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Patients with coronavirus disease 19 (COVID-19) commonly show abnormalities of liver tests (LTs) of undetermined cause. Considering drugs as tentative culprits, the current systematic review searched for published COVID-19 cases with suspected drug-induced liver injury (DILI) and established diagnosis using the diagnostic algorithm of RUCAM (Roussel Uclaf Causality Assessment Method). Data worldwide on DILI cases assessed by RUCAM in COVID-19 patients were sparse. A total of 6/200 reports with initially suspected 996 DILI cases in COVID-19 patients and using all RUCAM-based DILI cases allowed for a clear description of clinical features of RUCAM-based DILI cases among COVID-19 patients: (1) The updated RUCAM published in 2016 was equally often used as the original RUCAM of 1993, with both identifying DILI and other liver diseases as confounders; (2) RUCAM also worked well in patients treated with up to 18 drugs and provided for most DILI cases a probable or highly probable causality level for drugs; (3) DILI was preferentially caused by antiviral drugs given empirically due to their known therapeutic efficacy in other virus infections; (4) hepatocellular injury was more often reported than cholestatic or mixed injury; (5) maximum LT values were found for alanine aminotransferase (ALT) 1.541 U/L and aspartate aminotransferase (AST) 1.076 U/L; (6) the ALT/AST ratio was variable and ranged from 0.4 to 1.4; (7) the mean or median age of the COVID-19 patients with DILI ranged from 54.3 to 56 years; (8) the ratio of males to females was 1.8–3.4:1; (9) outcome was favorable for most patients, likely due to careful selection of the drugs and quick cessation of drug treatment with emerging DILI, but it was fatal in 19 patients; (10) countries reporting RUCAM-based DILI cases in COVID-19 patients included China, India, Japan, Montenegro, and Spain; (11) robust estimation of the percentage contribution of RUCAM-based DILI for the increased LTs in COVID-19 patients is outside of the current scope. In conclusion, RUCAM-based DILI with its clinical characteristics in COVID-19 patients and its classification as a confounding variable is now well defined, requiring a new correct description of COVID-19 features by removing DILI characteristics as confounders.
The LiverTox database compiles cases of idiosyncratic drug-induced liver injury (iDILI) with the promised aims to help identify hepatotoxicants and provide evidence-based information on iDILI. Weaknesses of this approach include case selection merely based on published case number and not on a strong causality assessment method such as the Roussel Uclaf Causality Assessment Method (RUCAM). The aim of this analysis was to find out whether the promised aims have been achieved by comparison of current iDILI case data with those promised in 2012 in LiverTox. First, the LiverTox criteria of likelihood categories applied to iDILI cases were analyzed regarding robustness. Second, the quality was analyzed in LiverTox cases caused by 46 selected drugs implicated in iDILI. LiverTox included iDILI cases of insufficient quality because most promised details were not fulfilled: (1) Standard liver injury definition; (2) incomplete narratives or inaccurate for alternative causes; and (3) not a single case was assessed for causality with RUCAM, as promised. Instead, causality was arbitrarily judged on the iDILI case number presented in published reports with the same drug. All of these issues characterize the paradox of LiverTox, requiring changes in the method to improve data quality and database reliability. In conclusion, establishing LiverTox is recognized as a valuable effort, but the paradox due to weaknesses between promised data quality and actual data must be settled by substantial improvements, including, for instance, clear definition and identification of iDILI cases after evaluation with RUCAM to establish a robust causality grading.
Causality assessment in liver injury induced by drugs and herbs remains a debated issue, requiring innovation and thorough understanding based on detailed information. Artificial intelligence (AI) principles recommend the use of algorithms for solving complex processes and are included in the diagnostic algorithm of Roussel Uclaf Causality Assessment Method (RUCAM) to help assess causality in suspected cases of idiosyncratic drug-induced liver injury (DILI) and herb-induced liver injury (HILI). From 1993 until the middle of 2020, a total of 95,865 DILI and HILI cases were assessed by RUCAM, outperforming by case numbers any other causality assessment method. The success of RUCAM can be traced back to its quantitative features with specific data elements that are individually scored leading to a final causality grading. RUCAM is objective, user friendly, transparent, and liver injury specific, with an updated version that should be used in future DILI and HILI cases. Support of RUCAM was also provided by scientists from China, not affiliated to any network, in the results of a scientometric evaluation of the global knowledge base of DILI. They highlighted the original RUCAM of 1993 and their authors as a publication quoted the greatest number of times and ranked first in the category of the top 10 references related to DILI. In conclusion, for stakeholders involved in DILI and HILI, RUCAM seems to be an effective diagnostic algorithm in line with AI principles.
