Pre-treatment risk predictors of valproic acid-induced dyslipidemia in pediatric patients with epilepsy - Liang, Tiantian; Lin, Chenquan; Ning, Hong; Qin, Fuli; Zhang, Bikui; Zhao, Yichang; Cao, Ting; Jiao, Shimeng; Chen, Hui; He, Yifang; Cai, Hualin (Frontiers in Pharmacology, 2024)
Valproic acid (VPA) stands as one of the most frequently prescribed medications in children with newly diagnosed epilepsy. Despite its infrequent adverse effects within therapeutic range, prolonged VPA usage may result in metabolic disturbances including insulin resistance and dyslipidemia. These metabolic dysregulations in childhood are notably linked to heightened cardiovascular risk in adulthood.Therefore, identification and effective management of dyslipidemia in children hold paramount significance.In this retrospective cohort study, we explored the potential associations between physiological factors, medication situation, biochemical parameters before the first dose of VPA (baseline) and VPA-induced dyslipidemia (VID) in pediatric patients.Binary logistic regression was utilized to construct a predictive model for blood lipid disorders, aiming to identify independent pre-treatment risk factors. Additionally, The Receiver Operating Characteristic (ROC) curve was used to evaluate the performance of the model.Through binary logistic regression analysis, we identified for the first time that direct bilirubin (DBIL) (odds ratios (OR) = 0.511, P = 0.01), duration of medication (OR = 0.357, P = 0.009), serum albumin (ALB) (OR = 0.913, P = 0.043), BMI (OR = 1.140, P = 0.045), and aspartate aminotransferase (AST) (OR = 1.038, P = 0.026) at baseline were independent risk factors for VID in pediatric patients with epilepsy.Notably, the predictive ability of DBIL (AUC = 0.690, P < 0.0001) surpassed that of other individual factors. Furthermore, when combined into a predictive model, incorporating all five risk factors, the predictive capacity significantly increased (AUC=0.777, P < 0.0001), enabling the anticipation of 77.7% of dyslipidemia events.DBIL emerges as the most potent predictor, and in conjunction with the other four factors, it can effectively forecast VID in pediatric patients with epilepsy. This insight can guide the formulation of individualized strategies for the clinical administration of VPA in children.