Persistence of a SARS-CoV-2 T-cell response in patients with long COVID and lung sequelae after COVID-19.

1 year after an acute COVID-19 episode, patients with either lung sequelae or long COVID show a stronger SARS-CoV-2-specific T-cell response than fully recovered individuals, suggesting persistent cell stimulation by residual viral reservoirs https://bit.ly/40bPZm7.

Validity of prognostic models of critical COVID-19 is variable. A systematic review with external validation.

OBJECTIVES: To identify prognostic models which estimate the risk of critical COVID-19 in hospitalized patients and to assess their validation properties. STUDY DESIGN AND SETTING: We conducted a systematic review in Medline (up to January 2021) of studies developing or updating a model that estimated the risk of critical COVID-19, defined as death, admission to intensive care unit, and/or use of mechanical ventilation during admission. Models were validated in two datasets with different backgrounds (HM [private Spanish hospital network], n = 1,753, and ICS [public Catalan health system], n = 1,104), by assessing discrimination (area under the curve [AUC]) and calibration (plots). RESULTS: We validated 18 prognostic models. Discrimination was good in nine of them (AUCs ≥ 80%) and higher in those predicting mortality (AUCs 65%-87%) than those predicting intensive care unit admission or a composite outcome (AUCs 53%-78%). Calibration was poor in all models providing outcome's probabilities and good in four models providing a point-based score. These four models used mortality as outcome and included age, oxygen saturation, and C-reactive protein among their predictors. CONCLUSION: The validity of models predicting critical COVID-19 by using only routinely collected predictors is variable. Four models showed good discrimination and calibration when externally validated and are recommended for their use.

COVID-19 and lung involvement

In late December 2019, a novel coronavirus emerged and had a rapid and worldwide spread, resulting in an ongoing pandemic. This virus, designated SARS-CoV-2, causes a respiratory disease named COVID-19 which can range in severity, depending not only on the viral infection but also conditioned by the immune system and the host's response. COVID-19 is often associated with aggressive and uncontrolled inflammation that may lead to acute respiratory distress syndrome (ARDS), multiorgan damage and failure, and death. In this chapter, we review the general characteristics of SARS-CoV-2 infection, its interaction with target cells and the resulting immune response, as well as current and potential therapeutic interventions.

Inhaled corticosteroids for the treatment of COVID-19.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has caused severe illness and mortality for millions worldwide. Despite the development, approval and rollout of vaccination programmes globally to prevent infection by SARS-CoV-2 and the development of coronavirus disease 2019 (COVID-19), treatments are still urgently needed to improve outcomes. Early in the pandemic it was observed that patients with pre-existing asthma or COPD were underrepresented among those with COVID-19. Evidence from clinical studies indicates that the inhaled corticosteroids (ICS) routinely taken for asthma and COPD could have had a protective role in preventing severe COVID-19 and, therefore, may be a promising treatment for COVID-19. This review summarises the evidence supporting the beneficial effects of ICS on outcomes in patients with COVID-19 and explores the potential protective mechanisms.

SARS-CoV-2 T-cell response in COVID-19 convalescent patients with and without lung sequelae.

A specific T-cell response persists in the majority of COVID-19 patients 6 months after hospital discharge. This response is more prominent in those who required critical care during the acute COVID-19 episode but is reduced in patients with lung sequelae. https://bit.ly/3fBuVA4.

Elevated plasma levels of epithelial and endothelial cell markers in COVID-19 survivors with reduced lung diffusing capacity six months after hospital discharge.

BACKGROUND: Some COVID-19 survivors present lung function abnormalities during follow-up, particularly reduced carbon monoxide lung diffusing capacity (DLCO). To investigate risk factors and underlying pathophysiology, we compared the clinical characteristics and levels of circulating pulmonary epithelial and endothelial markers in COVID-19 survivors with normal or reduced DLCO 6 months after discharge. METHODS: Prospective, observational study. Clinical characteristics during hospitalization, and spirometry, DLCO and plasma levels of epithelial (surfactant protein (SP) A (SP-A), SP-D, Club cell secretory protein-16 (CC16) and secretory leukocyte protease inhibitor (SLPI)), and endothelial (soluble intercellular adhesion molecule 1 (sICAM-1), soluble E-selectin and Angiopoietin-2) 6 months after hospital discharge were determined in 215 COVID-19 survivors. RESULTS: DLCO was < 80% ref. in 125 (58%) of patients, who were older, more frequently smokers, had hypertension, suffered more severe COVID-19 during hospitalization and refer persistent dyspnoea 6 months after discharge. Multivariate regression analysis showed that age ≥ 60 years and severity score of the acute episode ≥ 6 were independent risk factors of reduced DLCO 6 months after discharge. Levels of epithelial (SP-A, SP-D and SLPI) and endothelial (sICAM-1 and angiopoietin-2) markers were higher in patients with reduced DLCO, particularly in those with DLCO ≤ 50% ref. Circulating SP-A levels were associated with the occurrence of acute respiratory distress syndrome (ARDS), organizing pneumonia and pulmonary embolisms during hospitalization. CONCLUSIONS: Reduced DLCO is common in COVID-19 survivors 6 months after hospital discharge, especially in those older than 60 years with very severe acute disease. In these individuals, elevated levels of epithelial and endothelial markers suggest persistent lung damage.

SARS-CoV-2 T-cell response in COVID-19 convalescent patients with and without lung SEQUELAE

Patients infected by SARS-CoV-2 may develop pneumonia (COVID19) and require hospital admission and, eventually, critical care [1]. This has been related with a weaker innate immune response with impaired production of type I interferons [2]. In this setting, an antigen specific T-cell response is needed for the elimination of SARS-CoV-2, as well as to develop long-lasting memory to respond to potential future SARS-CoV-2 infections [3, 4]. However, this response needs to be contained once the virus is eradicated to avoid further damaging the host.

Low birth weight as a potential risk factor for severe COVID-19 in adults.

The identification of factors predisposing to severe COVID-19 in young adults remains partially characterized. Low birth weight (LBW) alters cardiovascular and lung development and predisposes to adult disease. We hypothesized that LBW is a risk factor for severe COVID-19 in non-elderly subjects. We analyzed a prospective cohort of 397 patients (18-70 years) with laboratory-confirmed SARS-CoV-2 infection attended in a tertiary hospital, where 15% required admission to Intensive Care Unit (ICU). Perinatal and current potentially predictive variables were obtained from all patients and LBW was defined as birth weight ≤ 2.500 g. Age (adjusted OR (aOR) 1.04 [1-1.07], P = 0.012), male sex (aOR 3.39 [1.72-6.67], P < 0.001), hypertension (aOR 3.37 [1.69-6.72], P = 0.001), and LBW (aOR 3.61 [1.55-8.43], P = 0.003) independently predicted admission to ICU. The area under the receiver-operating characteristics curve (AUC) of this model was 0.79 [95% CI, 0.74-0.85], with positive and negative predictive values of 29.1% and 97.6% respectively. Results were reproduced in an independent cohort, from a web-based survey in 1822 subjects who self-reported laboratory-positive SARS-CoV-2 infection, where 46 patients (2.5%) needed ICU admission (AUC 0.74 [95% CI 0.68-0.81]). LBW seems to be an independent risk factor for severe COVID-19 in non-elderly adults and might improve the performance of risk stratification algorithms.