Clinical trial Recruiting at 3 sites Interventional Ages 18 to 90

Using airway resistance changes to guide suctioning for ventilated patients

Official title: Mechanisms of Dynamic Airway Resistance Monitoring and Machine Learning for Assessing Pulmonary Inflammation and Guiding Sputum Suction in Mechanically Ventilated Patients

Run by Affiliated Hospital of Nantong University · NCT07375667 · Data updated 2026-11-12

This study will test whether monitoring airway viscous resistance from ventilator waveforms can help time sputum suctioning for patients on mechanical ventilation with ARDS, AECOPD, or severe pneumonia.

Quick facts

Study typeInterventional
Ages18 Years to 90 Years
SexAll
Enrollment258 (estimated)
SponsorAffiliated Hospital of Nantong University
Academic / other
Locations3 sites (Bengbu, Anhui and 2 other locations)
StatusRecruiting
StartedOctober 30, 2025
Main results expectedDecember 30, 2028
Study endsDecember 30, 2029
Registry record updatedJanuary 29, 2026
Trial IDNCT07375667 on ClinicalTrials.gov

Is this trial a fit for you?

Likely a good fit

Patients on invasive mechanical ventilation for ARDS, acute exacerbation of COPD, or severe pneumonia who meet ICU clinical criteria are the intended participants.

Probably not a fit

Patients with multiple organ failure or active multi-site bleeding (who are excluded) or those not on mechanical ventilation are unlikely to benefit from the intervention.

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

The trial continuously derives airway viscous resistance metrics from ventilator waveforms and compares dynamic patterns to conventional suctioning schedules. It correlates changes in viscous resistance with inflammatory biomarkers over time to explore temporal relationships. The team aims to establish reference thresholds for special populations and to validate the feasibility and reliability of resistance-based monitoring. Data will be collected at multiple tertiary hospitals in China and used to inform optimal suctioning timing.

Why it matters

Potential benefit: If successful, this approach could reduce pulmonary inflammation and complications by prompting suctioning at more precise times, potentially lowering ventilator-associated pneumonia rates and improving recovery.

How similar studies have gone: Previous work supports that timely suctioning improves outcomes, but using ventilator-derived viscous resistance and machine-learning guidance is a novel approach with limited prior clinical validation.

Who can join: the full rules

Show full inclusion / exclusion criteria
Inclusion Criteria:

* Clinical diagnosis of Acute Respiratory Distress Syndrome (ARDS)
* Clinical diagnosis of Acute Exacerbation of Chronic Obstructive Pulmonary Disease (AECOPD)
* Clinical diagnosis of Severe pneumonia

Exclusion Criteria:

* Clinical diagnosis of multiple organ failure;
* Clinical diagnosis of multiple organ bleeding;

Where it's running

  • The First Affiliated Hospital of Bengbu Medical University
    Bengbu, Anhui, China
    Recruiting
  • Peking Union Medical College Hospital
    Beijing, Beijing Municipality, China
    Recruiting
  • the Second Affiliated Hospital of Zhejiang University School of Medicine
    Hangzhou, Zhejiang, China
    Recruiting

Study contacts

Similar studies

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How to take part

  1. Review the eligibility criteria above with your treating physician.
  2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
  3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.
Last reviewed 2026-11-14 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.