Risk Score For Predicting In-hospital Mortality In COVID-19

The RIM score, a simple and widely available tool that can help identify patients at risk of fatal COVID-19 outcomes

Keywords: COVID-19; neutrophil-to-platelet ratio; NPR; neutrophil-to-lymphocyte ratio; NLR; hemogram-derived-ratios


The AUC (Area Under the Curve) of the models including NLR (neutrophil-platelet ratio) and NPR (neutrophillymphocyte ratio) performed similarly in both cohorts:

1. Training cohort:
– NLR 0.873 (IC 95%: 0.849-0.898)
– NPR 0.875 (IC 95%: 0.851-0.899)

2. Validation cohort:
– NLR 0.856 (IC 95%: 0.818-0.895)
– NPR 0.863 (IC 95%: 0.826-0.901)

The AUC was 0.885 (95% CI 0.885-0.919) for VNLR (rate of change of NLR) and 0.891 (95% CI 0.861-0.922) for VNPR (rate of change of NPR) in the validation cohort.

Description of the Study:

  • Title: Risk Score for Predicting In-Hospital Mortality in COVID-19 (RIM Score).
  • Principal Investigators: Alejandro López-Escobar, Rodrigo Madurga, José María Castellano, Sara Velázquez, Rafael Suárez del Villar, Justo Menéndez, Alejandro Peixoto, Sara Jimeno, Paula Sol Ventura and Santiago Ruiz de Aguiar.
  • Centres of Implementation: 10 hospitals of the HM Hospitales Group in different regions of Spain (including Madrid, Barcelona and Galicia).
  • Study Population: 2543 patients with COVID-19 hospitalised between 1 March and 10 June 2020. Patients with missing SaO2 at admission (n = 299) or laboratory data in the first 24 hours of admission (n = 258), whose age was less than 18 years (n = 5) or who were deceased at hospital admission (n = 26) were excluded from the analysis. Thus, of the total of 2543 patients admitted, 1955 (76.8%) were included in the final analysis.
  • Study Type: Retrospective study.
  • Design: The 1955 patients were divided into two groups, 1310 belonged to the training cohort and 645 to the validation cohort. Four different models were generated to predict in-hospital mortality. The following variables were included: age, sex, oxygen saturation, C-reactive protein level, neutrophil-platelet ratio (NPR), neutrophillymphocyte ratio (NLR) and the rate of change of both haemogram ratios (VNLR and VNPR) during the first week after admission.
  • Methods: The accuracy of the models in predicting in-hospital mortality were evaluated using the area under the receiver-operator-characteristic curve (AUC).

Objectives of the Study:

Principal Objective: To develop and validate a risk score for predicting in-hospital mortality in COVID-19 (Risk of In-hospital Mortality Score in COVID 19, RIM Score).

More about this Study:

Scientific Context: Coronavirus disease 2019 (COVID-19) has become a pandemic since the outbreak in Wuhan City, China, in December 2019, affecting more than 100 million patients worldwide by January 2021, with a death toll exceeding two million. Due to the high number of cases, many healthcare systems have collapsed because of the rapid evolution from a banal disease, which can be treated on an outpatient basis, to a disease with systemic complications including severe acute respiratory failure requiring admission to the Intensive Care Unit (ICU), and death.

Generating an accurate predictive tool to forecast the clinical course of the disease could be very useful for risk stratification, clinical decision making and rational optimisation of resources, including the administration of drugs to avoid serious adverse effects and ultimately reduce case fatality. Several studies have proposed simple clinical scores to identify patients at risk of progression to more severe forms of COVID-19.

Recent data have provided observational evidence linking the haemogram-derived ratios, neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR), to more severe cases of COVID-19.

Hm Hospitales

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