Post analysis simulated correlation of the El-Ganzouri airway difficulty score with difficult airway

Ruggero M. Corso; Davide Cattano; Matteo Buccioli; Elisa Carretta; Stefano Maitan

doi:10.1016/j.bjane.2014.09.003

Scientific Article

Post analysis simulated correlation of the El-Ganzouri airway difficulty score with difficult airway

Correlação simulada após análise dos escores de El-Ganzouri para via aérea difícil

Ruggero M. Corso; Davide Cattano; Matteo Buccioli; Elisa Carretta; Stefano Maitan

http://dx.doi.org/10.1016/j.bjane.2014.09.003 Braz J Anesthesiol, vol.66, n3, p.298-303, 2016

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Abstract

ABSTRACT BACKGROUND: Difficult airway (DA) occurs frequently (5-15%) in clinical practice. The El-Ganzouri Risk Index (EGRI) has a high sensitivity for predicting a difficult intubation (DI). However difficult mask ventilation (DMV) was never included in the EGRI. Since DMV was not included in the EGRI assessment, and obstructive sleep apnea (OSA) is also correlated with DMV, a study correlating the prediction of DA and OSA (identified by STOP-Bang questionnaire, SB) seemed important. METHODS: We accessed a database previously collected for a post analysis simulation of the airway difficulty predictivity of the EGRI, associated with normal and difficult airway, particularly DMV. As secondary aim, we measured the correlation between the SB prediction system and DA, compared to the EGRI. RESULTS: A total of 2747 patients were included in the study. The proportion of patients with DI was 14.7% (95% CI 13.4-16) and the proportion of patients with DMV was 3.42% (95% CI 2.7-4.1). The incidence of DMV combined with DI was (2.3%). The optimal cutoff value of EGRI was 3. EGRI registered also an higher ability to predict DMV (AUC = 0.76 (95% CI 0.71-0.81)). Adding the SB variables in the logistic model, the AUC increases with the inclusion of "observed apnea" variable (0.83 vs. 0.81, p = 0.03). The area under the ROC curve for the patients with DI and DMV was 0.77 (95% CI 0.72-0.83). CONCLUSIONS: This study confirms that the incidence of DA is not negligible and suggests the use of the EGRI as simple bedside predictive score to improve patient safety.

Keywords

Difficult airway, Predictive score, Sleep apnea

Resumo

RESUMO JUSTIFICATIVA: A via aérea difícil (VAD) ocorre com frequência (5-15%) na prática clínica. O Índice de Risco de El-Ganzouri (EGRI) tem uma alta sensibilidade para prever intubação difícil (ID). No entanto, a ventilação difícil via máscara (VDM) nunca foi incluída no EGRI. Como a VDM não foi incluída na avaliação EGRI e a apneia obstrutiva do sono (AOS) também está correlacionada com a VDM, um estudo que correlacionasse a previsão da VAD e AOS (identificada pelo questionário STOP-Bang, SB) pareceu importante. MÉTODOS: Acessamos um banco de dados previamente coletados para simular uma análise posterior da previsibilidade do EGRI para via aérea difícil, associado à via aérea normal e difícil, particularmente VDM. Como objetivo secundário, avaliamos a correlação entre o sistema de previsão do SB e da VAD, em comparação com o EGRI. RESULTADOS: Foram incluídos no estudo 2.747 pacientes. A proporção de pacientes com ID foi de 14,7% (IC de 95%; 13,4-16) e a proporção de pacientes com VDM foi de 3,42% (IC de 95% 2,7-4,1). A incidência da VDM combinada com a de ID foi de 2,3%. O valor de corte ideal do EGRI foi 3. EGRI também registrou uma capacidade maior de prever VDM (ASC = 0,76 (IC de 95%; 0,71-0,81)). Ao somar as variáveis do SB no modelo logístico, a ASC aumenta com a inclusão da variável "apneia observada" (0,83 vs. 0,81, p = 0,03). A área sob a curva ROC para os pacientes com ID e VDM foi de 0,77 (IC de 95%; 0,72-0,83). CONCLUSÕES: Este estudo confirma que a incidência de VAD não é desprezível e sugere o uso do EGRI como um escore de cabeceira preditivo simples para melhorar a segurança do paciente.

Palavras-chave

Via aérea difícil, Escore preditivo, Apneia do sono

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Post analysis simulated correlation of the El-Ganzouri airway difficulty score with difficult airway

Correlação simulada após análise dos escores de El-Ganzouri para via aérea difícil

Ruggero M. Corso; Davide Cattano; Matteo Buccioli; Elisa Carretta; Stefano Maitan

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