Back to resultsMachine Learning Ventilator Decision System VS. Standard Controlled Ventilation
Primary Purpose
Mechanical Ventilation, Critically Ill Patients
Status
Not yet recruiting
Phase
Not Applicable
Locations
Study Type
Interventional
Intervention
Machine Learning Ventilator Decision System
Sponsored by
About this trial
This is an interventional treatment trial for Mechanical Ventilation
Eligibility Criteria
Inclusion Criteria:
- only the first ICU stay was eligible;
- adults ≥ 18 years of age on ICU admission;
- estimate mechanical ventilation time ≥24 hours;
Sites / Locations
Arms of the Study
Arm 1
Arm 2
Arm Type
Experimental
Active Comparator
Arm Label
Group A
Group B
Arm Description
Machine Learning Ventilator Decision System Ventilation
Standard Controlled Ventilation
Outcomes
Primary Outcome Measures
Mechanical ventilation time
Secondary Outcome Measures
Length of ICU stay time
Length of hospital stay
In-hospital mortality
Full Information
1. Study Identification
Unique Protocol Identification Number
NCT05132751
Brief Title
Machine Learning Ventilator Decision System VS. Standard Controlled Ventilation
Official Title
Effect of a Machine Learning Ventilator Decision System Versus Standard Controlled Ventilation on in Critical Care: a Randomized Trial
Study Type
Interventional
2. Study Status
Record Verification Date
November 2021
Overall Recruitment Status
Not yet recruiting
Study Start Date
January 1, 2022 (Anticipated)
Primary Completion Date
January 1, 2022 (Anticipated)
Study Completion Date
December 1, 2024 (Anticipated)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Sponsor-Investigator
Name of the Sponsor
Hu Anmin
4. Oversight
Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
No
5. Study Description
Brief Summary
Ventilator-induced lung injury is associated with increased morbidity and mortality. Despite intense efforts in basic and clinical research, an individualized ventilation strategy for critically ill patients remains a major challenge. However, an individualized mechanical ventilation approach remains a challenging task: A multitude of factors, e.g., lab values, vitals, comorbidities, disease progression, and other clinical data must be taken into consideration when choosing a patient's specific optimal ventilation regime. The aim of this work was to evaluate the machine learning ventilator decision system, which is able to suggest a dynamically optimized mechanical ventilation regime for critically-ill patients. Compare with standard controlled ventilation, to test whether the clinical application of the machine learning ventilator decision system reduces mechanical ventilation time and mortality.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Mechanical Ventilation, Critically Ill Patients
7. Study Design
Primary Purpose
Treatment
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Model Description
ventilator decision system
Masking
ParticipantInvestigatorOutcomes Assessor
Allocation
Randomized
Enrollment
300 (Anticipated)
8. Arms, Groups, and Interventions
Arm Title
Group A
Arm Type
Experimental
Arm Description
Machine Learning Ventilator Decision System Ventilation
Arm Title
Group B
Arm Type
Active Comparator
Arm Description
Standard Controlled Ventilation
Intervention Type
Device
Intervention Name(s)
Machine Learning Ventilator Decision System
Intervention Description
Artificial intelligence ventilator system for personalized mechanical ventilation
Primary Outcome Measure Information:
Title
Mechanical ventilation time
Time Frame
through study completion, an average of 5 days
Secondary Outcome Measure Information:
Title
Length of ICU stay time
Time Frame
through study completion, an average of 1 week
Title
Length of hospital stay
Time Frame
through study completion, an average of 2 weeks
Title
In-hospital mortality
Time Frame
through study completion, an average of 2 weeks
10. Eligibility
Sex
All
Minimum Age & Unit of Time
18 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria:
only the first ICU stay was eligible;
adults ≥ 18 years of age on ICU admission;
estimate mechanical ventilation time ≥24 hours;
12. IPD Sharing Statement
Plan to Share IPD
Undecided
Learn more about this trial
Machine Learning Ventilator Decision System VS. Standard Controlled Ventilation
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