AUTHOR=Yu Yuncui , Nie Xiaolu , Song Ziyang , Xie Yuefeng , Zhang Xuan , Du Zhaoyang , Wei Ran , Fan Duanfang , Liu Yiwei , Zhao Qiuye , Peng Xiaoxia , Jia Lulu , Wang Xiaoling TITLE=Signal Detection of Potentially Drug-Induced Liver Injury in Children Using Electronic Health Records JOURNAL=Frontiers in Pediatrics VOLUME=8 YEAR=2020 URL=https://www.frontiersin.org/journals/pediatrics/articles/10.3389/fped.2020.00171 DOI=10.3389/fped.2020.00171 ISSN=2296-2360 ABSTRACT=

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.