Evaluation and Further Development of an Artificial Intelligence-based Algorithm for Clinical Decision Support
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Artificial Intelligence-based Decision support.
- Who it may be relevant to
- Registry conditions: Invasive Mechanical Ventilation. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- United States, Germany, Serbia, Spain, Switzerland
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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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
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.
Interventions
- Other Artificial Intelligence-based Decision support
Decision support to optimise invasive mechanical ventilation settings
Primary outcome measures
- Relative time of same device settings of the health care provider and the IntelliLung algorithm [Time frame: From date of intubation to date of extubation or date of discharge, which ever came first, assessed up to 12 month]
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
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Study design
- Observational model
- Other
Study locations
Spain · 3 centers
- Better Care Sl — Sabadell
- Fundacio Parc Tauli — Sabadell
- Fundacion Publica Andaluza Progreso Y Salud — Seville
Germany · 2 centers
- University Hospital Carl Gustav Carus Dresden — Dresden
- Institut Fur Angewandte Informatik (Infai) Ev — Leipzig
United States · 1 center
- Cleveland Clinic Foundation, Cleveland, USA — Cleveland
Serbia · 1 center
- Institut Mihajlo Pupin — Belgrade
Switzerland · 1 center
- Inselspital, Universitätsspital Bern — Bern
Identifiers
NCT: NCT05668637 · TUD-IntelliLung-Study-A