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Background: Coronavirus disease 2019 (COVID-19) is a pandemic outbreak of RNA coronaviruses (SARS-CoV-2), associated with acute respiratory distress syndrome, multiple organ failure, and death. The surface electrocardiogram is the first line assessment of cardiac electrical system. We aimed to interpret classically the electrocardiographic parameters at admission and during hospital course and association of them with prognosis in patients admitted with diagnosis of infection with SARS-CoV-2.
Methods: Surface electrocardiograms (ECG) were obtained from 180 patients with SARS-CoV-2 infection at a large tertiary referral university hospital at north of Iran in Babol. The electrocardiographic waves, intervals and segments in addition to supraventricular and ventricular arrhythmias were depicted. Our cohort included two groups: discharged alive and dead during the hospital course. We compared the ECG characteristics of patients who died vs. survived ones.
Results: Some ECG parameters of 180 hospitalized patients were significantly associated with mortality, like heart rate (p< 0.001), bundle branch block (P= 0.035), fragmented QRS (P= 0.015), ST elevation (P= 0.004), T p-e duration (P= 0.006), premature atrial and ventricular complexes (P= 0.030, P= 0.004) and atrial fibrillation (P= 0.003).
Conclusion: The SARS-CoV-2 infection had several impacts on cardiac electrical system which may monitored with a simple and easily accessible tool like ECG. This tool also helpful in the risk stratification of patients.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11246685 | PMC |
http://dx.doi.org/10.22088/cjim.15.3.444 | DOI Listing |
J Clin Invest
September 2025
The University of Texas at Austin, Austin, United States of America.
Background: Following SARS-CoV-2 infection, ~10-35% of COVID-19 patients experience long COVID (LC), in which debilitating symptoms persist for at least three months. Elucidating biologic underpinnings of LC could identify therapeutic opportunities.
Methods: We utilized machine learning methods on biologic analytes provided over 12-months after hospital discharge from >500 COVID-19 patients in the IMPACC cohort to identify a multi-omics "recovery factor", trained on patient-reported physical function survey scores.
JAMA Netw Open
September 2025
Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia.
Importance: Long COVID (ie, post-COVID-19 condition) is a substantial public health concern, and its association with health-related social needs, such as food insecurity, remains poorly understood. Identifying modifiable risk factors like food insecurity and interventions like food assistance programs is critical for reducing the health burden of long COVID.
Objective: To investigate the association of food insecurity with long COVID and to assess the modifying factors of Supplemental Nutrition Assistance Program (SNAP) participation and employment status.
JAMA Netw Open
September 2025
Centre de recherche intégrée pour un système apprenant en santé et services sociaux, Centre intégré de santé et de services sociaux de Chaudière-Appalaches, Lévis, Québec, Canada.
Importance: Caregivers of community-dwelling older adults play a protective role in emergency department (ED) care transitions. When the demands of caregiving result in caregiver burden, ED returns can ensue.
Objective: To develop models describing whether caregiver burden is associated with ED revisits and hospital admissions up to 30 days after discharge from an initial ED visit.