Early Prediction of Sepsis (ExPRESS)
Early Prediction of Sepsis in Hospitalized Patients Using a Machine Learning Algorithm, a Randomized Clinical Validation Trial.
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Actual)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Locations
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-
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Malmö, Sweden, 20502
- Intensiv- och perioperativ vård
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-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Description
Inclusion Criteria:
- Adult patient (age ≥18 years).
- Patient is admitted to the ICU during the recruitment period of the trial.
Exclusion Criteria:
- Patient is participating in another interventional clinical trial which, as judged by the investigator, could potentially impact variables used by the sepsis prediction algorithm or has participated in such interventional clinical trial within the last 30 days.
- Patient is known to be pregnant.
- Death is deemed imminent and inevitable, at the investigator's discretion.
- Patient has, due to chronic reduced mental capacity, been assessed by the investigator as incapable of making an informed decision
- Patient has previously been enrolled in this trial.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: Triple
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Sham Comparator: Standard of Care
Subjects are monitored for potential development of sepsis according to the local established clinical management guidelines.
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Standard of Care, i.e. no sepsis prediction alert.
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Experimental: Standard of Care + AlgoDx Sepsis Prediction Algorithm
Subjects are monitored for potential development of sepsis according to the local established clinical management guidelines, and sepsis prediction algorithm alerts are unblinded to clinical staff.
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When applicable, a sepsis prediction alert is displayed in the AlgoDx Medical Device Software.
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Validate the prognostic accuracy of the algorithm at predicting sepsis.
Time Frame: Up to 30 days (ICU hospitalization period)
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In order to clinically validate the sepsis prediction performance the following endpoints have been selected:
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Up to 30 days (ICU hospitalization period)
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Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- SEP-SE-02
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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