The aggregate index of systemic inflammation may predict mortality in COVID-19 patients with chronic renal failure.

ABSTRACT

OBJECTIVE: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), was first detected in December 2019 and then spread globally, resulting in a pandemic. Initially, it was unknown if chronic kidney disease (CKD) contributed to the mortality caused by COVID-19. The immunosuppression associated with this disease may minimize the COVID-19-described hyper-inflammatory state or immunological dysfunction, and a high prevalence of comorbidities may lead to a poorer clinical prognosis. Patients with COVID-19 have abnormal circulating blood cells associated with inflammation. Risk stratification, diagnosis, and prognosis primarily rely on hematological features, such as white blood cells and their subpopulations, red cell distribution width, mean platelet volume, and platelet count, in addition to their combined ratios. In non-small-cell lung cancer, the aggregate index of systemic inflammation (AISI), (neutrophils x monocytes x platelets/lymphocytes) is evaluated. In light of the relevance of inflammation in mortality, the objective of this study is to determine the impact of AISI on the hospital mortality of CKD patients. PATIENTS AND METHODS: This study is an observational retrospective study. Data and test outcomes of all CKD patients, stages 3-5, hospitalized for COVID-19 and followed between April and October 2021 were analyzed. RESULTS: Patients were divided into two groups according to death (Group 1-Alive, Group 2-Died). Neutrophil count, AISI and C-reactive protein (CRP) levels were increased in Group-2 [10.3±4.6 vs. 7.65±4.22; p=0.001, 2,084.1 (364.8-2,577.5) vs. 628.9 (53.1-2,275); p=0.00 and 141.9 (20.5-318) vs. 84.75 (0.92-195); p=0.00; respectively]. Receiver operating characteristic (ROC) analysis demonstrated 621.1 as a cut-off value for AISI to predict hospital mortality with 81% sensitivity and 69.1% specificity [area under ROC curve 0.820 (95% CI 0.733-0.907), p<.005]. Cox regression analysis was used to analyze the effect of risk variables on survival. In survival analysis, AISI and CRP were identified as important survival predictors [hazard ratio (HR) 1.001, 95% CI 1-1.001; p=0.00 and HR 1.009, 95% CI 1.004-1.013; p=0.00]. CONCLUSIONS: This study demonstrated the discriminative effectiveness of AISI in predicting disease mortality in COVID-19 patients with CKD. Quantification of AISI upon admission might assist in the early detection and treatment of individuals with a bad prognosis.