Combination of red blood cell distribution width and body mass index (COR-BMI) predicts in-hospital mortality in patients with different diagnoses?

• Main Authors: Isabela Borges Ferreira, Emanuelle do Nascimento Santos Lima, Nayara Cristina da Silva, Isaías Valente Prestes, Geórgia das Graças Pena
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2019-01-01
• Series: PLoS ONE
• Online Access: https://doi.org/10.1371/journal.pone.0219549

<h4>Background</h4>The combination of red blood cell distribution width and body mass index (COR-BMI) is indicated as a new prognostic index of survival in patients with laryngeal cancer. However, the ability of this prediction in other types of cancer or whether its use can be expanded to non-oncological patients is unknown. The aim of this study was to investigate the prediction of prognosis of in-hospital mortality of the COR-BMI in oncological and non-oncological patients.<h4>Methods</h4>A retrospective study was performed with all hospitalized patients between 2014 and 2016, totaling 2930 patients, 262 oncological and 2668 non-oncological. The COR-BMI was divided into three classes: 0, RDW ≤ 13.1% and BMI ≥ 25 kg/m2; 1, RDW ≤ 13.1% and BMI < 18.5 or ≥ 18.5 but < 25 kg/m2 and RDW > 13.1% and BMI ≥ 18.5 but < 25 or BMI ≥ 25 kg/m2; and 2, RDW > 13.1% and BMI < 18.5 kg/m2. In order to analyze the relationship between COR-BMI and in-hospital mortality in the studied population, the Cox Proportional Hazards Model was used in a multivariate analysis based on a conceptual model.<h4>Results</h4>The COR-BMI was an independent predictor of in-hospital mortality in non-oncological patients (1 versus 0: HR = 3.34; CI = 1.60-6.96, p = 0.001; 2 versus 0: HR = 3.38; CI = 1.22-9.39, p = 0.019). The survival rate of these patients was lower among those with the highest scores on the COR-BMI. This prediction was not found in oncological patients.<h4>Conclusion</h4>The present study suggests that the COR-BMI may have its practical use expanded to non-oncological patients as an independent predictor of in-hospital mortality.