Incidence and risk factors of perioperative respiratory adverse events in pediatric surgical patients: Development and validation of a predictive model in Brazil.

Sirtoli, Isabela S; Castro, Stela J; Neto, Paulo C S; Pando, Cleiton; Mendanha, Clarissa; Scorsatto, Raissa M; Stefani, Luciana C · PLoS One · 2026

prospective_cohort · Level II

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Abstract

Enhancing the safety of paediatric patients undergoing surgery is crucial, particularly in settings with limited resources and fragmented health systems. This study focused on investigating perioperative respiratory adverse events in Brazil. To determine the incidence and associated risk factors of perioperative respiratory adverse events in pediatric surgical patients, and develop a predictive model to improve bedside decision. Observational cohort study. Two high complexity public teaching hospitals in Southern Brazil. Patients under 16 years undergoing elective or nonelective procedures between August 2020 and February 2022. The primary outcome was perioperative respiratory adverse events. Patients were prospectively followed during surgery and recovery stay. Preoperative data were collected through interviews with parents and legal guardians, and multilevel logistic regression models were used for analysis. Among 1339 children, 214 (15.9%) experimented perioperative respiratory adverse events. Desaturation was the most frequent respiratory complication, occurring in 111 children (8.3%), followed by laryngospasm (84, 6.3%). The final risk model exhibited good discrimination with an AUROC of 0.71 (95% CI 0.68-0.75) and had superior accuracy (AUROC, 0.69 vs. 0.62; p = 0.004) compared to the COLDS score in patients under 6 years. Variables included in the model were age < 1 year, current upper respiratory infection, history of prematurity, lung or airway disease, and the interaction between tracheal intubation and airway surgery. The study identifies a high incidence of perioperative respiratory adverse events (PRAE) in Brazilian pediatric surgical patients and key risk factors. A novel risk prediction model for children under 16 outperforms existing tools. These findings are vital for resource-limited settings. Future research should validate these results in varied healthcare contexts, develop targeted interventions, and assess the model clinical effectiveness to enhance pediatric surgical care and patient safety. Study registration: UTN code U1111-1274-8584.

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