Andropogon virginicus is an invasive weed that seriously threatens agricultural production and economics worldwide. In this research, dried aerial parts of A. virginicus were extracted, applying Soxhlet and liquid-liquid phase methods to acquire the total crude (T-Anvi), hexane (H-Anvi), ethyl acetate (E-Anvi), butanol (B-Anvi), and water (W-Anvi) extracts, respectively. In which, T-Anvi contains the highest total phenolic and flavonoid contents (24.80 mg gallic acid and 37.40 mg rutin equivalents per g dry weight, respectively). Via anti-radical (ABTS and DPPH), and reducing power assays, E-Anvi exhibits the most potent activities (IC50 = 13.96, 43.59 and 124.11 µg/mL, respectively), stronger than butylated hydroxytoluene (BHT), a standard antioxidant, while the lipid peroxidation inhibitory effect of E-Anvi (LPI = 90.85% at the concentration of 500 µg/mL) is close to BHT. E-Anvi shows the most substantial inhibition (IC50 = 2.58 mg/mL) on tyrosinase. Notably, α-amylase is significantly suppressed by H-Anvi (IC50 = 0.72 mg/mL), over twice stronger than the positive control, palmitic acid. In the cytotoxic assay, E-Anvi is the strongest extract inhibiting K562 cells (IC50 = 112.01 µg/mL). Meanwhile, T-Anvi shows the highest prevention on Meg-01 expansion (IC50 = 91.40 µg/mL). Dominant compounds detected in E-Anvi by high-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (HPLC-ESI-MS/MS) are identified as flavonoids. However, among four major compounds identified in H-Anvi by gas chromatography-mass spectrometry (GC-MS), palmitic acid and phytol are the most abundant compounds with peak areas of 27.97% and 16.42%, respectively. In essence, this is the first report describing that A. virginicus is a potential natural source of antioxidants, tyrosinase and α-amylase inhibitors, and anti-chronic myeloid leukemia (CML) agents which may be useful in future therapeutics as promising alternative medicines.
Background: A large number of idiosyncratic drug induced liver injury (iDILI) and herb induced liver injury(HILI) cases of variable quality has been published but some are a matter of concern if the cases were not evaluated for causality using a robust causality assessment method (CAM) such as RUCAM (Roussel Uclaf Causality Assessment Method) as diagnostiinjuryc algorithm. The purpose of this analysis was to evaluate the worldwide use of RUCAM in iDILI and HILI cases. Methods: The PubMed database (1993–30 June 2020) was searched for articles by using the following key terms: Roussel Uclaf Causality Assessment Method; RUCAM; Idiosyncratic drug induced liver injury; iDILI; Herb induced liver injury; HILI. Results: Considering reports published worldwide since 1993, our analysis showed the use of RUCAM for causality assessment in 95,885 cases of liver injury including 81,856 cases of idiosyncratic DILI and 14,029 cases of HILI. Among the top countries providing RUCAM based DILI cases were, in decreasing order, China, the US, Germany, Korea, and Italy, with China, Korea, Germany, India, and the US as the top countries for HILI. Conclusion: Since 1993 RUCAM is certainly the most widely used method to assess causality in IDILI and HILI. This should encourage practitioner, experts, and regulatory agencies to use it in order to reinforce their diagnosis and to take sound decisions.
The spectrum of alcoholic liver disease (ALD) is broad and includes alcoholic fatty liver, alcoholic steatohepatitis, alcoholic hepatitis, alcoholic fibrosis, alcoholic cirrhosis, and alcoholic hepatocellular carcinoma, best explained as a five-hit sequelae of injurious steps. ALD is not primarily the result of malnutrition as assumed for many decades but due to the ingested alcohol and its metabolic consequences although malnutrition may marginally contribute to disease aggravation. Ethanol is metabolized in the liver to the heavily reactive acetaldehyde via the alcohol dehydrogenase (ADH) and the cytochrome P450 isoform 2E1 of the microsomal ethanol-oxidizing system (MEOS). The resulting disturbances modify not only the liver parenchymal cells but also non-parenchymal cells such as Kupffer cells (KCs), hepatic stellate cells (HSCs), and liver sinusoidal endothelial cells (LSECs). These are activated by acetaldehyde, reactive oxygen species (ROS), and endotoxins, which are produced from bacteria in the gut and reach the liver due to gut leakage. A variety of intrahepatic signaling pathways and innate or acquired immune reactions are under discussion contributing to the pathogenesis of ALD via the five injurious hits responsible for disease aggravation. As some of the mechanistic steps are based on studies with in vitro cell systems or animal models, respective proposals for humans may be considered as tentative. However, sufficient evidence is provided for clinical risk factors that include the amount of alcohol used daily for more than a decade, gender differences with higher susceptibility of women, genetic predisposition, and preexisting liver disease. In essence, efforts within the last years were devoted to shed more light in the pathogenesis of ALD, much has been achieved but issues remain to what extent results obtained from experimental studies can be transferred to humans.
