Identification of the risk factors in perioperative respiratory adverse events in children under general anesthesia and the development of a predictive model

Background: This study explored the risk factors of perioperative respiratory adverse events in children under 12 years old undergoing general anesthesia surgery. A prediction model was constructed according to the related risk factors to provide a basis for timely clinical intervention and decision-making. Methods: Children under 12 years old who underwent general anesthesia in our hospital between January 2016 and December 2020 were included in this study. The clinical data, including age, gender, weight, American Society of Anesthesiologists (ASA) grade classification, operation season, preoperative hospital stay, anesthesia time, and postoperative pain score, were collated. Continuous variables were converted to categorical variables. Logistic regression analysis was used to screen independent risk factors and a nomogram was constructed to predict the probability of adverse events. Fitting curves and receiver operating characteristic (ROC) curves were utilized to verify the model. Results: Logistic regression analyses demonstrated that age [odds ratio (OR) =1.32, 95% confidence interval (CI): 1.08 to 1.49], body weight (OR =1.49, 95% CI: 1.21 to 1.84), anesthesia time (OR =1.61, 95% CI: 1.32 to 1.78), and surgery season (OR =1.12, 95% CI: 1.07 to 1.39) were independent risk factors for respiratory adverse events in children undergoing general anesthesia (P<0.05). The risk of respiratory related adverse events increased in children with grade II ASA classification compared to children with grade I ASA classification (P<0.05). Similarly, the risk of respiratory adverse events increased in children with level III pain scores compared to children with level I pain scores (P<0.05). The calibration curve showed that the predicted curve was consistent with the actual curve. The area under the ROC curve (AUC) was 0.707, indicating that model showed great predictive ability. Conclusions: Age, weight, anesthesia time, operation season, ASA grade, and pain score were identified as independent risk factors for respiratory adverse events in children undergoing general anesthesia. Using the above risk factors, a nomogram was established to predict the risk of respiratory system-related adverse events. The predicted results were highly consistent with the actual risk, and the false positive rate was within a reasonable range.