zithromax and Chemical-and-Drug-Induced-Liver-Injury

Drug-induced liver injury (DILI) should be considered in all patients with recent elevation of liver tests without obvious etiology and normal hepatobiliary imaging. There is currently no biomarker that is helpful in diagnosis which relies on clinical and laboratory findings. Diagnosis is dependent on temporal relationship with a recently started drug or herbal and dietary supplement and elevated liver tests with exclusion of competing etiologies. The implicated agent should be discontinued and the patient should be observed closely. This is particularly important in patients with jaundice who have approximately 10% risk of liver related mortality and/or need for liver transplantation. There is no specific therapy for DILI which is only symptomatic such as for itching. Patients with jaundice and coagulopathy usually require hospitalization.

Topics: Acetylcysteine; Aged; Anti-Bacterial Agents; Anticholesteremic Agents; Atorvastatin; Azithromycin; Checklist; Chemical and Drug Induced Liver Injury; Female; Humans; Jaundice; Middle Aged; Pruritus; Symptom Assessment

Given the speed of viral infection spread, repurposing of existing drugs has been given the highest priority in combating the ongoing COVID-19 pandemic. Only drugs that are already registered or close to registration, and therefore have passed lengthy safety assessments, have a chance to be tested in clinical trials and reach patients quickly enough to help in the current disease outbreak. Here, we have reviewed available evidence and possible ways forward to identify already existing pharmaceuticals displaying modest broad-spectrum antiviral activity which is likely linked to their high accumulation in cells. Several well studied examples indicate that these drugs accumulate in lysosomes, endosomes and biological membranes in general, and thereby interfere with endosomal pathway and intracellular membrane trafficking crucial for viral infection. With the aim to identify other lysosomotropic drugs with possible inherent antiviral activity, we have applied a set of clear physicochemical, pharmacokinetic and molecular criteria on 530 existing drugs. In addition to publicly available data, we have also used our in silico model for the prediction of accumulation in lysosomes and endosomes. By this approach we have identified 36 compounds with possible antiviral effects, also against coronaviruses. For 14 of them evidence of broad-spectrum antiviral activity has already been reported, adding support to the value of this approach. Presented pros and cons, knowledge gaps and methods to identify lysosomotropic antivirals, can help in the evaluation of many drugs currently in clinical trials considered for repurposing to target COVID-19, as well as open doors to finding more potent and safer alternatives.

Topics: Anti-Inflammatory Agents; Antiviral Agents; Arrhythmias, Cardiac; Azithromycin; Betacoronavirus; Chemical and Drug Induced Liver Injury; Chloroquine; Computer Simulation; Coronavirus Infections; COVID-19; COVID-19 Drug Treatment; Drug Evaluation, Preclinical; Drug Repositioning; Endosomes; Humans; Hydrogen-Ion Concentration; Hydroxychloroquine; Intracellular Membranes; Lysosomes; Membrane Lipids; Models, Biological; Pandemics; Phospholipids; Pneumonia, Viral; SARS-CoV-2; Surface-Active Agents; Virus Internalization

Topics: Chemical and Drug Induced Liver Injury; Databases, Factual; Drug Labeling; Humans; Pharmaceutical Preparations; Risk

Topics: Aged; Anti-Bacterial Agents; Azithromycin; Chemical and Drug Induced Liver Injury; Cholestasis, Intrahepatic; Humans; Male

