Cardiac arrhythmias in patients hospitalized with COVID-19: The ACOVID study.
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ABSTRACT:
SUBMITTER: Zareini B
PROVIDER: S-EPMC8322796 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Cardiac manifestation of COVID-19 has been reported during the COVID pandemic. The role of cardiac arrhythmias in COVID-19 is insufficiently understood. This study assesses the incidence of cardiac arrhythmias and their prognostic implications in hospitalized COVID-19-patients. A total of 166 patients from eight centers who were hospitalized for COVID-19 from 03/2020-06/2020 were included. Medical records were systematically analyzed for baseline characteristics, biomarkers, cardiac arrhythmias and clinical outcome parameters related to the index hospitalization. Predisposing risk factors for arrhythmias were identified. Furthermore, the influence of arrhythmia on the course of disease and related outcomes was assessed using univariate and multiple regression analyses. Arrhythmias were detected in 20.5% of patients. Atrial fibrillation was the most common arrhythmia. Age and cardiovascular disease were predictors for new-onset arrhythmia. Arrhythmia was associated with a pronounced increase in cardiac biomarkers, prolonged hospitalization, and admission to intensive- or intermediate-care-units, mechanical ventilation and in-hospital mortality. In multiple regression analyses, incident arrhythmia was strongly associated with duration of hospitalization and mechanical ventilation. Cardiovascular disease was associated with increased mortality. Arrhythmia was the most common cardiac event in association with hospitalization for COVID-19. Older age and cardiovascular disease predisposed for arrhythmia during hospitalization. Whereas in-hospital mortality is affected by underlying cardiovascular conditions, arrhythmia during hospitalization for COVID-19 is independently associated with prolonged hospitalization and mechanical ventilation. Thus, incident arrhythmia may indicate a patient subgroup at risk for a severe course of disease.
| S-EPMC7796041 | biostudies-literature
Project description:Arrhythmias have been reported frequently in COVID-19 patients, but the incidence and nature have not been well characterized. Patients admitted with COVID-19 and monitored by telemetry were prospectively enrolled in the study. Baseline characteristics, hospital course, treatment and complications were collected from the patients' medical records. Telemetry was monitored to detect the incidence of cardiac arrhythmias. The incidence and types of cardiac arrhythmias were analyzed and compared between survivors and non-survivors. Among 143 patients admitted with telemetry monitoring, overall in-hospital mortality was 25.2% (36/143 patients) during the period of observation (mean follow-up 23.7 days). Survivors were less tachycardic on initial presentation (heart rate 90.6 ± 19.6 vs. 99.3 ± 23.1 bpm, p = 0.030) and had lower troponin (peak troponin 0.03 vs. 0.18 ng/ml. p = 0.004), C-reactive protein (peak C-reactive protein 97 vs. 181 mg/dl, p = 0.029), and interleukin-6 levels (peak interleukin-6 30 vs. 246 pg/ml, p = 0.003). Sinus tachycardia, the most common arrhythmia (detected in 39.9% [57/143] of patients), occurred more frequently in non-survivors (58.3% vs. 33.6% in survivors, p = 0.009). Premature ventricular complexes occurred in 28.7% (41/143), and non-sustained ventricular tachycardia in 15.4% (22/143) of patients, with no difference between survivors and non-survivors. Sustained ventricular tachycardia and ventricular fibrillation were not frequent (seen only in 1.4% and 0.7% of patients, respectively). Contrary to reports from other regions, overall mortality was higher and ventricular arrhythmias were infrequent in this hospitalized and monitored COVID-19 population. Either disease or management-related factors could explain this divergence of clinical outcomes, and should be urgently investigated.
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Project description:Atrial arrhythmias (AA) are common in hospitalized COVID-19 patients with limited data on their association with COVID-19 infection, clinical and imaging outcomes. In the related research article using retrospective research data from one quaternary care and five community hospitals, patients aged 18 years and above with positive SARS-CoV-2 polymerase chain reaction test were included. 6927 patients met the inclusion criteria. The data in this article provides demographics, home medications, in-hospital events and COVID-19 treatments, multivariable generalized linear regression regression models using a log link with a Poisson distribution (multi-parameter regression [MPR]) to determine predictors of new-onset AA and mortality in COVID-19 patients, computerized tomography chest scan findings, echocardiographic findings, and International Classification of Diseases-Tenth Revision codes. The clinical outcomes were compared to a propensity-matched cohort of influenza patients. For influenza, data is reported on baseline demographics, comorbid conditions, and in-hospital events. Generalized linear regression models were built for COVID-19 patients using demographic characteristics, comorbid conditions, and presenting labs which were significantly different between the groups, and hypoxia in the emergency room. Statistical analysis was performed using R programming language (version 4, ggplot2 package). Multivariable generalized linear regression model showed that, relative to normal sinus rhythm, history of AA (adjusted relative risk [RR]: 1.38; 95% CI: 1.11-1.71; p = 0.003) and newly-detected AA (adjusted RR: 2.02 95% CI: 1.68-2.43; p < 0.001) were independently associated with higher in-hospital mortality. Age in increments of 10 years, male sex, White race, prior history of coronary artery disease, congestive heart failure, end-stage renal disease, presenting leukocytosis, hypermagnesemia, and hypomagnesemia were found to be independent predictors of new-onset AA in the MPR model. The dataset reported is related to the research article entitled "Incidence, Mortality, and Imaging Outcomes of Atrial Arrhythmias in COVID-19" [Jehangir et al. Incidence, Mortality, and Imaging Outcomes of Atrial Arrhythmias in COVID-19, American Journal of Cardiology] [1].
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Project description:The lack of available biomarkers for diagnosing and predicting different stages of coronavirus disease 2019 (COVID-19) is currently one of the main challenges that clinicians are facing. Recent evidence indicates that the plasma levels of specific miRNAs may be significantly modified in COVID-19 patients. Large-scale deep sequencing analysis of small RNA expression was performed on plasma samples from 40 patients hospitalized for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (between March and May 2020) (median 13.50 [IQR 9–24] days since symptoms initiation) and 21 healthy noninfected individuals. Patients were categorized as hospitalized not requiring oxygen therapy (n = 6), hospitalized requiring low-flow oxygen (n = 23), and hospitalized requiring high-flow oxygen support (n = 11). A total of 1218 different micro(mi)RNAs were identified. When compared with healthy noninfected donors, SARS-CoV-2 infected patients showed significantly (fold change [FC] >1.2 and adjusted p [padj] <0.05) altered expression of 190 miRNAs. The top 10 differentially expressed (DE) miRNAs were miR-122-5p, let-7b-5p, miR-146a-5p, miR-342-3p, miR-146b-5p, miR-629-5p, miR-24-3p, miR-12136, let-7a-5p, and miR-191-5p, which displayed FC and padj values ranging from 153 to 5 and 2.51 × 10-32 to 2.21 × 10-21, respectively, which unequivocally diagnosed SARS-CoV-2 infection. No differences in blood cell counts and biochemical plasma parameters, including interleukin 6, ferritin and D-dimer, were observed between COVID-19 patients on high-flow oxygen therapy, low-flow oxygen therapy, or not requiring oxygen therapy. Notably, 31 significantly deregulated miRNAs were found when patients on high- and low-flow oxygen therapy were compared. Similarly, 6 DE miRNAs were identified between patients on high flow and those not requiring oxygen therapy. SARS-CoV-2 infection generates a specific miRNA signature in hospitalized patients. Furthermore, specific miRNA profiles are associated with COVID-19 prognosis in severe patients.
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