Early Prediction of Sepsis

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.

Completed

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Key information

Conditions

Sepsis Infections Inflammation Pathologic Processes Pathological Conditions, Signs and Symptoms Systemic Inflammatory Response Syndrome

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Intensiv- och perioperativ vård

Malmö, 20502, Sweden

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

Unblinded AlgoDx Sepsis Prediction Algorithm

Device

When applicable, a sepsis prediction alert is displayed in the AlgoDx Medical Device Software.

Blinded AlgoDx Sepsis Prediction Algorithm

Other

Standard of Care, i.e. no sepsis prediction alert.

Primary outcomes

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).

Sponsors and collaborators

Lead sponsor

AlgoDx

Industry

Registry information

Official study title

Early Prediction of Sepsis in Hospitalized Patients Using a Machine Learning Algorithm, a Randomized Clinical Validation Trial.

Acronym: ExPRESS

Important dates

Study start: 2020
Primary completion: 2021
Study completion: 2021
First posted: Sep 30, 2020
Registry last updated: Nov 3, 2021

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

Completed