This thesis focuses on predicting weaning failure from mechanical ventilation in critically ill patients using a combination of respiratory muscle strength, airway occlusion pressure at 100 milliseconds (P0.1), and lung ultrasound score (LUS). Weaning from mechanical ventilation is a critical process in intensive care units (ICUs), where both premature and delayed extubation can lead to serious complications, including diaphragm dysfunction, ventilator-associated pneumonia, and airway trauma.

The study builds on prior research that has established the utility of different physiological markers in predicting weaning outcomes. The LUS, developed by Bouhemad et al., assesses lung aeration and has been shown to be an effective predictor of post-extubation distress. Similarly, diaphragmatic thickness and thickening fraction (DTF) have been linked to successful weaning. The P0.1 index, which measures central respiratory drive, has also been found to predict extubation success.

This observational study, conducted in a critical care unit, aims to integrate these parameters to improve the accuracy of weaning predictions. It involves assessing patients undergoing spontaneous breathing trials (SBT) through bedside ultrasonography, lung ultrasound, and respiratory drive monitoring. The study population includes critically ill patients eligible for weaning after at least 48 hours of mechanical ventilation, with specific inclusion and exclusion criteria to ensure valid results.

The methodology involves measuring LUS, diaphragmatic and intercostal muscle thickness, and P0.1 during the SBT, followed by statistical analysis to determine their predictive power. Ethical considerations include obtaining informed consent and ensuring patient safety.

The expected outcome is that the combined assessment of these physiological markers will provide a more reliable predictor for weaning success, reducing re-intubation rates and improving patient outcomes in the ICU.