Evaluation and Further Development of an Artificial Intelligence-based Algorithm for Clinical Decision Support

Description

Invasive mechanical ventilation is one of the most important and life-saving therapies in the intensive care unit (ICU). In most severe cases, extracorporeal lung support is initiated when mechanical ventilation is insufficient. However, mechanical ventilation is recognised as potentially harmful, because inappropriate mechanical ventilation settings in ICU patients are associated with organ damage, contributing to disease burden. Studies revealed that mechanical ventilation is often not provided adequately despite clear evidence and guidelines. Variables at the ventilator and extracorporeal lung support device can be set automatically using optimization functions and clinical recommendations, but the handling of experts may still deviate from those settings depending upon the clinical characteristics of individual patients. Artificial intelligence can be used to learn from those deviations as well as the patient's condition in an attempt to improve the combination of settings and accomplish lung support with reduced risk of damage.

Conditions

Invasive Mechanical Ventilation

Study Overview

Study Details

Study overview

Invasive mechanical ventilation is one of the most important and life-saving therapies in the intensive care unit (ICU). In most severe cases, extracorporeal lung support is initiated when mechanical ventilation is insufficient. However, mechanical ventilation is recognised as potentially harmful, because inappropriate mechanical ventilation settings in ICU patients are associated with organ damage, contributing to disease burden. Studies revealed that mechanical ventilation is often not provided adequately despite clear evidence and guidelines. Variables at the ventilator and extracorporeal lung support device can be set automatically using optimization functions and clinical recommendations, but the handling of experts may still deviate from those settings depending upon the clinical characteristics of individual patients. Artificial intelligence can be used to learn from those deviations as well as the patient's condition in an attempt to improve the combination of settings and accomplish lung support with reduced risk of damage.

Retrospective Use of Patient Treatment Data for the Evaluation and Further Development of an Artificial Intelligence-based Algorithm for Clinical Decision Support in Invasive Mechanical Ventilation of Intensive Care Patients

Evaluation and Further Development of an Artificial Intelligence-based Algorithm for Clinical Decision Support

Condition
Invasive Mechanical Ventilation
Intervention / Treatment

-

Contacts and Locations

Cleveland

Cleveland Clinic Foundation, Cleveland, USA, Cleveland, Ohio, United States, 44195

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

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Eligibility Criteria

    Ages Eligible for Study

    18 Years to

    Sexes Eligible for Study

    ALL

    Accepts Healthy Volunteers

    No

    Collaborators and Investigators

    Technische Universität Dresden,

    Jakob Wittenstein, MD, PRINCIPAL_INVESTIGATOR, University Hospital Carl Gustav Carus at Technischen Universität Dresden, Germany

    Study Record Dates

    2025-02-28