Dynamics of Blood Viral Load Is Strongly Associated with Clinical Outcomes in Coronavirus Disease 2019 (COVID-19) Patients: A Prospective Cohort Study

Liting Chen, Gaoxiang Wang, Xiaolu Long, Hongyan Hou, Jia Wei, Yang Cao, Jiaqi Tan, Weiyong Liu, Liang Huang, Fankai Meng, Lifang Huang, Na Wang, Jianping Zhao, Gang Huang, Ziyong Sun, Wei Wang, Jianfeng Zhou, Liting Chen, Gaoxiang Wang, Xiaolu Long, Hongyan Hou, Jia Wei, Yang Cao, Jiaqi Tan, Weiyong Liu, Liang Huang, Fankai Meng, Lifang Huang, Na Wang, Jianping Zhao, Gang Huang, Ziyong Sun, Wei Wang, Jianfeng Zhou

Abstract

The prevalence and clinical relevance of viremia in patients with coronavirus disease 2019 (COVID-19) have not been well studied. A prospective cohort study was designed to investigate blood viral load and clearance kinetics in 52 patients (median age, 62 years; 31 [59.6%] male) and explore their association with clinical features and outcomes based on a novel one-step RT droplet digital PCR (RT-ddPCR). By using one-step RT-ddPCR, 92.3% (48 of 52) of this cohort was quantitatively detected with viremia. The concordance between the blood and oropharyngeal swab tests was 60.92% (53 of 87). One-step RT-ddPCR was tested with a 3.03% false-positive rate and lower 50% confidence interval of detection at 54.026 copies/mL plasma. There was no reduction in the blood viral load in all critical patients, whereas the general and severe patients exhibited a similar ability to clear the viral load. The viral loads in critical patients were significantly higher than those in their general and severe counterparts. Among the 52 study patients, 30 (58%) were discharged from the hospital. Among half of the 30 discharged patients, blood viral load remained positive, of which 76.9% (10 of 13) completely cleared their blood viral load at follow-up. Meanwhile, none of their close contacts had evidence of infection. Quantitative determination of the blood viral test is of great clinical significance in the management of patients with coronavirus disease 2019.

Copyright © 2021 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Figures

Figure 1
Figure 1
The sensitivity and accuracy of plasma severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cell-free RNA quantification. A: Dilution curve of plasmid standards quantification by RT droplet digital PCR (ddPCR). Correlation between expected and observed copy number are shown. Each black square represents a single replicate well of the dilution experiment, whereas the regression line is based on the average concentration at each dilution. B: SARS-CoV-2 concentration–time curve of plasma (blue) and oropharyngeal swab (red) samples from patient DF. C: Probit analysis sigmoid curve reporting the lower 50% confidence interval of detection (LOD50) of one-step RT-ddPCR. The red dashed line represents the plasma SARS-CoV-2 concentration when the detection probability is 50%. D: Comparison of plasma and oropharyngeal swab SARS-CoV-2 concentration of time-matched samples.
Figure 2
Figure 2
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) dynamics of 52 patients. One humoral immunodeficient, 21 general, 16 severe, and 14 critical patients are presented. Squares in different colors represent different virus loads. Asterisks indicate patients met discharge standards at the specific days; circles, patients were deceased at the specific days; triangles, patients were getting worse at the specific days.
Figure 3
Figure 3
Analysis of severity-associated clinical factors. A: Plasma severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) loads in general, severe, and critical patients were compared. B: Levels of plasma SARS-CoV-2 cell-free RNA before and after disease progression were analyzed. CH: The levels of peak SARS-CoV-2–specific IgM (C), IgG (D), high-sensitivity C-reactive protein (hsCRP) (E), peak serum ferritin (F), peak soluble IL-6 (sIL-6) (G), and peak soluble IL-8 (sIL-8) (H) were compared among general, severe, and critical patients. Error bars indicate means ± SD. ∗∗∗P < 0.001 (paired t-test); †P < 0.05, ††P < 0.01, and †††P < 0.001 (Tukey multiple comparisons test). AU, arbitrary units.

