International journal of cardiology
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With the recent emergence of SARS-CoV-2 and COVID-19, healthcare facilities and personnel are expected to rapidly triage and care for patients with even the most complex medical conditions. Adults with congenital heart disease (ACHD) represent an often-intimidating group of complex cardiovascular disorders. Given that general internists and general cardiologists will often be asked to evaluate this group during the pandemic, we propose here an abbreviated triage algorithm that will assist in identifying the patient's overarching ACHD phenotype and baseline cardiac status. The strategy outlined allows for rapid triage and groups various anatomic CHD variants into overarching phenotypes, permitting care teams to quickly review key points in the management of moderate to severely complex ACHD patients.
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Editorial Comment
Interventional cardiology in the neonate: Still a macgyver procedure?
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The novel coronavirus disease, affecting ~9 million people in the past five months and causing >460,000 deaths worldwide, is completely new to mankind. More than 2,000 research projects registered at ClinTrials.gov are aiming at finding effective treatments for rapid transfer to clinical practice. Unfortunately, just few studies have a sufficiently valid design to provide reliable information for clinical practice.
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Patient delay is a worldwide unsolved problem in ST-segment elevated myocardial infarction (STEMI). An accurate warning system based on electrocardiogram (ECG) may be a solution for this problem, and artificial intelligence (AI) may offer a path to improve its accuracy and efficiency. ⋯ In a comparative test with cardiologists, the algorithm had an AUC of 0.9740 (95% CI, 0.9419 to 1), and its sensitivity (recall), specificity, accuracy, precision, and F1 score were 90%, 98% and 94%, 97.82% and 0.9375 respectively, while the medical doctors had sensitivity (recall), specificity, accuracy, precision and F1 score of 71.73%, 89.33%, 80.53%, 87.05% and 0.8817 respectively. This study developed an AI-based, cardiologist-level algorithm for identifying STEMI.
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Meta Analysis
Heart failure, frailty, and pre-frailty: A systematic review and meta-analysis of observational studies.
Frailty is a syndrome characterized by reduced physiological reserves, increased vulnerability to stressors and adverse health outcomes. Frailty can change the prognosis and treatment approach of several chronic diseases, including heart failure (HF). The aim of this study was to conduct a systematic review and meta-analysis assessing the association of HF with frailty and pre-frailty. ⋯ In conclusion, frailty and pre-frailty are frequent in people with HF. Persons with HF have 3.4-fold increased odds of frailty. Longitudinal studies examining bidirectional pathophysiological pathways between HF and frailty are needed to further clarify this relationship and to assess if specific treatment for HF may prevent or delay the onset of frailty and vice versa.