International journal of cardiology
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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.
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Current European Society of Cardiology (ESC)/European Atherosclerosis Society (EAS) guidelines for the management of dyslipidemias have further reduced low density lipoprotein-cholesterol (LDL-C) targets, as compared to the guidelines released in 2016. These targets are particularly restraining for patients at very high risk (VHR). ⋯ In VHR patients enrolled in this large cohort of established ASCVD managed by cardiologists, the lipid management and LDL-C targets attainment is largely suboptimal.
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Hydroxychloroquine and azithromycin combination therapy is often prescribed for coronavirus disease 2019 (COVID-19). Electrocardiographic (ECG) monitoring is warranted because both medications cause corrected QT-interval (QTc) prolongation. Whether QTc duration significantly varies during the day, potentially requiring multiple ECGs, remains to be established. ⋯ Therapy with hydroxychloroquine and azithromycin prolongs QTc interval in patients with COVID-19, particularly in those with high levels of transaminases. Because QTc duration remains stable during the 24 h, multiple daily ECG are not recommendable.
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Deep learning (DL) has shown promising results in improving atrial fibrillation (AF) detection algorithms. However, these models are often criticized because of their "black box" nature. ⋯ The morphology based DL model developed in this study was able to discriminate AF from SR with a very high accuracy. DL model visualization may help clinicians gain insights into which (unrecognized) ECG features are most sensitive to discriminate AF from SR.