ABSTRACT
OBJECTIVES: Mixed cryoglobulinaemic vasculitis (MCV) is an immune-complex-mediated systemic vasculitis characterised by heterogeneous clinical manifestations mainly involving lymphatic system, skin, kidney and peripheral nervous system. Although MCV patients have been included in priority programs for vaccination against SARS-CoV-2 in Italy, limited information is available for these patients. Aims of this multicentre Italian study were to investigate SARS-CoV-2 vaccination rate in MCV patients and its safety profile. METHODS: All MCV patients referring to participating centres were assessed with an interview-based survey about vaccination, reasons for not getting vaccinated, adverse events (AE), and disease flares within a month after vaccination. RESULTS: A total of 416 patients were included in the study. Among participants, 7.7% did not get vaccinated, mainly for fear related to vaccine side-effects (50%) or medical decision (18.8%). They were more frequently treated with chronic glucocorticoids or rituximab (p=0.049 and p=0.043, respectively). Mild and self-limiting AE were recorded in 31.7% of cases, while post-vaccination vasculitis flares were observed in 5.3% of subjects. Disease relapses were mainly observed in patients with peripheral neuropathy or skin vasculitis (40% and 25%, respectively). CONCLUSIONS: Vaccination against SARS-CoV-2 has been performed in a high percentage of MCV patients with encouraging safety profile. Vasculitis flares rate was in line with that observed for other autoimmune diseases, despite patients with purpura or peripheral neuropathy seem to be at risk for symptoms' exacerbation. Patients' hesitancy, rituximab and glucocorticoids treatment were the main reasons for delaying vaccination.
ABSTRACT
The coronavirus disease 2019 (COVID-19) has severely stressed the sanitary systems of all countries in the world. One of the main issues that physicians are called to tackle is represented by the monitoring of pauci-symptomatic COVID-19 patients at home and, generally speaking, everyone the access to the hospital might or should be severely reduced. Indeed, the early detection of interstitial pneumonia is particularly relevant for the survival of these patients. Recent studies on rheumatoid arthritis and interstitial lung diseases have shown that pathological pulmonary sounds can be automatically detected by suitably developed algorithms. The scope of this preliminary work consists of proving that the pathological lung sounds evidenced in patients affected by COVID-19 pneumonia can be automatically detected as well by the same class of algorithms. In particular the software VECTOR, suitably devised for interstitial lung diseases, has been employed to process the lung sounds of 28 patient recorded in the emergency room at the university hospital of Modena (Italy) during December 2020. The performance of VECTOR has been compared with diagnostic techniques based on imaging, namely lung ultrasound, chest X-ray and high resolution computed tomography, which have been assumed as ground truth. The results have evidenced a surprising overall diagnostic accuracy of 75% even if the staff of the emergency room has not been suitably trained for lung auscultation and the parameters of the software have not been optimized to detect interstitial pneumonia. These results pave the way to a new approach for monitoring the pulmonary implication in pauci-symptomatic COVID-19 patients.