Development of an Accurate Bedside Swallowing Evaluation Decision Tree Algorithm for Detecting Aspiration in Acute Respiratory Failure Survivors
Moss M, White SD, Warner H, Dvorkin D, Fink D, Gomez-Taborda S, Higgins C, Krisciunas GP, Levitt JE, McKeehan J, McNally E, Rubio A, Scheel R, Siner JM, Vojnik R, Langmore SE. Development of an Accurate Bedside Swallowing Evaluation Decision Tree Algorithm for Detecting Aspiration in Acute Respiratory Failure Survivors. CHEST Journal 2020, 158: 1923-1933. PMID: 32721404, PMCID: PMC7674978, DOI: 10.1016/j.chest.2020.07.051.Peer-Reviewed Original ResearchConceptsAcute respiratory failure survivorsNegative predictive valueHigh riskMulticenter prospective studyRisk of aspirationFlexible endoscopic evaluationRecursive partitioning analysisDetection of aspirationARF survivorsEndoscopic evaluationAirway safetyMechanical ventilationMedian timeAspiration riskProspective studyPatientsPredictive valueStudy designFinal analysisStudy proceduresGold standard evaluationSurvivorsThin liquidsExtubationPartitioning analysis