SepsisExPRESSNCT04570618
Early Prediction of Sepsis
A study testing Unblinded AlgoDx Sepsis Prediction Algorithm and Blinded AlgoDx Sepsis Prediction Algorithm in people with Sepsis, run by AlgoDx at 1 site in Sweden.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Sepsis
- What is being tested?
- Unblinded AlgoDx Sepsis Prediction Algorithm and Blinded AlgoDx Sepsis Prediction Algorithm
- Type of treatment
- Medical device
- Could I receive a placebo?
- Yes, some participants may receive a placebo
- How many people
- 320 participants
- Where
- 1 siteSweden
- Study dates
- 1 Dec 2020to 1 Nov 2021
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Adult patient (age ≥18 years).
- Patient is admitted to the ICU during the recruitment period of the trial.
Who cannot join
- 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.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Early Prediction of Sepsis in Hospitalized Patients Using a Machine Learning Algorithm, a Randomized Clinical Validation Trial.
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.
- Conditions
- Sepsis
- Being tested
- Unblinded AlgoDx Sepsis Prediction Algorithm, Blinded AlgoDx Sepsis Prediction Algorithm
- Keywords
- Prediction
- Medical subject headings
- Sepsis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Unblinded AlgoDx Sepsis Prediction AlgorithmDevice
When applicable, a sepsis prediction alert is displayed in the AlgoDx Medical Device Software.
Blinded AlgoDx Sepsis Prediction AlgorithmOther
Standard of Care, i.e. no sepsis prediction alert.
| Study group | Role | What they receive |
|---|---|---|
| Standard of Care | Sham comparator | Subjects are monitored for potential development of sepsis according to the local established clinical management guidelines. Receives: Other: Blinded AlgoDx Sepsis Prediction Algorithm |
| Standard of Care + AlgoDx Sepsis Prediction Algorithm | Experimental | 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. Receives: Device: Unblinded AlgoDx Sepsis Prediction Algorithm |
What is being measured
The primary outcome is the main question the study is designed to answer.
Validate the prognostic accuracy of the algorithm at predicting sepsis.
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).
Measured: Up to 30 days (ICU hospitalization period)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted30 Sep 2020
- Study start1 Dec 2020
- Primary completion1 Nov 2021
- Study completion1 Nov 2021
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for SepsisStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Triple blind
- Who is masked
- Participant, Care provider, Investigator
- Enrolment
- 320 participants (actual)
Sponsor and investigators
- Lead sponsor
- AlgoDx
- Sponsor type
- Industry (pharma, biotech, devices)
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04570618
- Sponsor's protocol ID
- SEP-SE-02
- Acronym
- ExPRESS
- Status last verified
- Nov 2021
- First submitted
- 22 Sep 2020
- Last updated
- 3 Nov 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Persson I, Macura A, Becedas D, Sjovall F. Early prediction of sepsis in intensive care patients using the machine learning algorithm NAVOY(R) Sepsis, a prospective randomized clinical validation study. J Crit Care. 2024 Apr;80:154400. doi: 10.1016/j.jcrc.2023.154400.
PubMed 38245375
Study at a glance
From the registry record, last updated by the sponsor on 3 Nov 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Early Prediction of Sepsis in Hospitalized Patients Using a Machine Learning Algorithm, a Randomized Clinical Validation Trial.
- ClinicalTrials.gov ID
- NCT04570618
- Acronym / sponsor ID
- ExPRESS / SEP-SE-02
- Conditions
- Sepsis
- Keywords
- Prediction
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 320 participants (actual)
- Lead sponsor
- AlgoDxIndustry (pharma, biotech, devices)
- Study start
- 1 Dec 2020 (actual)
- Primary completion
- 1 Nov 2021 (actual)
- Study completion
- 1 Nov 2021 (actual)
- First posted
- 30 Sep 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Triple blind (participant, care provider, investigator)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Standard of Care | Sham comparator | Other: Blinded AlgoDx Sepsis Prediction AlgorithmSubjects are monitored for potential development of sepsis according to the local established clinical management guidelines. |
| Standard of Care + AlgoDx Sepsis Prediction Algorithm | Experimental | Device: Unblinded AlgoDx Sepsis Prediction AlgorithmSubjects 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- Adult patient (age ≥18 years).
- Patient is admitted to the ICU during the recruitment period of the trial.
Key exclusion criteria (5 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Unblinded AlgoDx Sepsis Prediction AlgorithmWhen applicable, a sepsis prediction alert is displayed in the AlgoDx Medical Device Software. | Device | Standard of Care + AlgoDx Sepsis Prediction Algorithm |
| Blinded AlgoDx Sepsis Prediction AlgorithmStandard of Care, i.e. no sepsis prediction alert. | Other | Standard of Care |
Primary outcome
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).
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 3 Nov 2021.
- Derived from this study: PubMed 38245375Persson I, Macura A, Becedas D, Sjovall F. Early prediction of sepsis in intensive care patients using the machine learning algorithm NAVOY(R) Sepsis, a prospective randomized clinical validation study. J Crit Care. 2024 Apr;80:154400. doi: 10.1016/j.jcrc.2023.154400.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Unblinded AlgoDx Sepsis Prediction Algorithm and Blinded AlgoDx Sepsis Prediction Algorithm in people with Sepsis, run by AlgoDx at 1 site in Sweden.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 3 Nov 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Sweden. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. Some participants in this study may receive a placebo. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Validate the prognostic accuracy of the algorithm at predicting sepsis. (time frame: Up to 30 days (ICU hospitalization period)). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04570618, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 3 Nov 2021.