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Published on: September 13, 2018
Early viral load outperforms cytokines and lymphocytes in predicting SFTS prognosis: A dynamic immune profiling study
Keping Chen1, Gan Cao2, Yurong Xu1
1Clinical Laboratory, Zhongda Hospital, Medical School, Southeast University, Nanjing 210009, China.
Background:
Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with high mortality, yet its pathophysiology remains incompletely understood. To elucidate the immunopathogenesis and improve disease prognosis, this study investigated the cytokine and lymphocyte responses in SFTS patients and evaluated their values, together with viral load, in predicting SFTS prognosis.
Methods:
A total of 96 patients with SFTS were enrolled from two hospitals. Blood samples were collected from each patient every 2-3 days throughout the hospitalization period. Cytokines and lymphocytes were quantified using flow cytometry, and their correlations with viral load were assessed. Dynamic changes in these parameters were analyzed, and logistic regression along with receiver operating characteristic (ROC) curves were employed to evaluate their prognostic value.
Results:
IL-10 showed the strongest positive correlation with viral load, whereas total T lymphocytes and helper T lymphocyte subsets demonstrated the strongest negative correlation. At 4-6 days post-symptom onset, only SFTS viral load was significantly associated with SFTS prognosis. In contrast, at 7-9 days post‑symptom onset, viral load, IL‑6, IL‑10, IFN‑γ, total T lymphocyte percentage and count, and helper T‑lymphocyte subset counts exhibited significant prognostic associations. For predicting SFTS outcome, the area under the ROC curve for viral load was 0.9798 at 4-6 days and 0.9737 at 7-9 days post-symptom onset, outperforming cytokines and lymphocyte subsets at the corresponding time points.
Conclusions:
The immunopathogenesis of SFTS involved a cytokine storm (IL-6, IL-10, IFN-α, and IFN-γ) and lymphocyte depletion. Viral load served as a superior biomarker for early prognostic prediction.
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