PLoS ONE (Jan 2022)

A logistic regression model based on inpatient health records to predict drug-induced liver injury caused by ramipril-An angiotensin-converting enzyme inhibitor.

  • Phuong Nguyen Thi Thu,
  • Mai Ngo Thi Quynh,
  • Hung Nguyen Van,
  • Hoi Nguyen Thanh,
  • Khue Pham Minh

DOI
https://doi.org/10.1371/journal.pone.0272786
Journal volume & issue
Vol. 17, no. 8
p. e0272786

Abstract

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Drug-induced liver injury (DILI) is a rare side effect of angiotensin-converting enzyme inhibitors (ACEIs). Ramipril is a widely used ACE compound because of its effectiveness in the treatment of hypertension and heart failure, as well as its low risk of adverse effects. However, the clinical features of ramipril, and the risk of DILI, have not been adequately studied. A retrospective cohort study was performed based on data from 3909 inpatients to compare the risk of DILI conferred by ramipril and other ACEIs. A logistic regression model was then constructed and validated against data from 1686 patients using ramipril, of which 117 patients were diagnosed with DILI. The use of ramipril increased the risk of DILI by 2.68 times (odds ratio = 2.68; 95% confident interval (CI):1.96-3.71) compared with the group using other ACEIs. The clinical features of DILI in the ramipril group were similar to those from the ACEI group (P>0.05), except that the ALT level was higher (P<0.05). A logistic regression model including Body mass index (BMI), comorbidity, liver disease, daily dose, alanine aminotransferase (ALT), and alkaline phosphatase (ALP) was built and successfully validated for DILI risk prediction, with the area under the receiver operating characteristic curve of the model of 0.82 (95% CI: 0.752-0.888). We recommend that clinicians should be aware of the levels of ALT and ALP as well as BMI, comorbidities, and liver disease before prescribing ramipril to avoid the risk of DILI in patients.