Breathing variability predicts the suggested need for corrective intervention due to the perceived severity of patient-ventilator asynchrony during NIV

AbstractPatient-ventilator asynchrony is associated with intolerance to noninvasive ventilation (NIV) and worsened outcomes. Our goal was to develop a tool to determine a patient needs  for  intervention by a practitioner due to the presence of patient-ventilator asynchrony. We postulated that a clinician can determine when a patient needs corrective intervention due to the perceived severity of patient-ventilator asynchrony. We hypothesized a new measure, patient breathing vari ability, would indicate when corrective intervention is suggested by a bedside practitioner due to the perceived severity of patient-ventilator asynchrony. With IRB approval data was collected on 78 NIV patients. A panel of experts reviewed retrospective data from a development set of 10 NIV patient s to categorize them into one of the three categories. The three categories were; “No to mild asynchrony—no intervention needed”, “moderate asynchrony—non-emergent corrective intervention required”, and “severe asynchrony—immediate intervention required”. A stepwise regression with a F-test forward selection criterion was used to develop a positive linear logic model predicting the expert panel’s categorizations of the need for corrective intervention. The model was incorporated into a software tool for clinical implementation. The tool was implemented prospectively on 68 N IV patients simultaneous to a bedside practitioner scoring the need for corrective intervention due to the perce...

Source: Journal of Clinical Monitoring and Computing - October 28, 2019 Category: Information Technology Source Type: research