Sherri L Katz1,2,3,4, Andrea Monsour5, Nicholas Barrowman2,3, Lynda Hoey2, Matthew Bromwich1,2,3, Franco Momoli2,4, Theodora Chan6, Reuben Goldberg3, Abhilasha Patel3, Li Yin3, Kimmo Murto2,3,7. 1. Children's Hospital of Eastern Ontario, Department of Pediatrics, Ottawa, Ontario, Canada. 2. Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada. 3. University of Ottawa, Faculty of Medicine, Ottawa, Ontario, Canada. 4. University of Ottawa, School of Epidemiology and Public Health, Ottawa, Ontario, Canada. 5. Child Health Evaluative Sciences, The Hospital for Sick Children Research Institute, Toronto, Ontario, Canada. 6. McMaster University, School of Physiotherapy, Hamilton, Ontario, Canada. 7. Children's Hospital of Eastern Ontario, Department of Anesthesia, Ottawa, Ontario, Canada.
Abstract
STUDY OBJECTIVES: Obstructive sleep apnea (OSA) is commonly treated with adenotonsillectomy (AT), bringing risk of perioperative respiratory adverse events (PRAEs). We aimed to concurrently identify clinical and polysomnographic predictors of PRAEs in children undergoing AT. METHODS: Retrospective study of children undergoing AT at a tertiary-care pediatric hospital, with prior in-hospital polysomnography, January 2010 to December 2016. PRAEs included those requiring oxygen, jaw thrust, positive airway pressure, or mechanical ventilation. Relationships of PRAEs to preoperative comorbidities or polysomnography results were examined with univariable logistic regression. Variables with P < .1 and age were included in backward stepwise multivariable logistic regression. Predictive performance (area under the curve, AUC) was validated with bootstrap resampling. RESULTS: Analysis included 374 children, median age 6.1 years; 286 (76.5%) had ≥ 1 comorbidity. 344 (92.0%) had sleep-disordered breathing; 232 (62.0%) moderate-severe; 66 (17.6%) had ≥ 1 PRAE. PRAEs were more frequent in children with craniofacial, genetic, cardiac, airway anomaly, or neurological conditions, AHI ≥ 5 events/h and oxygen saturation nadir ≤ 80% on preoperative polysomnography. Prediction modeling identified cardiac comorbidity (odds ratio [OR] 2.09 [1.11, 3.89]), airway anomaly (OR 3.19 [1.33, 7.49]), and younger age (OR < 3 years: 4.10 (1.79, 9.26; 3 to 6 years: 2.21 [1.18, 4.15]) were associated with PRAEs (AUC 0.74; corrected AUC 0.68). CONCLUSIONS: Prediction modeling concurrently evaluating comorbidities and polysomnography metrics identified cardiac disease, airway anomaly, and young age as independent predictors of PRAEs. These findings suggest that medical comorbidity and age are more important factors in predicting PRAEs than PSG metrics in a medically complex population.
STUDY OBJECTIVES: Obstructive sleep apnea (OSA) is commonly treated with adenotonsillectomy (AT), bringing risk of perioperative respiratory adverse events (PRAEs). We aimed to concurrently identify clinical and polysomnographic predictors of PRAEs in children undergoing AT. METHODS: Retrospective study of children undergoing AT at a tertiary-care pediatric hospital, with prior in-hospital polysomnography, January 2010 to December 2016. PRAEs included those requiring oxygen, jaw thrust, positive airway pressure, or mechanical ventilation. Relationships of PRAEs to preoperative comorbidities or polysomnography results were examined with univariable logistic regression. Variables with P < .1 and age were included in backward stepwise multivariable logistic regression. Predictive performance (area under the curve, AUC) was validated with bootstrap resampling. RESULTS: Analysis included 374 children, median age 6.1 years; 286 (76.5%) had ≥ 1 comorbidity. 344 (92.0%) had sleep-disordered breathing; 232 (62.0%) moderate-severe; 66 (17.6%) had ≥ 1 PRAE. PRAEs were more frequent in children with craniofacial, genetic, cardiac, airway anomaly, or neurological conditions, AHI ≥ 5 events/h and oxygen saturation nadir ≤ 80% on preoperative polysomnography. Prediction modeling identified cardiac comorbidity (odds ratio [OR] 2.09 [1.11, 3.89]), airway anomaly (OR 3.19 [1.33, 7.49]), and younger age (OR < 3 years: 4.10 (1.79, 9.26; 3 to 6 years: 2.21 [1.18, 4.15]) were associated with PRAEs (AUC 0.74; corrected AUC 0.68). CONCLUSIONS: Prediction modeling concurrently evaluating comorbidities and polysomnography metrics identified cardiac disease, airway anomaly, and young age as independent predictors of PRAEs. These findings suggest that medical comorbidity and age are more important factors in predicting PRAEs than PSG metrics in a medically complex population.
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