Evidence map›Paper›PMID 42382468›Full record

ArticleJournal of inflammation research2026

PD-1/TIGIT CD4⁺ T-Cell Signature for Risk Stratification of Post-Weaning Mortality in Venoarterial Extracorporeal Membrane Oxygenation Patients.

Zengtao Wang, Xing Hao, Junyan Han, Chenglong Li, Liangshan Wang, Jing Chen, Jie Chen, Yu Cao, Yu Jiang, Haoyu Ji and 7 more

Abstract read
In one paragraph

Article in Journal of inflammation research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

17 authors.

Zengtao Wang *Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, People's Republic of China.
Xing Hao *Center for Cardiac Intensive Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, People's Republic of China.
Junyan Han *Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, People's Republic of China.
Chenglong LiCenter for Cardiac Intensive Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, People's Republic of China.
Liangshan WangCenter for Cardiac Intensive Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, People's Republic of China.
Jing ChenCenter for Cardiac Intensive Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, People's Republic of China.
Jie ChenCenter for Cardiac Intensive Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, People's Republic of China.
Yu CaoBiomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, People's Republic of China.ORCID 0009-0004-6988-9466
Yu JiangBiomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, People's Republic of China.
Haoyu JiBiomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, People's Republic of China.
Jiarui LiBiomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, People's Republic of China.
Ju ZhangBiomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, People's Republic of China.
Hong WangCenter for Cardiac Intensive Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, People's Republic of China.
Mingxi HuaBiomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, People's Republic of China.
Hui ZengBiomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, People's Republic of China.
Xiaotong HouCenter for Cardiac Intensive Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, People's Republic of China.
Chen ChenBiomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Mortality after successful weaning from venoarterial extracorporeal membrane oxygenation (VA-ECMO) remains common, yet few immune biomarkers enable post-weaning risk stratification. We examined whether circulating CD4⁺ T-cell subsets defined by programmed cell death protein 1 (PD-1) and T cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domains (TIGIT) were associated with off-ECMO mortality in adults supported with VA-ECMO. Methods: We conducted flow cytometric profiling of circulating T cells in 125 adult VA-ECMO patients, classified as survivors (n = 70), on-ECMO mortality (n = 33), and off-ECMO mortality after successful weaning (n = 22). We first quantified CD3⁺, CD4⁺, and CD8⁺ T-cell counts using BD Trucount tubes, and assessed conventional CD4⁺ and CD8⁺ differentiation subsets by flow cytometry. We then quantified PD-1/TIGIT-defined CD4⁺ T cell subsets and assessed their ability to discriminate off-ECMO mortality among successfully weaned patients using receiver operating characteristic (ROC) analyses with bootstrap resampling. A PD-1/TIGIT-based risk classification was constructed using ROC-derived cut-offs. Results: Although CD3⁺/CD4⁺/CD8⁺ T-cell counts and conventional CD4⁺ differentiation subsets did not differ across outcome groups, the off-ECMO mortality group showed a higher frequency of CD4⁺PD-1 Conclusion: A circulating CD4⁺ T cell signature defined by PD-1 and TIGIT expression associates with off-ECMO mortality and may aid risk stratification after VA-ECMO weaning.

Indexed as

CD4⁺ T cellsimmune dysregulationPD-1risk stratificationTIGITVA-ECMO

Identifiers

PMID42382468
PMCPMC13317771

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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.