Clinical trial NCT05668637: Evaluation and Further Development of an Artificial Intelligence-based Algorithm for Clinical Decision Support
Official title: 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
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Invasive Mechanical Ventilation
Keywords: Mechanical ventilation
ventilator-induced lung injury
ARDS
artificial intelligence
Lead sponsor: Technische Universität Dresden
Sponsor class: OTHER
First posted: 2022-12-30
Enrollment: 318542
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Observational model: OTHER
Time perspective: RETROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Intensive care patients receiving invasive mechanical ventilation

Brief summary: 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.


Eligibility criteria: Inclusion Criteria:

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

Exclusion Criteria:

• Patients receiving one-lung ventilation

Primary outcomes:
measure: Relative time of same device settings of the health care provider and the IntelliLung algorithm
timeFrame: From date of intubation to date of extubation or date of discharge, which ever came first, assessed up to 12 month
Secondary outcomes:
Other outcomes:
Locations:
city: Cleveland
country: United States
facility: Cleveland Clinic Foundation, Cleveland, USA
state: Ohio
city: Dresden
country: Germany
facility: University Hospital Carl Gustav Carus Dresden
city: Leipzig
country: Germany
facility: Institut Fur Angewandte Informatik (Infai) Ev
city: Belgrade
country: Serbia
facility: Institut Mihajlo Pupin
city: Sabadell
country: Spain
facility: Better Care Sl
city: Sabadell
country: Spain
facility: Fundacio Parc Tauli
city: Sevilla
country: Spain
facility: Fundacion Publica Andaluza Progreso Y Salud
city: Bern
country: Switzerland
facility: Inselspital, Universitätsspital Bern
Study officials:
affiliation: University Hospital Carl Gustav Carus at Technischen Universität Dresden, Germany
name: Jakob Wittenstein, MD
role: PRINCIPAL_INVESTIGATOR
References: