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Development and validation of a prediction model for preoperative anxiety in children aged 2-12 years old
Zhangqin Cheng1, Liuyi Wang1, Lifang Li1
1Xuzhou Medical University, Xuzhou, China.
Insights
A new clinical prediction model identifies children at high risk for severe preoperative anxiety. This tool helps anesthesiologists proactively manage pediatric patients, reducing risks of adverse perioperative events.
Area of Science:
- Pediatric Anesthesiology
- Clinical Prediction Modeling
- Child Psychology
Background:
- Preoperative anxiety in children increases the risk of adverse perioperative events, including reflux aspiration, prolonged induction, and delirium.
- Early identification of high-risk children allows for timely interventions by anesthesiologists.
- Predicting severe preoperative anxiety is crucial for improving pediatric surgical outcomes.
Purpose of the Study:
- To develop and validate a clinical prediction model for identifying children aged 2-12 years at high risk of severe preoperative anxiety.
- To identify key predictors of severe preoperative anxiety in pediatric surgical patients.
- To aid anesthesiologists in proactive management of anxious children.
Main Methods:
- A cohort of 480 children (aged 2-12 years) undergoing elective surgery was divided into derivation (n=340) and validation (n=140) groups.
- Preoperative anxiety was assessed using the modified Yale Preoperative Anxiety Scale (score >30 defined as high anxiety).
- Binary logistic regression was used to build the prediction model, with internal and external validation performed.
Main Results:
- The model demonstrated good discrimination, with an AUC of 0.961 in the derivation cohort and 0.896 in the validation cohort.
- Key predictors of high preoperative anxiety included parental anxiety, being an only child, history of surgery, and age.
- Interventions (pharmacological and non-pharmacological) and parental education level were found to be protective factors.
Conclusions:
- A validated clinical prediction model for severe preoperative anxiety in children has been developed.
- This model can assist clinicians in identifying vulnerable pediatric patients before surgery.
- Proactive management based on this model can potentially mitigate perioperative risks in children.
Background:
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.
Aim:
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.
Methods:
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.
Results:
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).
Conclusions:
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.
Clinical Trial Registration Identifier:
ChiCTR2100054409 (https://www.chictr.org.cn/index.aspx).
