RESUMO
BACKGROUND: The novel coronavirus has a high mortality rate (over 1% for patients older than 50 years). This can only be partially ascribed to other comorbidities. A possible explanation is a factor that assures a prompt response to SARS-CoV-2 in younger people, independent from the novelty of the virus itself. A factor is believed to stimulate the immune system and provide immunity against more antigens. The only external stimulation received by healthy people is vaccination (eg, the diphtheria, tetanus, and pertussis [DTP] vaccine). One hypothesis is that vaccination helps develop specific immunity but generates sprouting immunity against antigens in transit. The underlying immunological phenomena are the "bystander effect" and "trained immunity." The developed immunity gives protection for years until it naturally fades out. After the fifth decade of life, the immune system is almost incompetent when a viral infection occurs, and thus, at this stage, the novel coronavirus can enter the body and cause acute respiratory distress syndrome. OBJECTIVE: The initial aim is to demonstrate that blood monocytes and natural killer cells show overpowering hyperactivity, while CD4+ and CD8+ T cells experience impediments to their defensive functions in patients with severe SARS-CoV-2 infection. The secondary objectives are to correlate clinical data and vaccination history with laboratory immune patterns in order to identify protective factors. Subsequently, we are also interested in characterizing the phenotypes and state of the degree of activation of peripheral blood mononuclear cells, including monocytes, natural killer cells, and CD4+ and CD8+ T cells, in healthy subjects vaccinated with the Pfizer vaccine. METHODS: Data will be collected using the following 3 approaches: (1) an experimental analysis to study the innate immune response and to identify genetic profiles; (2) an epidemiological analysis to identify the patients' vaccination history; and (3) a clinical analysis to detect the immunological profile. RESULTS: The protocol was approved by the Ethics Committee on April 16, 2020, and the study started on April 27, 2020. As of February 2021, enrollment has been completed. Immunological analysis is ongoing, and we expect to complete this analysis by December 2022. CONCLUSIONS: We will recognize different populations of patients, each one with a specific immunological pattern in terms of cytokines, soluble factor serum levels, and immune cell activity. Anamnestic data, such as preceding vaccinations and comorbidities, biochemical findings like lymphocyte immunophenotyping, and pre-existing persistent cytomegalovirus infection, allow depicting the risk profile of severe COVID-19. Proof of the roles of these immunological phenomena in the development of COVID-19 can be the basis for the implementation of therapeutic immunomodulatory treatments. TRIAL REGISTRATION: ClinicalTrials.gov NCT04375176; https://clinicaltrials.gov/ct2/show/NCT04375176. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/29892.
RESUMO
BACKGROUND: Renal transplantation is the gold standard treatment for end-stage renal disease, however, in 20% of cases, the graft develops a delayed graft function (DGF) that is associated with both early and late worsening of the outcome. The aim of this study was to examine and validate in a population of transplanted patients the appropriateness of the predictive score systems of DGF available to identify patients who might take advantage of a tailored immunosuppressive therapy. MATERIALS AND METHODS: We conducted a systematic review of the literature to identify articles concerning scoring systems predicting DGF to identify those applicable to the study population and subsequently comparing their appropriateness for defining the most accurate one. RESULTS: From an analysis of the scientific literature, we found 7 scoring systems predicting DGF. Of these, 3 can be calculated for the study population. We enrolled 247 renal transplants in the study. DGF was recorded in 41 cases (15.95%). The Irish score recognized 25 of 41 cases (60.98%), the Jeldres score 41 of 41 cases (100%), and the Chapal score only 7 of 41 (17.07%). Although the Irish score did not identify all cases of DGF, the analysis of data revealed that it is the most accurate, with area under the receiver operating characteristic almost overlapping. CONCLUSIONS: The study resulted in some interesting and promising conclusions about the predictability of DGF, defining the Irish score as the most reliable. This result can be considered the fundamental requirement to develop a custom therapeutic algorithm to be applied to all recipients with higher probability of developing DGF.