Early Prediction of Sepsis

NCT04570618 | Completed

• 1 other identifier: SEP-SE-02
• Study Type: interventional
• Target: 320
• Locations: 1 country
• Sites: 1

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.

Conditions

Sepsis

Keywords

Prediction

Outcome Measures

Primary Outcomes (1)

• 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).

  Up to 30 days (ICU hospitalization period)

Study Arms (2)

Standard of Care

SHAM COMPARATOR

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 + 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.

Device: Unblinded AlgoDx Sepsis Prediction Algorithm

Interventions

Unblinded AlgoDx Sepsis Prediction Algorithm DEVICE

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

Standard of Care + AlgoDx Sepsis Prediction Algorithm

Blinded AlgoDx Sepsis Prediction Algorithm OTHER

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

Standard of Care

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

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

You may not qualify if:

• 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.

Sponsors & Collaborators

• AlgoDx: lead

Study Sites (1)

Intensiv- och perioperativ vård

Malmo, 20502, Sweden

Location

Related Publications (1)

• 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.

  PMID: 38245375 DERIVED

MeSH Terms

Conditions

Sepsis

Condition Hierarchy (Ancestors)

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

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: TRIPLE
• Who Masked: PARTICIPANT, CARE PROVIDER, INVESTIGATOR
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: September 22, 2020
• First Posted: September 30, 2020
• Study Start: December 1, 2020
• Primary Completion: November 1, 2021
• Study Completion: November 1, 2021
• Last Updated: November 3, 2021

Record last verified: 2021-11

Data Sharing

• IPD Sharing: Will not share

Locations

SE (1)