Liver Transplantation and Coronavirus Disease 2019 (COVID-19)

Overview

The COVID-19 pandemic together with the strategies that are applied to control it are generating high morbidity and mortality worldwide. Its impact on health systems is worrisome, affecting all the population, even those who are not infected or at risk. The indirect impact of the COVID-19 pandemic on the access to the medical care of patients on the waiting list for organ transplantation might be multifactorial, including the need to relocate health-related resources (medical personnel, supplies, critical care unit beds, etc), the risk of COVID-19 transmission among donors or patients on the waiting list, and also after transplantation. Additionally, the pandemic reduces significantly the donor pool. We consider that it is important to assess the impact that the pandemic has in particular individual populations, such as in patients requiring a liver transplant. Along with the lockdown, the rate of organ donation has dropped, and liver transplant programs across the world have reduced or suspended their activity. Unfortunately, this is invariably associated with an increase in mortality on the waiting list. Knowing the impact of the pandemic on patients who require a liver transplant will provide tools to understand and plan the health resources related to the care of these patients, not only at present but also in the following years.

The COVID-19 pandemic together with the strategies that are applied to control it is generating high morbidity and mortality worldwide. Its impact on health systems is worrisome, affecting all the population, even those who are not infected or at risk. The indirect impact of the COVID-19 pandemic on the access to the medical care of patients on the waiting list for organ transplantation might be multifactorial, including the need to relocate health-related resources (medical personnel, supplies, critical care unit beds, etc), the risk of COVID-19 transmission among donors or patients on the waiting list, and also after transplantation. Additionally, the pandemic reduces significantly the donor pool. We consider that it is important to assess the impact that the pandemic has in particular individual populations, such as in patients requiring a liver transplant. Along with the lockdown, the rate of organ donation has dropped, and liver transplant programs across the world have reduced or suspended their activity. Unfortunately, this is invariably associated with an increase in mortality on the waiting list. Knowing the impact of the pandemic on patients who require a liver transplant will provide tools to understand and plan the health resources related to the care of these patients, not only at present but also in the following years. The primary objectives of the study will be To Compare the following outcomes in patients requiring liver transplantation during the epidemiological weeks of COVID-19 pandemic in Argentina and the same weeks of 2019 according to national data registry of procurement and transplantation: 1. Number of patients registered on the liver transplant waiting list 2. Number of deaths on the liver transplant waiting list 3. Number of liver transplants For this purpose, we will carry out a time series analyses using the national data registry of procurement and transplantation database. The effect of both periods will be analysed as time interrupted series, which is a quasi-experimental design. The following two periods will be compared as segments of the interrupted time series: * Baseline period (Period not exposed to the pandemic represented by the same epidemiological weeks of 2019 ) * Pandemic period COVID-19. (Period between the epidemiological weeks of 2020 affected by the pandemic declared by the WHO from 11/March/2020) The unit of analysis will be the epidemiological weeks, and the study population will be all Argentinian over 17 years of age. Regarding patients who require liver transplantation, those who registered for isolated liver transplantation in the National Procurement and Transplant Institute will be included. A Poisson regression model will be used to assess the association between the period and the incidence of the events of interest. ARIMA models will be used following the 4 steps proposed by Box and Jenkings