Antibiotics are a known cause of idiosyncratic drug-induced liver injury (DILI). According to the Centers for Disease Control and Prevention, the five most commonly prescribed antibiotics in the United States are azithromycin, ciprofloxacin, cephalexin, amoxicillin, and amoxicillin-clavulanate. We quantified the frequency of acute DILI for these common antibiotics in the All of Us Research Program, one of the largest electronic health record (EHR)-linked research cohorts in the United States. Retrospective analyses were conducted applying a standardized phenotyping algorithm to de-identified clinical data available in the All of Us database for 318,598 study participants. Between February 1984 and December 2022, more than 30% of All of Us participants (n = 119,812 individuals) had been exposed to at least 1 of our 5 study drugs. Initial screening identified 591 potential case patients that met our preselected laboratory-based phenotyping criteria. Because DILI is a diagnosis of exclusion, we then used phenome scanning to narrow the case counts by (i) scanning all EHRs to identify all alternative diagnostic explanations for the laboratory abnormalities, and (ii) leveraging International Classification of Disease 9th revision (ICD)-9 and ICD 10th revision (ICD)-10 codes as exclusion criteria to eliminate misclassification. Our final case counts were 30 DILI cases with amoxicillin-clavulanate, 24 cases with azithromycin, 24 cases with ciprofloxacin, 22 cases with amoxicillin alone, and < 20 cases with cephalexin. These findings demonstrate that data from EHR-linked research cohorts can be efficiently mined to identify DILI cases related to the use of common antibiotics.

Topics: Amoxicillin; Amoxicillin-Potassium Clavulanate Combination; Anti-Bacterial Agents; Azithromycin; Cephalexin; Chemical and Drug Induced Liver Injury; Ciprofloxacin; Humans; Population Health; Retrospective Studies; United States

A report of acute azithromycin-induced hepatocellular injury is described.. An 83-year-old male was admitted with possible community-acquired pneumonia and received azithromycin and ceftriaxone. After 2 doses of azithromycin, the patient's aspartate aminotransferase and alanine aminotransferase were greater than 3 times the upper limit of normal and continued to rise with subsequent doses. A diagnostic abdominal ultrasound revealed hepatomegaly. Total bilirubin remained within normal limits during the course. Rosuvastatin and fenofibrate were held on admission and were not resumed in the setting of elevated liver enzymes. Rivaroxaban was held in the setting of worsening renal function. Hepatitis serologies were negative. Liver enzymes, international normalized ratio (INR), and activated partial thromboplastin time (aPTT) continued to climb until hospital day 5 when azithromycin was discontinued in response. Liver enzymes, INR, aPTT, and lactate dehydrogenase all decreased from hospital days 6 through 8.. A potentially serious liver injury occurred with the initiation of azithromycin and began to resolve quickly after its discontinuation. While cholestatic injury with azithromycin is well described, this is only the third reported case of direct hepatocellular injury.

Topics: Aged, 80 and over; Azithromycin; Carcinoma, Hepatocellular; Chemical and Drug Induced Liver Injury; Humans; International Normalized Ratio; Liver Neoplasms; Male

In late 2019, a new coronavirus-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-was discovered in Wuhan, China, and the World Health Organization later declared coronavirus disease 2019 (COVID-19) a pandemic. Numerous drugs have been repurposed and investigated for therapeutic effectiveness in the disease, including those from "Solidarity," an international clinical trial (azithromycin, chloroquine, hydroxychloroquine, the fixed combination lopinavir/ritonavir, and remdesivir).. Our objective was to evaluate adverse drug reaction (ADR) reporting for drugs when used in the treatment of COVID-19 compared with use for other indications, specifically focussing on sex differences.. We extracted reports on COVID-19-specific treatments from the global ADR database, VigiBase, using an algorithm developed to identify reports that listed COVID-19 as the indication. The Solidarity trial drugs were included, as were any drugs reported ≥ 100 times. We performed a descriptive comparison of reports for the same drugs used in non-COVID-19 indications. The data lock point date was 7 June 2020.. In total, 2573 reports were identified for drugs used in the treatment of COVID-19. In order of frequency, the most reported ADRs were electrocardiogram QT-prolonged, diarrhoea, nausea, hepatitis, and vomiting in males and diarrhoea, electrocardiogram QT-prolonged, nausea, vomiting, and upper abdominal pain in females. Other hepatic and kidney-related events were included in the top ten ADRs in males, whereas no hepatic or renal terms were reported for females. COVID-19-related reporting patterns differed from non-pandemic reporting for these drugs.. Review of a global database of suspected ADR reports revealed sex differences in the reporting patterns for drugs used in the treatment of COVID-19. Patterns of ADR sex differences need further elucidation.

