A machine learning analysis to evaluate the outcome measures in inflammatory myopathies.

OBJECTIVE: To assess the long-term outcome in patients with Idiopathic Inflammatory Myopathies (IIM), focusing on damage and activity disease indexes using artificial intelligence (AI). BACKGROUND: IIM are a group of rare diseases characterized by involvement of different organs in addition to the musculoskeletal. Machine Learning analyses large amounts of information, using different algorithms, decision-making processes and self-learning neural networks. METHODS: We evaluate the long-term outcome of 103 patients with IIM, diagnosed on 2017 EULAR/ACR criteria. We considered different parameters, including clinical manifestations and organ involvement, number and type of treatments, serum creatine kinase levels, muscle strength (MMT8 score), disease activity (MITAX score), disability (HAQ-DI score), disease damage (MDI score), and physician and patient global assessment (PGA). The data collected were analysed, applying, with R, supervised ML algorithms such as lasso, ridge, elastic net, classification, and regression trees (CART), random forest and support vector machines (SVM) to find the factors that best predict disease outcome. RESULTS AND CONCLUSION: Using artificial intelligence algorithms we identified the parameters that best correlate with the disease outcome in IIM. The best result was on MMT8 at follow-up, predicted by a CART regression tree algorithm. MITAX was predicted based on clinical features such as the presence of RP-ILD and skin involvement. A good predictive capacity was also demonstrated on damage scores: MDI and HAQ-DI. In the future Machine Learning will allow us to identify the strengths or weaknesses of the composite disease activity and damage scores, to validate new criteria or to implement classification criteria.

Intravenous immunoglobulin as an important adjunct in the prevention and therapy of coronavirus 2019 disease.

The coronavirus disease-19 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) challenged globally with its morbidity and mortality. A small percentage of affected patients (20%) progress into the second stage of the disease clinically presenting with severe or fatal involvement of lung, heart and vascular system, all contributing to multiple-organ failure. The so-called 'cytokines storm' is considered the pathogenic basis of severe disease and it is a target for treatment with corticosteroids, immunotherapies and intravenous immunoglobulin (IVIg). We provide an overview of the role of IVIg in the therapy of adult patients with COVID-19 disease. After discussing the possible underlying mechanisms of IVIg immunomodulation in COVID-19 disease, we review the studies in which IVIg was employed. Considering the latest evidence that show a link between new coronavirus and autoimmunity, we also discuss the use of IVIg in COVID-19 and anti-SARS-CoV-2 vaccination related autoimmune diseases and the post-COVID-19 syndrome. The benefit of high-dose IVIg is evident in almost all studies with a rapid response, a reduction in mortality and improved pulmonary function in critically ill COVID-19 patients. It seems that an early administration of IVIg is crucial for a successful outcome. Studies' limitations are represented by the small number of patients, the lack of control groups in some and the heterogeneity of included patients. IVIg treatment can reduce the stay in ICU and the demand for mechanical ventilation, thus contributing to attenuate the burden of the disease.