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
|Condition or disease||Intervention/treatment||Phase|
|Sepsis||Device: Unblinded AlgoDx Sepsis Prediction Algorithm Other: Blinded AlgoDx Sepsis Prediction Algorithm||Not Applicable|
|Study Type :||Interventional (Clinical Trial)|
|Estimated Enrollment :||300 participants|
|Intervention Model:||Parallel Assignment|
|Masking:||Triple (Participant, Care Provider, Investigator)|
|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|
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.
- 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:
- specificity, and
- sensitivity of the AlgoDx Sepsis Prediction Algorithm in the SoC group (not possible to assess these in the SoC + Algorithm cohort).
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
|Intensiv- och perioperativ vård||Recruiting|
|Malmö, Sweden, 20502|
|Contact: Fredrik Sjövall, MD PhD +4640337606 firstname.lastname@example.org|