Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Sevilla, Spain.
Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, Sevilla, Spain.
Virol J. 2023 Oct 6;20(1):226. doi: 10.1186/s12985-023-02195-9.
Despite the extensive vaccination campaigns in many countries, COVID-19 is still a major worldwide health problem because of its associated morbidity and mortality. Therefore, finding efficient treatments as fast as possible is a pressing need. Drug repurposing constitutes a convenient alternative when the need for new drugs in an unexpected medical scenario is urgent, as is the case with COVID-19.
Using data from a central registry of electronic health records (the Andalusian Population Health Database), the effect of prior consumption of drugs for other indications previous to the hospitalization with respect to patient outcomes, including survival and lymphocyte progression, was studied on a retrospective cohort of 15,968 individuals, comprising all COVID-19 patients hospitalized in Andalusia between January and November 2020.
Covariate-adjusted hazard ratios and analysis of lymphocyte progression curves support a significant association between consumption of 21 different drugs and better patient survival. Contrarily, one drug, furosemide, displayed a significant increase in patient mortality.
In this study we have taken advantage of the availability of a regional clinical database to study the effect of drugs, which patients were taking for other indications, on their survival. The large size of the database allowed us to control covariates effectively.
尽管许多国家开展了广泛的疫苗接种活动,但 COVID-19 仍然是一个全球性的主要健康问题,因为它会导致发病率和死亡率。因此,尽快找到有效的治疗方法是当务之急。当需要针对意外医疗情况的新药时,药物再利用是一种便捷的替代方法,就像 COVID-19 一样。
利用电子健康记录中央登记处(安达卢西亚人口健康数据库)的数据,在 2020 年 1 月至 11 月期间在安达卢西亚住院的所有 COVID-19 患者的回顾性队列中,研究了先前用于其他适应症的药物的消费对患者预后(包括生存和淋巴细胞进展)的影响,该队列包括 15968 名个体。
调整协变量后的风险比和淋巴细胞进展曲线分析支持 21 种不同药物的消费与患者生存更好之间存在显著关联。相反,一种药物呋塞米显示出患者死亡率的显著增加。
在这项研究中,我们利用了区域临床数据库的可用性来研究患者因其他适应症而服用的药物对其生存的影响。数据库的大规模允许我们有效地控制协变量。