Investigating long-term risk of aortic aneurysm and dissection from fluoroquinolones and the key contributing factors using machine learning methods

The connection between fluoroquinolones and severe heart conditions, such as aortic aneurysm (AA) and aortic dissection (AD), has been acknowledged, but the full extent of long-term risks remains uncertain. Addressing this knowledge deficit, a retrospective cohort study was conducted in Taiwan, utilizing data from the National Health Insurance Research Database spanning from 2004 to 2010, with follow-up lasting until 2019. The study included 232,552 people who took fluoroquinolones and the same number of people who didn't, matched for age, sex, and index year. The Cox regression model was enlisted to calculate the hazard ratio (HR) for AA/AD onset. Additionally, five machine learning algorithms assisted in pinpointing critical determinants for AA/AD among those with fluoroquinolones. Intriguingly, within the longest follow-up duration of 16 years, exposed patients presented with a markedly higher incidence of AA/AD unexposed patients (80 vs. 30 per 100,000 person-years). After adjusting for multiple factors, exposure to fluoroquinolones was linked to a higher risk of AA/AD (HR 1.62, 95%CI 1.45-1.78). Machine learning identified ten factors that significantly affected AA/AD risk in those exposed. The findings illustrate a 62% elevation in the long-term risk of adverse outcomes associated with AA/AD following the administration of fluoroquinolones and concurrently delineate the salient factors contributing to AA/AD, underscoring the imperative for healthcare practitioners to meticulously evaluate the implications of prescribing these antibiotics in light of the associated risks and determinants.