Relationships between RDW, NLR, CAR, and APACHE II scores in the context of predicting the prognosis and mortality in ICU patients

M. Deniz, P. Ozgun, E. Ozdemir

Intensive Care Unit, Izzet Baysal State Hospital, Bolu, Turkey. drmdeniz@gmail.com

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• Emergency Medicine
• Internal Medicine

OBJECTIVE: Intensive care units (ICU) are tasked with critical care and treatment with a view to improving prognosis. The Acute Physiology and Chronic Health Evaluation II (APACHE II) is one of the most commonly used scoring systems to predict prognosis. In this context, the objective of this study is to evaluate the prognostic value of Red Cell Distribution Width (RDW), Neutrophil-Lymphocyte ratio (NLR), and C-reactive protein to albumin ratio (CAR) in predicting the prognosis and mortality in patients admitted to the ICU.

PATIENTS AND METHODS: The RDW, NLR, and CAR values and APACHE II scores of patients admitted into an ICU, where heterogeneous groups of patients are usually treated, were recorded, categorized based on survival status, and investigated for any correlation between surviving patients’ mortality and length of stay (LoS) in ICU and the said parameters.

RESULTS: The ICU mortality among the 2,147 patients included in the study was 43.2%. The most common diagnosis of the patients admitted to the ICU was sepsis. The RDW, NLR, and CAR values and APACHE II scores of the deceased patients were significantly higher than those of the survived patients. There was a significant correlation between LoS in ICU and the said parameters in the positive direction in the survived group only. The APACHE II score had the highest prognostic value in predicting mortality, followed by RDW, CAR, and NLR values in descending order.

CONCLUSIONS: Among the parameters investigated in this study, RDW had the highest prognostic value in predicting the prognosis and mortality. Hence, it may be incorporated into or used alongside the APACHE II scoring system to predict patient outcomes with higher accuracy. However, further randomized controlled studies are needed to determine the cut-off values in predicting the prognosis and mortality.

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