Development of a prediction nomogram model of recurrent febrile seizures in pediatric children.

The purpose of this study is to develop a prediction nomogram of recurrent febrile seizures in pediatric children based on the identified predictors for developing recurrent febrile seizures. This is a retrospective observational study. The medical records of 320 febrile seizure-afflicted children admitted to Zhoushan Women and Children Hospital from March 2019 to January 2023 were retrospectively reviewed. Children were divided into the recurrent febrile seizures group and the non-recurrent febrile seizures group. The predictors of recurrent febrile seizures were identified by univariate and multivariate analyses. A prediction nomogram model was developed via R software. The performance of the nomogram was internally validated to assess the model's discrimination and consistency, and decision curve analysis was employed to assess clinical utility. There were 41 out of 320 cases that had recurrent febrile seizures during the observation period, with a 12.81% prevalence rate of recurrent febrile seizures. The predictors of recurrent febrile seizures were young age at the first febrile seizures, a family history of febrile seizures in a first-degree relative, diurnal variation of initial febrile seizures occurrence, gender, and a low level of C-reactive protein. The area under the receiver operating characteristic curve of the nomogram is 0.795 (95% confidence interval: 0.720-0.871). Calibration plots and the result of the Hosmer-Lemeshow test (P = 0.472) reveal satisfactory consistency. Decision curve analysis showed a significant net benefit of the nomogram. CONCLUSIONS: The prediction nomogram model demonstrates good performance and clinical utility, which would be a convenient tool for the detection of children in pediatrics with high-risk recurrent febrile seizures. It is useful for pediatric medical staff to provide early medical interventions and family counseling. WHAT IS KNOWN: • A proportion of children experience recurrences of febrile seizures. • Recognition of risk factors for recurrent FS in pediatrics would be useful for the prediction of risk probabilities and help provide tailored counseling and follow-up. WHAT IS NEW: • A nomogram model is developed for risk prediction of recurrent febrile seizures in this study, which would be a convenient risk prediction tool in pediatrics. • The predictor of diurnal variation of recurrent febrile seizures is with new ideas.

The development of a nomogram model for the individualized prediction of diaper dermatitis risk in pediatric hospitalized children aged 1-36 months.

AIMS AND OBJECTIVE: To develop a nomogram model for individualized prediction of diaper dermatitis in pediatric hospitalized infants and toddlers aged 1-36 months. BACKGROUND: Diaper dermatitis is a common skin health problem in pediatrics, which brings pain and discomfort to the child. However, there is a scarcity of risk prediction tools for diaper dermatitis in infants and toddlers hospitalized in pediatrics. DESIGN: A cross-sectional study. METHODS: 210 cases each for caregivers and hospitalized children aged 1-36 months were selected as the research objects. A prediction nomogram model was established based on the risk factors according to the results of univariate analysis and multivariate logistic regression analysis. The predictive performance of the nomogram model was evaluated by discrimination and calibration. The clinical utility of the model was evaluated by decision curve analysis. This study was reported using the TRIPOD checklist. RESULTS: 41 hospitalized children with diaper dermatitis with a prevalence of 19.52%. The risk factors included: age in months, diarrhea, history of diaper dermatitis, without prophylactic application of buttock protection products, frequency of diaper change per day ≤6.6 times, and the level of caregivers' knowledge of infantile diaper dermatitis. The results showed that the C-index of the nomogram model was 0.891(95% CI: 0.832, 0.950), the calibration curve manifested a satisfactory consistency, and the net benefit was satisfactory. CONCLUSIONS: The nomogram has a good predictive ability and satisfactory clinical utility, which is useful for pediatric medical staff screening high-risk patients with diaper dermatitis. RELEVANCE TO CLINICAL PRACTICE: The prediction nomogram model can help pediatric medical staff to calculate the risk probability of diaper dermatitis in pediatrics, formulate interventions timely, and optimize pediatric DD standardized care protocols. NO PATIENT OR PUBLIC CONTRIBUTION: the children's caregivers enrolled in this study only for the data collection.