Evidence map›Paper›PMID 41460586›Full record

ArticleClinical and experimental medicine2025

Neutrophil extracellular traps associated with severity and prognosis of community-acquired pneumonia.

Yaqi Wang, Huaiya Xie, Luo Wang, Junping Fan, Ying Zhang, Siqi Pan, Qiaoling Chen, Wangji Zhou, Xueqi Liu, Aohua Wu and 5 more

Abstract read
In one paragraph

Article in Clinical and experimental medicine, 2025. 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. A Large-Scale Single-Cell Atlas Reveals the Peripheral Immune Panorama of Bacterial Pneumonia.American journal of respiratory and critical care medicine · 2025
    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

15 authors.

Yaqi WangDepartment of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Huaiya XieDepartment of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Luo WangDepartment of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Junping FanDepartment of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Ying ZhangInternational Medical Services, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Siqi PanDepartment of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Qiaoling ChenDepartment of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Wangji ZhouDepartment of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Xueqi LiuDepartment of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Aohua WuDepartment of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Hong ZhangDepartment of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Lan SongDepartment of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Jihai LiuEmergency Department, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Jinglan WangDepartment of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Xinlun TianDepartment of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China. tianxl@pumch.cn.

Funding

Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences 2021-I2M-1-048
6 · The paper itself

Abstract

This study aimed to verify whether neutrophil extracellular traps (NETs) was related to the severity of respiratory tract infections (RTI) and establish a prognostic model for severe respiratory infections. Peripheral blood mononuclear cells (PBMC) were isolated from RTI patients for RNA sequencing. Weighted Graph Co-expression Network Analysis was performed to identify gene modules and analyze the correlation between gene modules and clinical features. The prognostic model was established by LASSO regression. The concentration of IL-8 in plasma was measured by Enzyme linked immunosorbent assay (ELISA). The gene expression levels in PBMC were detected by quantitative reverse transcription polymerase chain reaction (qRT-PCR). In total, 120 patients with RTIs were enrolled between July 2022 and March 2024. Enrichment analysis showed that NETs formation was enhanced during the early stages of pneumonia and sepsis. IL-8 had the strongest correlation with NETs formation, and the concentration of IL-8 in the plasma of patients with sepsis was significantly higher than that in patients with pneumonia and healthy controls (p < 0.001). NET-related genes were positively correlated with the SOFA score and 7-category ordinal scale. The expression level of MPO and PADI4 in sepsis patients were higher than that in community-acquired pneumonia (CAP) alone and healthy controls. The AUC of the prognostic prediction model for severe CAP composed of two genes (PADI4-CD177) showed the best performance, with an AUC of 0.917. This study confirmed that NETs formation was activated in RTI and the 2-gene signature provided a rapid and highly accurate biomarker for predicting the prognosis of severe CAP, which awaits further verification in a prospective cohort.

Indexed as

Community-Acquired InfectionsExtracellular TrapsPneumoniaAdultAgedBiomarkersCommunity-Acquired PneumoniaFemaleHumansInterleukin-8Leukocytes, MononuclearMaleMiddle AgedNeutrophilsPeroxidasePrognosisBiomarkersCXCL8 protein, humanInterleukin-8PeroxidaseProtein-Arginine Deiminase Type 4Community-acquired pneumoniaNeutrophil extracellular trapsSepsisTranscriptome

Identifiers

PMID41460586
PMCPMC12769636

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Registered trials

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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 OpenQuestion graph.