Simple Parameters from Complete Blood Count Predict In-Hospital Mortality in COVID-19

Introduction. The clinical course of Coronavirus Disease 2019 (COVID-19) is highly heterogenous, ranging from asymptomatic to fatal forms. The identification of clinical and laboratory predictors of poor prognosis may assist clinicians in monitoring strategies and therapeutic decisions. Materials and Methods. In this study, we retrospectively assessed the prognostic value of a simple tool, the complete blood count, on a cohort of 664 patients (F 260; 39%, median age 70 (56-81) years) hospitalized for COVID-19 in Northern Italy. We collected demographic data along with complete blood cell count; moreover, the outcome of the hospital in-stay was recorded. Results. At data cut-off, 221/664 patients (33.3%) had died and 453/664 (66.7%) had been discharged. Red cell distribution width (RDW) (chi(2) 10.4; p<0.001), neutrophil-to-lymphocyte (NL) ratio (chi(2) 7.6; p=0.006), and platelet count (chi(2) 5.39; p=0.02), along with age (chi(2) 87.6; p<0.001) and gender (chi(2) 17.3; p<0.001), accurately predicted in-hospital mortality. Hemoglobin levels were not associated with mortality. We also identified the best cut-off for mortality prediction: a NL ratio>4.68 was characterized by an odds ratio for in-hospital mortality (OR)=3.40 (2.40-4.82), while the OR for a RDW>13.7% was 4.09 (2.87-5.83); a platelet count>166,000/mu L was, conversely, protective (OR: 0.45 (0.32-0.63)). Conclusion. Our findings arise the opportunity of stratifying COVID-19 severity according to simple lab parameters, which may drive clinical decisions about monitoring and treatment.

Automated summary

A retrospective study in Northern Italy involving 664 COVID-19 hospitalized patients found that simple laboratory parameters like red cell distribution width, neutrophil-to-lymphocyte ratio, and platelet count accurately predicted in-hospital mortality, providing guidance for clinical decisions.