Machine Learning Ventilator Decision System VS. Standard Controlled Ventilation

Hu Anmin

Status: Not yet enrolling

Conditions: Critically Ill Patients; Mechanical Ventilation

Treatments: Device: Machine Learning Ventilator Decision System

Study type: Interventional

Funder types: Other

Identifiers

NCT05132751

LL-KY-2021396

Details and patient eligibility

About

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.

Enrollment: 300 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion and exclusion criteria

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;

Trial design

Primary purpose: Treatment

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Triple Blind

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300 participants in 2 patient groups

Group A

Experimental group

Description:

Machine Learning Ventilator Decision System Ventilation

Treatment:

Device: Machine Learning Ventilator Decision System

Group B

Active Comparator group

Description:

Standard Controlled Ventilation

Treatment:

Device: Machine Learning Ventilator Decision System