NCT07511712: VERDICT

Using Real-Time Lung Visuals to Reduce Mental Strain and Improve Diagnosis Speed

Not yet recruiting NA Last updated 13 April 2026

What this trial tests

NA trial testing Real-time Graphical Lung Function Visualization (Digital Twin) in Mechanical Ventilation in 34 participants. Not yet recruiting.

Timeline

15 April 2026

Primary endpoint
31 July 2026

31 July 2026

Quick facts

Lead sponsor	Second Affiliated Hospital, School of Medicine, Zhejiang University
Phase	NA
Status	Not yet recruiting
Study type	INTERVENTIONAL
Allocation	randomized
Design	crossover
Masking	single
Primary purpose	health services research
Enrollment	34
Start date	15 April 2026
Primary completion	31 July 2026
Estimated completion	31 July 2026
Sites	1 location across China

Drugs / interventions tested

• Real-time Graphical Lung Function Visualization (Digital Twin)
• Standard Ventilator Waveform Monitoring

Conditions studied

• Mechanical Ventilation — all drugs for Mechanical Ventilation →
• Clinical Competence — all drugs for Clinical Competence →
• Education Curriculum — all drugs for Education Curriculum →
• Self Concept — all drugs for Self Concept →

Sponsor

Second Affiliated Hospital, School of Medicine, Zhejiang University

Who can join

Adults 18 to 65, any sex, with Mechanical Ventilation or Clinical Competence. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

The goal of this clinical simulation study is to learn if a "Digital Twin" graphical lung display reduce the mental workload of clinicians. The study also evaluates if this helps physicians diagnose and manage ventilator-related crises more effectively than standard ventilator screens.

The main questions it aims to answer are:

Does the Digital Twin display lower the cognitive stress (mental workload) experienced by clinicians during a crisis? Does the Digital Twin display reduce the time it takes for clinicians to identify specific respiratory complications? Does the use of real-time physiological visualization improve the accuracy of clinical decision-making? Researchers will compare the performance of clinicians using a standard ventilator display (the "Black Box" condition) to their performance when provided with an additional synchronized 3D lung and advanced waveform display (the "Digital Twin" condition).

Participants will:

Complete four randomized mechanical ventilation crisis scenarios using a high-fidelity lung simulator (ASL 5000).

Manage scenarios involving high airway resistance, low lung compliance, auto-PEEP, and patient-ventilator asynchrony.

Undergo a 14-day "washout" period between sessions to ensure no memory bias between the control and intervention groups.

Complete a NASA-TLX survey after each scenario to measure their perceived mental, physical, and temporal demand.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.