Sars-Cov-2 infection causes fever and cough that may rapidly lead to acute respiratory distress syndrome (ARDS). Few biomarkers have been identified but, unfortunately, these are individually poorly specific, and novel biomarkers are needed to better predict patient outcome. The aim of this study was to evaluate the diagnostic performance of circulating platelets (PLT)-derived extracellular vesicles (EVs) as biomarkers for Sars-Cov-2 infection, by setting a rapid and reliable test on unmanipulated blood samples. PLT-EVs were quantified by flow cytometry on two independent cohorts of Sars-CoV-2+ (n = 69), Sars-Cov-2− (n = 62) hospitalized patients, and healthy controls. Diagnostic performance of PLT-EVs was evaluated by receiver operating characteristic (ROC) curve. PLT-EVs count were higher in Sars-Cov-2+ compared to Sars-Cov-2− patients or HC. ROC analysis of the combined cohorts showed an AUC = 0.79 and an optimal cut-off value of 1472 EVs/μL, with 75% sensitivity and 74% specificity. These data suggest that PLT-EVs might be an interesting biomarker deserving further investigations to test their predictive power.

We describe the outcomes in cancer patients during the initial outbreak of the COVID-19 in Europe from the retrospective, multi-center observational OnCovid study. We identified 204 cancer patients from eight centers in the United Kingdom, Italy, and Spain aged >18 (mean = 69) and diagnosed with COVID-19 between 26 February and 1 April 2020. A total of 127 (62%) were male, 184 (91%) had a diagnosis of solid malignancy, and 103 (51%) had non-metastatic disease. A total of 161 (79%) had >1 co-morbidity. A total of 141 (69%) patients had >1 COVID-19 complication. A total of 36 (19%) were escalated to high-dependency or intensive care. A total of 59 (29%) died, 53 (26%) were discharged, and 92 (45%) were in-hospital survivors. Mortality was higher in patients aged >65 (36% vs. 16%), in those with >2 co-morbidities (40% vs. 18%) and developing >1 complication from COVID-19 (38% vs. 4%, p = 0.004). Multi-variable analyses confirmed age > 65 and >2 co-morbidities to predict for patient mortality independent of tumor stage, active malignancy, or anticancer therapy. During the early outbreak of SARS-CoV-2 infection in Europe co-morbid burden and advancing age predicted for adverse disease course in cancer patients. The ongoing OnCovid study will allow us to compare risks and outcomes in cancer patients between the initial and later stages of the COVID-19 pandemic.

Background: Balance impairment is a common disability in post-stroke survivors, leading to reduced mobility and increased fall risk. Robotic gait training (RAGT) is largely used, along with traditional training. There is, however, no strong evidence about RAGT superiority, especially on balance. This study aims to determine RAGT efficacy on balance of post-stroke survivors. Methods: PubMed, Cochrane Library, and PeDRO databases were investigated. Randomized clinical trials evaluating RAGT efficacy on post-stroke survivor balance with Berg Balance Scale (BBS) or Timed Up and Go test (TUG) were searched. Meta-regression analyses were performed, considering weekly sessions, single-session duration, and robotic device used. Results: A total of 18 trials have been included. BBS pre-post treatment mean difference is higher in RAGT-treated patients, with a pMD of 2.17 (95% CI 0.79; 3.55). TUG pre-post mean difference is in favor of RAGT, but not statistically, with a pMD of −0.62 (95%CI − 3.66; 2.43). Meta-regression analyses showed no relevant association, except for TUG and treatment duration (β = −1.019, 95% CI − 1.827; −0.210, p-value = 0.0135). Conclusions: RAGT efficacy is equal to traditional therapy, while the combination of the two seems to lead to better outcomes than each individually performed. Robot-assisted balance training should be the focus of experimentation in the following years, given the great results in the first available trials. Given the massive heterogeneity of included patients, trials with more strict inclusion criteria (especially time from stroke) must be performed to finally define if and when RAGT is superior to traditional therapy.

In recent years, the association of venetoclax (VEN) with hypomethylating agents (HMAs) significantly improved the outcome of patients with newly diagnosed acute myeloid leukemia (AML) who were unfit for intensive chemotherapy and became the standard of care after the publication of the pivotal RCT VIALE-A. However, it is still not clear to what extent the results observed in the VIALE-A apply to a real-world setting. For this reason, we carried out a systematic review and meta-analysis of real-world studies on newly diagnosed patients with AML, ineligible for intensive induction chemotherapy, receiving first-line VEN+HMA. We then compared their results in term of survival with those from the VIALE-A. Kaplan-Meier curves were extracted from all included studies and individual survival data was reconstructed. We then estimated a pooled survival curve and compared it with the results of the VIALE-A using the log-rank test. We also conducted a secondary analysis including only studies considering VEN plus azacytidine (AZA) as treatment, as this was the schedule originally used in the VIALE-A. Nineteen real-world studies met the inclusion criteria and were included in the systematic review. Most of them reported a worse survival than the VIALE-A. The pooled survival curve was similar to that reported in the VIALE-A during the first three months of treatment but diverged thereafter (p-value = 0.0001). The pooled median survival among the real-world studies was 9.37 months (95%CI 8.81–10.5), substantially lower than that reported in the VIALE-A (14.7 months; 95%CI 11.9–18.7). Results slightly increased when the analysis was restricted to the studies using VEN+AZA as treatment (median survival: 11.5 months; 95%CI 10.2–14.8). Survival of newly diagnosed AML patients treated with VEN+HMAs in a real-world setting seems to be lower than previously reported in the VIALE-A, while the effect of VEN+AZA is more in line with expected results. Future studies are needed to evaluate whether this apparent discrepancy is due to the different characteristics of enrolled patients or to a non-optimal adherence to therapy, and whether alternative regimens can provide better results in terms of safety and effectiveness.

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 ( 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) ( 10.4; ), neutrophil-to-lymphocyte (NL) ratio ( 7.6; ), and platelet count ( 5.39; ), along with age ( 87.6; ) and gender ( 17.3; ), accurately predicted in-hospital mortality. Hemoglobin levels were not associated with mortality. We also identified the best cut-off for mortality prediction: a was characterized by an odds ratio for in-hospital (2.40-4.82), while the OR for a