References

    1. Li Q., Guan X., Wu P., Wang X., Zhou L., Tong Y. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med. 2020;382:1199–1207.
    1. Zhu N., Zhang D., Wang W., Li X., Yang B., Song J., Zhao X., Huang B., Shi W., Lu R., Niu P., Zhan F., Ma X., Wang D., Xu W., Wu G., Gao G.F., Tan W., China Novel Coronavirus Investigating and Research Team A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med. 2020;382:727–733.
    1. Mahase E. Covid-19: WHO declares pandemic because of “alarming levels” of spread, severity, and inaction. BMJ. 2020;368:m1036.
    1. Liu Y., Yang Y., Zhang C., Huang F., Wang F., Yuan J., Wang Z., Li J., Li J., Feng C., Zhang Z., Wang L., Peng L., Chen L., Qin Y., Zhao D., Tan S., Yin L., Xu J., Zhou C., Jiang C., Liu L. Clinical and biochemical indexes from 2019-nCoV infected patients linked to viral loads and lung injury. Sci China Life Sci. 2020;63:364–374.
    1. Li H., Liu L., Zhang D., Xu J., Dai H., Tang N., Su X., Cao B. SARS-CoV-2 and viral sepsis: observations and hypotheses. Lancet. 2020;395:1517–1520.
    1. Chen W., Lan Y., Yuan X., Deng X., Li Y., Cai X., Li L., He R., Tan Y., Deng X., Gao M., Tang G., Zhao L., Wang J., Fan Q., Wen C., Tong Y., Tang Y., Hu F., Li F., Tang X. Detectable 2019-nCoV viral RNA in blood is a strong indicator for the further clinical severity. Emerg Microbes Infect. 2020;9:469–473.
    1. Yu F., Yan L., Wang N., Yang S., Wang L., Tang Y., Gao G., Wang S., Ma C., Xie R., Wang F., Tan C., Zhu L., Guo Y., Zhang F. Quantitative detection and viral load analysis of SARS-CoV-2 in infected patients. Clin Infect Dis. 2020;71:793–798.
    1. Rački N., Morisset D., Gutierrez-Aguirre I., Ravnikar M. One-step RT-droplet digital PCR: a breakthrough in the quantification of waterborne RNA viruses. Anal Bioanal Chem. 2014;406:661–667.
    1. World Health Organization . WHO; Geneva: 2020. Clinical management of severe acute respiratory infection when novel coronavirus (nCoV) infection is suspected: interim guidance. Available at .
    1. Ai T., Yang Z., Hou H., Zhan C., Chen C., Lv W., Tao Q., Sun Z., Xia L. Correlation of chest CT and RT-PCR testing for coronavirus disease 2019 (COVID-19) in China: a report of 1014 cases. Radiology. 2020;296:E32–E40.
    1. Stone M., Lanteri M.C., Bakkour S., Deng X., Galel S.A., Linnen J.M., Muñoz-Jordán J.L., Lanciotti R.S., Rios M., Gallian P., Musso D., Levi J.E., Sabino E.C., Coffey L.L., Busch M.P. Relative analytical sensitivity of donor nucleic acid amplification technology screening and diagnostic real-time polymerase chain reaction assays for detection of Zika virus RNA. Transfusion. 2017;57:734–747.
    1. Xu Y., Li X., Zhu B., Liang H., Fang C., Gong Y., Guo Q., Sun X., Zhao D., Shen J., Zhang H., Liu H., Xia H., Tang J., Zhang K., Gong S. Characteristics of pediatric SARS-CoV-2 infection and potential evidence for persistent fecal viral shedding. Nat Med. 2020;26:502–505.
    1. Wölfel R., Corman V.M., Guggemos W., Seilmaier M., Zange S., Müller M.A., Niemeyer D., Jones T.C., Vollmar P., Rothe C., Hoelscher M., Bleicker T., Brünink S., Schneider J., Ehmann R., Zwirglmaier K., Drosten C., Wendtner C. Virological assessment of hospitalized patients with COVID-2019. Nature. 2020;581:465–469.
    1. Chen J., Qi T., Liu L., Ling Y., Qian Z., Li T., Li F., Xu Q., Zhang Y., Xu S., Song Z., Zeng Y., Shen Y., Shi Y., Zhu T., Lu H. Clinical progression of patients with COVID-19 in Shanghai, China. J Infect. 2020;80:e1–e6.

Source: PubMed

3
Abonnieren