Laboratory findings in predicting intensive care need and death of COVID-19 patients T he Coronavirus 2019 (COVID-19) outbreak began in December 2019 in Wuhan, China. Despite efforts to contain it, the epidemic spread around the world. On March 11, 2020, the World Health Organization (WHO) confirmed a pandemic. The number of coronavirus cases had reached 65 million and the number of deaths attributed to the disease was 1.5 million worldwide in December 2020 [1].Coronaviruses are an infectious agent for the common cold with subgroups that differ in contagiousness and risk of death. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes the illness coronavirus 2019 (COVID-19), is 10-20 times more transmissible than the original SARS-CoV [2, 3]. Countries across the globe are struggling to cope with economic difficulties caused by quarantine measures, as well as health resource constraints, such as insufficient medical facilities and healthcare personnel. Clinical and laboratory findings that can provide a reliable COVID-19 prognosis will help to perform risk stratification to distinguish patients at high risk of developing serious disease. It will also provide guidance for the best possible management of health resources [4]. The identification of laboratory parameters that can be used to predict the severity or Objectives: The ability to predict the course of COVID-19 is very valuable in terms of the optimal use of health resources. The aim of this study was to examine the value of biochemical and hematological parameters in the estimation of hospital stay, disease severity, and likelihood of death. Methods: Routine blood analysis data of confirmed COVID-19 cases (n=222) were collected and analyzed. The patients were divided into 3 groups: outpatient, inpatient, and patients requiring intensive care. Results: There were significant differences between the 3 groups in terms of age, lymphocyte, neutrophil, hemoglobin, hematocrit, mean corpuscular volume (MCV), red blood cell distribution width (RDW), neutrophil-to-lymphocyte ratio (NLR), neutrophil-to-monocyte ratio (NMR), platelet-to-lymphocyte ratio (PLR), procalcitonin, C-reactive protein (CRP), and D-dimer values. Univariate analysis for mortality revealed significant differences in neutrophil, NLR, PLR, NMR, procalcitonin, and CRP values. Multivariable logistic regression yielded significant differences in only NMR and procalcitonin values. A positive correlation was determined between the length of hospital stay and age, MPV, procalcitonin, and D-dimer values. Conclusion:The neutrophil count was the most appropriate parameter to predict the need for intensive care (area under the curve: 0.782, sensitivity: 73%, specificity: 75%, with a cutoff of 4.43). The NMR and procalcitonin values were significant to predict death in multivariate analysis. Age, CRP, and D-dimer values were the parameters most associated with the duration of hospitalization.
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