Working…
ClinicalTrials.gov
ClinicalTrials.gov Menu

Early Prediction of Sepsis (ExPRESS)

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Know the risks and potential benefits of clinical studies and talk to your health care provider before participating. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT04570618
Recruitment Status : Recruiting
First Posted : September 30, 2020
Last Update Posted : December 7, 2020
Sponsor:
Information provided by (Responsible Party):
AlgoDx

Brief Summary:
In this clinical trial a novel Medical Device Software will be validated prospectively. The software incorporates a machine learning algorithm capable of predicting sepsis by using routine clinical variables in adult patients at Intensive Care Units.

Condition or disease Intervention/treatment Phase
Sepsis Device: Unblinded AlgoDx Sepsis Prediction Algorithm Other: Blinded AlgoDx Sepsis Prediction Algorithm Not Applicable

Layout table for study information
Study Type : Interventional  (Clinical Trial)
Estimated Enrollment : 300 participants
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Triple (Participant, Care Provider, Investigator)
Primary Purpose: Diagnostic
Official Title: Early Prediction of Sepsis in Hospitalized Patients Using a Machine Learning Algorithm, a Randomized Clinical Validation Trial.
Actual Study Start Date : December 1, 2020
Estimated Primary Completion Date : March 1, 2021
Estimated Study Completion Date : March 1, 2021

Resource links provided by the National Library of Medicine

MedlinePlus related topics: Sepsis

Arm Intervention/treatment
Sham Comparator: Standard of Care
Subjects are monitored for potential development of sepsis according to the local established clinical management guidelines.
Other: Blinded AlgoDx Sepsis Prediction Algorithm
Standard of Care, i.e. no sepsis prediction alert.

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.
Device: Unblinded AlgoDx Sepsis Prediction Algorithm
When applicable, a sepsis prediction alert is displayed in the AlgoDx Medical Device Software.




Primary Outcome Measures :
  1. Validate the prognostic accuracy of the algorithm at predicting sepsis. [ Time Frame: Up to 30 days (ICU hospitalization period) ]

    In order to clinically validate the sepsis prediction performance the following endpoints have been selected:

    • accuracy,
    • specificity, and
    • sensitivity of the AlgoDx Sepsis Prediction Algorithm in the SoC group (not possible to assess these in the SoC + Algorithm cohort).



Information from the National Library of Medicine

Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the contacts provided below. For general information, Learn About Clinical Studies.


Layout table for eligibility information
Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Criteria

Inclusion Criteria:

  1. Adult patient (age ≥18 years).
  2. Patient is admitted to the ICU during the recruitment period of the trial.

Exclusion Criteria:

  1. 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.
  2. Patient is known to be pregnant.
  3. Death is deemed imminent and inevitable, at the investigator's discretion.
  4. Patient has, due to chronic reduced mental capacity, been assessed by the investigator as incapable of making an informed decision
  5. Patient has previously been enrolled in this trial.

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): NCT04570618


Locations
Layout table for location information
Sweden
Intensiv- och perioperativ vård Recruiting
Malmö, Sweden, 20502
Contact: Fredrik Sjövall, MD PhD    +4640337606    fredrik.sjovall@med.lu.se   
Sponsors and Collaborators
AlgoDx
Layout table for additonal information
Responsible Party: AlgoDx
ClinicalTrials.gov Identifier: NCT04570618    
Other Study ID Numbers: SEP-SE-02
First Posted: September 30, 2020    Key Record Dates
Last Update Posted: December 7, 2020
Last Verified: December 2020
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

Layout table for additional information
Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by AlgoDx:
Prediction
Additional relevant MeSH terms:
Layout table for MeSH terms
Sepsis
Toxemia
Infection
Systemic Inflammatory Response Syndrome
Inflammation
Pathologic Processes