Lymphocyte blood levels that remain low can predict the deat
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The outbreak of COVID-19 caused by SARS-CoV-2 has been rapidly spreading on a global scale and poses a great threat to human health. However, efficient indicators for disease severity have not been fully investigated. Here, this study aim to investigate whether dynamic changes of lymphocyte counts can predict the deterioration of patients with COVID-19.

Researchers collected data from 2923 patients with laboratory-confirmed COVID-19. Patients were then screened, and we focused on 145 severe cases and 60 critical cases (29 recovered cases, 31 deaths). The length of hospitalization was divided into five time points, namely admission, 25%, 50%, 75% and discharge or death, according to the principle of interquartile distance. A series of laboratory findings and clinical data were collected and analyzed during hospitalization.

The results showed that there were differences in levels of leukocytes, neutrophils and lymphocytes at almost every time point in the severe cases and 60 critical cases (29 recovered cases, 31 deaths). Further analysis showed that 70.2% of the COVID-19 cases had low circulating lymphocyte count, of which 64.1% were severe cases and 85.0% were critical cases (75.9% recovered cases and 93.5% died).

Moreover, the lymphocyte count in dead cases was significantly lower than that of critical cases who recovered, at almost every time point in the critical groups. We also divided critical patients into group A (less than 1.1 × 109/L) and group B (>1.1 × 109/L) according to number of lymphocytes. Through survival analysis, we found that there was no significant difference in survival between group A and group B at admission. However, the survival rate according to lymphocyte levels in group A was significantly lower than that of group B at 25% hospital stay (on average day 6.5), 50% and 75% time points.

Lymphocyte counts that remain lower after the first week following symptom onset are highly predictive of in-hospital death of adults with COVID-19. This predictor may help clinicians identify patients with a poor prognosis and may be useful for guiding clinical decision-making at an early stage.