Clinical utility of diaphragmatic ultrasonography for mechanical ventilator weaning in adults: A study protocol for systematic review and meta‐analysis

Abstract Background and Aims Mechanical ventilation is associated with several risks, including barotrauma, ventilator‐associated pneumonia, and ventilator‐induced diaphragmatic dysfunction. A delay in weaning from mechanical ventilation increases these risks, and prolonged weaning has been shown to increase hospital mortality. Various tools have been used in clinical practice to predict successful weaning from mechanical ventilation; however, they have a low prognostic accuracy. The use of ultrasonography in intensive care units is an area of growing interest since it is a noninvasive, convenient, and safe modality. Since ultrasonography can provide real‐time assessment of diaphragmatic morphology and function, it may have clinical utility in predicting successful mechanical ventilator weaning. This study aimed to describe a protocol to assess the effectiveness of diaphragmatic ultrasonography in the decision‐making process for ventilator weaning in terms of its impact on clinical outcomes. Methods This systematic review of published analytical research will use an aggregative thematic approach according to the Preferred Reporting Items for Systematic Review and Meta‐Analysis Protocols guidelines. We will perform a comprehensive search for studies on the MEDLINE, Embase, and Cochrane Central Register of Controlled Trials databases. Two authors will independently perform abstract and full‐text screening and data extraction. Additionally, a meta‐analysis and the risk of bias evaluation will be conducted, as appropriate. Conclusion Systematic reviews on the effectiveness of diaphragmatic ultrasonography in the decision‐making process for ventilator weaning in terms of its impact on clinical outcomes are lacking. The results of this systematic review may serve as a basis for future clinical trials. Systematic review registration: This protocol was registered with the Open Science Framework: https://osf.io/cn8xf .