Airway Abnormalities in Patients With Congenital Heart Disease: Incidence and Associated Factors

Objectives: Airway abnormalities complicate the perioperative course of patients with congenital heart disease (CHD), leading to significant morbidity and mortality. The literature describing airway abnormalities in those patients is scarce. This study aimed to determine the incidence of airway abnormalities in CHD patients and identify associated factors, genetic syndromes, and cardiac diagnoses. Design: Retrospective study conducted after institutional review board approval. Setting: Tertiary children's hospital. Participants: Patients presenting for cardiac diagnostic, interventional, or surgical procedures from 2012 to 2018. A total of 9,495 encounters were reviewed. Exclusion criteria: age >18 years. Methods/Interventions: Age, weight, sex, intubation technique, number of intubation attempts, and difficult intubation (DI) were recorded. Using the International Classification of Diseases, Ninth and Tenth Revisions codes, genetic syndromes, acquired and congenital airway abnormalities, and cardiac diagnoses were identified. Multivariate generalized estimating equations modeling was used to identify independent predictors of airway abnormalities. Results: A total of 4,797 patients, with 8,657 encounters were included. The median age was 1.3 years (interquartile range [IQR]: 0.2-6.0) and weight was 9.2 kg (IQR: 4.3-19.2), and 55% were male. A total of 16.7% had at least 1 genetic syndrome; 8.5% had congenital airway abnormalities and 9.7% acquired. Incidence of DI was 1.1%. The most common syndromes were Down, 22q11.2 microdeletion, and CHARGE. The most frequent congenital airway abnormalities were laryngomalacia and bronchomalacia, and the most frequent acquired were partial and total vocal cord paralysis. Conclusion: The likelihood of a coexistent airway abnormality should be considered in premature CHD patients, weight <10 kg, and in those with specific cardiac lesions and a concomitant genetic syndrome. Preoperative identification of patients at high risk of airway abnormalities is useful in planning their perioperative airway management. (C) 2020 Elsevier Inc. All rights reserved.