Increased risk of COVID-19-related admissions in patients with active solid organ cancer in the West Midlands region of the UK: a retrospective cohort study.

OBJECTIVE: Susceptibility of patients with cancer to COVID-19 pneumonitis has been variable. We aim to quantify the risk of hospitalisation in patients with active cancer and use a machine learning algorithm (MLA) and traditional statistics to predict clinical outcomes and mortality. DESIGN: Retrospective cohort study. SETTING: A single UK district general hospital. PARTICIPANTS: Data on total hospital admissions between March 2018 and June 2020, all active cancer diagnoses between March 2019 and June 2020 and clinical parameters of COVID-19-positive admissions between March 2020 and June 2020 were collected. 526 COVID-19 admissions without an active cancer diagnosis were compared with 87 COVID-19 admissions with an active cancer diagnosis. PRIMARY AND SECONDARY OUTCOME MEASURES: 30-day and 90-day post-COVID-19 survival. RESULTS: In total, 613 patients were enrolled with male to female ratio of 1:6 and median age of 77 years. The estimated infection rate of COVID-19 was 87 of 22 729 (0.4%) in the patients with cancer and 526 of 404 379 (0.1%) in the population without cancer (OR of being hospitalised with COVID-19 if having cancer is 2.942671 (95% CI: 2.344522 to 3.693425); p<0.001). Survival was reduced in patients with cancer with COVID-19 at 90 days. R-Studio software determined the association between cancer status, COVID-19 and 90-day survival against variables using MLA. Multivariate analysis showed increases in age (OR 1.039 (95% CI: 1.020 to 1.057), p<0.001), urea (OR 1.005 (95% CI: 1.002 to 1.007), p<0.001) and C reactive protein (CRP) (OR 1.065 (95% CI: 1.016 to 1.116), p<0.008) are associated with greater 30-day and 90-day mortality. The MLA model examined the contribution of predictive variables for 90-day survival (area under the curve: 0.749); with transplant patients, age, male gender and diabetes mellitus being predictors of greater mortality. CONCLUSIONS: Active cancer diagnosis has a threefold increase in risk of hospitalisation with COVID-19. Increased age, urea and CRP predict mortality in patients with cancer. MLA complements traditional statistical analysis in identifying prognostic variables for outcomes of COVID-19 infection in patients with cancer. This study provides proof of concept for MLA in risk prediction for COVID-19 in patients with cancer and should inform a redesign of cancer services to ensure safe delivery of cancer care.

Patient with liver dysfunction while maintained on veno-venous extracorporeal membrane oxygenation should not be overlooked as a potential donor.

This report describes transplantation of liver allograft from a circulatory death donor who was supported by veno-venous extracorporeal membrane oxygenation (ECMO) for 14 days and presented with severely altered liver functions. Successful liver transplant was done in a patient with hepatocellular carcinoma (HCC) in the background of primary sclerosing cholangitis. There was immediate graft function and uneventful recovery with stable graft function at 1-year follow-up. This case illustrates the ability of veno-venous ECMO to resuscitate organs in the presence of severe dysfunction, and perhaps, lessons from this case may be incorporated to optimize the condition of organs rescued from these marginal donors and exemplify the use of ECMO in normothermic regional perfusion in donors after circulatory death.