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.

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.

Mitral valve prolapse (MVP) is the most frequent valvulopathy with a prevalence of 1.2%–2.4% in general population and it is characterized by a benign course. Although it can be associated with some complications, ventricular arrhythmias (VA) and sudden cardiac death (SCD) as ultimate expressions, are the most worrying. The estimated risk of SCD in MVP is between 0.2% and 1.9% per year including both MVP patients with left ventricular (LV) dysfunction due to severe MR and MVP patients without significant MR. The latter ones constitute a particular phenotype called “malignant MVP” characterized by bileaflet myxomatous prolapse, ECG repolarization abnormalities and complex VAs (c‐VAs) with polymorphic/right bundle branch block morphology (RBBB) and LV fibrosis of the papillary muscles (PMs) and inferobasal wall secondary to mechanical stretching visualized as late gadolinium enhancement (LGE) areas by cardiac magnetic resonance (CMR). In MVP, the first diagnostic approach is transthoracic echocardiography (TTE) that defines the presence of mitral annular disjunction (MAD) which seems to be associated with “arrhythmic MVP” (AMVP). From an ECG point of view, AMVP is characterized by frequent premature ventricular contractions (PVCs) arising from one or both PMs, fascicular tissue, and outflow tract, as well as by T‐wave inversion in the inferolateral leads. The aim of the present paper is to describe TTE red flags that could identify MVP patients at high risk to develop complex arrhythmias as supported by the corresponding findings of LGE‐CMR and anatomy studies. TTE could be a co‐partner in phenotyping high‐risk arrhythmic MVP patients.