Machine Learning Ventilator Decision System VS. Standard Controlled Ventilation

Not Applicable

Not yet recruiting

• Conditions: Mechanical Ventilation; Critically Ill Patients
• Interventions: Device: Machine Learning Ventilator Decision System

• Registration Number: NCT05132751
• Lead Sponsor: Hu Anmin

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.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2021-10-07
• Status Verified: 2021-11
• Study First Submitted QC: 2021-11-12
• Last Update Submitted: 2021-11-12
• Study First Posted: 2021-11-24
• Last Update Posted: 2021-11-24
• Study Start: 2022-01-01
• Primary Completion: 2022-01-01
• Study Completion: 2024-12-01

Recruitment & Eligibility

• Status: NOT_YET_RECRUITING
• Sex: All
• Target Recruitment: 300

Inclusion Criteria

1. only the first ICU stay was eligible;
2. adults ≥ 18 years of age on ICU admission;
3. estimate mechanical ventilation time ≥24 hours;

Exclusion Criteria

Not provided

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Arm && Interventions

Group	Intervention	Description
Group B	Machine Learning Ventilator Decision System	Standard Controlled Ventilation
Group A	Machine Learning Ventilator Decision System	Machine Learning Ventilator Decision System Ventilation

Primary Outcome Measures

Name	Time	Method
Mechanical ventilation time	through study completion, an average of 5 days

Secondary Outcome Measures

Name	Time	Method
Length of ICU stay time	through study completion, an average of 1 week
Length of hospital stay	through study completion, an average of 2 weeks
In-hospital mortality	through study completion, an average of 2 weeks