Coronavirus disease 2019 (COVID-19) has rapidly become a global pandemic. Because the severity of the disease is highly variable, predictive models to stratify patients according to their mortality risk are needed. Our aim was to develop a model able to predict the risk of fatal outcome in patients with COVID-19 that could be used easily at the time of patients' arrival at the hospital. We constructed a prospective cohort with 611 adult patients in whom COVID-19 was diagnosed between March 10 and April 12, 2020, in a tertiary hospital in Madrid, Spain. The analysis included 501 patients who had been discharged or had died by April 20, 2020. The capacity of several biomarkers, measured at the beginning of hospitalization, to predict mortality was assessed individually. Those biomarkers that independently contributed to improve mortality prediction were included in a multivariable risk model. High IL-6 level, C-reactive protein level, lactate dehydrogenase (LDH) level, ferritin level, d-dimer level, neutrophil count, and neutrophil-to-lymphocyte ratio were all predictive of mortality (area under the curve >0.70), as were low albumin level, lymphocyte count, monocyte count, and ratio of peripheral blood oxygen saturation to fraction of inspired oxygen (SpO2/FiO2). A multivariable mortality risk model including the SpO2/FiO2 ratio, neutrophil-to-lymphocyte ratio, LDH level, IL-6 level, and age was developed and showed high accuracy for the prediction of fatal outcome (area under the curve 0.94). The optimal cutoff reliably classified patients (including patients with no initial respiratory distress) as survivors and nonsurvivors with 0.88 sensitivity and 0.89 specificity. This mortality risk model allows early risk stratification of hospitalized patients with COVID-19 before the appearance of obvious signs of clinical deterioration, and it can be used as a tool to guide clinical decision making.

An early analysis of circulating monocytes may be critical for predicting COVID-19 course and its sequelae. In 131 untreated, acute COVID-19 patients at emergency room arrival, monocytes showed decreased surface molecule expression, including low HLA-DR, in association with an inflammatory cytokine status and limited anti-SARS-CoV-2-specific T cell response. Most of these alterations had normalized in post-COVID-19 patients 6 months after discharge. Acute COVID-19 monocytes transcriptome showed upregulation of anti-inflammatory tissue repair genes such as BCL6, AREG and IL-10 and increased accessibility of chromatin. Some of these transcriptomic and epigenetic features still remained in post-COVID-19 monocytes. Importantly, a poorer expression of surface molecules and low IRF1 gene transcription in circulating monocytes at admission defined a COVID-19 patient group with impaired SARS-CoV-2-specific T cell response and increased risk of requiring intensive care or dying. An early analysis of monocytes may be useful for COVID-19 patient stratification and for designing innate immunity-focused therapies.

The clinical burden of influenza is increasing worldwide. Aging, immunosuppression, and underlying respiratory illness are determinants of poor clinical outcomes, including greater mortality. Bacterial infections seem to be the main reason. Updated information on the role of bacterial infection as the cause of complications would be of value in improving the prognosis of patients with influenza. A systematic review and meta-analysis were performed by using the PubMed repository using keywords like: Influenza, H1N1, Streptococcus pneumoniae, bacterial coinfection, secondary coinfection, bacterial complications in pneumonia, and seasonal influenza. Only articles written in English were included in publications from 2010 to 2020. The analyses were conducted following the preferred reporting items for systematic review and meta-analyses guidelines. The results were independently validated using a TrinetX database cohort of roughly 4 million patients. We included 135 studies that contained data from 48,259 patients hospitalized with influenza of any age. Bacterial infections were diagnosed in 5391 (11.2%). Streptococcus pneumoniae (30.7%) and Staphylococcus aureus (30.4%) were the most frequent microorganisms, followed by Haemophilus influenzae (7.1%) and Pseudomonas aeruginosa (5.9%). The random-effects model of the meta-analysis indicated that bacterial infections posed a 3.4-fold increased risk of death compared with influenza infection alone. Unexpectedly, asthma was protective (odds ratio 0.8). Bacterial infections diagnosed in 11.2% of patients with influenza increase 3.4-fold the mortality risk. S. pneumoniae, S. aureus, H. influenzae, and P. aeruginosa account for nearly 75% of the cases. Earlier diagnosis and use of antibiotics should improve outcomes in this population.

