The Impact of Arrhythmia on Prognosis in Hospitalized Covid-19 Patients. A Cardiac Telemetric Monitoring Study

Background: Cardiovascular abnormalities have been largely reported in patients with COVID-19. Among these, myocardial injury and rhythm disorders represent one of the most important complications in patients affected by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection. Moreover, a poorer prognosis has been documented in COVID-19 patients when complicated by arrhythmias, independently by age and sex. Objective(s): The aims of the present study were to identify some of non-cardiac and cardiac comorbidities and some myocardial electrical features (including QT dispersion) associated with arrhythmia in hospitalized COVID-19 patients. Moreover, another objective was to contribute in analyzing the impact of arrhythmias on outcome in this setting of patients. Method(s): At admission, each patient underwent cardiac telemetry monitoring through entire hospitalization period. In all the subjects, laboratory analyses, standard 12-lead electrocardiogram (both at admission and on discharge), and lung imaging examination (by means of both ultrasound scans and computed tomography) were performed. Patients exhibiting arrhythmia during in-hospital period were divided into three groups: i, with brady-arrhythmias;ii, with tachy-arrhythmias;and, iii, with tachy- and brady-arrhythmias. Result(s): Two-hundred patients completed the study (males, 123;mean age, 70.1 years);of these, 80 patients (40%) exhibited rhythm disorders on cardiac telemetry. Patients with arrhythmia resulted to be older (p<0.0001) than patients without arrhythmia. Moreover, patients with arrhythmia showed: i, greater number of comorbidities (p<0.0001);ii, higher values of creatinine (p=0.007), B-type natriuretic peptide (p<0.0001), troponin (p<0.0001), c-reactive protein (p=0.01), ferritin (p=0.001), d-dimer (p<0.0001), and procalcitonin (p=0.0008);iii, QT interval (p=0.002), QTc interval (p=0.04), and QTc dispersion (p=0.01);and, iiii, lower values of sodium (p=0.03), magnesium (p=0.04), glomerular filtration rate (p<0.0001), and hemoglobin (p=0.008) as compared to patients without arrhythmia. By comparing the three subgroups of patients, no significant differences were found. Multivariate analysis showed that age (OR=1.14 [95% CI: 1.07-1.22];p=0.0004), coronary artery disease (OR=12.7 [95% CI: 2.38-68.01];p=0.005), and circulating troponin (OR=1.05 [95% CI: 1.003-1.10];p=0.04) represented risk factors independently associated with arrhythmia. By analyzing allcause in-hospital mortality, it resulted a ~forty-fold higher among patients with arrhythmia (OR=39.66 [95% CI: 5.20-302.51];p=0.0004) when compared to patients without rhythm disorders. Conclusion(s): In the present study, arrhythmias have been to be associated with ageing, coronary artery disease, subtle myocardial injury, hyperinflammatory status, coagulative unbalance, and abnormalities in myocardial electrical impulse propagation in patients affected by SARS-CoV-2 infection. In alignment with previous reports, the presence of arrhythmia seems to be associated with a worse in-hospital prognosis. Given its usefulness, routinary use of cardiac telemetric monitoring should be encouraged in COVID wards.

Predictors of in-hospital mortality of COVID-19 patients and the role of telemetry in an internal medicine ward during the third phase of the pandemic.

OBJECTIVE: The first pandemic phase of COVID-19 in Italy was characterized by high in-hospital mortality ranging from 23% to 38%. During the third pandemic phase there has been an improvement in the management and treatment of COVID-19, so mortality and predictors may have changed. A prospective study was planned to identify predictors of mortality during the third pandemic phase. PATIENTS AND METHODS: From 15 December 2020 to 15 May 2021, 208 patients were hospitalized (median age: 64 years; males: 58.6%); 83% had a median of 2 (IQR,1-4) comorbidities; pneumonia was present in 89.8%. Patients were monitored remotely for respiratory function and ECG trace for 24 hours/day. Management and treatment were done following the timing and dosage recommended by international guidelines. RESULTS: 79.2% of patients necessitated O2-therapy. ARDS was present in 46.1% of patients and 45.4% received non-invasive ventilation and 11.1% required ICU treatment. 38% developed arrhythmias which were identified early by telemetry and promptly treated. The in-hospital mortality rate was 10%. At multivariate analysis independent predictors of mortality were: older age (R-R for≥70 years: 5.44), number of comorbidities ≥3 (R-R 2.72), eGFR ≤60 ml/min (RR 2.91), high d-Dimer (R-R for≥1,000 ng/ml:7.53), and low PaO2/FiO2 (R-R for <200: 3.21). CONCLUSIONS: Management and treatment adherence to recommendations, use of telemetry, and no overcrowding appear to reduce mortality. Advanced age, number of comorbidities, severe renal failure, high d-Dimer and low P/F remain predictors of poor outcome. The data help to identify current high-risk COVID-19 patients in whom management has yet to be optimized, who require the greatest therapeutic effort, and subjects in whom vaccination is mandatory.

How does integrated reporting change in light of COVID-19? A revisiting of the content of the integrated reports

The crisis connected to the spread of the COVID-19 pandemic represents an epochal event destined to generate strong economic and social consequences. The impact of the pandemic on business activities and business models also entails rethinking reporting practices. The pandemic has, in fact, created an enormous need for investors and stakeholders in general for future-oriented information relating to the impacts of this event on organizations. Integrated reporting is an ideal tool to provide information related to the effects of the pandemic and provide a holistic view of the future prospects of organizations. This study, using legitimacy theory and based on a two-step methodology, highlighted a series of information that companies will need to have to include in integrated reports to maintain and defend legitimacy. The results provide a double perspective: the first based on content elements and the second based on capitals. The results represent an important guideline for companies for the preparation of future integrated reports.

Clinical application of lung ultrasound score on COVID-19 setting: a regional experience in Southern Italy.

OBJECTIVE: We aimed to assess the correlation between LUS Soldati proposed score and clinical presentation, course of disease and the possible need of ventilation support/intensive care. PATIENTS AND METHODS: All consecutive patients with laboratory confirmed SARS-CoV-2 infection and hospitalized in two COVID Centers were enrolled. All patients performed blood gas analysis and lung ultrasound (LUS) at admission. The LUS acquisition was based on standard sequence of 14 peculiar anatomic landmarks with a score between 0-3 based on impairment of LUS picture. Total score was computed with their sum with a total score ranging 0 to 42, according to Soldati LUS score. We evaluated the course of hospitalization until either discharge or death, the ventilatory support and the transition in intensive care if needed. RESULTS: One hundred and fifty-six patients were included in the final analysis. Most of patients presented moderate-to-severe respiratory failure (FiO2 <20%, PaO2 <60 mmHg) and consequent recommendation to invasive mechanic ventilation (CPAP/NIV/OTI). The median ultrasound thoracic score was 28 (IQR 18-36) and most of patients could be ascertained either in a score 2 (40%) or score 3 pictures (24.4%). The bivariate correlation analysis displayed statistically significant and high positive correlations between the LUS score and the following parameters: ventilation (rho=0.481, p<0.001), lactates (rho=0.464, p<0.001), dyspnea (rho=0.398, p=0.001) mortality (rho=0.410, p=0.001). Conversely, P/F (rho= -0.663, p<0.001), pH (rho = -0.363, p=0.003) and pO2 (rho = -0.400 p=0.001) displayed significant negative correlations. CONCLUSIONS: LUS score improve the workflow and provide an optimal management both in early diagnosis and prognosis of COVID-19 related lung pathology.