![]() Several studies derived from the SEMI-COVID-19 Registry have reported clinical characteristics with prognostic value as well as prognostic scores. Over 24,000 patients over 18 years of age were included. The Spanish Society of Internal Medicine (SEMI, for its initials in Spanish) sponsored a nationwide COVID-19 patient registry in which 150 Spanish hospitals participated. Applying the nomogram to the validation cohort, the area under the receiver operating characteristics curve (AUROC) was 0.861 (95% CI 0.823–0.900). The RIM Score-COVID includes five variables commonly measured upon a patient’s arrival at the emergency department (ED): age, sex, baseline oxygen saturation (SpO2), C-reactive protein (CRP) level, and NPR. Our group created a prognostic nomogram (Risk of In-hospital Mortality Score in COVID-19 (RIM Score-COVID)) that is highly accurate for predicting in-hospital mortality. Several studies have established a link between the most severe cases of COVID-19 and blood cell count-derived ratios, such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), or neutrophil-to-platelet ratio (NPR). A number of prognostic models for COVID-19 have been proposed since the beginning of the pandemic. 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. 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.
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