Risk factors for drug-resistant epilepsy (DRE) in children and a model to predict development of DRE

Abstract

Purpose. This study was conducted to investigate possible risk factors that could increase the occurrence of drug-resistant epilepsy (DRE), in hopes that the results could be used to educate the patient and their caregivers as well as increase early detection efforts. Methods. Case control study was conducted at neurology outpatient pediatric RSDS between May to December 2022. Risk factor of DRE such as sex, age of onset, type of seizure, initial seizure frequencies, history of cranial hemorrhage, cerebral infection, febrile seizure, status epilepticus, neonatal seizure, neonatal asphyxia, family history of epilepsy, present of neurological deficit, electroencephalogram (EE) finding, and result of neuroimaging examination were obtained through anamnesis and clinical examination. Risk factors were analyzed with bivariate analysis and multivariate analysis. A model was generated to predict probabilities of DRE in children with epilepsy. Results. DRE was observed in 84/137 (54%) patients. Bivariate analysis showed age of onset <1 years old (OR 2.31, p = 0.016), initial seizure frequencies >5 times/day (OR 3.0, p = 0.011), neonatal seizure (OR 3, p = 0.034), presence of neurologic deficit (OR 3.1, p=0.002), and abnormality of EEG (OR 2.82, p = 0.013) are significantly associated with DRE. Logistic regression revealed that initial seizure frequencies > 5 times/day (OR=2.5; 95%CI 1.051 to 6.028; P=0.038), present of neurological deficit (OR=2.58; 95%CI 1.205 to 5.531; P=0.031), and EE abnormality (OR=2.84; 95%CI 1.170 6.914; P=0.021) were significantly correlated with DRE. Our model sensitivity was 75.3% and 55.76% to predict DRE (AUC = 0.704, p=0.000). Conclusion. Seizure onsets of >5 times, neurological deficits, and EEG abnormality were found to be associated with drug resistant epilepsy.