Intelligent Lung Support in the Intensive Care Unit

NCT ID: NCT06595602

Last Updated: 2025-09-26

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

RECRUITING

Total Enrollment

530 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-05-25

Study Completion Date

2027-12-31

Brief Summary

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The aim of this observational study is to test the IntelliLung decision support system based on artificial intelligence. This system is intended to help to set the ventilator. The study includes patients with and without ARDS (acute respiratory distress syndrome) who are receiving invasive mechanical ventilation, as well as patients with additional extracorporeal lung support. The study will be conducted in several centers.

The main question of the study:

How well do the mechanical ventilation settings of healthcare staff match the recommendations of the IntelliLung system?

Detailed Description

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Conditions

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Mechanical Ventilation Intensive Care Medicine

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Invasively mechanically ventilated patients expected to stay ventilated for more than 24 h.

Artificial intelligence based decision support system (AI-DSS); software

Intervention Type DEVICE

The device is intended for monitoring and recommending ventilator settings, ventilation mode to qualified Intensive Care Unit (ICU) health care professionals (HCP). This is for medical indications that require invasive mechanical ventilation of the respiratory system in the ICU under international / EU guidelines.

The device receives clinical data via the ICU's data integration platform that includes patient physical and demographic data as well as current vital signs, ventilation parameters, blood gas analysis, general blood laboratory reports, fluid balance and medication. Prediction models based on artificial intelligence algorithms are used to deduce therapy suggestions from received data. The algorithm is carried out on a secured cloud platform.

Interventions

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Artificial intelligence based decision support system (AI-DSS); software

The device is intended for monitoring and recommending ventilator settings, ventilation mode to qualified Intensive Care Unit (ICU) health care professionals (HCP). This is for medical indications that require invasive mechanical ventilation of the respiratory system in the ICU under international / EU guidelines.

The device receives clinical data via the ICU's data integration platform that includes patient physical and demographic data as well as current vital signs, ventilation parameters, blood gas analysis, general blood laboratory reports, fluid balance and medication. Prediction models based on artificial intelligence algorithms are used to deduce therapy suggestions from received data. The algorithm is carried out on a secured cloud platform.

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

1. Male and female patients, age ⪰18 years
2. Written informed consent
3. Invasively mechanically ventilated patients expected to be intubated for more than 24 hours.

Exclusion Criteria

1. Expected to die within ≤48 hours
2. Participation in an interventional mechanical ventilation trial
3. Mechanical Ventilation with a closed-loop ventilation mode
4. Persons dependent on the sponsor and/or investigator
5. Subjects who are currently imprisoned or otherwise in confinement ordered by law or other official authorities
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Dipartimento di Scienze Chirurgiche e Diagnostiche Integrate, University of Genoa, Genoa, Italy

UNKNOWN

Sponsor Role collaborator

Critical Care Department, Parc Taulí Hospital Universitari, Institut d'Investigació I Innovació Parc Taulí (I3PT-CERCA), Sabadell, Spain

UNKNOWN

Sponsor Role collaborator

Department of Anaesthesiology and Intensive Care, National Medical Institute of the Ministry of Interior and Administration, Warsaw, Polan

UNKNOWN

Sponsor Role collaborator

Department of Intensive Care Medicine. Hospital Universitario de La Princesa. Universidad Autonoma de Madrid, Madrid, Spain

UNKNOWN

Sponsor Role collaborator

Department of Anesthesiology and Intensive Care Medicine, Pulmonary Engineering Group, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresde

UNKNOWN

Sponsor Role collaborator

Technische Universität Dresden

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Jakob Wittenstein

Role: PRINCIPAL_INVESTIGATOR

epartment of Anesthesiology and Intensive Care Medicine, Pulmonary Engineering Group, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany

Locations

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Department of Anesthesiology and Intensive Care Medicine, Pulmonary Engineering Group, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany

Dresden, , Germany

Site Status RECRUITING

Dipartimento di Scienze Chirurgiche e Diagnostiche Integrate, University of Genoa, Genoa, Italy

Genova, , Italy

Site Status NOT_YET_RECRUITING

Department of Anaesthesiology and Intensive Care, National Medical Institute of the Ministry of Interior and Administration, Warsaw, Poland

Warsaw, , Poland

Site Status NOT_YET_RECRUITING

Department of Intensive Care Medicine. Hospital Universitario de La Princesa. Universidad Autonoma de Madrid, Madrid, Spain

Madrid, , Spain

Site Status NOT_YET_RECRUITING

Critical Care Department, Parc Taulí Hospital Universitari, Institut d'Investigació I Innovació Parc Taulí (I3PT-CERCA), Sabadell, Spain

Sabadell, , Spain

Site Status NOT_YET_RECRUITING

Countries

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Germany Italy Poland Spain

Central Contacts

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Jakob Wittenstein, M.D.

Role: CONTACT

+49 351 458 19777

Raphael Theilen

Role: CONTACT

+49 351 458 19777

Facility Contacts

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Jakob Wittenstein, MD

Role: primary

+49 351 458 19777

Lorenzo Ball

Role: primary

Konstanty Szuldrzynski

Role: primary

Fernando Suarez Sipmann

Role: primary

Lluis Blanch

Role: primary

Other Identifiers

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101057434

Identifier Type: OTHER_GRANT

Identifier Source: secondary_id

TUD-INTELL-086

Identifier Type: -

Identifier Source: org_study_id

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