Marc Moss1, S David White2, Heather Warner3, Daniel Dvorkin4, Daniel Fink5, Stephanie Gomez-Taborda6, Carrie Higgins7, Gintas P Krisciunas8, Joseph E Levitt9, Jeffrey McKeehan7, Edel McNally10, Alix Rubio6, Rebecca Scheel11, Jonathan M Siner12, Rosemary Vojnik9, Susan E Langmore13. 1. Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Denver, Aurora, CO. Electronic address: marc.moss@CUAnschutz.edu. 2. University of Colorado Denver Rehabilitation Therapy Services, University of Colorado Hospital, Aurora, CO. 3. Section of Otolaryngology, Department of Surgery, Yale School of Medicine, New Haven, CT; Department of Communication Disorders, Southern Connecticut State University, New Haven, CT. 4. Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Denver, Aurora, CO; The Bioinformatics CRO, Inc, Niceville, FL. 5. Department of Otolaryngology, University of Colorado School of Medicine, Aurora, CO. 6. Department of Otolaryngology, Boston Medical Center, Boston, MA. 7. Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Denver, Aurora, CO. 8. Department of Otolaryngology, Boston Medical Center, Boston, MA; Department of Otolaryngology, Boston University School of Medicine, Boston, MA. 9. Division of Pulmonary and Critical Care, Stanford University, Stanford, CA. 10. Department of Otolaryngology, Boston Medical Center, Boston, MA; Sargent College of Health and Rehabilitation Sciences, Boston University, Boston, MA. 11. Sargent College of Health and Rehabilitation Sciences, Boston University, Boston, MA; Division of Speech Language Pathology, Massachusetts General Hospital, Boston, MA. 12. Section of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, CT. 13. Department of Otolaryngology, Boston Medical Center, Boston, MA; Department of Otolaryngology, Boston University School of Medicine, Boston, MA; Sargent College of Health and Rehabilitation Sciences, Boston University, Boston, MA.
Abstract
BACKGROUND: The bedside swallowing evaluation (BSE) is an assessment of swallowing function and airway safety during swallowing. After extubation, the BSE often is used to identify the risk of aspiration in acute respiratory failure (ARF) survivors. RESEARCH QUESTION: We conducted a multicenter prospective study of ARF survivors to determine the accuracy of the BSE and to develop a decision tree algorithm to identify aspiration risk. STUDY DESIGN 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). RESULTS: Overall, 213 patients were included in the final analysis. Median time from extubation to BSE was 25 hours (interquartile range, 21-45 hours). The 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 (NPV) 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 NPV of 97% (95% CI, 95%-99%). INTERPRETATION: The BSE demonstrates variable accuracy to identify patients at high risk for aspiration. Our decision tree algorithm may enhance the BSE and may be used to identify patients at high risk for aspiration, yet requires further validation. TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT02363686; URL: www.clinicaltrials.gov.
BACKGROUND: The bedside swallowing evaluation (BSE) is an assessment of swallowing function and airway safety during swallowing. After extubation, the BSE often is used to identify the risk of aspiration in acute respiratory failure (ARF) survivors. RESEARCH QUESTION: We conducted a multicenter prospective study of ARF survivors to determine the accuracy of the BSE and to develop a decision tree algorithm to identify aspiration risk. STUDY DESIGN 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). RESULTS: Overall, 213 patients were included in the final analysis. Median time from extubation to BSE was 25 hours (interquartile range, 21-45 hours). The 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 (NPV) 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 NPV of 97% (95% CI, 95%-99%). INTERPRETATION: The BSE demonstrates variable accuracy to identify patients at high risk for aspiration. Our decision tree algorithm may enhance the BSE and may be used to identify patients at high risk for aspiration, yet requires further validation. TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT02363686; URL: www.clinicaltrials.gov.
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