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DOI 10.3389/fpubh.2020.00299

Медицинская библиотека · Frontiers in public health · 2020

Leucocyte Subsets Effectively Predict the Clinical Outcome of Patients With COVID-19 Pneumonia: A Retrospective Case-Control Study.

Gan Jiahua, Li Jingjing, Li Shusheng, Yang Chunguang

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

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-α) 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.

Для цитирования: Gan Jiahua, Li Jingjing, Li Shusheng, Yang Chunguang. Leucocyte Subsets Effectively Predict the Clinical Outcome of Patients With COVID-19 Pneumonia: A Retrospective Case-Control Study.. Frontiers in public health. 2020. DOI: 10.3389/fpubh.2020.00299.

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