Decreased Gas6 and sAxl Plasma Levels Are Associated with Hair Loss in COVID-19 Survivors.

Post-acute conditions after coronavirus disease 2019 (COVID-19) are quite common, although the underlying pathogenetic mechanisms leading to these conditions are not yet completely understood. In this prospective observational study, we aimed to test the hypothesis that Growth Arrest-Specific 6 (Gas6) and its soluble receptors, Axl (sAxl) and MerTK (sMer), might be implicated. A total of 263 subjects underwent a structured clinical evaluation one year after their hospital discharge for COVID-19, and they consented to donate a blood sample to measure their circulating Gas6, sAxl, and sMer levels. A total of 98 (37.3%) post-COVID-19 subjects complained of at least one residual physical symptom one year after their hospital discharge. Univariate analysis revealed that sAxl was marginally associated with residual symptoms, but at the level of logistic regression analysis, only the diffusing capacity of the lungs for carbon monoxide (DLCO) (OR 0.98, CI 95%: 0.96-0.99; p = 0.007) and the female sex (OR 2.49, CI 95%: 1.45-4.28; p = 0.001) were independently associated with long-lasting symptoms. A total of 69 (26.2%) subjects had hair loss. At the level of univariate analysis, Gas6, sAxl, DLCO, and the female gender were associated with its development. In a logistic regression analysis model, Gas6 (OR 0.96, CI 95%: 0.92-0.99; p = 0.015) and sAxl (OR 0.98, CI 95%; 0.97-1.0; p = 0.014), along with the female sex (OR 6.58, CI 95%: 3.39-12.78; p = 0.0001), were independent predictors of hair loss. Decreased levels of Gas6 and sAxl were associated with a history of hair loss following COVID-19. This was resolved spontaneously in most patients, although 23.7% complained of persistent hair loss one year after hospital discharge.

Ongoing Mycophenolate Treatment Impairs Anti-SARS-CoV-2 Vaccination Response in Patients Affected by Chronic Inflammatory Autoimmune Diseases or Liver Transplantation Recipients: Results of the RIVALSA Prospective Cohort.

Vaccines are the most effective means to prevent the potentially deadly effects of SARS-CoV-2 infection, but not all vaccinated individuals gain the same degree of protection. Patients undergoing chronic immunosuppressive therapy due to autoimmune diseases or liver transplants, for example, may show impaired anti-SARS-CoV-2 antibody response after vaccination. We performed a prospective observational study with parallel arms, aiming to (a) evaluate seroconversion after anti-SARS-CoV-2 mRNA vaccine administration in different subgroups of patients receiving immunosuppressive treatment for rheumatological or autoimmune diseases or to prevent organ rejection after liver transplantation and (b) identify negative predictors of IgG anti-SARS-CoV-2 development. Out of 437 eligible patients, 183 individuals were enrolled at the Rheumatology and Hepatology Tertiary Units of "Maggiore della Carità" University Hospital in Novara: of those, 52 were healthy subjects, while among the remaining 131 patients, 30 had a diagnosis of spondyloarthritis, 25 had autoimmune hepatitis, 10 were liver transplantation recipients, 23 suffered from connective tissue diseases (including 10 cases that overlapped with other diseases), 40 were treated for rheumatoid arthritis, and 5 had vasculitis. Moreover, all patients were receiving chronic immunosuppressive therapy. The immunogenicity of mRNA COVID-19 vaccines was evaluated by measuring IgG anti-SARS-CoV-2 antibody titers before vaccination and after 10, 30, and 90 days since the first dose administration. Of the selected cohort of patients, 24.0% did not develop any detectable anti-SARS-CoV-2 IgG after a complete mRNA-based two doses primary vaccination cycle. At univariate analysis, independent predictors of an absent antibody response to vaccine were a history of liver transplantation (OR 11.5, 95% CI 2.5-53.7, p = 0.0018), the presence of a comorbid active neoplasia (OR 26.4, 95% CI 2.8-252.4, p = 0.0045), and an ongoing immunosuppressive treatment with mycophenolate (MMF) (OR 14.0, 95% CI 3.6-54.9, p = 0.0002) or with calcineurin inhibitors (OR 17.5, 95% CI 3.1-99.0, p = 0.0012). At multivariate analysis, only treatment with MMF (OR 24.8, 95% CI 5.9-103.2, p < 0.0001) and active neoplasia (OR 33.2, 95% CI 5.4-204.1, p = 0.0002) were independent predictors of seroconversion failure. These findings suggest that MMF dose reduction or suspension may be required to optimize vaccine response in these patients.

Simple Parameters from Complete Blood Count Predict In-Hospital Mortality in COVID-19.

INTRODUCTION: The clinical course of Coronavirus Disease 2019 (COVID-19) is highly heterogenous, ranging from asymptomatic to fatal forms. The identification of clinical and laboratory predictors of poor prognosis may assist clinicians in monitoring strategies and therapeutic decisions. MATERIALS AND METHODS: In this study, we retrospectively assessed the prognostic value of a simple tool, the complete blood count, on a cohort of 664 patients (F 260; 39%, median age 70 (56-81) years) hospitalized for COVID-19 in Northern Italy. We collected demographic data along with complete blood cell count; moreover, the outcome of the hospital in-stay was recorded. RESULTS: At data cut-off, 221/664 patients (33.3%) had died and 453/664 (66.7%) had been discharged. Red cell distribution width (RDW) (χ 2 10.4; p < 0.001), neutrophil-to-lymphocyte (NL) ratio (χ 2 7.6; p = 0.006), and platelet count (χ 2 5.39; p = 0.02), along with age (χ 2 87.6; p < 0.001) and gender (χ 2 17.3; p < 0.001), accurately predicted in-hospital mortality. Hemoglobin levels were not associated with mortality. We also identified the best cut-off for mortality prediction: a NL ratio > 4.68 was characterized by an odds ratio for in-hospital mortality (OR) = 3.40 (2.40-4.82), while the OR for a RDW > 13.7% was 4.09 (2.87-5.83); a platelet count > 166,000/µL was, conversely, protective (OR: 0.45 (0.32-0.63)). CONCLUSION: Our findings arise the opportunity of stratifying COVID-19 severity according to simple lab parameters, which may drive clinical decisions about monitoring and treatment.

Fatality rate and predictors of mortality in an Italian cohort of hospitalized COVID-19 patients.

Clinical features and natural history of coronavirus disease 2019 (COVID-19) differ widely among different countries and during different phases of the pandemia. Here, we aimed to evaluate the case fatality rate (CFR) and to identify predictors of mortality in a cohort of COVID-19 patients admitted to three hospitals of Northern Italy between March 1 and April 28, 2020. All these patients had a confirmed diagnosis of SARS-CoV-2 infection by molecular methods. During the study period 504/1697 patients died; thus, overall CFR was 29.7%. We looked for predictors of mortality in a subgroup of 486 patients (239 males, 59%; median age 71 years) for whom sufficient clinical data were available at data cut-off. Among the demographic and clinical variables considered, age, a diagnosis of cancer, obesity and current smoking independently predicted mortality. When laboratory data were added to the model in a further subgroup of patients, age, the diagnosis of cancer, and the baseline PaO2/FiO2 ratio were identified as independent predictors of mortality. In conclusion, the CFR of hospitalized patients in Northern Italy during the ascending phase of the COVID-19 pandemic approached 30%. The identification of mortality predictors might contribute to better stratification of individual patient risk.