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

T

Technische Universität Dresden

Status

Enrolling

Conditions

Invasive Mechanical Ventilation

Treatments

Other: Artificial Intelligence-based Decision support

Study type

Observational

Funder types

Other

Identifiers

NCT05668637
TUD-IntelliLung-Study-A

Details and patient eligibility

About

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.

Enrollment

318,542 estimated patients

Sex

All

Ages

18+ years old

Volunteers

No Healthy Volunteers

Inclusion criteria

• Subjects who are 18 years or older and receive invasive mechanical ventilation for > 4 hours

Exclusion criteria

• Patients receiving one-lung ventilation

Trial contacts and locations

8

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Central trial contact

Thea Koch, PhD; Jakob Wittenstein, MD

Data sourced from clinicaltrials.gov

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