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Development and validation of a postoperative delirium prediction model for pediatric patients: A prospective,
Nan Lin1, Kexian Liu1, Jingyi Feng2
1Nursing Department.
Insights
A new prediction model identifies children at high risk for postoperative delirium, a serious complication after surgery. Key predictors include age, developmental delay, surgery type, pain, and dexmedetomidine use.
Area of Science:
- Pediatric Anesthesiology
- Critical Care Medicine
- Surgical Outcomes Research
Background:
- Postoperative delirium (POD) is a significant complication in children, associated with adverse outcomes.
- Early identification of high-risk pediatric patients is crucial for timely intervention and improved care.
- Existing risk assessment tools for POD in pediatric populations are limited.
Purpose of the Study:
- To develop and validate a predictive model for identifying children at high risk of postoperative delirium.
- To determine the sensitivity and specificity of the developed prediction model.
- To identify key demographic and clinical factors associated with POD in pediatric surgical patients.
Main Methods:
- A multivariate logistic regression model was developed using data from 1134 children (0-16 years) undergoing major elective surgery.
- Risk factors were identified, and the model's predictive ability was assessed using the area under the receiver operating characteristics curve (AUROC).
- Model validation was performed on an independent cohort of 100 pediatric patients.
Main Results:
- The prevalence of postoperative delirium in the study sample was 11.1%.
- The final prediction model included five predictors: age, developmental delay, type of surgery, pain, and dexmedetomidine exposure.
- The model demonstrated strong predictive performance with an AUROC of 0.889, sensitivity of 0.754, and specificity of 0.867 in the development cohort.
Conclusions:
- A validated prediction model for pediatric postoperative delirium has been established.
- Factors such as young age, developmental delay, specific surgical types (e.g., otorhinolaryngology), pain, and dexmedetomidine increase delirium risk.
- This model can serve as a foundation for developing targeted strategies to prevent and manage POD in children.
Abstract:
Postoperative delirium is a serious complication that relates to poor outcomes. A risk prediction model could help the staff screen for children at high risk for postoperative delirium. Our study aimed to establish a postoperative delirium prediction model for pediatric patients and to verify the sensitivity and specificity of this model.Data were collected from a total of 1134 children (0-16yr) after major elective surgery between February 2020 to June 2020. Demographic and clinical data were collected to explore the risk factors. Multivariate logistic regression analysis was used to develop the model, and we assessed the predictive ability of the model by using the area under the receiver operating characteristics curve (AUROC). Further data were collected from another 100 patients in October 2020 to validate the model.Prevalence of postoperative delirium in this sample was 11.1%. The model consisted of 5 predictors, namely, age, developmental delay, type of surgery, pain, and dexmedetomidine. The AUROC was 0.889 (P < .001, 95% confidence interval (CI):0.857-0.921), with sensitivity and specificity of 0.754 and 0.867, and the Youden of 0.621. The model verification results showed the sensitivity of 0.667, the specificity of 0.955.Children undergoing surgery are at risk for developing delirium during the postoperative period, young age, developmental delay, otorhinolaryngology surgery, pain, and exposure to dexmedetomidine were associated with increased odds of delirium. Our study established a postoperative delirium prediction model for pediatric patients, which may be a base for development of strategies to prevent and treat postoperative delirium in children.
