A prognostic model and pre-discharge predictors of post-COVID-19 syndrome after hospitalization for SARS-CoV-2 infection.

Background: Post-COVID-19 syndrome (PCS) has been increasingly recognized as an emerging problem: 50% of patients report ongoing symptoms 1 year after acute infection, with most typical manifestations (fatigue, dyspnea, psychiatric and neurological symptoms) having potentially debilitating effect. Early identification of high-risk candidates for PCS development would facilitate the optimal use of resources directed to rehabilitation of COVID-19 convalescents. Objective: To study the in-hospital clinical characteristics of COVID-19 survivors presenting with self-reported PCS at 3 months and to identify the early predictors of its development. Methods: 221 hospitalized COVID-19 patients underwent symptoms assessment, 6-min walk test, and echocardiography pre-discharge and at 1 month; presence of PCS was assessed 3 months after discharge. Unsupervised machine learning was used to build a SANN-based binary classification model of PCS development. Results: PCS at 3 months has been detected in 75% patients. Higher symptoms level in the PCS group was not associated with worse physical functional recovery or significant echocardiographic changes. Despite identification of a set of pre-discharge predictors, inclusion of parameters obtained at 1 month proved necessary to obtain a high accuracy model of PCS development, with inputs list including age, sex, in-hospital levels of CRP, eGFR and need for oxygen supplementation, and level of post-exertional symptoms at 1 month after discharge (fatigue and dyspnea in 6MWT and MRC Dyspnea score). Conclusion: Hospitalized COVID-19 survivors at 3 months were characterized by 75% prevalence of PCS, the development of which could be predicted with an 89% accuracy using the derived neural network-based classification model.

Efficacy and Safety of Masitinib in Corticosteroid-Dependent Severe Asthma: A Randomized Placebo-Controlled Trial.

Background: Masitinib is an oral tyrosine kinase inhibitor that selectively targets mast cell activity and platelet-derived growth factor receptor (PDGFR) signaling, both of which are implicated in various mechanisms of asthma pathogenesis. Objective: Assessment of masitinib as an add-on to standard maintenance therapy as compared with placebo in the treatment of oral corticosteroid-dependent severe asthma. Methods: We conducted a randomized (2:1), placebo-controlled study of masitinib (6 mg/kg/d) in adults with severe asthma uncontrolled by high dose inhaled corticosteroids and long-acting beta-adrenoreceptor agonists plus oral corticosteroids (OCS) (≥7.5 mg/d). No minimum baseline blood eosinophil count was specified. Following a protocol amendment, the primary endpoint was reduction of annualized severe asthma exacerbation rate adjusted for the overall time on treatment (SAER). Subgroup analysis according to yearly cumulative OCS intake was also performed, a higher OCS dose indicating more severe asthma that is harder to control. Results: Following an average exposure of approximately 13 months, masitinib (n = 240) reduced the SAER by 35% relative to placebo (n = 115) (rate ratio (RR) 0.65 (95% CI [0.47-0.90]; P = 0.010)). For patients with eosinophil ≥150 cell/µL, masitinib (n = 181) reduced SAER by 38% relative to placebo (n = 87); RR 0.62 (95% CI [0.42-0.91]; P = 0.016). Benefit of masitinib was shown to increase in the most severely affected patients (OCS intake of >1000 mg/year), with a significant (P < 0.01) reduction in SAER of 50%-70%. Safety was consistent with the known masitinib profile. Conclusion: Orally administered masitinib reduces the risk of asthma exacerbations in severe asthma patients, with an acceptable safety profile. Masitinib may potentially provide a new treatment option for oral corticosteroid-dependent severe asthma.