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Early Prediction of Sepsis

NCT ID: NCT04570618

Last Updated: 2021-11-03

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

320 participants

Study Classification

INTERVENTIONAL

Study Start Date

2020-12-01

Study Completion Date

2021-11-01

Brief Summary

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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.

Detailed Description

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Conditions

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Sepsis

Keywords

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Prediction

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

TRIPLE

Participants Caregivers Investigators

Study Groups

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Standard of Care

Subjects are monitored for potential development of sepsis according to the local established clinical management guidelines.

Group Type SHAM_COMPARATOR

Blinded AlgoDx Sepsis Prediction Algorithm

Intervention Type OTHER

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

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.

Group Type EXPERIMENTAL

Unblinded AlgoDx Sepsis Prediction Algorithm

Intervention Type DEVICE

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

Interventions

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Unblinded AlgoDx Sepsis Prediction Algorithm

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

Intervention Type DEVICE

Blinded AlgoDx Sepsis Prediction Algorithm

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

Intervention Type OTHER

Eligibility Criteria

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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.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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AlgoDx

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Intensiv- och perioperativ vård

Malmo, , Sweden

Site Status

Countries

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Sweden

References

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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.

Reference Type DERIVED
PMID: 38245375 (View on PubMed)

Other Identifiers

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SEP-SE-02

Identifier Type: -

Identifier Source: org_study_id