Abstract
Objectives As a result of developed generalized inflammation, the main prognostic factor determining morbidity and mortality in coronavirus disease 2019 (COVID-19) patients is acute respiratory distress syndrome. The purpose of our study was to define (1) the laboratory tests that will contribute to the diagnosis and follow-up of COVID-19 patients, (2) the differences between the laboratory-confirmed (LC), unconfirmed (LUC), and control (C) groups, and (3) the variation between groups of acute-phase reactants and biomarkers that can be used as an indicator of disease severity and inflammation.
Materials and Methods A total of 102 patients undergoing treatment with COVID-19 interim guidelines were evaluated. Reverse transcriptase-polymerase chain reaction (RT-PCR) test was positive in 56 (LC), classified as mild or severe, and negative in 46 (LUC) patients. In addition, 30 healthy subjects (C) with negative RT-PCR tests were also evaluated.All statistical analyses were performed with the SPSS 22.0 program and the p-values for significant findings were less than 0.05. Parametric/nonparametric distribution was determined by performing the Kolmogorov–Smirnov test for all groups. Student's t-test was used for variables with parametric distribution and the Mann–Whitney U-test for variables with the nonparametric distribution. A cut-off level for biomarkers was determined using the ROC (receiver operator characteristic) curve.
Results In the LC group, platelet, platecrit, mean platelet volume, platelet diameter width, white blood cell, lymphocyte, eosinophil, neutrophil, immature granulocyte, immature lymphocyte, immature monocyte, large immune cell, and atypical lymphocyte counts among the complete blood count parameters of mature and immature cell counts showed a significant difference according to the C and LUC groups. C-reactive protein, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and C-reactive protein-to-albumin ratio (CAR) indices were significantly elevated in LC patients and were significantly higher in patients classified as severe compared to mild. When CAR optimal cutoff was determined as 0.475, area under the curve was 0.934, sensitivity was 90.91%, specificity was 86.21%, positive predictive value was 92.59%, and negative predictive value was 83.33%. The diagnostic accuracy for CAR was 89.29%.
Conclusion The CAR index with the highest diagnostic value and the highest predictability could be the most useful biomarker in the diagnosis and evaluation of disease severity in COVID-19 patients.
Predictive value of C-Reactive Protein/Albumin ratio in patients with chronic complicated diabetes mellitus