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Hematologic changes predict clinical outcome in recovered patients with COVID-19.

ABSTRACT: 2019 coronavirus disease (COVID-19) presents as a newly recognized pneumonia that has brought about a global pandemic and is increasingly considered as a systemic illness. We investigated the clinical and laboratory features of recovered COVID-19 patients without pre-existing hematologic diseases at Wuhan No. 1 Hospital. Fifty-nine male and 68 female Chinese patients were included with the median age at 64 years in the present study. Eosinopenia (37.80%), monocytosis (51.97%), lymphocytopenia (25.20%), and anemia (51.97%) were the most common hematologic findings in our cohort, particularly in severe or critically ill COVID-19. The levels of changes in leukocytes, neutrophils, lymphocytes, monocytes, eosinophils, basophils, platelets, hemoglobin levels, mean corpuscular volume (MCV), and mean cell hemoglobin concentration (MCHC) are overall associated with lung involvement, oxygen demand, and disease activity. However, changes of eosinophils (end hospitalization-baseline) (coefficients = 10.32; 95% CI = 1.03-19.60, P = 0.03) and basophils (Max?-?Min) (coefficients = 71.43; 95% CI = 8.55-134.31, P = 0.03) were independent predictors of delayed recovery in the hospital by the multivariate analysis in this recovered population. A variety of hematologic changes are associated with the severity and clinical outcome of recovered COVID-19 patients, which warrants further exploration of their underlying mechanisms.

SUBMITTER: Mao J

PROVIDER: S-EPMC7848253 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Hematologic changes predict clinical outcome in recovered patients with COVID-19.

Mao Jian J Dai Rong R Du Rui-Chan RC Zhu Yan Y Shui Li-Ping LP Luo Xiao-Hua XH

Annals of hematology 20210201 3

2019 coronavirus disease (COVID-19) presents as a newly recognized pneumonia that has brought about a global pandemic and is increasingly considered as a systemic illness. We investigated the clinical and laboratory features of recovered COVID-19 patients without pre-existing hematologic diseases at Wuhan No. 1 Hospital. Fifty-nine male and 68 female Chinese patients were included with the median age at 64 years in the present study. Eosinopenia (37.80%), monocytosis (51.97%), lymphocytopenia (2 ...[more]

PMID: 33523290

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Project description:Background: The clinical characteristics of coronavirus disease 2019 (COVID-19) have been well-studied, while effective predictors for clinical outcome and research on underlying mechanisms are scarce. Methods: Hospitalized COVID-19 pneumonia patients with definitive clinical outcome (cured or died) were retrospectively studied. The diagnostic performance of the leucocyte subsets and other parameters were compared using the area under the receiver operating characteristic curve (AUC). Further, the correlations between leucocyte subsets and inflammation-related factors associated with clinical outcome were subsequently investigated. Results: Among 95 subjects included, 56 patients were cured, and 39 died. Older age, elevated aspartate aminotransferase, total bilirubin, serum lactate dehydrogenase, blood urea nitrogen, prothrombin time, D-dimer, Procalcitonin, and C-reactive protein levels, decreased albumin, elevated serum cytokines (IL2R, IL6, IL8, IL10, and TNF-?) levels, and a decreased lymphocyte count indicated poor outcome in patients with COVID-19 pneumonia. Lymphocyte subset (lymphocytes, T cells, helper T cells, suppressor T cells, natural killer cells, T cells+B cells+NK cells) counts were positively associated with clinical outcome (AUC: 0.777; AUC: 0.925; AUC: 0.900; AUC: 0.902; AUC: 0.877; AUC: 0.918, resp.). The neutrophil-to-lymphocyte ratio (NLR), neutrophil to T lymphocyte count ratio (NTR), neutrophil percentage to T lymphocyte ratio (NpTR) effectively predicted mortality (AUC: 0.900; AUC: 0.905; AUC: 0.932, resp.). Binary logistic regression showed that NpTR was an independent prognostic factor for mortality. Serum IL6 levels were positively correlated with leucocyte count, neutrophil count, and eosinophil count and negatively correlated with lymphocyte count. Conclusion: These results indicate that leucocyte subsets predict the clinical outcome of patients with COVID-19 pneumonia with high efficiency. Non-self-limiting inflammatory response is involved in the development of fatal pneumonia.

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Hematologic changes predict clinical outcome in recovered patients with COVID-19.

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Hematologic changes predict clinical outcome in recovered patients with COVID-19.

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