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


Journal

Anesthesia and analgesia
ISSN: 1526-7598
Titre abrégé: Anesth Analg
Pays: United States
ID NLM: 1310650

Informations de publication

Date de publication:
01 04 2021
Historique:
pubmed: 2 10 2020
medline: 7 4 2021
entrez: 1 10 2020
Statut: ppublish

Résumé

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.

Sections du résumé

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.
METHODS
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.
RESULTS
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.
CONCLUSIONS
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.

Identifiants

pubmed: 33002926
pii: 00000539-202104000-00020
doi: 10.1213/ANE.0000000000005195
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1084-1091

Informations de copyright

Copyright © 2020 International Anesthesia Research Society.

Déclaration de conflit d'intérêts

The authors declare no conflicts of interest.

Références

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Auteurs

Carolyne Pehora (C)

From the Department of Anesthesia and Pain Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.

David Faraoni (D)

From the Department of Anesthesia and Pain Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.
Department of Anesthesiology & Pain Medicine, University of Toronto, Toronto, Ontario, Canada.

Soichiro Obara (S)

Department of Anesthesia, Teikyo University Graduate School of Public Health, Tokyo, Japan.

Reshma Amin (R)

Division of Respiratory Medicine, Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.

Brenda Igbeyi (B)

Department of Family Medicine, Labrador South Health Centre, Labrador-Grenfell Regional Health, Forteau, Newfoundland, Canada.

Adel Al-Izzi (A)

Department of Critical Care Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.

Aman Sayal (A)

Division of Respiratory Medicine, Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.

Aarti Sayal (A)

Division of Respiratory Medicine, Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.

Conor Mc Donnell (C)

From the Department of Anesthesia and Pain Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.
Department of Anesthesiology & Pain Medicine, University of Toronto, Toronto, Ontario, Canada.

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