Evidence map›Paper›PMID 40453472›Full record

ArticleBiosafety and health2025

Longitudinal analysis of cytokine dynamics in severe fever with thrombocytopenia syndrome patients - High-incidence regions of China (2010-2023).

Yanhan Wen, Yeqing Tong, Lei Gong, Aqian Li, Xiaoxia Huang, Tingting Tian, Tiezhu Liu, Lina Sun, Jiandong Li, Dexin Li and 4 more

Abstract read
In one paragraph

Article in Biosafety and health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Yanhan WenNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Yeqing TongDepartment of Infectious Diseases, Hubei Provincial Center for Disease Control and Prevention, Wuhan 430070, China.
Lei GongDepartment of Infectious Diseases Control and Prevention, Anhui Provincial Center for Disease Control and Prevention, Hefei 230061, China.
Aqian LiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Xiaoxia HuangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Tingting TianNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Tiezhu LiuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Lina SunNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Jiandong LiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Dexin LiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Mifang LiangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Wei WuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Jiabing WuAnhui Provincial Center for Disease Control and Prevention, Hefei 230061, China.
Shiwen WangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Severe fever with thrombocytopenia syndrome (SFTS) is a life-threatening tick-borne disease characterized by cytokine dysregulation and immune-mediated hyperinflammation. This multicenter retrospective study analyzed the dynamics of 17 cytokines across acute and recovery phases using 287 serum samples collected between 2010 and 2023 from high-incidence regions of China, evaluating their associations with disease severity, sex, age, and antibody responses. The results demonstrated that elevations of interleukin (IL)-6, interferon (IFN)-α, IL-8, and IFN-γ-induced protein 10 (IP-10) during the acute phase were associated with hyperinflammation, while IL-10 balanced inflammatory control and may have contributed to viral persistence. During recovery, most cytokines declined; however, IL-8 and IP-10 remained elevated longer in some patients, reflecting heterogeneity in recovery trajectories. Severe cases exhibited significantly higher levels of IL-10, IFN-γ, IL-6, IFN-α, tumor necrosis factor (TNF)-α, IL-8, and IP-10, underscoring their potential as biomarkers for disease severity prediction. Sex-based differences revealed higher IFN-γ and IL-8 levels in females, potentially due to hormonal and genetic factors, while older patients exhibited elevated IL-10, IFN-γ, and IFN-α, reflecting immune dysregulation and age-related shifts in adaptive immunity. Correlation analysis revealed distinct immune response patterns, with IL-10 strongly correlating with IFN-γ and minimal antibody-cytokine associations observed during the acute phase. In contrast, in the recovery phase, immunoglobulin G (IgG) negatively correlated with IL-10, IFN-γ, and IP-10, and immunoglobulin M (IgM) positively correlated with IL-10, IFN-γ, IL-6, IFN-α, TNF-α, IL-8, and IP-10, reflecting dynamic immune regulation and the interplay between humoral and cellular immunity. These findings provide critical insights into the immunopathogenesis of SFTS, supporting the development of cytokine-targeted therapies and advanced diagnostic tools to improve clinical outcomes.

Indexed as

Antibody-cytokine correlationsCytokine dynamicsDisease severity biomarkersSevere fever with thrombocytopenia syndrome (SFTS)

Identifiers

PMID40453472
PMCPMC12125691

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.