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An Algorithm Driven Sepsis Prediction Biomarker

NCT03015454 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 142

Last updated 2021-09-23

No results posted yet for this study

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).

Conditions

  • Sepsis
  • Septic Shock
  • Severe Sepsis

Interventions

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.

Sponsors & Collaborators

Principal Investigators

  • Ritankar Das · Dascena

Study Design

Allocation
RANDOMIZED
Purpose
SCREENING
Masking
NONE
Model
FACTORIAL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2016-12-31
Primary Completion
2017-02-28

Countries

  • United States

Study Locations

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Entities

Diseases
Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT03015454 on ClinicalTrials.gov