Evidence map›Paper›PMID 41580628›Full record

ArticleBMC infectious diseases2026

Toll-like receptor 5 on monocyte as a biomarker of mortality risk in patients with sepsis.

Hong Tan, Hanyi Wang, Xuanyi Zhou, Wenjun Que, Xiaoliang Yang

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Article in BMC infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Hong Tan *Department of Blood Transfusion, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China.
Hanyi Wang *Key Laboratory of Diagnostic Medicine Designated by the Ministry of Education, Chongqing Medical University, Chongqing, 400016, China.
Xuanyi ZhouDepartment of Blood Transfusion, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China.
Wenjun QueDepartment of Blood Transfusion, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China.
Xiaoliang YangDepartment of Blood Transfusion, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China. yangxiaoliang2010@yeah.net.

Funding

the Natural Science Foundation of Chongqing, China CSTB2022NSCQ-MSX1031the Scientific and Technological Research Program of Chongqing Municipal Education Commission KJQN202100435
6 · The paper itself

Abstract

objectiveTo evaluate the expression of Toll-like receptor 5 on monocyte at ICU admission as a potentially novel early screening biomarker to predict the mortality risk of sepsis.

methodsPatients with sepsis (n = 107), ICU non-septic controls (n = 53) and healthy controls (n = 55) from May 2023 to December 2024 were enrolled. The expression of Toll-like receptor 5 on monocyte were detected by Flow cytometry within 4 h at ICU admission. The efficacy of Toll-like receptor 5 for predicting mortality risk of sepsis were analyzed by receiver operating characteristic curves. The Toll-like receptor 5 was categorized into higher and lower groups on the basis of the cutoff value, and Kaplan-Meier survival rates were analyzed to evaluate the relationship between Toll-like receptor 5 and the mortality risk of sepsis.

resultsToll-like receptor 5 levels on monocyte at ICU admission in patients with sepsis were significantly higher than those in ICU non-septic patients and the healthy controls. The expression of Toll-like receptor 5 on monocyte in septic non-survivors were significantly higher than that in survivors. Moreover, the AUC of Toll-like receptor 5 (0.6983, P = 0.0006) for predicting mortality risk of sepsis were higher than PCT (0.5741, P = 0.2012) ,CRP (0.5820, P = 0.1582) and WBC (0.6381, P = 0.0172), but lower than APACHE II (0.7101, P = 0.0003) and SOFA score (0.7888, P < 0.0001). The AUC of Toll-like receptor 5 combined with SOFA score for estimating 28-day mortality in septic patients increased from 0.6983 to 0.8030 (P < 0.0001). Toll-like receptor 5, SOFA and APACHE II scores at ICU admission were found to be independent predictors of sepsis 28-day mortality. In addition, septic patients with higher Toll-like receptor 5 level (≥ 2.05) had poorer survival than those with lower levels (< 2.05) (P = 0.0002).

conclusionThe expression of TLR5 on monocyte at ICU admission were valuable for predicting the mortality risk of sepsis. These findings can be used as a early screening biomarker to predict the mortality risk of sepsis.

Indexed as

BiomarkersMonocytesSepsisToll-Like Receptor 5AdultAgedCase-Control StudiesFemaleHumansIntensive Care UnitsMaleMiddle AgedPrognosisROC CurveBiomarkersTLR5 protein, humanToll-Like Receptor 5BiomarkerMonocyteMortalitySepsisToll-like receptor 5

Identifiers

PMID41580628
PMCPMC12911410

What Socratic holds

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LicenceCC BY-NC-ND
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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.