The clinical importance of a cytokine network in the acute phase of sepsis
Open accessAbstract
Sepsis remains a major cause of death. Cytokines interact closely with each other and play a crucial role in the progression of sepsis. We focussed on the associations of a cytokine network with prognosis and disease severities in sepsis. This retrospective study included 31 patients with sepsis and 13 healthy controls. Blood samples were collected from patients on days 1, 2, 4, 6, 8, 11 and 15 and from healthy controls. Levels of PAI-1, IFN-α, IFN-γ, IL-1β, IL-6, IL-8, IL-12/IL-23p40, IL-17A, TNF-α, MCP-1, IL-4 and IL-10 were measured. SOFA, JAAM DIC and ISTH DIC scores were evaluated at the same times blood samples were taken. Network analysis revealed a network formed by PAI-1, IL-6, IL-8, MCP-1 and IL-10 on days 1, 2 and 4 throughout the acute phase of sepsis. There were positive correlations of each cytokine and the combined score (IL-6 + IL-8 + IL-10 + MCP-1) with the SOFA, JAAM DIC and ISTH DIC scores throughout the acute phase. A Cox proportional hazards model focussed on the acute phase showed that the above combined score was significantly related with patient prognosis, suggesting that the cytokine network of IL-6, IL-8, MCP-1 and IL-10 could play a pivotal role in the acute phase of sepsis.
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In septic shock, underlying dysregulated immune responses produce cytokines in response to infection.
“In septic shock, underlying dysregulated immune responses produce cytokines in response to infection [23].”
From Non-Diabetic Hypoglycemia: Evaluation and Management in Adults (2025) · cites this paper as [23]
The Introduction (page unavailable) describes pathogen-associated signals activating immune cells in sepsis and an inflammatory response driven by cytokines. The Discussion (page unavailable) also says activated immune cells produce cytokines. These passages support the proposed mechanism in sepsis, but do not establish it specifically for septic shock. (LLM, conf=0.83)
Experimental — accuracy not yet measuredThis systemic overdrive accelerates glucose utilization that may outpace the body's gluconeogenic capacity.
“This systemic overdrive accelerates glucose utilization that eventually may outpace the body's gluconeogenic capacity.”
From Non-Diabetic Hypoglycemia: Evaluation and Management in Adults (2025) · cites this paper as [23]
The Introduction and Discussion describe a systemic inflammatory response and a cytokine network in sepsis, but do not address glucose utilization or gluconeogenic capacity. Searches for those terms and for glucose metabolism and hypoglycemia found no passage in our copy supporting the claimed metabolic effect; page numbers were not available. (LLM, conf=0.76)
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- Authors
- Matsumoto, H., Ogura, H., Shimizu, K., Ikeda, M., Hirose, T., Matsuura, H., Kang, S., Takahashi, K., Tanaka, T., & Shimazu, T.
- Affiliations
- The University of Osaka (JP)
- Osaka City University (JP)
- Corresponding author
- Matsumoto, Hisatake
- ORCID
- Venue
- Scientific Reports
- Published
- 2018-09-18
- Volume
- 8
- Issue
- 1
- Pages
- 13995-13995
- ISSN
- 2045-2322 (ISSN-L)
- PMC
- PMC6143513
- OpenAlex
- W2891533504
- Cited by
- 193
- References
- 47
- Citations by year
- 2026: 14 · 2025: 30 · 2024: 20 · 2023: 18 · 2022: 36 · 2021: 34 · 2020: 27 · 2019: 14
- FWCI
- 14.63
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Scientific Reports (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- A Grant-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science, and Technology in Japan.
- Topics
- Health Sciences › Medicine › Epidemiology › Sepsis Diagnosis and Treatment
- Life Sciences › Immunology and Microbiology › Immunology › Inflammation biomarkers and pathways
- Health Sciences › Medicine › Nephrology › Acute Kidney Injury Research
- Keywords
- sepsis, cytokine network, prognostic factors, interleukin-6, interleukin-8, MCP-1, IL-10, plasminogen activator inhibitor-1, SOFA score, disseminated intravascular coagulation, disease severity, network analysis
- MeSH terms
- Aged, Aged, 80 and over, Female, Follow-Up Studies, Humans, Male, Middle Aged, Prognosis, Prospective Studies, ROC Curve, Severity of Illness Index, Biomarkers, Survival Rate, Case-Control Studies, Cytokines, Disease Progression, Sepsis
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