Objective To systematically evaluate the safety profiles of anti-seizure medications (ASMs) regarding metabolic adverse events in the pediatric population, identify risk signals across different age stages, and provide evidence-based support for clinical individualized medication and pharmacovigilance. MethodsData from the Food and Drug Administration (FDA) adverse event reporting system (FAERS) spanning Q1 2013 to Q3 2024 were analyzed. Reports involving metabolic adverse events in patients aged 0~18 years after ASMs use were screened. Data mining methods, including Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), and Bayesian Confidence Propagation Neural Network (BCPNN), were applied. Standardized classification was performed using the Medical Dictionary for Regulatory Activities (MedDRA) v26.1 to analyze adverse reaction signals across metabolic pathways, including glucose, lipids, proteins/amino acids, and bone/calcium/phosphorus/magnesium, as well as trace metals. Stratified safety evaluations were conducted across four age groups: infants (0~2 years), toddlers (2~6 years), children (6~2 years), and adolescents (12~18 years). ResultsA total of 2,356 metabolic adverse event reports were included. Significant signals were observed for protein and amino acid metabolism disorders (ROR=5.44), bone/calcium/magnesium/phosphorus metabolism disorders (ROR=1.59), and iron/trace metal metabolism disorders (ROR=1.83), with some signals being specific to the pediatric population. Several drugs, including valproate, topiramate, levetiracetam, and gabapentin, showed strong risk signals across multiple metabolic pathways, primarily manifesting as hyperammonemia, hypocalcemia, and hypomagnesemia. Risk profiles varied significantly by age group: lacosamide showed prominent signals for bone metabolism disorders in the 0~2 years group; perampanel showed significant signals for amino acid metabolism disorders in the 2~6 years group; and in the 12~18 years group, clonazepam and gabapentin showed extremely high ROR values (>48) for iron/trace metal metabolism disorders. The median onset time for metabolic adverse events associated with novel ASMs was significantly later than that of traditional ASMs (38 days vs. 8 days), suggesting a relatively delayed but prolonged metabolic toxicity for newer agents. ConclusionThe use of ASMs in minors can trigger multi-system metabolic disturbances, with significant differences in risk profiles across different drugs and age groups. We recommend strengthening the dynamic monitoring of metabolic parameters during treatment, with particular attention to the potential toxicity of high-risk drugs within specific age windows, thereby promoting the establishment of precision dosing and early intervention strategies.
ObjectiveTo conduct pharmacovigilance signal mining and safety analysis of losartan potassium based on the FDA adverse event reporting system (FAERS) database, providing references for rational clinical drug use. MethodsThe study collected adverse event reports from the FAERS database from the first quarter of 2004 to the first quarter of 2024. After data cleaning and de-duplication, reports with losartan potassium as the main suspected drug were selected. Adverse events were coded and classified using the preferred term (PT) and system organ class (SOC) in the medical dictionary for regulatory activities (MedDRA). Two non-Bayesian methods, reporting odds ratio (ROR) and proportional reporting ratio (PRR), were used for signal detection, and the generated effective signals needed to meet specific statistical thresholds. Additionally, subgroup analyses based on age and weight were conducted, and descriptive statistics and Weibull distribution tests were performed on the time-to-onset (TTO) to analyze the risk pattern over time. ResultsA total of 11 175 adverse event reports with losartan potassium as the main suspected drug were identified. Female reporters were more than male (55.8% vs. 35.6%), and the majority of patients were aged 65-85 years (32.3%). A total of 369 effective adverse event signals were generated, involving 27 SOC. The most frequent system organ categories for adverse events included nervous system disorders, various examinations, and gastrointestinal disorders. In terms of signal strength, vascular diseases and metabolic and nutritional disorders showed the strongest association signals. At the preferred term level, dizziness, elevated blood pressure, and hypertension had the highest reporting frequencies, among which heart failure was a significant signal not mentioned in the drug instructions. Subgroup analysis showed that the signal strength of hyponatremia was higher in elderly patients (>80 years old). The median time to onset of adverse events was 106 days, with most events concentrated within one month and one year after medication. The Weibull distribution test (shape parameter β=0.62, 95%CI 0.61 to 0.64) indicated that the overall risk decreased over time (early failure type). ConclusionThis study confirmed the known adverse reactions of losartan potassium (such as dizziness and hyperkalemia) through large-scale real-world data and revealed potential risk signals (such as heart failure and hyponatremia in specific populations). The analysis of medication time provided a basis for monitoring key time points in clinical practice. It is recommended that clinicians pay particular attention to high-risk patients such as the elderly and those on combination therapy when using losartan potassium, and strengthen the monitoring of blood potassium, blood sodium, and renal function, as well as be vigilant about the risk of adverse events in the early and long-term use.
