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Research Article on Children with Sleep Disorders

Wednesday 21, Oct 2020

Predicting Perioperative Respiratory Adverse Events in Children With Sleep-Disordered Breathing

Carolyne Pehora 1, David Faraoni 1 2, Soichiro Obara 3, Reshma Amin 4, Brenda Igbeyi 5, Adel Al-Izzi 6, Aman Sayal 4, Aarti Sayal 4, Conor Mc Donnell 1 2

Affiliations expand

· PMID: 33002926

· DOI: 10.1213/ANE.0000000000005195


Background: No evidence currently exists to quantify the risk and incidence of perioperative respiratory adverse events (PRAEs) in children with sleep-disordered breathing (SDB) undergoing all procedures requiring general anesthesia. Our objective was to determine the incidence of PRAEs and the risk factors in children with polysomnography-confirmed SDB undergoing procedures requiring general anesthesia.


Retrospective review of all patients with polysomnography-confirmed SDB undergoing general anesthesia from January 2009 to December 2013. Demographic and perioperative outcome variables were compared between children who experienced PRAEs and those who did not. Generalized estimating equations were used to build a predictive model of PRAEs.


In a cohort of 393 patients, 51 PRAEs occurred during 43 (5.6%) of 771 anesthesia encounters. Using generalized estimating equations, treatment with continuous positive airway pressure or bilevel positive airway pressure (odds ratio, 1.63; 95% confidence interval [CI], 1.05-2.54; P = .031), outpatient (odds ratio, 1.37; 95% CI, 1.03-1.91; P = .047), presence of severe obstructive sleep apnea (odds ratio, 1.63; 95% CI, 1.09-2.42; P = .016), use of preoperative oxygen (odds ratio 1.82; 95% CI, 1.11-2.97; P = .017), history of prematurity (odds ratio, 2.31; 95% CI, 1.33-4.01; P = .003), and intraoperative airway management with endotracheal intubation (odds ratio, 3.03; 95% CI, 1.79-5.14; P < .001) were associated with PRAEs.


We propose the risk factors identified within this cohort of SDB patients could be incorporated into a preoperative risk assessment tool that might better to identify the risk of PRAE during general anesthesia. Further investigation and validation of this model could contribute to improved preoperative risk stratification, decision-making (postoperative admission and level of monitoring), and health care resource allocation.