Sepsis
Conditions
Keywords
Prediction
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.
Interventions
DEVICEUnblinded AlgoDx Sepsis Prediction Algorithm
When applicable, a sepsis prediction alert is displayed in the AlgoDx Medical Device Software.
OTHERBlinded AlgoDx Sepsis Prediction Algorithm
Standard of Care, i.e. no sepsis prediction alert.
Sponsors
AlgoDx
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
DIAGNOSTIC
Masking
TRIPLE (Subject, Caregiver, Investigator)
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Validate the prognostic accuracy of the algorithm at predicting sepsis. | 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). |
Countries
Sweden
Outcome results
None listed