The case of a liver-transplant recipient with severe acute respiratory syndrome coronavirus 2 infection who had a favorable outcome.
Kazuhiko HayashiYuki ItoRyosuke YamaneMichiyo YoshizakiKomei MatsushitaGo KajikawaTakashi KozawaTaro MizutaniYuko ShimizuKenichi NaganoKosuke TachiKentaro YoshiokaHidemi GotoPublished in: Clinical journal of gastroenterology (2021)
The outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified in 2019; thereafter, the COVID-19 outbreak became a health emergency of international concern. The impact of COVID-19 on liver-transplant recipients is unclear. Thus, it is currently unknown whether liver-transplant recipients are at a higher risk of developing complications related to COVID-19. Here, we report the case of liver-transplant recipients who were infected with SARS-CoV-2. A 20-year-old man who had undergone living-donor liver transplantation from his father at 5 years of age because of congenital biliary atresia was referred to our hospital for SARS-CoV-2 infection. Chest computed tomography did not show any abnormalities; however, laboratory results revealed liver dysfunction. He received tacrolimus as maintenance therapy that was continued at the same dose. He has not developed severe pulmonary disease and was discharged after 10 days of hospitalization. Limited data are available on post-transplant patients with COVID-19, and this case of a young patient without metabolic comorbidities did not show any association of severe COVID-19 under tacrolimus treatment. The progression of COVID-19 in liver-transplant recipients is complex, and COVID-19 risk should be evaluated in each patient until the establishment of optimal guidelines.
Keyphrases
- respiratory syndrome coronavirus
- sars cov
- coronavirus disease
- computed tomography
- healthcare
- emergency department
- mental health
- stem cells
- case report
- magnetic resonance
- big data
- pulmonary hypertension
- positron emission tomography
- magnetic resonance imaging
- machine learning
- single cell
- climate change
- mesenchymal stem cells
- risk factors
- cell therapy
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