![]() A highly accurate tool for predicting the clinical course of this disease could be very useful for risk stratification, clinical decision-making, and ultimately for reducing mortality. ![]() The early detection of patients with COVID-19 who may have worse outcomes is a priority. The disease’s spectrum ranges from a minor illness that can be treated on an outpatient basis to severe acute respiratory failure that may require admission to the intensive care unit (ICU) or death. The COVID-19 pandemic, a disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has had a huge impact on healthcare systems worldwide and resulted in more than 523 million known infections and well over 6.2 million deaths globally as of. This tool showed good predictive ability in successive disease waves. The RIM Score-COVID is a simple, easy-to-use method for predicting in-hospital COVID-19 mortality that uses parameters measured in most EDs. The model’s accuracy in predicting in-hospital COVID-19 mortality was assessed using the area under the receiver operating characteristics curve (AUROC). The cohort was divided into three time periods: T1 from February 1 to J(first wave), T2 from June 11 to Decem(second wave, pre-vaccination period), and T3 from January 1 to Decem(vaccination period). ![]() Validation was performed in the Spanish SEMI-COVID-19 Registry, which included consecutive patients hospitalized with confirmed COVID-19 in Spain. The nomogram uses five variables measured on arrival to the emergency department (ED): age, sex, oxygen saturation, C-reactive protein level, and neutrophil-to-platelet ratio. The RIM Score-COVID is a simple nomogram with high predictive capacity for in-hospital death due to COVID-19 designed using clinical and analytical parameters of patients diagnosed in the first wave of the pandemic. This work aims to validate the RIM Score-COVID in the SEMI-COVID-19 Registry. All rights reserved.The significant impact of COVID-19 worldwide has made it necessary to develop tools to identify patients at high risk of severe disease and death. Early diagnosis of these tumours, accompanied by a correct genetic diagnosis, should eventually become a priority to enable better treatment, early detection of complications, proper screening of family members and related tumours, as well as an improvement in the overall prognosis of these patients.įeocromocitoma Functional imaging Genetics Genética Imagen funcional MEN2 Paraganglioma Pheochromocytoma SDHx VHL.Ĭopyright © 2016 Sociedad Española de Nefrología. In turn, these genes are associated with a characteristic biochemical phenotype (noradrenergic and adrenergic), and clinical features (location, biological behaviour, age of presentation, etc.) in a large number of cases. ![]() These genes have a singular transcriptional signature and can be grouped into 2 clusters (or groups): cluster 1 (VHL and SHDx), involved in angiogenesis and hypoxia pathways and cluster 2 (MEN2 and NF1), linked to the kinase signalling pathway. Advances in genetic research have identified many genes involved in the pathogenesis of these tumours, suggesting that up to 35-45% may have an underlying germline mutation. Pheochromocytomas and paragangliomas are tumours derived from neural crest cells, which can be diagnosed by biochemical measurement of metanephrine and methoxytyramine. ![]()
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