Signal Detection of Pediatric Drug-Induced Coagulopathy Using Routine Electronic Health Records

Xiaolu Nie; Yuncui Yu; Lulu Jia; Houyu Zhao; Zhenping Chen; Liqiang Zhang; Xiaoling Cheng; Yaqi Lyu; Wang Cao; Xiaoling Wang; Xiaoxia Peng

doi:10.3389/fphar.2022.935627

Signal Detection of Pediatric Drug-Induced Coagulopathy Using Routine Electronic Health Records

Front Pharmacol. 2022 Jul 20:13:935627. doi: 10.3389/fphar.2022.935627. eCollection 2022.

Authors

Xiaolu Nie^{1

2

3}, Yuncui Yu⁴, Lulu Jia⁴, Houyu Zhao², Zhenping Chen⁵, Liqiang Zhang⁶, Xiaoling Cheng⁴, Yaqi Lyu⁷, Wang Cao⁴, Xiaoling Wang⁴, Xiaoxia Peng^{1

3}

Affiliations

¹ Center for Clinical Epidemiology and Evidence-based Medicine, National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, Beijing, China.
² Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
³ Hainan Institute of Real World Data, Qionghai, China.
⁴ Department of Pharmacy, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
⁵ Hematologic Disease Laboratory, National Center for Children's Health, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, Beijing, China.
⁶ Hematology Center, National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, Beijing, China.
⁷ Department of Medical Record Management, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.

Abstract

Background: Drug-induced coagulopathy (DIC) is a severe adverse reaction and has become a significantly increased clinical problem in children. It is crucial to the detection of the DIC safety signal for drug post-marketing scientific supervision purposes. Therefore, this study aimed to detect potential signals for DIC in children using the routine electronic medical record (EMR) data. Methods: This study extracted EMR data from Beijing Children's Hospital between 2009 and 2020. A two-stage modeling method was developed to detect the signal of DIC. We calculated the crude incidence by mining cases of coagulopathy to select the potential suspected drugs; then, propensity score-matched retrospective cohorts of specific screened drugs from the first stage were constructed and estimated the odds ratio (OR) and 95% confidence interval (CI) using conditional logistic regression models. The current literature evidence was used to assess the novelty of the signal. Results:In the study, from a total of 340 drugs, 22 drugs were initially screened as potentially inducing coagulopathy. In total, we identified 19 positive DIC associations. Of these, potential DIC risk of omeprazole (OR: 2.23, 95% CI: 1.88-2.65), chlorpheniramine (OR:3.04, 95% CI:2.56-3.60), and salbutamol sulfate (OR:1.36, 95% CI:1.07-1.73) were three new DIC signals in both children and adults. Twelve associations between coagulopathy and drugs, meropenem (OR: 3.38, 95% CI: 2.72-4.20), cefoperazone sulbactam (OR: 2.80, 95% CI: 2.30-3.41), fluconazole (OR: 2.11, 95% CI: 1.71-2.59), voriconazole (OR: 2.82, 95% CI: 2.20-3.61), ambroxol hydrochloride (OR: 2.12, 95% CI: 1.74-2.58), furosemide (OR: 2.36, 95% CI: 2.08-2.67), iodixanol (OR: 2.21, 95% CI: 1.72-2.85), cefamandole (OR: 1.82, 95% CI: 1.56-2.13), ceftizoxime (OR: 1.95, 95% CI: 1.44-2.63), ceftriaxone (OR: 1.95, 95% CI: 1.44-2.63), latamoxef sodium (OR: 1.76, 95% CI: 1.49-2.07), and sulfamethoxazole (OR: 1.29, 95% CI: 1.01-1.64), were considered as new signals in children. Conclusion: The two-stage algorithm developed in our study to detect safety signals of DIC found nineteen signals of DIC, including twelve new signals in a pediatric population. However, these safety signals of DIC need to be confirmed by further studies based on population study and mechanism research.

Keywords: children; drug scientific supervision; drug-induced coagulopathy; electronic health records; post-marketing pharmacovigilance; signal detection.