The Impact of Comorbidities, EEG Abnormalities, and ASM Use as a Predicting Outcomes in Pediatric Status Epilepticus.

BACKGROUND

Pediatric patients admitted to the pediatric intensive care unit (PICU) often present with diverse clinical conditions that influence their prognosis. Identifying key prognostic factors is crucial for optimizing treatment strategies and improving patient outcomes.

METHODS

A retrospective analysis was conducted on the clinical data of 203 pediatric patients with status epilepticus (SE) admitted to the PICU from January 2020 and December 2024. Based on result of the GOS score at 3 months after discharge, patients were categorized into the good prognosis group and the poor prognosis group. Perform statistical analysis on the data of two groups to identify risk factors associated with poor prognosis. The predictive value of the STEPSS and END-IT scoring systems was evaluated using ROC curve analysis.

RESULTS

Among the 203 pediatric patients, the proportion of patients in the good prognosis group (68.5%) was significantly higher than that in the poor prognosis group (31.5%). The median hospital stay was longer in the poor prognosis group [11.0 (7.0, 16.0) days] compared to the good prognosis group [9.0 (7.0, 13.0) days]. The presence of comorbidities (79.7% vs 63.3%), abnormal EEG findings (98.0% vs 89.0%), and polypharmacy with ASMs (82.8% vs 31.7%) were significantly associated with poor prognosis. Logistic regression analysis indicated that the use of multiple ASMs was an independent risk factor for poor prognosis, with patients receiving two or more ASMs being 4.48 times more likely to have an unfavorable outcome (95% CI: 2.223-9.029). The predictive value of the STEPSS and END-IT scoring systems was limited, with AUC values of 0.475 (P = 0.570) and 0.535 (P = 0.419), respectively.

CONCLUSION

Comorbidities, abnormal EEG findings, and increased ASM use are significant risk factors for poor prognosis in PICU patients with SE. ASM usage plays a crucial role in patient outcomes. Further research is needed to refine prognostic models and enhance clinical decision-making.