail@example.com|
|Contact: Chris Barton, MD||415-206-5762||Chris.Barton@ucsf.edu|
|Principal Investigator:||Ritankar Das, MSc||Dascena|