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Research on signal mining of adverse events of tizanidine based on FAERS database / 药物流行病学杂志
Article in Zh | WPRIM | ID: wpr-1023180
Responsible library: WPRO
ABSTRACT
Objective Based on U.S.Food and Drug Administration Adverse Event Reporting System(FAERS)database,the signal mining of tizanidine adverse drug events(ADEs)was conducted to explore the occurrence characteristics of ADE,hoping to provide references for the safe clinical application of tizanidine.Methods The reporting odds ratio(ROR)and medicines and healthcare products regulatory agency methods(MHRA)were used to analyse the ADE of tizanidine using FAERS registration data from the first quarter of 2004 to the second quarter of 2022.After valid signals were obtained,the MedDRA was used for translation and system organ classification.Results A total of 7 135 reports of tizanidine ADE were obtained,including 1 732 patients,1 304 ADE types were involved.According to the results of 2 ADE signal mining methods,at the preferred term(PT)level,177 signals were detected.There were 32 PT signals not included in the drug instructions,including potassium wasting nephropathy,cardio-respiratory arrest,and foetal growth restriction etc.In 1 732 patients,the number of ADE cases of female was 2.37 times that in male(1 057 vs.446),and the age group between 40 and 64 accounted for a large proportion(36.03%).The highest proportion(32.79%)reported by consumers.The system organ class involved mainly included various neurological diseases and psychosis.The median time to onset of tizanidine-related ADEs was 75 d(interquartile range28-223 d),but it was necessary to be vigilant that ADE may still occur 1 year after starting the drug(13.38%).Conclusion This study aims to suggest that clinical application of tizanidin-related ADE should be paid full attention to the occurrence of ADE such as potassium-wasting nephropathy and suicidally completed,as well as key populations such as women and patients of 40-64 years old.
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Full text: 1 Database: WPRIM Language: Zh Journal: Chinese Journal of Pharmacoepidemiology Year: 2024 Document type: Article
Full text: 1 Database: WPRIM Language: Zh Journal: Chinese Journal of Pharmacoepidemiology Year: 2024 Document type: Article