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.

AimThis study aimed to explore how different dimensions of caregivers' reaction shape their caring experience, and the factors associated with different reaction patterns.DesignA second analysis of a multisite cross-sectional study were conducted. Caregivers of children with imperforate anus (IA) were enrolled in three tertiary children's hospitals in Eastern China between November 2018 and February 2019.MethodsThe caregiver's experience, stigma feeling, social support level and perception of uncertainty were assessed by Caregiver Reaction Assessment, Parent Stigma Scale, Social Support Scale and Parent's Perception of Uncertainty Scale accordingly. The demographic information of caregivers as well as the children's clinical data were collected. Latent profile analysis was conducted to determine different patterns of caregiver's reaction, and logistics analysis was used to explore the associated factors of the reaction pattern.FindingsA total number of 229 caregivers (median age = 30, quartiles: 28, 36) were included. Three distinguishable caregiving reaction types were identified (Class 1: low burden and high benefit, 4.8%; Class 2: moderate burden and benefit, 48.9%; Class 3: high burden and low benefit, 46.3%). In logistics analysis, the Class 1 and Class 2 were combined as one group due to the low population in Class 1. The marital status of caregiver (OR = 0.067, 95% CI: 0.006, 0.700, P = 0.024), IA type (OR = 1.745, 95% CI: 1.198, 2.541, P = 0.004), children aged &gt; 2 years (OR = 3.219, 95% CI: 1.364, 7.597, P = 0.008), social support (OR = 0.907, 95% CI: 0.865, 0.951, P &lt; 0.001) and perception of uncertainty (OR = 1.054, 95% CI: 1.026, 1.083, P &lt; 0.001) were associated with different caregiver reaction patterns.ConclusionNearly half of the caregivers of children with IA experience reaction of high burden and low benefit, but considerable proportion of caregivers could benefit from the caregiving rather than burden from. Married caregivers may have more negative reaction, especially when children &gt; 2 years and diagnosed with intermediate or high type of IA. However, increasing caregiver's social support and reducing perception of uncertainty may have the potential to modify their reaction pattern.