ABSTRACT
INTRODUCTION: Developing prognostic markers can be useful for clinical decision-making. Peripheral blood (PB) examination is simple and basic that can be performed in any facility. We aimed to investigate whether PB examination can predict prognosis in coronavirus disease (COVID-19). METHODS: Complete blood count (CBC) and PB cell morphology were examined in 38 healthy controls (HCs) and 40 patients with COVID-19. Patients with COVID-19, including 26 mild and 14 severe cases, were hospitalized in Juntendo University Hospital (Tokyo, Japan) between April 1 and August 6, 2020. PB examinations were performed using Sysmex XN-3000 automated hematology analyzer and Sysmex DI-60 employing the convolutional neural network-based automatic image-recognition system. RESULTS: Compared with mild cases, severe cases showed a significantly higher incidence of anemia, lymphopenia, and leukocytosis (P < .001). Granular lymphocyte counts were normal or higher in mild cases and persistently decreased in fatal cases. Temporary increase in granular lymphocytes was associated with survival of patients with severe infection. Red cell distribution width was significantly higher in severe cases than in mild cases (P < .001). Neutrophil dysplasia was consistently observed in COVID-19 cases, but not in HCs. Levels of giant neutrophils and toxic granulation/Döhle bodies were increased in severe cases. CONCLUSION: Basic PB examination can be useful to predict the prognosis of COVID-19, by detecting SARS-CoV-2 infection-induced multi-lineage changes in blood cell counts and morphological anomalies. These changes were dynamically correlated with disease severity and may be associated with disruption of hematopoiesis and the immunological system due to bone marrow stress in severe infection.
Subject(s)
Blood Cell Count , COVID-19/blood , Leukocytosis/etiology , Lymphocytes/ultrastructure , Lymphopenia/etiology , Neutrophils/ultrastructure , SARS-CoV-2 , Aged , Anemia/blood , Anemia/etiology , Blood Cell Count/instrumentation , Blood Cell Count/methods , COVID-19/mortality , Cell Shape , Cytoplasmic Granules/ultrastructure , Erythrocyte Indices , Female , Humans , Image Processing, Computer-Assisted , Leukocytosis/blood , Lymphocyte Count , Lymphopenia/blood , Male , Middle Aged , Neural Networks, Computer , Prognosis , Severity of Illness IndexABSTRACT
COVID-19 induces haemocytometric changes. Complete blood count changes, including new cell activation parameters, from 982 confirmed COVID-19 adult patients from 11 European hospitals were retrospectively analysed for distinctive patterns based on age, gender, clinical severity, symptom duration, and hospital days. The observed haemocytometric patterns formed the basis to develop a multi-haemocytometric-parameter prognostic score to predict, during the first three days after presentation, which patients will recover without ventilation or deteriorate within a two-week timeframe, needing intensive care or with fatal outcome. The prognostic score, with ROC curve AUC at baseline of 0.753 (95% CI 0.723-0.781) increasing to 0.875 (95% CI 0.806-0.926) on day 3, was superior to any individual parameter at distinguishing between clinical severity. Findings were confirmed in a validation cohort. Aim is that the score and haemocytometry results are simultaneously provided by analyser software, enabling wide applicability of the score as haemocytometry is commonly requested in COVID-19 patients.