Predicting progression from SeLECTS with SWAS to EE-SWAS: risk factor identification and model development

Area of Science:

• Pediatric Neurology
• Epileptology
• Clinical Prediction Modeling

Background:

• Self-limited epilepsy with centrotemporal spikes (SeLECTS) can progress to epileptic encephalopathy with spike-and-wave activation in sleep (EE-SWAS).
• Early identification of risk factors is crucial for timely intervention and mitigating cognitive decline.

Purpose of the Study:

• To identify early risk factors for progression from SeLECTS to EE-SWAS.
• To develop and validate a predictive model for EE-SWAS progression.

Main Methods:

• Analysis of a pediatric cohort with a high spike-and-wave index (>50%).
• Evaluation of baseline clinical and EEG features in 77 SeLECTS patients.
• Development of a nomogram-based predictive model using multivariate logistic regression and validated externally.

Main Results:

• Prolonged spike-and-wave clusters, high-amplitude spikes with secondary generalization, and younger age at first seizure were independent predictors of EE-SWAS progression.
• The predictive model demonstrated high discriminative ability (C-index 0.932 in derivation, 0.934 in validation).

Conclusions:

• This study presents the first validated tool for early risk stratification of SWAS-associated SeLECTS.
• The model facilitates anticipation of EE-SWAS progression, enabling optimized therapeutic strategies and potentially mitigating cognitive decline.