Automatic Adjustment for Asynchronies During Mechanical Ventilation

NCT ID: NCT06295237

Last Updated: 2025-03-07

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

TERMINATED

Clinical Phase

NA

Total Enrollment

30 participants

Study Classification

INTERVENTIONAL

Study Start Date

2024-02-15

Study Completion Date

2024-12-15

Brief Summary

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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

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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.

Conditions

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Mechanical Ventilation Complication

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

CROSSOVER

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.
Primary Study Purpose

TREATMENT

Blinding Strategy

SINGLE

Outcome Assessors
Anonymized evaluation

Study Groups

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Standard of Care

Optimized ventilator settings to control and reduce the number of asynchronies

Group Type NO_INTERVENTION

No interventions assigned to this group

Activated automatic detection and adjustment of asynchronies

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

Group Type ACTIVE_COMPARATOR

Intellisync+

Intervention Type DEVICE

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

Interventions

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Intellisync+

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

Intervention Type DEVICE

Eligibility Criteria

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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)
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Fundación de Investigación Biomédica - Hospital Universitario de La Princesa

OTHER

Sponsor Role collaborator

Hospital San Carlos, Madrid

OTHER

Sponsor Role lead

Responsible Party

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Miguel Sanchez Garcia

Director Critical Care Department

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Miguel Sanchez-Garcia, MD

Role: STUDY_CHAIR

Hospial Clinico San Carlos

Locations

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Hospital Clinico San Carlos

Madrid, Madrid, Spain

Site Status

Countries

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Spain

Other Identifiers

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i-Sync

Identifier Type: -

Identifier Source: org_study_id

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