Predictive Value of Prognostic Nutritional Index on COVID-19 Severity

Abstract

Background: The prognostic nutritional index (PNI) has been described as a simple risk-stratified tool for several diseases. We explored the predictive role of the PNI on coronavirus disease 2019 (COVID-19) severity. Methods: A total of 101 patients with COVID-19 were included in this retrospective study from January 2020 to March 2020. They were divided into two groups according to COVID-19 severity: non-critical (n = 56) and critical (n = 45). The PNI was calculated upon hospital admission: 10 × serum albumin (g/dL) + 0.005 × total lymphocyte count (/mm³). Critical COVID-19 was defined as having one of the following features: respiratory failure necessitating mechanical ventilation; shock; organ dysfunction necessitating admission to the intensive care unit (ICU). The correlation between the PNI with COVID-19 severity was analyzed. Results: The PNI was significantly lower in critically ill than that in non-critically ill patients (P < 0.001). The receiver operating characteristic curve indicated that the PNI was a good discrimination factor for identifying COVID-19 severity (P < 0.001). Multivariate logistic regression analysis showed the PNI to be an independent risk factor for critical illness due to COVID-19 (P = 0.002). Conclusions: The PNI is a valuable biomarker that could be used to discriminate COVID-19 severity.

Keywords: COVID-19; nutrition – clinical; prognosis; prognostic nutritional index; severity.

Figure 1

The ROC curves of PNI and its components for the prediction of critical COVID-19.

Figure 2

The ROC curves of PNI and GPS for the prediction of critical COVID-19.

Figure 3

Linear regression between PNI and clinical parameters (CRP and hemoglobin).