Ultrasound Assessment During Weaning from Mechanical Ventilation

This study is a multicenter, prospective, observational trial to develop an ultrasound-based predictive model for extubation failure in mechanically ventilated ICU patients. Extubation failure, defined as re-intubation or death within 48 hours post-extubation, remains a significant challenge, occurring in 15-35% of cases. Prolonged mechanical ventilation is associated with increased morbidity, infection risk, and hospital costs. Traditional predictors, such as maximal inspiratory pressure (Pimax), rapid shallow breathing index (RSBI or Tobin index), and other clinical parameters, have shown limited accuracy in identifying patients who are ready for extubation.

Recent advances in bedside ultrasound have allowed for the assessment of key physiological functions, such as pulmonary aeration, diaphragmatic function, and cardiac performance, offering a more comprehensive approach to predicting extubation outcomes. In this study, ultrasound will be used to evaluate the modified Lung Ultrasound Score (LUS) for lung aeration, diaphragm excursion, and thickening fraction (TFdi) for diaphragmatic function, and left ventricular diastolic function (E/e') to assess cardiac performance.

Study Procedures The study will include approximately 15 intensive care units (ICUs) across Argentina, Chile, Peru, Ecuador, Italy, Spain, the United States, and Canada. Ethical approval has been obtained from each participating institution. Adult patients (≥18 years) on invasive mechanical ventilation (MV) for at least 48 hours and ready to initiate a spontaneous breathing trial (SBT) will be eligible. Ultrasound assessments will be performed between 20 and 30 minutes after initiating the trial.

Key ultrasound measures include:

Pulmonary Ultrasound (LUS score): Evaluation of anterior and lateral lung regions to assess loss of lung aeration during the SBT.

Cardiac Ultrasound: Assessment of systolic function using mitral annular plane systolic excursion (MAPSE) and tricuspid annular plane systolic excursion (TAPSE) to evaluate right ventricular (RV) and left ventricular (LV) systolic function. Diastolic function will be measured through the E/e' ratio.

Diaphragm Ultrasound: Evaluation of diaphragmatic function through excursion and thickening fraction.

Data from these ultrasound assessments will be collected prospectively and entered into a centralized database. Each patient may be included in the study for multiple extubations if applicable.

Quality Assurance and Data Management

The study employs rigorous data collection and validation procedures, including:

A quality assurance plan that ensures data accuracy and completeness, including site monitoring and auditing.

Data validation checks to ensure consistency with predefined rules. Source data verification through comparison with external data sources, such as medical records and case report forms.

A data dictionary detailing each variable\'s definition, coding, and range, to ensure uniform data entry across all sites.

Standard operating procedures (SOPs) guide the processes of patient recruitment, data collection, and data management.

A sample size assessment determined that the trial requires a sufficient number of patients to ensure the detection of statistically significant differences in extubation outcomes. Additionally, a plan for managing missing data has been developed to address cases where information is unavailable or inconsistent.

Statistical Analysis The primary goal of this study is to create a predictive model for extubation failure, based on lung, diaphragm, and cardiac ultrasound parameters. The primary outcome is extubation failure, defined as the need for re-intubation or death within 48 hours. Secondary outcomes include the predictive performance of the model in patients not requiring preventive non-invasive ventilation (NIV) and in neurocritical patients.

The statistical analysis plan will incorporate both univariate and multivariate analyses to determine the predictive value of each ultrasound parameter. Cox proportional hazard models will be employed to assess time-to-event data, while logistic regression models will be used for binary outcomes such as extubation failure.

By combining these diverse ultrasound measurements, the study aims to provide a robust, non-invasive tool for predicting extubation success or failure, thereby enabling more personalized, evidence-based management of critically ill patients in the ICU.

Primary outcomes

• To develop a predictive model for extubation failure using lung ultrasound, echocardiography, and diaphragmatic parameters [The primary outcome assessment period comprises the first 48 hours after extubation.]: The primary objective of this study is to develop a predictive model for extubation failure by utilizing lung ultrasound, echocardiography, and diaphragmatic parameters. This model aims to improve the accuracy of identifying patients at risk of re-intubation or other complications after being taken off mechanical ventilation.

Secondary outcomes

• To assess the predictive accuracy of the ultrasound model in patients who do not require non-invasive ventilation as a preventive measure against failure [The evaluation period comprises the first 48 hours after extubation.]: This objective focuses on determining how accurately the ultrasound model can predict extubation failure in patients who are not considered to need non-invasive ventilation (NIV) as a preventive measure. The goal is to assess if the model can reliably identify patients at risk of failure, even when they are not typically considered high-risk based on clinical criteria.
• Evaluate the predictive performance of the ultrasound model in patients with indication for preventive non-invasive ventilation [The evaluation period comprises the first 48 hours after extubation.]: In this case, the study aims to determine how well the ultrasound model predicts extubation failure in patients who have been identified as needing non-invasive ventilation to prevent failure. The objective is to validate the model\'s usefulness in this higher-risk group, where preventive measures are already being considered.
• Examine the correlation between clinical criteria for preventive non-invasive ventilation and the ultrasound model's predictions [The evaluation period comprises the first 48 hours after extubation.]: This objective aims to explore the relationship between traditional clinical criteria used to prescribe non-invasive ventilation as a preventive measure and the predictions made by the ultrasound-based model. By comparing both approaches, the study will determine how closely they align and whether the model provides added value in decision-making
• Describe the proportion of extubation failure within 7 days after extubation [The evaluation period includes the first 7 days after extubation.]: This objective seeks to document how many patients experience extubation failure within the first 7 days post-extubation. Understanding this timeframe will provide insights into the critical period for monitoring patients and assessing the accuracy of the ultrasound model in predicting failure during this vulnerable period.

Sex: All, ages: 18 Years to any

Inclusion Criteria:

* Adult patients (18 years or older).
* Receiving mechanical ventilatory assistance for more than 48 hours.
* The patient is deemed ready to undergo a Spontaneous Breathing Trial, as determined by the attending physician.
* Ultrasound measurements are performed between 20 and 30 minutes after the initiation of the trial.

Exclusion Criteria:

* Patients with known or diagnosed neuromuscular disease.
* Limitation of therapeutic effort
* History of severe valvulopathy, severe coronary artery disease, known left ventricular ejection fraction \<35%, or known grade 3 diastolic dysfunction, or who are considered candidates for tracheostomy due to their severity.
* History of home ventilatory support
* Patients who do not have a good acoustic window or have any type of limitation to perform pulmonary, cardiac, or diaphragmatic ultrasound.
* Patients who at the discretion of the treating medical team cannot be placed on a T-tube.

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