Development of an accurate bedside swallowing evaluation decision tree algorithm for detecting aspiration in acute respiratory failure survivors.
The bedside swallowing evaluation (BSE) is an assessment of swallowing function and airway safety during swallowing. After extubation, the BSE is often used to identify the risk of aspiration in acute respiratory failure (ARF) survivors.We conducted a multi-center prospective study of ARF survivors to determine the accuracy of the BSE and to develop a decision tree algorithm to identify aspiration risk.and Methods: Patients extubated after ≥48 hours of mechanical ventilation were eligible. Study procedures included the BSE followed by a gold-standard evaluation, the flexible endoscopic evaluation of swallowing (FEES).Overall, 213 patients were included in the final analysis. Median time from extubation to BSE was 25 hours (interquartile range=21-45 hours). FEES was completed 1 hour after the BSE (interquartile range=0.5-2 hours). A total of 33% (70/213, 95%CI=26.6-39.2%) of patients aspirated on at least one FEES bolus consistency test. Thin liquids were the most commonly aspirated consistency; 27% (54/197, 95%CI =21-34%). The BSE detected any aspiration with an accuracy of 52% (95%CI =45-58%), a sensitivity of 83% (95%CI =74-92%), and negative predictive value of 81% (95%CI=72-91%). Using recursive partitioning analyses, a five variable BSE-based decision tree algorithm was developed that improved the detection of aspiration with an accuracy of 81% (95%CI=75-87%), sensitivity of 95% (95%CI =90-98%), and negative predictive value of 97% (95%CI =95-99%).The BSE demonstrates variable accuracy to identify patients at high risk for aspiration. Our decision tree algorithm may enhance the BSE and be used to identify patients at high risk for aspiration yet requires further validation.