Topics: Abdominal Pain; Adenosine Monophosphate; Alanine; Antibodies, Monoclonal, Humanized; Antiviral Agents; Azithromycin; Chemical and Drug Induced Liver Injury; Chloroquine; COVID-19 Drug Treatment; Databases, Pharmaceutical; Diarrhea; Drug Combinations; Drug Eruptions; Drug Repositioning; Drug-Related Side Effects and Adverse Reactions; Female; Humans; Hydroxychloroquine; Long QT Syndrome; Lopinavir; Male; Nausea; Oseltamivir; Ritonavir; Sex Distribution; Sex Factors; Vomiting

The purpose of the present study is to establish a new animal model of azithromycin (AZ)-induced liver injury and study the molecular pathological change during the process. First, mice were respectively injected intraperitoneally with AZ of different high doses. Our results showed that 800 mg/kg AZ injection significantly induced liver injury in the mice, which reflected an ideal process of liver injury and repair. In this study, we analyzed the molecular pathological changes during the process by hematoxylin and eosin staining, immunohistochemistry, Western blot, and quantitative real-time reverse transcription polymerase chain reaction in the liver of mice at 0, 12, 24, 48, and 72 h after 800 mg/kg injection. Our results showed that the expression of heat shock protein 70, proliferating cell nuclear antigen, vascular endothelial growth factor, caspase 3, and cytochrome P450 2E1 were significantly differently expressed during liver injury induced by 800 mg/kg AZ in mice. Our results will be conducive for further study of the pathogenesis and prevention of drug-induced liver injury.

Topics: Animals; Anti-Bacterial Agents; Apoptosis; Azithromycin; Blotting, Western; Caspase 3; Chemical and Drug Induced Liver Injury; Cytochrome P-450 CYP2E1; Disease Models, Animal; Dose-Response Relationship, Drug; Gene Expression; HSP70 Heat-Shock Proteins; Immunohistochemistry; Liver; Male; Mice, Inbred BALB C; Proliferating Cell Nuclear Antigen; Vascular Endothelial Growth Factor A

Rare cases of azithromycin-induced hepatotoxicity have been reported, with variable clinical and histologic features. We characterized clinical features and outcomes of azithromycin-induced liver injury.. We identified patients with azithromycin-induced liver injury from the Drug-Induced Liver Injury Network Prospective Study who had causality scores of definite, highly likely, or probable. Demographic, clinical, and laboratory data and 6-month outcomes were examined.. Eighteen patients (72% female; mean age, 37 y) had causality scores of definite (n = 1), highly likely (n = 9), or probable (n = 8). Common presenting symptoms were jaundice, abdominal pain, nausea, and/or pruritus. For 16 patients, abnormal results from liver tests were first detected 14 days after azithromycin cessation (range, 9-20 d). The median duration of azithromycin treatment was 4 days (range, 2-7 d). The pattern of injury was hepatocellular in 10 patients, cholestatic in 6 patients, and mixed in 2 patients. The mean peak level of alanine aminotransferase was 2127 IU/L, of alkaline phosphatase was 481 IU/L, and of total bilirubin was 9.2 mg/dL. Liver histology showed ductopenia and veno-occlusive changes in a few patients. Two individuals had severe hypersensitivity cutaneous reactions. After 6 months, 8 patients had recovered, 4 patients had chronic injury, 1 patient died, and 1 patient underwent liver transplantation (outcomes were unavailable for 4 patients). Two of the patients who died or underwent liver transplantation had underlying chronic liver disease.. Azithromycin-induced liver injury occurs within 1 to 3 weeks after azithromycin initiation and predominantly is hepatocellular in nature. Although most patients recover fully, severe cutaneous reactions, chronic injury, and serious complications leading to death or liver transplantation can occur (ClinicalTrials.gov identifier, NCT00345930).

