The predictive value of prognostic nutritional index in patients with COVID-19

Abstract

Introduction and Aim: It is crucial to identify and start treating the COVID-19 patients who are most at risk of becoming seriously ill as soon as possible. There is some evidence that prognostic nutritional index (PNI) could predict the outcome of some diseases. The study objective was to determine whether PNI is a useful prognostic tool for predicting the outcome of COVID-19-positive patients.   Patients and Methods: At Al-Shifaa Hospital in Baghdad Medical City, a total of 160 patients with COVID-19 participated in a study that was designed as a cross-sectional. At the time of admission, information was collected on the patient's history, including clinical, laboratory, and demographic details. The PNI score was determined by 10 × serum albumin (g/dL) + 0.005 × total lymphocyte count (/mm3). Patients were followed up for survival.   Results: The mortality rate was 14.37%. Survived patients had a mean age of 55.85±16.03 years compared with 64.30 ±14.76 years for died patients with a significant difference. Diabetes was more common among died (39.13%) than survived patients (15.33%) with a significant difference. The median serum level of C-reactive protein (CRP), D-dimer and ferritin in deceased patients was 84 mg/L, 2208 ng/ml and 650 ng/ml, respectively compared with 48 mg/L, 858 ng/ml and 550 ng/ml in survived patients with highly significant differences. The mean PNI in survived and non-survived patients was 40.89±5.9 and 37.86±4.36, respectively with a significant difference. The area under the curve (AUC) for PNI was 0.888, 95%CI = 0.827 and 0.939, p = 0.002 At an ideal cutoff value of 39.08, the test's sensitivity and specificity are 80 % and 74 %, respectively.   Conclusion: The PNI score is an easy-to-use, speedy, and cost-effective tool that has the potential to be utilized on a routine basis to predict mortality in patients with COVID-19.