Diaphragmatic Ultrasound to Predict NIV Outcome in Patients With De-novo ARF

Over the last two decades, non-invasive ventilation (NIV) has been widely reported as an effective method to avoid the need of endotracheal intubation (ETI) and improve survival in the acute care setting. Given the risks associated with either premature NIV discontinuation or delays in NIV interruption, evaluating readiness to weaning from NIV is a critical challenge in patients with Acute Respiratory Failure (ARF). Up to date, bedside measurements used to predict NIV outcomes are extremely limited. NIV weaning as well as decision of ETI are mainly supported by clinical and physiologic parameters. More sophisticated techniques used to predict weaning outcome during spontaneous breathing trials have never achieved a bedside broad-spectrum use due to their invasiveness, the inconsistent results in demonstrating reproducible outcomes, the requirements of additional trainee personnel and complicated equipment, and the difficult application in awake and non-intubated patients. Recently, ultrasound has been used for the rapid assessment of diaphragm function in acutely ill patients. The advantages of the ultrasound in detecting diaphragm dysfunction as compared with other techniques are the less invasiveness, the avoidance of radiation hazards and the bedside feasibility. Direct imaging of changes in diaphragm thickening (DT) during spontaneous breathing may provide the assessment of both the muscle and the respiratory pump functioning. Indeed, DT has been correlated with the diaphragm strength and the muscle shortening. The volume of diaphragm muscle mass remains constant while it contracts. Consequently, as the muscle shortens it thickens itself and measurements of changes in such a thickening (DT) are inversely related to changes in diaphragm length. Studies in patients with diaphragm paralysis have confirmed the absence of DT. Moreover, since the diaphragm is the major muscle of inspiration, the presence of diaphragm shortening and contraction may predict successful