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Since the outbreak of highly virulent coronaviruses, significant interest was assessed to the brain and heart axis (BHA) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-affected patients. The majority of clinical reports accounted for unusual symptoms associated with SARS-CoV-2 infections which are of the neurological type, such as headache, nausea, dysgeusia, anosmia, and cerebral infarction. The SARS-CoV-2 enters the cells through the angiotensin-converting enzyme (ACE-2) receptor. Patients with prior cardiovascular disease (CVD) have a higher risk of COVID-19 infection and it has related to various cardiovascular (CV) complications. Infected patients with pre-existing CVDs are also particularly exposed to critical health outcomes. Overall, COVID-19 affected patients admitted to intensive care units (ICU) and exposed to stressful environmental constraints, featured with a cluster of neurological and CV complications. In this review, we summarized the main contributions in the literature on how SARS-CoV-2 could interfere with the BHA and its role in affecting multiorgan disorders. Specifically, the central nervous system involvement, mainly in relation to CV alterations in COVID-19-affected patients, is considered. This review also emphasizes the biomarkers and therapy options for COVID-19 patients presenting with CV problems.  相似文献   
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In this article, we address a missing data problem that occurs in transplant survival studies. Recipients of organ transplants are followed up from transplantation and their survival times recorded, together with various explanatory variables. Due to differences in data collection procedures in different centers or over time, a particular explanatory variable (or set of variables) may only be recorded for certain recipients, which results in this variable being missing for a substantial number of records in the data. The variable may also turn out to be an important predictor of survival and so it is important to handle this missing-by-design problem appropriately. Consensus in the literature is to handle this problem with complete case analysis, as the missing data are assumed to arise under an appropriate missing at random mechanism that gives consistent estimates here. Specifically, the missing values can reasonably be assumed not to be related to the survival time. In this article, we investigate the potential for multiple imputation to handle this problem in a relevant study on survival after kidney transplantation, and show that it comprehensively outperforms complete case analysis on a range of measures. This is a particularly important finding in the medical context as imputing large amounts of missing data is often viewed with scepticism.  相似文献   
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We have analysed the influence of human malignant, inflammatory and infectious disease on the capacity of peripheral lymphocytes to mediate antibody-dependent haemolysis. The application of an enzyme-like kinetic model for measurement of maximal cytotoxic function has permitted reproducible and sensitive determinations of the K-cell function. The results show that malignant disease is associated with enhancement of ADCC capacity.  相似文献   
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