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Medication compliance in children with epilepsy is crucial for a good prognosis. The aim of this study was to assess the determinants of medication compliance and to build a predictive model of the risk of non-compliance in patients with paediatric epilepsy.

The study involved children diagnosed with epilepsy and treated in hospital between 1 February and 30 September 2023. The authors assessed the demographic characteristics and medication compliance profiles of these patients. The performance of the predictive model was evaluated using the receiver operating characteristic (ROC) curve to determine its sensitivity and specificity.

A total of 168 children with epilepsy were included. The rate of non-adherence to medication was 32.74% (55 out of 168). Logistic regression identified parental education (OR = 2.844, 95% CI: 2.182-3.214), monthly household income (OR = 1.945, 95% CI: 1.203-2.422), number of medications taken (OR = 1.883, 95% CI: 1.314-2.201) and level of epilepsy knowledge received (OR = 2.517, 95% CI: 1.852-3.009) as significant factors influencing non-adherence (p < 0.05). A total score threshold of 6 was set for the predictive model. The area under the ROC curve was 0.713 (95% CI: 0.686-0.751), indicating the discriminative power of the model.

Conclusions: Medication compliance in children with epilepsy is suboptimal and influenced by a multitude of factors. This study developed a predictive model of medication compliance, which could serve as a valuable tool for clinical assessment and intervention planning regarding medication compliance in paediatric patients with epilepsy.

Source(s) :
Lijuan Zhang , Ping Li, Junping He, Jing Qian, Yiming Liu ;

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