Topics: Adolescent; Adult; Aged; Anti-Bacterial Agents; Azithromycin; Chemical and Drug Induced Liver Injury; Child; Child, Preschool; Female; Histocytochemistry; Humans; Infant; Liver; Male; Middle Aged; Prospective Studies; Survival Analysis; Time Factors; Young Adult

The bile salt export pump (BSEP) is expressed at the canalicular domain of hepatocytes, where it serves as the primary route of elimination for monovalent bile acids (BAs) into the bile canaliculi. The most compelling evidence linking dysfunction in BA transport with liver injury in humans is found with carriers of mutations that render BSEP nonfunctional. Based on mounting evidence, there appears to be a strong association between drug-induced BSEP interference and liver injury in humans; however, causality has not been established. For this reason, drug-induced BSEP interference is best considered a susceptibility factor for liver injury as other host- or drug-related properties may contribute to the development of hepatotoxicity. To better understand the association between BSEP interference and liver injury in humans, over 600 marketed or withdrawn drugs were evaluated in BSEP expressing membrane vesicles. The example of a compound that failed during phase 1 human trials is also described, AMG 009. AMG 009 showed evidence of liver injury in humans that was not predicted by preclinical safety studies, and BSEP inhibition was implicated. For 109 of the drugs with some effect on in vitro BSEP function, clinical use, associations with hepatotoxicity, pharmacokinetic data, and other information were annotated. A steady state concentration (C(ss)) for each of these annotated drugs was estimated, and a ratio between this value and measured IC₅₀ potency values were calculated in an attempt to relate exposure to in vitro potencies. When factoring for exposure, 95% of the annotated compounds with a C(ss)/BSEP IC₅₀ ratio ≥ 0.1 were associated with some form of liver injury. We then investigated the relationship between clinical evidence of liver injury and effects to multidrug resistance-associated proteins (MRPs) believed to play a role in BA homeostasis. The effect of 600+ drugs on MRP2, MRP3, and MRP4 function was also evaluated in membrane vesicle assays. Drugs with a C(ss)/BSEP IC₅₀ ratio ≥ 0.1 and a C(ss)/MRP IC₅₀ ratio ≥ 0.1 had almost a 100% correlation with some evidence of liver injury in humans. These data suggest that integration of exposure data, and knowledge of an effect to not only BSEP but also one or more of the MRPs, is a useful tool for informing the potential for liver injury due to altered BA transport.

Topics: Animals; ATP Binding Cassette Transporter, Subfamily B; ATP Binding Cassette Transporter, Subfamily B, Member 11; ATP-Binding Cassette Transporters; Biological Transport; Chemical and Drug Induced Liver Injury; Cluster Analysis; Drug-Related Side Effects and Adverse Reactions; Humans; Liver; Male; Multidrug Resistance-Associated Proteins; Pharmacokinetics; Rats; Rats, Sprague-Dawley; Recombinant Proteins; Risk Assessment; Risk Factors; Toxicity Tests

Drug-induced liver injury is the most common cause of market withdrawal of pharmaceuticals, and thus, there is considerable need for better prediction models for DILI early in drug discovery. We present a study involving 223 marketed drugs (51% associated with clinical hepatotoxicity; 49% non-hepatotoxic) to assess the concordance of in vitro bioactivation data with clinical hepatotoxicity and have used these data to develop a decision tree to help reduce late-stage candidate attrition. Data to assess P450 metabolism-dependent inhibition (MDI) for all common drug-metabolizing P450 enzymes were generated for 179 of these compounds, GSH adduct data generated for 190 compounds, covalent binding data obtained for 53 compounds, and clinical dose data obtained for all compounds. Individual data for all 223 compounds are presented here and interrogated to determine what level of an alert to consider termination of a compound. The analysis showed that 76% of drugs with a daily dose of <100 mg were non-hepatotoxic (p < 0.0001). Drugs with a daily dose of ≥100 mg or with GSH adduct formation, marked P450 MDI, or covalent binding ≥200 pmol eq/mg protein tended to be hepatotoxic (∼ 65% in each case). Combining dose with each bioactivation assay increased this association significantly (80-100%, p < 0.0001). These analyses were then used to develop the decision tree and the tree tested using 196 of the compounds with sufficient data (49% hepatotoxic; 51% non-hepatotoxic). The results of these outcome analyses demonstrated the utility of the tree in selectively terminating hepatotoxic compounds early; 45% of the hepatotoxic compounds evaluated using the tree were recommended for termination before candidate selection, whereas only 10% of the non-hepatotoxic compounds were recommended for termination. An independent set of 10 GSK compounds with known clinical hepatotoxicity status were also assessed using the tree, with similar results.

