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Leucocyte Subsets Effectively Predict the Clinical Outcome of Patients With Covid-19 Pneumonia

A Retrospective Case-Control Study

Datos Bibliográficos

ID22079171
AutoresJiahua Gan (Tongji Hospital), Jingjing Li (0009-0006-0033-1522, Union Hospital), Shusheng Li (0000-0002-6052-8355, Tongji Hospital), Chunguang Yang (0000-0002-3882-4940, Huazhong University of Science and Technology, autor de correspondencia)
Año2020
Volumen8
Páginas299-299
Fecha de publicación2020-06-18
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaFrontiers in Public Health (JOURNAL)
Identificadores de la revistaISSN: 2296-2565 • E-ISSN: 2296-2565
EditorialFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2020.00299
PMID32626680
OpenAlexW3014786535
IdiomaEN
Referencias citadas17

Background: Clinical characteristics of the coronavirus disease 2019 (COVID-19) have been well studied, while effective predictors for clinical outcome and research on underlying mechanism are scare. 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 value (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 cases died. Older age, higher aspartate aminotransferase levels, lower albumin levels, higher total bilirubin levels, higher serum lactate dehydrogenase levels, higher blood urea nitrogen levels, higher prothrombin time, high D-dimer levels, higher procalcitonin levels, higher serum cytokines (IL2R, IL6, IL8, IL10 and TNF-α) levels, higher leucocyte count or neutrophil count, lower lymphocyte count indicated poor outcome in patients with COVID-19 pneumonia. Lymphocyte subset (Lymphocyte, T cells, helper T cells, suppressor T cells, natural killer cells, T cells+ B cells+ NK cells) count was positively associated with clinical outcome (AUC: 0.777; AUC: 0.925; AUC: 0.900; AUC: 0.902; AUC: 0.877; AUC: 0.918, resp.). Neutrophil-to-lymphocyte ratio (NLR), neutrophil to T lymphocyte count ratio (NTR), neutrophil percentage to T lymphocyte ratio (NpTR) effectively predicted the 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, while negatively correlated with lymphocyte count. Conclusion: These results indicate that leucocyte subsets predict the clinical outcome of patients with COVID-19 pneumonia in high efficiency. Non-self-limiting inflammatory response is involved in the development of fatal pneumonia

Absolute neutrophil count · Area under the curve · Biology · Lactate dehydrogenase · Logistic regression · Lymphocyte · Neutropenia · Neutrophil to lymphocyte ratio · Pneumonia · Procalcitonin · Receiver operating characteristic · Sepsis · Toxicity · COVID-19 Clinical Research Studies · Long-Term Effects of COVID-19 · Medicine · SARS-CoV-2 and COVID-19 Research · Gastroenterology · Immunology · Internal Medicine

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