Acute Respiratory Distress Syndrome (ARDS) is characterized by severe hypoxemia and extensive lung injury. Recent studies indicate that lung functional phenotypes - particularly the distribution and evolution of lung perfusion - may be closely related to patient outcomes. Electrical impedance tomography (EIT) offers non-invasive, bedside, real-time monitoring of lung perfusion patterns and enables classification into distinct phenotypes and trajectory types over the course of illness. To date, limited data exist on perfusion phenotype trajectories in ARDS patients and their relationship with clinical outcomes. This study seeks to characterize dynamic lung dynamic ventilation-perfusion functional Phenotype using EIT and explore their prognostic significance. Objectives Primary Objective: To identify lung perfusion phenotype trajectories in ARDS patients using EIT and assess their association with 28-day mortality. Secondary Objectives: * To determine the relationship between different trajectory types and improvements in oxygenation and respiratory mechanics. * To investigate how ventilator settings (PEEP, driving pressure) interact with perfusion changes. * To support individualized mechanical ventilation strategies based on Ventilation-Perfusion Functional Phenotype monitoring
Design: Prospective, multicenter, observational cohort study * Setting: ≥2 tertiary ICUs equipped with EIT capability * Population: Adult patients with moderate-to-severe ARDS (Berlin definition, PaO₂/FiO₂ ≤ 200 mmHg) receiving mechanical ventilation * Intervention: Daily lung perfusion assessment using a 16-electrode EIT belt. Regional ventilation-perfusion (V/Q) ratios are calculated by combining tidal and pulsatile impedance changes. Phenotypes are classified as Matched V/Q, High V/Q (dead space), Low V/Q (shunt), or Globally Impaired V/Q. Trajectories are categorized as Stable, Improving, Deteriorating, or Fluctuating. * Endpoints: * Primary: Association between phenotype trajectory type and 28-day mortality * Secondary: Time to oxygenation improvement, duration of mechanical ventilation, ICU length of stay, interaction between trajectory and ventilator settings
Study Type
OBSERVATIONAL
Enrollment
120
* 16-electrode belt positioned around the thorax * Daily perfusion assessment (10 min recording) at baseline and after major clinical interventions (e.g., PEEP change, position change) * Pulmonary perfusion analysis will primarily be based on the pulse-synchronous impedance signal derived from EIT during brief respiratory pauses, estimating regional perfusion from cardiac-related impedance changes. When signal quality is insufficient, or in cases of significant arrhythmia or other conditions affecting pulse signal detection, the saline indicator method will be applied for validation or calibration. * This involves rapid intravenous bolus injection of 10-20 mL room-temperature saline, using the induced transient conductivity change as a perfusion marker:Ventilation-Perfusion Functional Phenotype will be derived by combining EIT-based tidal and pulsatile impedance changes, calculating the regional V/Q ratio.
Department of Critical Care Medicine，Ruijin Hospital，Shanghai Jiao Tong University School of Medicine
Shanghai, Shanghai Municipality, China
28-day all-cause mortality
Time frame: From enrollment to 28 days
Time to oxygenation improvement (PaO₂/FiO₂ > 200 mmHg)
Time frame: From enrollment until the event occurs, assessed up to 14 days
Duration of mechanical ventilation
Time frame: From intubation until successful extubation, assessed up to 28 days or until ICU discharge/death
ICU length of stay
Time frame: From ICU admission until discharge from ICU, assessed up to 60 days
Interaction between phenotype trajectory and ventilator settings (PEEP, driving pressure)
Time frame: Daily during EIT monitoring period, up to 14 days
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