Evidence map›Paper›PMID 40478888›Full record

ArticlePloS one2025

The role of S100A9 as a diagnostic and prognostic biomarker in septic shock.

Yingxue Hu, Qinghui Yang, Xiao Liu, Li Yuan, Fang Yan, Yang Li, Pingwei Ni

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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yingxue HuDepartment of Respiratory and Critical Care Medicine, North Sichuan Medical College, Nanchong, Sichuan, China.
Qinghui YangDepartment of Respiratory and Critical Care Medicine, North Sichuan Medical College, Nanchong, Sichuan, China.
Xiao LiuDepartment of Respiratory and Critical Care Medicine, Chengdu Fifth People's Hospital, Chengdu, Sichuan, China.ORCID 0000-0002-0334-8999
Li YuanGeriatric Diseases Institute of Chengdu, Department of Geriatrics, Chengdu Fifth People's Hospital, Chengdu, Sichuan, ChinaGeriatric Diseases Institute of Chengdu, Department of Intensive Care Medicine, Chengdu Fifth People's Hospital, Chengdu, Sichuan, ChinaCenter for Medicine Research and Translation, Chengdu Fifth People's Hospital, Chengdu, Sichuan, China.
Fang YanGeriatric Diseases Institute of Chengdu, Department of Clinical Laboratory, Chengdu Fifth People's Hospital, Chengdu, Sichuan, China.
Yang LiDepartment of Respiratory and Critical Care Medicine, Chengdu Fifth People's Hospital, Chengdu, Sichuan, China.
Pingwei NiDepartment of Respiratory and Critical Care Medicine, North Sichuan Medical College, Nanchong, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSepsis is a severe and potentially fatal systemic condition marked by excessive immune defense against infection. Within this research, we explored the serum concentration of S100A9 during hospital admission, aiming to assess its role and reliability as a viable biomarker for identifying septic shock and predicting mortality risk in sepsis. Furthermore, we explored whether combining S100A9 with conventional assessment tools could enhance diagnostic precision and prognostic accuracy, offering valuable insights to support early intervention and personalized treatment strategies for sepsis.

methodsThis study comprised 575 participants overall, with sepsis patients classified into non-shock and shock groups based on the severity of their condition. Additionally, age- and gender-matched ICU control cohort and healthy control group were recruited to ensure wide applicability and strong comparability of the findings. Enzyme-linked immunosorbent assay utilized for detecting serum S100A9 levels in subjects within 24 hours of admission, ROC curves were used to evaluate the disease identification and prognostic analysis. Differences in survival outcomes among patients with varying levels of S100A9 expression were analyzed using the Kaplan-Meier method.

resultsSerum S100A9 concentrations were elevated in septic patients upon admission. In the diagnosis of patients with septic shock, S100A9 performed similarly to APACHE II, and a considerable enhancement was noted in the sensitivity of detecting septic shock when S100A9 was combined with lactate and APACHE II. At the initiation of ICU stay, the area under the receiver operating characteristic curve (AUC) for the association between serum S100A9 levels and 28-day mortality was 0.78. This value surpassed the AUCs for IL-6 (0.66), procalcitonin (0.60), lactate (0.58) and C-reactive protein (0.47). Furthermore, septic patients with elevated serum S100A9 levels (≥ 630.77 pg/ml) exhibited lower survival rates compared to those with lower concentrations (< 630.77 pg/ml).

conclusionS100A9 is a promising biomarker for diagnosing septic shock and forecasting clinical outcomes in patients with sepsis. In addition, S100A9 has good predictive efficacy for the risk of death in sepsis patients.

Indexed as

Calgranulin BShock, SepticAgedBiomarkersCase-Control StudiesFemaleHumansMaleMiddle AgedPrognosisROC CurveBiomarkersCalgranulin BS100A9 protein, human

Identifiers

PMID40478888
PMCPMC12143512

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