Humoral and Cellular Immune Responses After a 3-dose Course of mRNA-1273 COVID-19 Vaccine in Kidney Transplant Recipients: A Prospective Cohort Study.

In kidney transplant recipients, there is discordance between the development of cellular and humoral response after vaccination against SARS-CoV-2. We sought to determine the interplay between the 2 arms of adaptive immunity in a 3-dose course of mRNA-1273 100 µg vaccine. Methods: Humoral (IgG/IgM) and cellular (N- and S-ELISpot) responses were studied in 117 kidney and 12 kidney-pancreas transplant recipients at the following time points: before the first dose, 14 d after the second dose' and before and after the third dose, with a median of 203 and 232 d after the start of the vaccination cycle, respectively. Results: After the second dose, 26.7% of naive cases experienced seroconversion. Before the third dose and in the absence of COVID-19, this percentage increased to 61.9%. After the third dose, seroconversion occurred in 80.0% of patients. Naive patients who had at any time point a detectable positivity for S-ELISpot were 75.2% of the population, whereas patients who maintained S-ELISpot positivity throughout the study were 34.3%. S-ELISpot positivity at 42 d was associated with final seroconversion (odds ratio' 3.14; 95% confidence interval' 1.10-8.96; P = 0.032). Final IgG titer was significantly higher in patients with constant S-ELISpot positivity (P < 0.001). Conclusions: A substantial proportion of kidney transplant recipients developed late seroconversion after 2 doses. Cellular immunity was associated with the development of a stronger humoral response.

A hybrid data envelopment analysis-artificial neural network prediction model for COVID-19 severity in transplant recipients.

In an overwhelming demand scenario, such as the SARS-CoV-2 pandemic, pressure over health systems may outburst their predicted capacity to deal with such extreme situations. Therefore, in order to successfully face a health emergency, scientific evidence and validated models are needed to provide real-time information that could be applied by any health center, especially for high-risk populations, such as transplant recipients. We have developed a hybrid prediction model whose accuracy relative to several alternative configurations has been validated through a battery of clustering techniques. Using hospital admission data from a cohort of hospitalized transplant patients, our hybrid Data Envelopment Analysis (DEA)-Artificial Neural Network (ANN) model extrapolates the progression towards severe COVID-19 disease with an accuracy of 96.3%, outperforming any competing model, such as logistic regression (65.5%) and random forest (44.8%). In this regard, DEA-ANN allows us to categorize the evolution of patients through the values of the analyses performed at hospital admission. Our prediction model may help guiding COVID-19 management through the identification of key predictors that permit a sustainable management of resources in a patient-centered model. Supplementary Information: The online version contains supplementary material available at 10.1007/s10462-021-10008-0.

Case report of COVID-19 in a kidney transplant recipient: Does immunosuppression alter the clinical presentation?

COVID-19 is novel infectious disease with an evolving understanding of its epidemiology and clinical manifestations. Immunocompromised patients often present atypical presentations of viral diseases. Herein we report a case of a COVID-19 infection in a solid organ transplant recipient, in which the first clinical symptoms were of gastrointestinal viral disease and fever, which further progressed to respiratory symptoms in 48 hours. In these high risk populations, protocols for screening for SARS-Cov2 may be needed to be re-evaluated.