Bedside predictors of difficult intubation: A systematic review

Andrea Vannucci, Laura F. Cavallone

Research output: Contribution to journalReview articlepeer-review

68 Scopus citations

Abstract

BACKGROUND: Unanticipated difficult intubation is associated with unwanted patient outcomes. The capability of predicting difficult airways may contribute to patient safety, efficient patient flow and rational use of limited resources. We evaluated current literature on performance of bedside airway tests in predicting difficult tracheal intubation. METHODS: Eligibility criteria were: prospective clinical studies; adult population of least 100 subjects; accepted definition of difficult intubation; direct laryngoscopy approach; true positive, false negative, false positive and true negative either reported or inferred. Medline and EMBASE database were searched for the following terms: "predictors", "prediction" and "risk factors" of "difficult intubation", "difficult laryngoscopy" and "difficult airway". The publication dates considered for the search were January 1st 2004 to March 31st 2014. Risk of bias was assessed according to QUADAS-2 criteria. RESULTS: Twenty-four studies involving 20,582 patients and consistent with eligibility criteria were included. Numerous airways screening tests were evaluated. The most frequently performed tests were: Mallampati Score, measurement of thyro-mental distance, upper lip bite test, inter-incisors gap, and sterno-mental distance. Assessed individual and combined tests are characterized by limited discriminative capacity, sensitivity, specificity, and positive likelihood ratio. CONCLUSION: Current bedside tests have limited and inconsistent capacity to discriminate between patients with difficult and easy airways. Most studies are characterized by high risk of bias and concerns of applicability. Reliable bedside criteria to predict difficult intubation remain elusive.

Original languageEnglish
Pages (from-to)69-83
Number of pages15
JournalMinerva anestesiologica
Volume82
Issue number1
StatePublished - Jan 2016

Keywords

  • Airway management
  • Intubation, intratracheal
  • Statistics and numerical data

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