A case of meropenem-induced liver injury and jaundice

Risk evaluation of carbapenem-induced liver injury based on machine learning analysis

INTRODUCTION

Information regarding carbapenem-induced liver injury is limited, and the rate of liver injury caused by meropenem (MEPM) and doripenem (DRPM) remains unknown. Decision tree (DT) analysis, a machine learning method, has a flowchart-like model where users can easily predict the risk of liver injury. Thus, we aimed to compare the rate of liver injury between MEPM and DRPM and construct a flowchart that can be used to predict carbapenem-induced liver injury.

METHODS

We investigated patients treated with MEPM (n = 310) or DRPM (n = 320) and confirmed liver injury as the primary outcome. We used a chi-square automatic interaction detection algorithm to construct DT models. The dependent variable was set as liver injury from a carbapenem (MEPM or DRPM), and factors including alanine aminotransferase (ALT), albumin-bilirubin (ALBI) score, and concomitant use of acetaminophen were used as explanatory variables.

RESULTS

The rates of liver injury were 22.9% (71/310) and 17.5% (56/320) in the MEPM and DRPM groups, respectively; no significant differences in the rate were observed (95% confidence interval: 0.710-1.017). Although the DT model of MEPM could not be constructed, DT analysis showed that the incidence of introducing DRPM in patients with ALT >22 IU/L and ALBI scores > -1.87 might be high-risk.

CONCLUSIONS

The risk of developing liver injury did not differ significantly between the MEPM and DRPM groups. Since ALT and ALBI score are evaluated in clinical settings, this DT model is convenient and potentially useful for medical staff in assessing liver injury before DRPM administration.

Drug-Induced Liver Injury: Highlights and Controversies in the Recent Literature

Drug-induced liver injury (DILI) remains an important, yet challenging diagnosis for physicians. Each year, additional drugs are implicated in DILI and this year was no different, with more than 1400 articles published on the subject. This review examines some of the most significant highlights and controversies in DILI-related research over the past year and their implications for clinical practice. Several new drugs were approved by the US Food and Drug Administration including a number of drugs implicated in causing DILI, particularly among the chemotherapeutic classes. The COVID-19 pandemic was also a major focus of attention in 2020 and we discuss some of the notable aspects of COVID-19-related liver injury and its implications for diagnosing DILI. Updates in diagnostic and causality assessments related to DILI such as the Roussel Uclaf Causality Assessment Method are included, mindful that there is still no single biomarker or diagnostic tool to unequivocally diagnose DILI. Glutamate dehydrogenase received renewed attention as being more specific than alanine aminotransferase. There were a few new reports of previously unrecognized hepatotoxins, including immune modulators and novel gene therapy drugs that we highlight. Updates and new developments of previously described hepatotoxins, such as immune checkpoint inhibitors and anti-tuberculosis drugs are reviewed. Finally, novel technologies such as organoid culture systems to better predict DILI preclinically may be coming of age and determinants of hepatocyte loss, such as calculating P_ALT are poised to improve our current means of estimating DILI severity and the risk of acute liver failure.