Metformin-Induced Acute Hepatitis

Mian, Arooj; Fawwaz, Baha Aldeen Bani; Singh, Gurdeep; Farooq, Aimen; Koteish, Ayman

doi:10.7759/cureus.38908

Cited by 4 publications

(2 citation statements)

References 9 publications

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“…The speci c reason for a metformin-induced increase in the frailty index remain unclear. Previous studies have suggested several possible factors: 1) lactic acidosis [34] , 2) induced hepatotoxicity such as acute hepatitis [35] , 3) hypoglycemia [36] , 4) gastrointestinal adverse reactions including nausea, vomiting, and diarrhea [37] , and 5) potential myasthenia. However, the link between metformin and muscular dystrophy remains uncon rmed.…”

Section: Discussionmentioning

confidence: 99%

Potential the relationship between clinical use metformin and frailty index:a Mendelian randomization study

Jiao,

Liang

2023

Preprint

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Background: Observational studies present conflicting evidence regarding the association between metformin use and the risk of an increase in the Frailty Index. Some studies suggest a significant increase, while others indicate the opposite. Objective: This study aims to explore the causal relationship between metformin use and an increased risk of the Fraility Index . Methods: We conducted a two-sample Mendelian randomization (MR) analysis using various methods: inverse-variance weighted (IVW), weighted median, MR-Egger regression, simple mode, and weighted mode. Publicly available summary statistics datasets from genome-wide association studies (GWAS) meta-analyses were utilized. These datasets focused on metformin use in individuals of European descent (n = 462933) as the exposure variable, and a GWAS on doctor-diagnosed frailty index increase in individuals from the UK Biobank (n =175226) as the outcome variable. Additionally, we validated the outcomes using data from another group of metformin patients. Results: We identified 61 single nucleotide polymorphisms (SNPs) associated with metformin use at genome-wide significance as instrumental variables (P<1e-5; linkage disequilibrium r2 <0.001). The IVW (b = 2.646518, SE = 0.3763135, P = 2.03E-12), MR-Egger regression (b = 1.986775, SE = 1.4747723, P = 1.83E-01), simple mode (b = 3.450373, SE = 1.0903862, P = 2.44E-03), weighted median (b = 2.388585, SE = 0.4366406, P =4.49E-08), and Weighted mode (b = 3.08067, SE = 0.9913658, P =2.88E-03) methods all indicated a potential causal relationship between metformin use and the frailty index. Cochran’s Q test and funnel plot analysis showed no evidence of heterogeneity or asymmetry, suggesting no directional pleiotropy. Similar trends were observed in both forward and reverse validation within an additional 49 datasets. Conclusion: Our MR analysis findings suggest a potential causal relationship between metformin use and an increase risk of frailty index.

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Section: Discussionmentioning

confidence: 99%

Potential the relationship between clinical use metformin and frailty index:a Mendelian randomization study

Jiao,

Liang

2023

Preprint

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“…Focusing on new drugs causing iDILI, a selection of reports is listed using exclusively the updated RUCAM (Table 11) [60,94,95,. • Atezolizumab score 7, probable Tzadok, 2022 [111] • Durvalumab score 6 or 7, probable Swanson, 2022 [112] • Ceftriaxone score 6, probable Asif, 2023 [113] • Enoxaparin score 8, probable Eze, 2023 [114] • Favipiravir score 6, probable Yamazaki, 2021 [115] • Fluoroquinolones scores 6-8, probable; score ≥9, highly probable Yang, 2019 [116] • Girosivan score 8, probable Ma, 2023 [117] • Ibuprofen score 8, probable Deng, 2022 [118] • Iguratimod Score 9, highly probable Li, 2018 [119] • Ipragliflozin score 7, probable Niijima, 2017 [120] • Liraglutide score 8, probable Inayat, 2023 [121] • Metformin score 10, highly probable Mian, 2023 [122] • Methotrexate scores 6-8, probable; ≥9, highly probable Qin, 2022 [123] • Nevirapine scores 6-8, probable Giacomelli, 2018 [124] Table 11. Cont.…”

Section: Updated Rucam In Idili Cases With New Drugsmentioning

confidence: 99%

Idiosyncratic DILI and RUCAM under One Hat: The Global View

Teschke,

Danan

2023

Livers

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Drugs are prescribed worldwide to treat diseases but with the risk of idiosyncratic drug-induced liver injury (iDILI). The most important difficulty is how best to establish causality. Based on strong evidence and principles of artificial intelligence (AI) to solve complex processes through quantitative algorithms using scored elements, progress was achieved with the Roussel Uclaf Causality Assessment Method (RUCAM) in its original and updated versions, often viewed now as the gold standard. As a highly appreciated diagnostic algorithm, the RUCAM is in global use with around 100,000 iDILI cases published worldwide using RUCAM to assess causality, largely outperforming any other specific causality assessment tool in terms of case numbers. Consequently, the RUCAM helps to establish a list of top-ranking drugs worldwide implicated in iDILI and to describe clinical and mechanistic features of iDILI caused by various drugs. In addition, the RUCAM was recently applied in iDILI cases of patients treated for coronavirus disease 2019 (COVID-19) infections or cancer patients treated with immune checkpoint inhibitors (ICIs), as well as in the search for new treatment options with conventional drugs in iDILI. Analyses of RUCAM-based iDILI cases are helpful to support pathogenetic steps like immune reactions, genetic predisposition as evidenced by human leucocyte antigens (HLA) genotypes for selected drugs, and the role of the gut microbiome. To achieve consistency in data collection, analysis, and specific clinical and pathogenetic presentation, researchers, regulatory agencies, and pharmaceutical firms should place iDILI and the updated RUCAM as the causality tool under one and the same hat in review articles and clinical guidelines for the diagnosis and treatment of iDILI.

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