Topics: Chemical and Drug Induced Liver Injury; Cytochrome P-450 Enzyme Inhibitors; Cytochrome P-450 Enzyme System; Decision Trees; Drug Evaluation, Preclinical; Drug-Related Side Effects and Adverse Reactions; Glutathione; Humans; Liver; Pharmaceutical Preparations; Protein Binding

We developed a semi-automated active monitoring system that uses sequential matched-cohort analyses to assess drug safety across a distributed network of longitudinal electronic health-care data. In a retrospective analysis, we show that the system would have identified cerivastatin-induced rhabdomyolysis. In this study, we evaluated whether the system would generate alerts for three drug-outcome pairs: rosuvastatin and rhabdomyolysis (known null association), rosuvastatin and diabetes mellitus, and telithromycin and hepatotoxicity (two examples for which alerting would be questionable). Over >5 years of monitoring, rate differences (RDs) in comparisons of rosuvastatin with atorvastatin were -0.1 cases of rhabdomyolysis per 1,000 person-years (95% confidence interval (CI): -0.4, 0.1) and -2.2 diabetes cases per 1,000 person-years (95% CI: -6.0, 1.6). The RD for hepatotoxicity comparing telithromycin with azithromycin was 0.3 cases per 1,000 person-years (95% CI: -0.5, 1.0). In a setting in which false positivity is a major concern, the system did not generate alerts for the three drug-outcome pairs.

Topics: Aged; Anti-Bacterial Agents; Azithromycin; Chemical and Drug Induced Liver Injury; Diabetes Mellitus; Drug Monitoring; Electronic Data Processing; Electronic Health Records; Female; Humans; Hydroxymethylglutaryl-CoA Reductase Inhibitors; Ketolides; Male; Outcome Assessment, Health Care; Product Surveillance, Postmarketing; Retrospective Studies; Rhabdomyolysis

Drug-induced liver injury (DILI) is a significant concern in drug development due to the poor concordance between preclinical and clinical findings of liver toxicity. We hypothesized that the DILI types (hepatotoxic side effects) seen in the clinic can be translated into the development of predictive in silico models for use in the drug discovery phase. We identified 13 hepatotoxic side effects with high accuracy for classifying marketed drugs for their DILI potential. We then developed in silico predictive models for each of these 13 side effects, which were further combined to construct a DILI prediction system (DILIps). The DILIps yielded 60-70% prediction accuracy for three independent validation sets. To enhance the confidence for identification of drugs that cause severe DILI in humans, the "Rule of Three" was developed in DILIps by using a consensus strategy based on 13 models. This gave high positive predictive value (91%) when applied to an external dataset containing 206 drugs from three independent literature datasets. Using the DILIps, we screened all the drugs in DrugBank and investigated their DILI potential in terms of protein targets and therapeutic categories through network modeling. We demonstrated that two therapeutic categories, anti-infectives for systemic use and musculoskeletal system drugs, were enriched for DILI, which is consistent with current knowledge. We also identified protein targets and pathways that are related to drugs that cause DILI by using pathway analysis and co-occurrence text mining. While marketed drugs were the focus of this study, the DILIps has a potential as an evaluation tool to screen and prioritize new drug candidates or chemicals, such as environmental chemicals, to avoid those that might cause liver toxicity. We expect that the methodology can be also applied to other drug safety endpoints, such as renal or cardiovascular toxicity.

