Children with preoperative anxiety are at risk of perioperative adverse events, such as reflux aspiration, prolonged induction time, wake agitation, and delirium. Identifying children at high risk of severe preoperative anxiety may help anesthesiologists intervene and manage them in advance. The authors hypothesized that the risk of developing serious preoperative anxiety in children is predictable by variables related to basic information about the parent and child. We developed a clinical prediction model to identify patients vulnerable to severe preoperative anxiety among children aged 2-12 years. We enrolled patients aged 2-12 years who underwent elective surgery under general anesthesia and divided them into derivation (n=340, 70.8%) and validation (n=140, 29.2%) groups. Preoperative anxiety was assessed using the modified Yale Preoperative Anxiety Scale, and a high level of preoperative anxiety was defined as a score of >30. The following predictors were collected preoperatively: gender, age, weight, children's education level, only child, history of surgery, waiting time in the anesthesia waiting area, parental education level, parental anxiety, whether venous access had been established in the ward, and whether they had received anti-anxiety interventions. A prediction model was built using binary logistic regression analysis; bootstrap was applied for internal validation, and external validation was performed using the validation datasets. The prediction model had good discrimination, with an area under the receiver operator characteristic curve (AUC) of 0.961 (95% CI=0.943-0.979) and 0.896 (95% CI=0.842-0.950) in the derivation and validation cohorts, respectively. The predictive variables included in the final clinical model were pharmacological intervention (OR=0.008, 95% CI=0.002-0.025), nonpharmacological intervention (OR=0.342, 95% CI=0.104-1.127), parental education level (OR=0.211, 95% CI=0.108-0.411), parental anxiety (OR=6.15, 95% CI=2.396-15.786), only child (OR=2.417, 95% CI=1.065-5.488), history of surgery (OR=3.513, 95% CI=1.137-10.860), and age (OR=0.692, 95% CI=0.500-0.957). In this study, a clinical prediction model was developed and validated for the first time. The proposed clinical prediction model can help doctors identify children most likely to develop a high level of preoperative anxiety. ChiCTR2100054409 (https://www.chictr.org.cn/index.aspx).
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