Section of Infectious Diseases, Boston Medical Center, Boston, Massachusetts, USA.
Boston University School of Medicine, Boston, Massachusetts, USA.
Clin Infect Dis. 2021 Dec 6;73(11):e3661-e3669. doi: 10.1093/cid/ciaa1346.
The expansion of the US opioid epidemic has led to significant increases in infections, such as infective endocarditis (IE), which is tied to injection behaviors. We aimed to estimate the population-level IE mortality rate among people who inject opioids and compare the risk of IE death against the risks of death from other causes.
We developed a microsimulation model of the natural history of injection opioid use. We defined injection behavior profiles by both injection frequency and injection techniques. We accounted for competing risks of death and populated the model with primary and published data. We modeled cohorts of 1 million individuals with different injection behavior profiles until age 60 years. We combined model-generated estimates with published data to project the total expected number of IE deaths in the United States by 2030.
The probabilities of death from IE by age 60 years for 20-, 30-, and 40-year-old men with high-frequency use with higher infection risk techniques compared to lower risk techniques for IE were 53.8% versus 3.7%, 51.4% versus 3.1%, and 44.5% versus 2.2%, respectively. The predicted population-level attributable fraction of 10-year mortality from IE among all risk groups was 20%. We estimated that approximately 257 800 people are expected to die from IE by 2030.
The expected burden of IE among people who inject opioids in the United States is large. Adopting a harm reduction approach, including through expansion of syringe service programs, to address injection behaviors could have a major impact on decreasing the mortality rate associated with the opioid epidemic.
美国阿片类药物泛滥的情况不断扩大,导致感染(如感染性心内膜炎)显著增加,而这些感染与注射行为有关。我们旨在评估注射阿片类药物人群中的感染性心内膜炎死亡率,并将其与其他死因的死亡风险进行比较。
我们开发了一个注射类阿片使用自然史的微观模拟模型。我们根据注射频率和注射技术来定义注射行为特征。我们考虑了死亡的竞争风险,并使用主要数据和已发表的数据对模型进行了填充。我们对具有不同注射行为特征的 100 万名个体进行建模,直到他们 60 岁。我们将模型生成的估计值与已发表的数据相结合,以预测 2030 年美国感染性心内膜炎死亡的总预期人数。
与使用低风险技术相比,20 岁、30 岁和 40 岁男性中,高频率使用且感染风险更高的技术的个体,在 60 岁时死于感染性心内膜炎的概率分别为 53.8%比 3.7%、51.4%比 3.1%和 44.5%比 2.2%。所有风险组中,10 年感染性心内膜炎死亡率的人群归因分数预计为 20%。我们估计,到 2030 年,预计将有大约 257800 人死于感染性心内膜炎。
美国注射类阿片药物人群中感染性心内膜炎的预期负担很大。采用减少伤害的方法,包括扩大注射器服务项目,解决注射行为问题,可能会对降低与阿片类药物泛滥相关的死亡率产生重大影响。