Topics: Animals; Anti-Infective Agents; Anti-Inflammatory Agents; Chemical and Drug Induced Liver Injury; Databases, Factual; Drug-Related Side Effects and Adverse Reactions; Humans; Liver; Models, Biological; Predictive Value of Tests

Drug-induced liver injury is one of the main causes of drug attrition. The ability to predict the liver effects of drug candidates from their chemical structures is critical to help guide experimental drug discovery projects toward safer medicines. In this study, we have compiled a data set of 951 compounds reported to produce a wide range of effects in the liver in different species, comprising humans, rodents, and nonrodents. The liver effects for this data set were obtained as assertional metadata, generated from MEDLINE abstracts using a unique combination of lexical and linguistic methods and ontological rules. We have analyzed this data set using conventional cheminformatics approaches and addressed several questions pertaining to cross-species concordance of liver effects, chemical determinants of liver effects in humans, and the prediction of whether a given compound is likely to cause a liver effect in humans. We found that the concordance of liver effects was relatively low (ca. 39-44%) between different species, raising the possibility that species specificity could depend on specific features of chemical structure. Compounds were clustered by their chemical similarity, and similar compounds were examined for the expected similarity of their species-dependent liver effect profiles. In most cases, similar profiles were observed for members of the same cluster, but some compounds appeared as outliers. The outliers were the subject of focused assertion regeneration from MEDLINE as well as other data sources. In some cases, additional biological assertions were identified, which were in line with expectations based on compounds' chemical similarities. The assertions were further converted to binary annotations of underlying chemicals (i.e., liver effect vs no liver effect), and binary quantitative structure-activity relationship (QSAR) models were generated to predict whether a compound would be expected to produce liver effects in humans. Despite the apparent heterogeneity of data, models have shown good predictive power assessed by external 5-fold cross-validation procedures. The external predictive power of binary QSAR models was further confirmed by their application to compounds that were retrieved or studied after the model was developed. To the best of our knowledge, this is the first study for chemical toxicity prediction that applied QSAR modeling and other cheminformatics techniques to observational data generated by the means of automate

Topics: Animals; Chemical and Drug Induced Liver Injury; Cluster Analysis; Databases, Factual; Humans; MEDLINE; Mice; Models, Chemical; Molecular Conformation; Quantitative Structure-Activity Relationship

Drug-induced liver injury is a major issue of concern and has led to the withdrawal of a significant number of marketed drugs. An understanding of structure-activity relationships (SARs) of chemicals can make a significant contribution to the identification of potential toxic effects early in the drug development process and aid in avoiding such problems. This process can be supported by the use of existing toxicity data and mechanistic understanding of the biological processes for related compounds. In the published literature, this information is often spread across diverse sources and can be varied and unstructured in quality and content. The current work has explored whether it is feasible to collect and use such data for the development of new SARs for the hepatotoxicity endpoint and expand upon the limited information currently available in this area. Reviews of hepatotoxicity data were used to build a structure-searchable database, which was analyzed to identify chemical classes associated with an adverse effect on the liver. Searches of the published literature were then undertaken to identify additional supporting evidence, and the resulting information was incorporated into the database. This collated information was evaluated and used to determine the scope of the SARs for each class identified. Data for over 1266 chemicals were collected, and SARs for 38 classes were developed. The SARs have been implemented as structural alerts using Derek for Windows (DfW), a knowledge-based expert system, to allow clearly supported and transparent predictions. An evaluation exercise performed using a customized DfW version 10 knowledge base demonstrated an overall concordance of 56% and specificity and sensitivity values of 73% and 46%, respectively. The approach taken demonstrates that SARs for complex endpoints can be derived from the published data for use in the in silico toxicity assessment of new compounds.