One of the most difficult challenges in clinical hepatology is the diagnosis of a drug-induced liver injury (DILI). The timing of the events, exclusion of alternative causes, and taking into account the clinical context should be systematically assessed and scored in a transparent manner. RUCAM (Roussel Uclaf Causality Assessment Method) is a well-established diagnostic algorithm and scale to assess causality in patients with suspected DILI. First published in 1993 and updated in 2016, RUCAM is now the worldwide most commonly used causality assessment method (CAM) for DILI. The following manuscript highlights the recent implementation of RUCAM around the world, by reviewing the literature for publications that utilized RUCAM, and provides a review of “best practices” for the use of RUCAM in cases of suspected DILI. The worldwide appreciation of RUCAM is substantiated by the current analysis of 46,266 DILI cases, all tested for causality using RUCAM. These cases derived from 31 reports published from 2014 to early 2019. Their first authors came from 10 countries, with China on top, followed by the US, and Germany on the third rank. Importantly, all RUCAM-based DILI reports were published in high profile journals. Many other reports were published earlier from 1993 up to 2013 in support of RUCAM. Although most of the studies were of high quality, the current case analysis revealed shortcomings in few studies, not at the level of RUCAM itself but rather associated with the work of the users. To ensure in future DILI cases a better performance by the users, a list of essential elements is proposed. As an example, all suspected DILI cases should be evaluated 1) by the updated RUCAM to facilitate result comparisons, 2) according to a prospective study protocol to ensure complete data sets, 3) after exclusion of cases with herb induced liver injury (HILI) from a DILI cohort to prevent confounding variables, and 4) according to inclusion of DILI cases with RUCAM-based causality gradings of highly probable or probable, in order to increase the specificity of the results. In conclusion, RUCAM benefits from its high appreciation and performs well provided the users adhere to published recommendations to prevent confounding variability.
The current Special Issue is devoted to the broad spectrum of hepatotoxicity with its molecular mechanisms and pathophysiology, presented in eight publications. Scientists were from various countries, including the US, Mexico, the Czech Republic, Germany, Portugal, China, and Japan. Contributions considered various types of experimental and human liver injury, elicited by a number of causal conditions and substances. ...
Liver injuries caused by the use of exogenous compounds such as drugs, herbs, and alcohol are commonly well diagnosed using laboratory tests, toxin analyses, or eventually reactive intermediates generated during metabolic degradation of the respective chemical in the liver and subject to covalent binding by target proteins. Conditions are somewhat different for idiosyncratic drug induced liver injury (DILI), for which metabolic intermediates as diagnostic aids are rarely available. Although the diagnosis of idiosyncratic DILI can well be established using the validated, liver specific, structured, and quantitative RUCAM (Roussel Uclaf Causality Assessment Method), there is an ongoing search for new diagnostic biomarkers that could assist in and also confirm RUCAM-based DILI diagnoses. With respect to idiosyncratic DILI and following previous regulatory letters of recommendations, selected biomarkers reached the clinical focus, including microRNA-122, microRNA-192, cytokeratin analogues, glutamate dehydrogenase, total HMGB-1 (High Mobility Group Box), and hyperacetylated HMGB-1 proteins. However, the new parameters total HMGB-1, and even more so the acetylated HMGB-1, came under critical scientific fire after misconduct at one of the collaborating partner centers, leading the EMA to recommend no longer the exploratory hyperacetylated HMGB1 isoform biomarkers in clinical studies. The overall promising nature of the recommended biomarkers was considered by EMA as highly dependent on the outstanding results of the now incriminated biomarker hyperacetylated HMGB-1. The EMA therefore correctly decided to officially retract its Letter of Support affecting all biomarkers listed above. New biomarkers are now under heavy scrutiny that will require re-evaluations prior to newly adapted recommendations. With Integrin beta 3 (ITGB3), however, a new diagnostic biomarker may emerge, possibly being drug specific but tested in only 16 patients; due to substantial remaining uncertainties, final recommendations would be premature. In conclusion, most of the currently recommended new biomarkers have lost regulatory support due to scientific misconduct, requiring now innovative approaches and re-evaluation before they can be assimilated into clinical practice.
Among the causality assessment methods used for the diagnosis of drug-induced liver injury (DILI), Roussel Uclaf Causality Assessment Method (RUCAM) remains the most widely used not only for individual cases but also for prospective and retrospective studies worldwide. This first place is justified by the characteristics of the method such as precise definition and classification of the liver injury, which determines the right scale in the scoring system, precise definition of the seven criteria, and the validation approach based on cases with positive rechallenge. RUCAM is used not only for any types of drugs but also for herbal medicines causing herb-induced liver injury, (HILI) and dietary supplements. In 2016, the updated RUCAM provided further specifications of criteria and instructions to improve interobserver variability. Although this method was criticized for criteria such as the age and alcohol consumption, recent consensus meeting of experts has recognized their value and recommended their incorporation into any method. While early studies searching for DILI in large databases especially in electronic medical records were based on codes of diseases or natural language without causality assessment, the recommendation is now to include RUCAM in the search for DILI/HILI. There are still studies on DILI detection or the identification of biomarkers that take into consideration the cases assessed as “possible,” although it is well known that these cases reduce the strength of the association between the cases and the offending compound or the new biomarker to be validated. Attempts to build electronic RUCAM or automatized application of this method were successful despite some weaknesses to be corrected. In the future, more reflections are needed on an expert system to standardize the exclusion of alternative causes according to the clinical context. Education and training on RUCAM should be encouraged to improve the results of the studies and the day-to-day work in pharmacovigilance departments in companies or in regulatory agencies. It is also expected to improve RUCAM with biomarkers or other criteria provided that the validation process replaces expert opinion by robust standards such as those used for the original method.