Signal Detection of Potentially Drug-Induced Liver Injury in Children Using Electronic Health Records - Yu, Yuncui; Nie, Xiaolu; Song, Ziyang; Xie, Yuefeng; Zhang, Xuan; Du, Zhaoyang; Wei, Ran; Fan, Duanfang; Liu, Yiwei; Zhao, Qiuye; Peng, Xiaoxia; Jia, Lulu; et al. (Frontiers in Pediatrics, 2020)
Background: This study proposes a quantitative 2-stage procedure to detect potential drug-induced liver injury (DILI) signals in pediatric inpatients using an data warehouse of electronic health records (EHRs). Methods: Eight years of medical data from a constructed database were used. A two-stage procedure was adopted: (i) stage 1: the drugs suspected of inducing DILI were selected and (ii) stage 2: the associations between the drugs and DILI were identified in a retrospective cohort study. Results: 1,196 drugs were filtered initially and 12 drugs were further potentially identified as suspect drugs inducing DILI. Eleven drugs (fluconazole, omeprazole, sulfamethoxazole, vancomycin, granulocyte colony-stimulating factor (G-CSF), acetaminophen, nifedipine, fusidine, oseltamivir, nystatin and meropenem) were showed to be associated with DILI. Of these, two drugs, nystatin [odds ratio[OR]=1.39, 95%CI:1.10–1.75] and G-CSF (OR = 1.91, 95%CI:1.55–2.35), were found to be new potential signals in adults and children. Three drugs [nifedipine [OR = 1.77, 95%CI:1.26–2.46], fusidine [OR = 1.43, 95%CI:1.08–1.86], and oseltamivi r [OR = 1.64, 95%CI:1.23–2.18]] were demonstrated to be new signals in pediatrics. The other drug-DILI associations had been confirmed in previous studies. Conclusions: A quantitative algorithm to detect potential signals of DILI has been described. Our work promotes the application of EHR data in pharmacovigilance and provides candidate drugs for further causality assessment studies.