Model-based patient matching for in-parallel pressure-controlled ventilation.

Area of Science:

• Biomedical Engineering
• Respiratory Medicine
• Critical Care

Background:

• COVID-19 surges created mechanical ventilator (MV) shortages, leading to care rationing.
• Co-mechanical ventilation (Co-MV) is a potential solution but lacks patient-matching guidelines.
• A model-based method for patient matching in pressure control MV was developed.

Purpose of the Study:

• To develop and validate a model-based method for matching patients for co-mechanical ventilation (Co-MV).
• To enable clinicians to analyze Co-MV strategies in a simulated environment before clinical application.
• To provide guidelines for optimizing MV settings in a multi-patient ventilation scenario.

Main Methods:

• Utilized a single-compartment lung model (SCM) to simulate tidal volume for patient pairs.
• Employed a double-compartment lung model (DCM) to determine actual MV settings for Co-MV.
• Matched patients based on estimated MV delivered tidal volume (mL/kg) using patient-specific respiratory mechanics.

Main Results:

• Successfully demonstrated patient matching and MV setting determination in model-based simulations.
• Showed good discrimination to prevent mismatched patient pairs.
• Highlighted the need for extra care in Co-MV for patients with restrictive respiratory mechanics and obesity.

Conclusions:

• The developed approach allows virtual analysis of patient matching for Co-MV, minimizing patient risk.
• Simulation results support the need for clinical validation in human trials.
• Provides a foundation for developing clinical guidelines for Co-MV.