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Automatic Adjustment for Asynchronies During Mechanical Ventilation

Comparison of the Prevalence of Asynchronies During Mechanical Ventilation With Manual Versus Automatic Adjustment Ventilator Settings Using the INTELLISYNC+® (HAMILTON) Tool. A Randomized Controlled Study

Status
Terminated
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT06295237
Acronym
i-Sync
Enrollment
30
Registered
2024-03-06
Start date
2024-02-15
Completion date
2024-12-15
Last updated
2025-03-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Mechanical Ventilation Complication

Keywords

Asyncronies, Mechanical ventilation, Automatic detection and adjustment

Brief summary

Asynchronies between the patient and the artificial ventilator are a frequent problem. They may cause altered sleep, ventilator-induced lung injury, prolong length of ICU stay, cause neuro-psycologic complications and increase mortality. Although reducing their incidence through ventilator setting adjustments is possible, they frequently go undetected and it also requires that attendings remain at the bedside to repeatedly modify ventilator parameters. Ventilator systems may detect and automatically adjust parameters of mechanical ventilation. This would avoid delays in detection and adjustment if the intensivist is not immediately available. The investigators intend to study an automatic detection and adjustment tool which is incorporated in the ventilator software.

Detailed description

The prevalence and time course of asynchronies will be evaluated in subjects under invasive (n=40) or non-invasive (n=40) mechanical ventilation. Intensivist-optimized ventilator settings will be compared to a software tool (Hamilton ventilators, Intellisync+) in its capacity to control and adjust the triggering and cycling by analysis of the ventilator curves. The outcome variable is the percentage of the duration of asynchronies during the two 2-hour study periods. This pilot study has a prospective, randomized cross-over design. The order of the 2 study periods will be randomized to either start with control with manual adjustment or automated adjustment with Intellisync+. The total sample size is 80 subjects, 40 receiving invasive mechanical ventilation and 40 on non-invasive mechanical ventilation.

Interventions

DEVICEIntellisync+

mechanical ventilator software automatically detecting and adjusting ventilator parameters to control or reduce the number of events.

Sponsors

Fundación de Investigación Biomédica - Hospital Universitario de La Princesa
CollaboratorOTHER
Hospital San Carlos, Madrid
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
TREATMENT
Masking
SINGLE (Outcomes Assessor)

Masking description

Anonymized evaluation

Intervention model description

Two 2-hour periods: 1) off mode consisting of a control period with optimized ventilator parameters and 2) on mode with an active automated detection and adjustment for asynchronies. The starting first period is randomized.

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* Age \>17 years * Partial ventilatory support (SPONT mode) connected to Hamilton C1 model, irrespective of chronic restrictive or obstructive lung disease, categorized by RCexp (Expiratory time constant): restrictive (RCExp \<0.6); obstructive (RCExp \>0.9); normal (RCExp 0.6 - 0.9). * Software version SW3.0.0 or superior and the IntelliSync+ software tool available in invasive and non-invasive ventilation. * Presence of asyncronies in pressure and volume curves tracings of the ventilator. * Signed informed content.

Exclusion criteria

* Pregnant * On extracorporeal respiratory support (ECMO or ECCO2R)

Design outcomes

Primary

MeasureTime frameDescription
Duration of asyncroniestwo hours per study armduration of asyncronies expressed as percentage of time during the respective 2-hour study periods

Countries

Spain

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026