Evidence map›Paper›PMID 41869834›Full record

ArticleMediators of inflammation2026

Circulating Platelet-Neutrophil Aggregates as Novel Biomarker for Coagulopathy Diagnosis and Disseminated Intravascular Coagulation Prediction in Sepsis.

Tenglong Dai, Shuang Liang, Bin Li, Huiru Zhao, Yu Su, Ying Liu, Cuiying Liang, Xinyang Yue, Hao Wang, Jun Wu

Abstract read
In one paragraph

Article in Mediators of inflammation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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

10 authors.

Tenglong DaiThrombosis Research Center, Peking University Fourth School of Clinical Medicine, Beijing, China.
Shuang LiangThrombosis Research Center, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China, ccmu.edu.cn.
Bin LiDivision of Critical Care Medicine, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China, ccmu.edu.cn.
Huiru ZhaoThrombosis Research Center, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China, ccmu.edu.cn.
Yu SuThrombosis Research Center, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China, ccmu.edu.cn.
Ying LiuDepartment of Blood Transfusion, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China, ccmu.edu.cn.
Cuiying LiangThrombosis Research Center, Peking University Fourth School of Clinical Medicine, Beijing, China.
Xinyang YueThrombosis Research Center, Peking University Fourth School of Clinical Medicine, Beijing, China.
Hao WangDivision of Critical Care Medicine, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China, ccmu.edu.cn.
Jun WuThrombosis Research Center, Peking University Fourth School of Clinical Medicine, Beijing, China.ORCID https://orcid.org/0000-0001-5178-0906

Funding

Beijing Jishuitan Hospital Affiliated to Capital Medical UniversityBeijing Municipal Health Commission High-Level Public Health Technical Talent Development ProjectBeijing Municipal Natural Science Foundation L246006Beijing Municipal Natural Science Foundation L254086Natural Science Foundation Cultivation Project ZR-202412Wu Jieping Clinical Research Fund
6 · The paper itself

Abstract

backgroundPlatelet-leukocyte aggregates (PLAs) drive immunothrombosis by promoting leukocyte activation and tissue factor release in sepsis. However, their utility as early predictors of sepsis-induced coagulopathy (SIC) and disseminated intravascular coagulation (DIC) remains unestablished. This study aimed to develop and validate a PLA-based model for SIC diagnosis and DIC prediction.

methodsA prospective prediction study was conducted with 101 sepsis patients in Beijing Jishuitan Hospital between May 2024 and May 2025. Percentage and mean fluorescence intensity (MFI) of different subtypes of PLAs were measured by flow cytometry. Receiver operating characteristic (ROC) curves and Cox regression were performed, assessing the performance of PLAs to diagnose SIC and predict DIC.

resultsPlatelet-neutrophil aggregate MFI (PNA-MFI) demonstrated excellent diagnostic accuracy for SIC (p < 0.001, AUC = 0.789, 95% CI: 0.699-0.880, cut-off value = 2797, sensitivity = 76.2%, specificity = 78.0%, negative predictive value (NPV) = 83.9%, and positive predictive value (PPV) = 68.8%) and superior DIC prediction (p < 0.001, AUC = 0.781, 95% CI: 0.680-0.883, cut-off value = 2621, sensitivity = 83.3%, specificity = 64.9%, NPV = 92.6%, and PPV = 42.6%). Kaplan-Meier analysis showed that high PNA-MFI patients (PNA-MFI ≥ 2621) were more likely to develop DIC (log-rank p  < 0.001, hazard ratio: 6.80 [high PNA-MFI/low PNA-MFI], and 95% CI:2.97-15.61).

conclusionPNA-MFI is a promising biomarker for SIC diagnosis and DIC prediction. While internally validated, external validation is essential prior to clinical implementation, and further multicenter studies are warranted to definitively establish its clinical value.

Indexed as

BiomarkersBlood PlateletsDisseminated Intravascular CoagulationNeutrophilsSepsisAdultAgedFemaleFlow CytometryHumansMaleMiddle AgedProspective StudiesROC CurveBiomarkersdisseminated intravascular coagulationplatelet–leukocyte aggregatesplatelet–neutrophil aggregatessepsis-induced coagulopathythrombosis

Identifiers

PMID41869834
PMCPMC13140174

What Socratic holds

Textmetadata
LicenceCC BY
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.