Exploring the drug-induced anemia signals in children using electronic medical records

ABSTRACT

Objectives: The objectives were to identify drugs related with anemia in children and evaluate the novelty of these correlations.

Methods: The authors established a two-step method for detecting the relationship between drugs and anemia using electronic medical records (EMRs), which were obtained from 247,136 patients in Beijing Children’s Hospital between 2007 and 2017. The authors extracted potential drugs by mining cases for hemoglobin abnormalities from the EMR and then performed a retrospective cohort study to correlate them with anemia by calculating the matched odds ratios and 95% confidence interval using unconditional logistic regression analysis.

Results: In total, nine positive drug-anemia associations were identified. Among them, the correlations of drugs fluconazole (OR 3.95; 95%CI: 2.65–5.87) and cefathiamidine (OR 3.49; 95%CI: 2.94–4.15) with anemia were considered new signals in both children and adults. Three associations of drugs, vancomycin, cefoperazone-sulbactam and ibuprofen, with anemia were considered new signals in children.

Conclusion: The authors detected nine signals of drug-induced anemia, including two new signals in children and adults and three new signals in children. This study could serve as a model for using EMR and automatic mining to monitor adverse drug reaction signals in the pediatric population.

KEYWORDS:

• Detection
• anemia
• children
• electronic medical record
• adverse drug reaction

Author contributions

D Fan contributed to the data collection, data analysis, interpretation of data and drafting the article. L Jia and X Wang contributed to the conception and design of the study. Y Yu, R Wei, X Feng and M Gao contributed to the data collection. Y Yu, X Nie and X Peng contributed to the data analysis. L Jia, Y Yu and X Ding contributed to drafting the article and offered important recommendations in terms of methodology.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Supplementary material

The supplemental data for this article can be accessed here.

Additional information

Funding

This paper was funded by the National Major Scientific and Technological Special Project for ‘Significant New Drugs Development’ during the 13th Five-year Plan Period (No. 2017ZX09304029) and Beijing Natural Science Foundation (No. 7194265).