Intensive care medicine

2019-20 coronavirus outbreak

World Wide Web

Emergency medicine

Systemic inflammation

Proportional hazards model

Multivariate analysis

Virology

Confounding

Computer science

Mean platelet volume

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

Outbreak

Coronavirus disease 2019 (COVID-19)

Immunology

Retrospective cohort study

Lymphocyte

Index (typography)

Inflammation

Infectious disease (medical specialty)

Internal medicine

Survival analysis

Medicine

Gastroenterology

Disease

Platelet

Molecules

Background. The rapid onset of a systemic pro-inflammatory state followed by acute respiratory distress syndrome is the leading cause of mortality in patients with COVID-19. We performed a retrospective observational study to explore the capacity of different complete blood cell count (CBC)-derived inflammation indexes to predict in-hospital mortality in this group. Methods. The neutrophil to lymphocyte ratio (NLR), derived NLR (dNLR), platelet to lymphocyte ratio (PLR), mean platelet volume to platelet ratio (MPR), neutrophil to lymphocyte × platelet ratio (NLPR), monocyte to lymphocyte ratio (MLR), systemic inflammation response index (SIRI), systemic inflammation index (SII), and the aggregate index of systemic inflammation (AISI) were calculated on hospital admission in 119 patients with laboratory confirmed COVID-19. Results. Non-survivors had significantly higher AISI, dNLR, NLPR, NLR, SII, and SIRI values when compared to survivors. Similarly, Kaplan–Meier survival curves showed significantly lower survival in patients with higher AISI, dNLR, MLR, NLPR, NLR, SII, and SIRI. However, after adjusting for confounders, only the SII remained significantly associated with survival (HR = 1.0001; 95% CI, 1.0000–1.0001, p = 0.029) in multivariate Cox regression analysis. Conclusions. The SII on admission independently predicts in-hospital mortality in COVID-19 patients and may assist with early risk stratification in this group.

The Systemic Inflammation Index on Admission Predicts In-Hospital Mortality in COVID-19 Patients