The Th1/Th2 balance plays a crucial role in the progression of different pathologies and is a determining factor in the evolution of infectious diseases. This work has aimed to evaluate the early, or on diagnosis, T-cell compartment response, T-helper subsets and anti-SARS-CoV-2 antibody specificity in COVID-19 patients and to classify them according to evolution based on infection severity. A unicenter, randomized group of 146 COVID-19 patients was divided into four groups in accordance with the most critical events during the course of disease. The immunophenotype and T-helper subsets were analyzed by flow cytometry. Asymptomatic SARS-CoV-2 infected individuals showed a potent and robust Th1 immunity, with a lower Th17 and less activated T-cells at the time of sample acquisition compared not only with symptomatic patients, but also with healthy controls. Conversely, severe COVID-19 patients presented with Th17-skewed immunity, fewer Th1 responses and more activated T-cells. The multivariate analysis of the immunological and inflammatory parameters, together with the comorbidities, showed that the Th1 response was an independent protective factor for the prevention of hospitalization (OR 0.17, 95% CI 0.03–0.81), with an AUC of 0.844. Likewise, the Th1 response was found to be an independent protective factor for severe forms of the disease (OR 0.09, 95% CI: 0.01–0.63, p = 0.015, AUC: 0.873). In conclusion, a predominant Th1 immune response in the acute phase of the SARS-CoV-2 infection could be used as a tool to identify patients who might have a good disease evolution.

Antibody‐mediated rejection is responsible for 30‐50% of renal graft failures. Differentiation of B cells into antibody‐producing plasmablasts depends on the collaboration of follicular helper T cells (Tfh). We analysed circulating Tfh (cTfh) in kidney recipients and studied cTfh relationship with anti‐HLA antibody production and graft outcome. cTfh were longitudinally analysed in a prospective cohort of patients (n=206), pre‐ and post‐transplantation. Clinical data, HLA sensitization and cTfh function were recorded. Both pre‐transplant and 6‐month post‐transplant cTfh were able to derive IgG‐producing plasmablasts. Pre‐transplant cTfh were decreased in patients, especially in those who received dialysis. However, these cells were increased in patients with previous allograft or transfusions, and in HLA‐sensitized recipients. After transplantation cTfh expanded, significantly more in patients who developed de novo anti‐HLA antibodies than in patients who remained unsensitized. Augmented pre‐transplant cTfh positively correlated with higher intensity of pre‐transplant anti‐HLA class I, and de novo anti‐HLA class I and anti‐HLA class II antibodies. Consistently, pre‐transplantation cTfh were higher in patients who experienced acute rejection (HR=1.14 (1.04‐1.25)). Thus, we show a role for Tfh in anti‐HLA sensitization and rejection. Multicentre studies with additional patient cohorts are needed to validate these results. Immunosuppressive drugs targeting Tfh could be useful to improve outcome.

The timing of the development of specific adaptive immunity after natural SARS-CoV-2 infection, and its relevance in clinical outcome, has not been characterized in depth. Description of the long-term maintenance of both cellular and humoral responses elicited by real-world anti-SARS-CoV-2 vaccination is still scarce. Here we aimed to understand the development of optimal protective responses after SARS-CoV-2 infection and vaccination. We performed an early, longitudinal study of S1-, M- and N-specific IFN-γ and IL-2 T cell immunity and anti-S total and neutralizing antibodies in 88 mild, moderate or severe acute COVID-19 patients. Moreover, SARS-CoV-2-specific adaptive immunity was also analysed in 234 COVID-19 recovered subjects, 28 uninfected BNT162b2-vaccinees and 30 uninfected healthy controls. Upon natural infection, cellular and humoral responses were early and coordinated in mild patients, while weak and inconsistent in severe patients. The S1-specific cellular response measured at hospital arrival was an independent predictive factor against severity. In COVID-19 recovered patients, four to seven months post-infection, cellular immunity was maintained but antibodies and neutralization capacity declined. Finally, a robust Th1-driven immune response was developed in uninfected BNT162b2-vaccinees. Three months post-vaccination, the cellular response was comparable, while the humoral response was consistently stronger, to that measured in COVID-19 recovered patients. Thus, measurement of both humoral and cellular responses provides information on prognosis and protection from infection, which may add value for individual and public health recommendations.