Assessment of Systemic Immune Inflammation Index to Predict SARS-CoV-2 Infection

Abstract

Coronavirus Disease 2019 (COVID-19) is an infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and has become a major health problem worldwide. Inflammation plays a vital role in the pathophysiology of COVID-19. Systemic Immune Inflammation Index (SII) is an index obtained from calculating the platelets counts, neutrophils, and lymphocytes, which can indicate the inflammation status and immunity. This study aimed to determine the potential of SII as a predictor of SARS-CoV-2 infection in suspected COVID-19 subjects. A retrospective study was carried out by obtaining medical record data in June 2020 at Sleman General Hospital. An unpaired T-test or the Mann-Whitney test was used to determine the statistical difference. A Receiver Operating Characteristic (ROC) curve was generated and used to get the cut-off values. Bivariate analysis was performed using Chi-Square. There were 84 subjects consisting of 46 (54.8%) males and 38 (45.2%) females with a mean age of 42.4±16.356 years. There was a significant difference in the neutrophils count (p=0.045), monocytes (p=0.001), and eosinophils (p=0.037) between subjects with positive and negative SARS-CoV-2 PCR. The median SII in the positive and negative SARS-CoV-2 PCR group was 780.12 (301.21-2178.90)x103/µL and 584.14 (117.79-1933.87)x103/µL (p=0.045), respectively. Bivariate analysis showed significant results at SII > 705 x103/µL in suspected COVID-19 patients to obtain a positive SARS-CoV-2 PCR result with Odds Ratio (OR) of 4.00 (95% CI 1.580-10.127), p=0.003. Patients with suspected SARS-CoV-2 infection with high SII levels had a greater risk of a positive SARS-CoV-2 in PCR test