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A Nomogram for Early Prediction of Post-traumatic Epilepsy in Children with Traumatic Brain Injury: Development and
Lijuan Zhang1, Hongyu Qi1, Hui Ye1
1Department of Surgical Intensive Care Unit, Children's Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, China.
Insights
A new prediction model helps identify children at high risk for early post-traumatic epilepsy (PTE) after traumatic brain injury (TBI). This tool aids in prioritizing care for pediatric TBI patients, improving outcomes.
Area of Science:
- Pediatric Neurology
- Neurotrauma Research
- Epileptology
Background:
- Post-traumatic epilepsy (PTE) is a common and debilitating consequence of pediatric traumatic brain injury (TBI).
- Accurate early risk stratification for PTE in children is crucial for timely intervention but remains a clinical challenge.
Purpose of the Study:
- To develop and validate a predictive model for early risk stratification of PTE in pediatric TBI patients.
- To create a practical tool for identifying children at higher risk of developing PTE post-injury.
Main Methods:
- Retrospective analysis of a pediatric TBI cohort (2018-2023), split into training (2018-2021) and validation (2022-2023) sets.
- Development of a multivariable logistic regression model and nomogram using readily available admission variables.
- Evaluation of model performance via discrimination (AUC), calibration, and decision curve analysis.
Main Results:
- The final model incorporated five key predictors: intraventricular hemorrhage, Glasgow Coma Scale score, early post-traumatic seizures, abnormal pupillary response, and albumin.
- The nomogram demonstrated strong predictive performance with high discrimination (AUC 0.942 training, 0.916 validation) and good calibration.
- Exploratory analyses suggested associations between severe intracranial injury markers and drug-resistant epilepsy (DRE).
Conclusions:
- An admission-based nomogram provides a practical approach for early PTE risk stratification in pediatric TBI.
- This tool can assist in prioritizing neurological monitoring and follow-up for at-risk children.
- External validation is recommended prior to widespread clinical adoption.
Objective:
Post-traumatic epilepsy (PTE) is a significant complication after pediatric traumatic brain injury (TBI), yet early risk stratification remains challenging. We aimed to develop and temporally validate a prediction model for early risk stratification of PTE in children with TBI.
Methods:
A retrospective cohort of children with TBI (2018-2023) was analyzed. Patients from 2018 to 2021 formed the training cohort and those from 2022 to 2023 the validation cohort. A multivariable logistic regression model was constructed and translated into a nomogram. Model performance was evaluated using discrimination, calibration, and decision curve analysis. Exploratory analyses assessed factors associated with drug-resistant epilepsy (DRE).
Results:
Among 579 patients (training: 402; validation: 177), PTE occurred in 13% and 14%, respectively. Five variables readily available at presentation (intraventricular hemorrhage, Glasgow Coma Scale score, early post-traumatic seizures, abnormal pupillary response, and albumin) independently predicted PTE and were incorporated into the nomogram. The model showed strong discrimination (AUC 0.942 training; 0.916 validation) and good calibration, with favorable clinical net benefit across relevant thresholds. Exploratory analyses identified potential associations between markers of severe intracranial injury and DRE.
Conclusions:
We present a practical admission-based nomogram for early risk stratification of PTE after pediatric TBI. The model may help prioritize neurological surveillance and follow-up in children at increased risk. External validation is required before routine clinical implementation.
