Cardiovascular and metabolic risk of antipsychotics in children and young adults: a multinational self-controlled case series study

EPIDEMIOLOGY AND PSYCHIATRIC SCIENCES(2021)

引用 3|浏览22
暂无评分
摘要
Aims The risk of antipsychotic-associated cardiovascular and metabolic events may differ among countries, and limited real-world evidence has been available comparing the corresponding risks among children and young adults. We, therefore, evaluated the risks of cardiovascular and metabolic events in children and young adults receiving antipsychotics. Methods We conducted a multinational self-controlled case series (SCCS) study and included patients aged 6-30 years old who had both exposure to antipsychotics and study outcomes from four nationwide databases of Taiwan (2004-2012), Korea (2010-2016), Hong Kong (2001-2014) and the UK (1997-2016) that covers a total of approximately 100 million individuals. We investigated three antipsychotics exposure windows (i.e., 90 days pre-exposure, 1-30 days, 30-90 days and 90 + days of exposure). The outcomes were cardiovascular events (stroke, ischaemic heart disease and acute myocardial infarction), or metabolic events (hypertension, type 2 diabetes mellitus and dyslipidaemia). Results We included a total of 48 515 individuals in the SCCS analysis. We found an increased risk of metabolic events only in the risk window with more than 90-day exposure, with a pooled IRR of 1.29 (95% CI 1.20-1.38). The pooled IRR was 0.98 (0.90-1.06) for 1-30 days and 0.88 (0.76-1.02) for 31-90 days. We found no association in any exposure window for cardiovascular events. The pooled IRR was 1.86 (0.74-4.64) for 1-30 days, 1.35 (0.74-2.47) for 31-90 days and 1.29 (0.98-1.70) for 90 + days. Conclusions Long-term exposure to antipsychotics was associated with an increased risk of metabolic events but did not trigger cardiovascular events in children and young adults.
更多
查看译文
关键词
Antipsychotics, cardiovascular events, children and young adults, metabolic syndrome, multi-national study, self-controlled case series
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要