Topics: Chemical and Drug Induced Liver Injury; Databases, Factual; Humans; Structure-Activity Relationship; Tetracyclines; Thiophenes

Drug-induced liver injury (DILI) is one of the most important reasons for drug development failure at both preapproval and postapproval stages. There has been increased interest in developing predictive in vivo, in vitro, and in silico models to identify compounds that cause idiosyncratic hepatotoxicity. In the current study, we applied machine learning, a Bayesian modeling method with extended connectivity fingerprints and other interpretable descriptors. The model that was developed and internally validated (using a training set of 295 compounds) was then applied to a large test set relative to the training set (237 compounds) for external validation. The resulting concordance of 60%, sensitivity of 56%, and specificity of 67% were comparable to results for internal validation. The Bayesian model with extended connectivity functional class fingerprints of maximum diameter 6 (ECFC_6) and interpretable descriptors suggested several substructures that are chemically reactive and may also be important for DILI-causing compounds, e.g., ketones, diols, and α-methyl styrene type structures. Using Smiles Arbitrary Target Specification (SMARTS) filters published by several pharmaceutical companies, we evaluated whether such reactive substructures could be readily detected by any of the published filters. It was apparent that the most stringent filters used in this study, such as the Abbott alerts, which captures thiol traps and other compounds, may be of use in identifying DILI-causing compounds (sensitivity 67%). A significant outcome of the present study is that we provide predictions for many compounds that cause DILI by using the knowledge we have available from previous studies. These computational models may represent cost-effective selection criteria before in vitro or in vivo experimental studies.

Topics: Bayes Theorem; Chemical and Drug Induced Liver Injury; Humans; Ligands

A case of azithromycin-induced hepatotoxicity in a 69-year-old woman with no history of liver disease is reported.. After receiving four days of high-dose azithromycin for the treatment of suspected bronchitis, a 69-year-old woman arrived at the emergency room with nausea, vomiting, diarrhea, elevated liver enzyme values, and visible signs of pruritus and jaundice. Her medical history included hypertension, hypothyroidism secondary to Graves disease, depression, dyslipidemia, and chronic obstructive pulmonary disease. She had no history of liver, cardiac, genitourinary, and renal diseases. Causes of primary liver injury, including metabolic, viral, and autoimmune liver diseases, were excluded. Her International Normalized Ratio was elevated, and substantial transaminitis was noted. There was no evidence of portal vein thrombosis on ultrasound, and extrahepatic obstruction was unlikely. Liver injury associated with right heart failure was unlikely, as right ventricular function was relatively preserved and right atrial pressure was not severely elevated. Ischemic hepatitis was also ruled out. After exclusion of other causes of liver disease, drug-induced hepatotoxicity was considered. A careful review of her medications prior to admission was conducted. A temporal relationship between initiation of azithromycin and the onset of clinical signs and symptoms was noted. The Naranjo et al. probability scale indicated a possible relationship between azithromycin and hepatotoxicity; however, two scales specifically used for evaluating drug-induced liver disease indicated a probable adverse drug-associated event.. A 69-year-old woman developed cholestatic hepatitis after four days of therapy with high-dose azithromycin for the treatment of suspected bronchitis.

Topics: Aged; Anti-Bacterial Agents; Azithromycin; Bronchitis; Chemical and Drug Induced Liver Injury; Female; Humans; Liver Function Tests

Topics: Anti-Bacterial Agents; Azithromycin; Chemical and Drug Induced Liver Injury; Humans; Infusions, Intravenous

Topics: Adult; Anti-Bacterial Agents; Anticholesteremic Agents; Azithromycin; Biopsy; Chemical and Drug Induced Liver Injury; Cholestasis; Cholestyramine Resin; Female; Humans; Jaundice; Plasmapheresis

Topics: Acute Kidney Injury; Aged; Anti-Bacterial Agents; Azithromycin; Bronchitis; Chemical and Drug Induced Liver Injury; Drug Hypersensitivity; Humans; Male

Topics: Acute Disease; Anti-Bacterial Agents; Azithromycin; Chemical and Drug Induced Liver Injury; Cholestasis, Intrahepatic; Female; Humans; Middle Aged