Incidence, clinical features and risk factors of tacrolimus induced idiosyncratic liver injury in renal transplant recipients: A nested case-control study

Construction and validation of a meropenem-induced liver injury risk prediction model: a multicenter case-control study

Objective

To construct and validate a risk prediction model for patients with meropenem-induced liver injury (MiLI).

Methods

A retrospective case-control study was conducted to collect data on inpatients treated with meropenem at Shiyan People's Hospital, Hubei, China from January 2018 to December 2022; this study served as the model construction dataset. Univariate analysis and multiple logistic regression analysis were employed to identify the related factors for MiLI, and a nomogram risk prediction model for MiLI was constructed. The recognition ability and prediction accuracy of the model were evaluated using the receiver operating characteristic (ROC) and calibration curves. The clinical efficacy was assessed via the decision curve analysis (DCA). The internal validation was performed using the bootstrap method, and external validation was conducted based on an external dataset from Shiyan Taihe Hospital between October 2021 and December 2023.

Results

A total of 1,625 individuals were included in the model construction dataset, of which 62 occurred MiLI. The external validation dataset included 1,032 cases, with 74 patients developing liver injury. Six variables were independent factors for MiLI and included in the final prediction model: being male (OR = 2.080, 95% CI: 1.050-4.123, P = 0.036), ICU admission (OR = 8.207, 95% CI: 4.094-16.453, P < 0.001), gallbladder disease (OR = 8.240, 95% CI: 3.605-18.832, P < 0.001), baseline ALP (OR = 1.012, 95% CI: 1.004-1.019, P = 0.004), GGT (OR = 1.010, 95% CI: 1.005-1.015, P < 0.001), and PLT (OR = 0.997, 95% CI: 0.994-0.999, P = 0.020). The c-statistic value for internal validation of the prediction model was 0.821; the sensitivity and specificity were 0.997 and 0.924, respectively. The c-statistic value of the prediction model in the model construction dataset was 0.837 (95% CI, 0.789-0.885), while in the external validation dataset was 0.851 (95% CI, 0.802-0.901). The P-values of the calibration curve in the two datasets were 0.935 and 0.084, respectively.

Conclusion

Being male, ICU admission, gallbladder disease, higher levels of baseline ALP and GGT, and lower levels of baseline PLT were the risk factors for MiLI. The nomogram model built based on these factors demonstrated favorable performance in discrimination, calibration, clinical applicability, and internal-external validation. The nomogram model can assist clinicians in early identification of high-risk patients receiving meropenem, predicting the risk of MiLI, and ensuring safe medication practices.

Drug Induced Liver Injury: Highlights and Controversies in the 2023 Literature

Drug-induced liver injury (DILI) remains an active field of clinical research and investigation with more than 4700 publications appearing in 2023 relating to hepatotoxicity of all causes and injury patterns. As in years past, we have attempted to identify and summarize highlights and controversies from the past year's literature. Several new and novel therapeutic agents were approved by the US Food and Drug Administration (FDA) in 2023, a number of which were associated with significant hepatotoxicity. Updates in the diagnosis and management of DILI using causality scores as well as newer artificial intelligence-based methods were published. Details of newly established hepatotoxins as well as updated information on previously documented hepatotoxic drugs is presented. Significant updates in treatment of DILI were also included as well as reports related to global DILI registries.

Incidence, clinical classification and risk factors of cyclosporin A-induced liver injury in allogeneic haematopoietic stem cell transplant recipients

AIMS

There is limited real-world data on cyclosporin A (CsA)-induced liver injury (CILI). This study aims to investigate the incidence, clinical classification and risk factors of CILI, thereby providing evidence to inform the treatment of CILI.

METHODS

Inpatients receiving haematopoietic stem cell transplantation (HSCT) and treated with CsA were included. Patient information was collected to assess suspicious CILI by the Roussel Uclaf causality assessment method (RUCAM) scale. We evaluated the pattern and severity of CILI. The independent risk factors of CILI were identified by multivariable logistic regression.

RESULTS

A total of 216 allogeneic HSCT (allo-HSCT) recipients were included in this study. The incidence of CILI was 15.3% (95% confidence interval [CI]: 10.4%-20.1%). Among these cases, 84.8% displayed a hepatocellular pattern, and 90.9% of CILI was of mild severity. Baseline alanine aminotransferase (ALT) level (OR = 1.030, 95% CI: 1.008-1.053, P = .008) and trough concentration level of CsA (OR = 1.007, 95% CI: 1.002-1.012, P = .009) were identified as independent risk factors for CILI.

CONCLUSIONS

The incidence of CILI in allo-HSCT recipients is notably high. Recipients with elevated baseline ALT levels and higher exposure to CsA are more susceptible to developing CILI.

Tacrolimus-induced cholestatic hepatotoxicity after renal transplantation: a case report

BACKGROUND

In this manuscript, we report a case of tacrolimus-associated hepatotoxicity in a kidney transplant recipient.

CASE PRESENTATION

In this case report, a 56 years old Arab male patient who received a kidney transplant presented with icterus, weakness, and lethargy two weeks after transplantation and tacrolimus initiation. In laboratory analysis hyperbilirubinemia and a rise in hepatic enzymes were observed. All possible causes of hepatotoxicity were examined. The panel for infectious causes was negative. Drug-induced liver injury was diagnosed. The patient's immunosuppressive regimen was changed to a cyclosporine-based regimen and after this change bilirubin and hepatic enzymes decreased and the patient was discharged without signs and symptoms of hepatitis.

CONCLUSION

It seems that the patient's hyperbilirubinemia was due to tacrolimus, and the patient's bilirubin decreased after stopping tacrolimus.