Background: Ex-premature infants have a high risk of postoperative apnea and bradycardia. This study aimed to develop a predictive model for postoperative desaturation and bradycardia in infants who underwent laparoscopic inguinal hernia repair (IHR) under general anesthesia based on identified risk factors.Methods: The retrospective cohort included infants who underwent laparoscopic IHR under general anesthesia at Severance Hospital in Korea between February 2013 and September 2019. Collected data included sex, gestational age (GA), postnatal age and post-conceptual age at surgery, birth weight, body weight at surgery, medical history and comorbidities, urgency of surgery, preoperative hemoglobin, anesthetic agents used, operation time, anesthesia time, intraoperative opioid dose, length of hospital stay, operation to discharge time, and postoperative ward. Feature selection was applied, and a machine learning model was developed to predict postoperative desaturation and bradycardia.Results: Three features for desaturation (cardiac comorbidities, GA, and body weight at surgery) and two features for bradycardia (GA and cardiac comorbidities) were selected for multivariate logistic regression analysis. Cardiac comorbidities were the most significant predictor for desaturation and bradycardia with odds ratios (95% confidence intervals) of 5.112 (1.881–13.888) and 26.597 (3.190–221.850), respectively.Conclusions: Preterm infants with cardiac comorbidities and lower GA may be more susceptible to postoperative desaturation or bradycardia.
Park et al. (Wed,) studied this question.