Clinical Outcome of Hospitalized COVID-19 Patients with History of Atrial Fibrillation.

Background and objectives: Pre-existing atrial fibrillation (AF) is a frequent comorbidity in hospitalized patients with COVID-19; however, little is still known about its prognostic role in infected patients. The aim of our study was to evaluate whether the pre-existing AF as comorbidity would contribute to increase the risk for severe forms of COVID-19, worse prognosis, or even higher mortality. Materials and Methods: We retrospectively evaluated all consecutive COVID-19 patients admitted to the emergency department of nine Italian Hospitals from 1 March to 30 April 2020.The prevalence and the type of pre-existing AF have been collected. The correlation between the history and type of AF and the development of severe ARDS and in-hospital mortality has been evaluated. Results: In total, 467 patients (66.88 ± 14.55 years; 63% males) with COVID-19 were included in the present study. The history of AF was noticed in 122 cases (26.1%), of which 12 (2.6%) with paroxysmal, 57 (12.2%) with persistent and 53 (11.3%) with permanent AF. Among our study population, COVID-19 patients with AF history were older compared to those without AF history (71.25 ± 12.39 vs. 65.34 ± 14.95 years; p < 0.001); however, they did not show a statistically significant difference in cardiovascular comorbidities or treatments. Pre-existing AF resulted in being independently associated with an increased risk of developing severe ARDS during the hospitalization; in contrast, it did not increase the risk of in-hospital mortality. Among patients with AF history, no significant differences were detected in severe ARDS and in-hospital mortality between patients with permanent and non-permanent AF history. Conclusions: Pre-existing AF is a frequent among COVID-19 patients admitted to hospital, accounting up to 25% of cases. It is independently associated with an increased risk of severe ARDS in hospitalized COVID-19 patients; in contrast, it did not affect the risk of death. The type of pre-existing AF (permanent or non-permanent) did not impact the clinical outcome.

Edoxaban for the treatment of pulmonary embolism in hospitalized COVID-19 patients.

PURPOSE: We aimed to investigate the clinical performance of edoxaban for the treatment of pulmonary embolism (PE) in hospitalized COVID-19 patients. METHODS: We conducted a retrospective analysis selecting hospitalized patients with COVID-19 admitted to our Institution from 20 May 2020 to 20 November 2020 with computer tomography (CT) detected PE at admission, treated with edoxaban after initial parenteral therapy. Clinical outcomes were compared between patients with and without ARDS at admission and between those with and without CT confirmed PE resolution. RESULTS: 50 patients were included. Mean follow-up was 42.5 ± 10 days. No baseline differences were found between patients with ARDS (30%) and those without ARDS at admission. Patients with PE resolution (84%) were younger (P = 0.03), had a shorter duration of fondaparinux therapy (9.9 ± 3.8 vs 15.8 ± 7.5 days; P = 0.0015) and length of hospitalization (36 ± 8 vs 46 ± 9 days: P = 0.0023) compared with those without PE resolution. 2 patients experienced major bleedings. At multivariate analysis the time to edoxaban switch was the only predictor of the PE resolution (HR: 0.92; 95% C.I. 0.86 to 0.99). CONCLUSION: Edoxaban was an effective and safe treatment for acute PE in COVID-19 setting.

Common cardiovascular risk factors and in-hospital mortality in 3,894 patients with COVID-19: survival analysis and machine learning-based findings from the multicentre Italian CORIST Study.

BACKGROUND AND AIMS: There is poor knowledge on characteristics, comorbidities and laboratory measures associated with risk for adverse outcomes and in-hospital mortality in European Countries. We aimed at identifying baseline characteristics predisposing COVID-19 patients to in-hospital death. METHODS AND RESULTS: Retrospective observational study on 3894 patients with SARS-CoV-2 infection hospitalized from February 19th to May 23rd, 2020 and recruited in 30 clinical centres distributed throughout Italy. Machine learning (random forest)-based and Cox survival analysis. 61.7% of participants were men (median age 67 years), followed up for a median of 13 days. In-hospital mortality exhibited a geographical gradient, Northern Italian regions featuring more than twofold higher death rates as compared to Central/Southern areas (15.6% vs 6.4%, respectively). Machine learning analysis revealed that the most important features in death classification were impaired renal function, elevated C reactive protein and advanced age. These findings were confirmed by multivariable Cox survival analysis (hazard ratio (HR): 8.2; 95% confidence interval (CI) 4.6-14.7 for age ≥85 vs 18-44 y); HR = 4.7; 2.9-7.7 for estimated glomerular filtration rate levels <15 vs ≥ 90 mL/min/1.73 m2; HR = 2.3; 1.5-3.6 for C-reactive protein levels ≥10 vs ≤ 3 mg/L). No relation was found with obesity, tobacco use, cardiovascular disease and related-comorbidities. The associations between these variables and mortality were substantially homogenous across all sub-groups analyses. CONCLUSIONS: Impaired renal function, elevated C-reactive protein and advanced age were major predictors of in-hospital death in a large cohort of unselected patients with COVID-19, admitted to 30 different clinical centres all over Italy.