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Published on: September 20, 2024
Promoting medication compliance in epileptic children: a cross sectional survey
Lijuan Zhang1, Ping Li2, Junping He1
1Department of Neurosurgery, Children's Hospital of Nanjing Medical University, Nanjing, Jiangsu province, China.
Insights
Medication non-compliance in pediatric epilepsy is common, affecting over 30% of children. Parental education, income, number of medications, and epilepsy knowledge significantly impact adherence, necessitating targeted interventions.
Area of Science:
- Pediatric Neurology
- Clinical Pharmacy
- Public Health
Background:
- Medication compliance is critical for managing epilepsy in children.
- Suboptimal adherence negatively impacts treatment outcomes and prognosis.
- Understanding factors influencing compliance is essential for effective pediatric epilepsy care.
Purpose of the Study:
- To identify determinants of medication non-compliance in pediatric epilepsy patients.
- To develop and validate a predictive model for identifying children at risk of non-compliance.
- To inform clinical strategies for improving medication adherence in this population.
Main Methods:
- A cohort of 168 children with epilepsy was analyzed.
- Demographic data and medication compliance were assessed.
- A predictive model was developed and its performance evaluated using ROC curve analysis.
Main Results:
- The medication non-compliance rate was 32.74%.
- Parental education, household income, number of medications, and epilepsy knowledge were significant predictors of non-compliance (p < 0.05).
- The predictive model demonstrated good discriminative ability (AUC = 0.713).
Conclusions:
- Medication compliance in pediatric epilepsy is influenced by socioeconomic and knowledge-based factors.
- A validated predictive model can aid in early identification of non-compliant patients.
- The findings support the development of targeted interventions to improve medication adherence.
Background:
Compliance with medication is crucial for the favorable prognosis of children with epilepsy. The objective of this study was to assess the determinants of medication compliance and to construct a predictive model for the risk of non-compliance among pediatric epilepsy patients.
Methods:
The study included children diagnosed with epilepsy and treated at our hospital between February 1 and September 30, 2023. We evaluated the demographic characteristics and medication compliance profiles of these patients. The predictive model's performance was assessed using the receiver operating characteristic (ROC) curve to determine its sensitivity and specificity.
Results:
A total of 168 children with epilepsy were analyzed. The rate of non-compliance with medication was found to be 32.74% (55 out of 168). Logistic regression identified the educational level of parents (OR = 2.844, 95% CI: 2.182-3.214), monthly household income (OR = 1.945, 95% CI: 1.203-2.422), the number of medications taken (OR = 1.883, 95% CI: 1.314-2.201), and the level of epilepsy knowledge received (OR = 2.517, 95% CI: 1.852-3.009) as significant factors influencing non-compliance (all 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 model's discriminative ability.
Conclusions:
The compliance to medication regimens among children with epilepsy is suboptimal and influenced by a multitude of factors. This study has developed a predictive model for medication compliance, which could serve as a valuable tool for clinical assessment and intervention planning regarding medication compliance in pediatric epilepsy patients.
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