Outcomes of Heart Failure Related Hospitalizations During the COVID-19 Pandemic

Association of New-Onset Atrial Fibrillation With All-Cause Mortality in COVID-19 Patients

Background The COVID-19 pandemic has brought about unprecedented global health challenges, with its impact extending beyond respiratory manifestations to encompass cardiovascular complications, including arrhythmias. Dysrhythmias in COVID-19 are multifactorial, ranging from direct myocardial insult due to the cytokine storm to metabolic derangements. Objective In this study, we aim to examine the incidence of new-onset atrial fibrillation and to study its association with all-cause mortality of COVID-19. Methods A cross-sectional study was conducted at Cabell Huntington Hospital, West Virginia, utilizing electronic medical records of COVID-19 patients from 2020 to 2021. Inclusion criteria comprised patients aged >18 years with COVID-19 diagnosis and cardiac arrhythmias during hospitalization. Logistic regression analysis was employed to examine the relationship between demographic and clinical variables and in-hospital mortality. Results Of the 264 eligible patients, those aged >66 years had lower odds of in-hospital mortality (p < 0.001), while gender, ejection fraction, and diabetes mellitus did not significantly predict mortality. Atrial fibrillation (p = 0.011) and heart failure (p = 0.030) were associated with increased odds of mortality, while hypertension showed no significant predictive power (p = 0.791). Conclusion This study highlights the significance of atrial fibrillation and heart failure as predictors of in-hospital mortality in COVID-19 patients. Our findings underscore the importance of recognizing and managing arrhythmias in COVID-19 and call for further research on the mechanisms and long-term effects of these cardiac complications in the context of the pandemic. These insights can guide clinical practice and interventions to optimize patient outcomes.

Predictors of disease severity in patients hospitalized with coronavirus disease 2019

BACKGROUND

Coronavirus disease 2019 (COVID-19), caused by a novel coronavirus, manifests as a respiratory illness primarily and symptoms range from asymptomatic to severe respiratory syndrome and even death. During the pandemic, due to overcrowding of medical facilities, clinical assessment to triage patients for home care or in-hospital treatment was an essential element of management.

OBJECTIVES

Study the demographic features, comorbidities and bio-markers that predict severe illness and mortality from COVID-19 infection.

DESIGN

Retrospective observational SETTING: Single tertiary care center PATIENTS AND METHODS: The study included all patients admitted with a positive PCR test for COVID-19 during the period from March 2020 to September 2020 (7 months). Data on demographics, clinical data and laboratory parameters was collected from medical records every 3 days during hospital stay or up until transfer to ICU.

MAIN OUTCOME MEASURES

Demographic, comorbidities and biochemical features that might predict severe COVID-19 disease.

SAMPLE SIZE

372 RESULTS: Of the 372 patients, 72 (19.4%) had severe disease requiring admission to intensive care unit (ICU); 6 (1.6%) died. Individuals over 62 years were more likely to be admitted to the ICU (P=.0001, while a BMI of 40 and higher increased the odds of severe disease (P=.032). Male gender (P=.042), hypertension (P=.006) and diabetes (P=.001) conferred a statistically significant increased risk of admission to ICU, while coexisting COPD, and ischemic heart disease did not. Laboratory features related to severe COVID-19 infection were: leukocytosis (P=.015), thrombocytopenia (P=.001), high levels of C-reactive protein (P=.0001), lactic dehydrogenase (P=.0001), D-dimer (P=.0001) and ferritin (P=.001). With the multivariate analysis, diabetes, high lac-tate dehydrogenase, C-reactive protein and thrombocytopenia were associated with severity of illness.

CONCLUSIONS

Particular demographic and clinical parameters may predict severe illness and need for ICU care.

LIMITATIONS

Single referral center, several cases of severe COVID-19 could not be included due to lack of consent and or data.

CONFLICT OF INTEREST

None.