Signs of Cardiac Injury in Critically Ill Paediatric Patients with COVID-19: a Single-Center Experience in Brazil. / Sinais de Injúria Cardíaca em Pacientes Pediátricos com COVID-19 Gravemente Enfermos: Uma Experiência de Centro Único no Brasil.

BACKGROUND: Some patients with COVID-19 present myocardial injury. OBJECTIVE: To detect myocardial injury in critically ill paediatric patients, and to compare cardiac involvement between children with severe acute respiratory syndrome (SARS) and children with multisystemic inflammatory syndrome (MIS-C). METHODS: All COVID-19 children admitted to a referral intensive care unit were prospectively enrolled and had a two-dimensional echocardiogram (2D-TTE) and a cardiac troponin I (cTnI) assay within the first 72 hours. For statistical analysis, two-sided p < 0.05 was considered significant. RESULTS: Thirty-three patients were included, of which 51.5% presented elevated cTnI and/or abnormal 2D-TTE and 36.4% needed cardiovascular support, which was more frequent in patients with both raised cTnI and 2D-TTE abnormalities than in patients with normal exams (83.3% and 33.3%, respectively; p 0.006, 95% CI = 0.15-0.73). The most common 2D-TTE findings were pericardial effusion (15.2%) and mitral/tricuspid regurgitation (15.2%). Signs of cardiac involvement were more common in MIS-C than in SARS. MIS-C patients also presented a higher rate of the need for cardiovascular support (66.7% vs 25%, p 0.03, 95% CI = -0.7 to -0.04) and a more frequent rate of raised cTnI (77.8% vs 20.8%; p 0.002, 95% CI = 0.19 to 0.79). The negative predictive values of cTnI for the detection of 2D-TTE abnormalities were 100% for MIS-C patients and 73.7% for SARS patients. CONCLUSION: signs of cardiac injury were common, mainly in MIS-C patients. 2D-TTE abnormalities were subtle. To perform a cTnI assay upon admission might help providers to discriminate those patients with a more urgent need for a 2D-TTE.

FUNDAMENTO: Alguns pacientes com COVID-19 apresentam injúria miocárdica. OBJETIVO: Detectar a injúria miocárdica em pacientes criticamente doentes, e comparar o envolvimento cardíaco entre crianças com síndrome respiratória aguda grave (SARS) e crianças com síndrome inflamatória multissistêmica (MIS-C). MÉTODOS: Todas as crianças acometidas da COVID-19 admitidas em uma unidade de terapia intensiva de referência foram cadastradas de forma prospectiva e fizeram uma ecografia transtorácica bidimensional (ETT-2D) e um teste de troponina I cardíaca (cTnI) nas primeiras 72 horas. Para a análise estatística, um p <0,05 bilateral foi considerado significativo. RESULTADOS: 33 pacientes foram incluídos, dos quais 51,5% apresentaram cTnI elevada e/ou ETT-2D anormal e 36,4% precisaram de suporte cardiovascular, que foi mais frequente em pacientes com cTnI elevada e anormalidades em ETT-2D do que em pacientes com exames normais (83,3% e 33,3%, respectivamente; p 0,006, 95% IC = 0,15-0,73). Os achados de ETT-2D mais comuns foram efusão pericárdica (15,2%) e regurgitação tricúspide/mitral (15,2%). Sinais de envolvimento cardíaco foram mais comuns na MIS-C que na SARS. Pacientes com MIS-C também apresentaram um índice mais alto de necessidade de suporte cardiovascular (66,7% X 25%, p 0,03, 95% IC = -0,7 a -0,04) e um índice mais frequente de cTnI elevada (77,8% X 20,8%; p 0,002, 95% IC = 0,19 a 0,79). Os valores preditivos negativos de cTnI para detecção de anormalidades de ETT-2D foram 100% para pacientes com MIS-C, e 73,7% para pacientes com SARS. CONCLUSÃO: Sinais de injúria cardíaca foram comuns, especialmente em pacientes com MIS-C. As anormalidades na ETT-2D foram sutis. A realização de um teste de cTnI na admissão pode ajudar os prestadores de assistência de saúde a discriminar os pacientes com uma necessidade mais urgente de uma ETT-2D.

Echocardiographic Features of Cardiac Injury Related to COVID-19 and Their Prognostic Value: A Systematic Review.

BACKGROUND: The available information on the echocardiographic features of cardiac injury related to the novel coronavirus disease 2019 (COVID-19) and their prognostic value are scattered in the different literature. Therefore, the aim of this study was to investigate the echocardiographic features of cardiac injury related to COVID-19 and their prognostic value. METHODS: Published studies were identified through searching PubMed, Embase (Elsevier), and Google scholar databases. The search was performed using the different combinations of the keywords "echocard*," "cardiac ultrasound," "TTE," "TEE," "transtho*," or "transeso*" with "COVID-19," "sars-COV-2," "novel corona, or "2019-nCOV." Two researchers independently screened the titles and abstracts and full texts of articles to identify studies that evaluated the echocardiographic features of cardiac injury related to COVID-19 and/or their prognostic values. RESULTS: Of 783 articles retrieved from the initial search, 11 (8 cohort and 3 cross-sectional studies) met our eligibility criteria. Rates of echocardiographic abnormalities in COVID-19 patients varied across different studies as follow: RV dilatation from 15.0% to 48.9%; RV dysfunction from 3.6% to 40%; and LV dysfunction 5.4% to 40.0%. Overall, the RV abnormalities were more common than LV abnormalities. The majority of the studies showed that there was a significant association between RV abnormalities and the severe forms and death of COVID-19. CONCLUSION: The available evidence suggests that RV dilatation and dysfunction may be the most prominent echocardiographic abnormality in symptomatic patients with COVID-19, especially in those with more severe or deteriorating forms of the disease. Also, RV dysfunction should be considered as a poor prognostic factor in COVID-19 patients.

COVID-19 pathways for brain and heart injury in comorbidity patients: A role of medical imaging and artificial intelligence-based COVID severity classification: A review.

Artificial intelligence (AI) has penetrated the field of medicine, particularly the field of radiology. Since its emergence, the highly virulent coronavirus disease 2019 (COVID-19) has infected over 10 million people, leading to over 500,000 deaths as of July 1st, 2020. Since the outbreak began, almost 28,000 articles about COVID-19 have been published (https://pubmed.ncbi.nlm.nih.gov); however, few have explored the role of imaging and artificial intelligence in COVID-19 patients-specifically, those with comorbidities. This paper begins by presenting the four pathways that can lead to heart and brain injuries following a COVID-19 infection. Our survey also offers insights into the role that imaging can play in the treatment of comorbid patients, based on probabilities derived from COVID-19 symptom statistics. Such symptoms include myocardial injury, hypoxia, plaque rupture, arrhythmias, venous thromboembolism, coronary thrombosis, encephalitis, ischemia, inflammation, and lung injury. At its core, this study considers the role of image-based AI, which can be used to characterize the tissues of a COVID-19 patient and classify the severity of their infection. Image-based AI is more important than ever as the pandemic surges and countries worldwide grapple with limited medical resources for detection and diagnosis.