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Speckle Tracking Echocardiography for the Prediction of Weaning Failure

Combined Thoracic Ultrasound Using Speckle Tracking for the Prediction of Weaning Failure : a Prospective Multicenter Study

Status
Recruiting
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT03657524
Enrollment
110
Registered
2018-09-05
Start date
2019-05-20
Completion date
2026-05-21
Last updated
2026-02-12

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

Conditions

Weaning Failure of Mechanical Ventilation

Brief summary

Deciding the optimal timing for extubation in patients who are mechanically ventilated can be challenging, and traditional weaning predictor tools are not accurate. Recent studies suggest that isolated sonographic assessment of the respiratory and cardiac function (ie diastolic function and filling pressure), in mechanically ventilated patients may assist in identifying patients at risk of weaning failure. Recently, the association of conventional echocardiography and lung ultrasound showed promising results for the prediction of post extubation distress. Speckle Tracking is an emerging tool in intensive care medicine that has never been investiguated for the prediction of weaning failure. It could early detects diastolic dysfunction and and elevated filling pressure. Of more, speckle tracking is known to be less operator dependant. The main objective of our study is to evaluate the diagnosis accuracy of speckle tracking echocardiography performed during a weaning trial to predict weaning failure. The secondary objectives are to assess the diagnosis accuracy of combined heart and lung ultrasound to predict weaning failure.

Detailed description

Deciding the optimal timing for extubation in patients who are mechanically ventilated can be challenging, and traditional weaning predictor tools are not accurate. Recent studies suggest that isolated sonographic assessment of the respiratory and cardiac function (ie diastolic function and filling pressure), in mechanically ventilated patients may assist in identifying patients at risk of weaning failure. Recently, the association of conventional echocardiography and lung ultrasound showed promising results for the prediction of post extubation distress. Speckle Tracking is an emerging tool in intensive care medicine that has never been investiguated for the prediction of weaning failure. It could early detects diastolic dysfunction and and elevated filling pressure. Of more, speckle tracking is known to be less operator dependant. The main objective of our study is to evaluate the diagnosis accuracy of speckle tracking echocardiography performed during a weaning trial to predict weaning failure. The secondary objectives are to assess the diagnosis accuracy of combined heart and lung ultrasound to predict weaning failure.

Interventions

OTHERechocardiography

Speckle tracking echocardiography

Sponsors

Assistance Publique Hopitaux De Marseille
Lead SponsorOTHER

Study design

Allocation
NON_RANDOMIZED
Intervention model
PARALLEL
Primary purpose
OTHER
Masking
NONE

Eligibility

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

Inclusion criteria

\- Patients hospitalized in intensive care unit under mechanical fulfilling the criteria of ventilation weaning trial.

Exclusion criteria

* Less than 18 years old. * Pregnancy * Non sinusal cardiac rhythm * Neuro Myopathy * Tracheotomy * Lack of echogenicity to perform at least a four chamber apical view

Design outcomes

Primary

MeasureTime frameDescription
lung and heart ultrasoundsJust before and during the weaning trialArea under the receiver operator characteristic curve (AUC) of global longitudinal strain and strain rate variations (before and during a weaning trial) to predict weaning failure.

Countries

France

Contacts

CONTACTLaurent ZIELESKIEWICZ
laurent.zieleskiewicz@ap-hm.fr04 91 96 53 77
STUDY_DIRECTORJean-Olivier ARNAUD

Assistance Publique Hôpitaux de Marseille

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 13, 2026