Evidence map›Paper›PMID 42490785›Full record

ArticleFrontiers in immunology2026

Immune dysregulation drives the relapse of peritoneal dialysis-associated peritonitis: a single-center prospective study.

Guang Yang, Xingbo Hong, Zhiwei Lai, Hua Zhang, Zuying Xiong, Zibo Xiong

Abstract read
In one paragraph

Article in Frontiers in immunology, 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
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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

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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

6 authors.

Guang Yang *Division of Renal Medicine, Peking University Shenzhen Hospital, Peking University, Shenzhen, China.
Xingbo Hong *Renal Division, Peking University (PKU)-Shenzhen Clinical Institute of Shenzhen University Medical College, Shenzhen, China.
Zhiwei LaiDivision of Renal Medicine, Peking University Shenzhen Hospital, Peking University, Shenzhen, China.
Hua ZhangDivision of Renal Medicine, Peking University Shenzhen Hospital, Peking University, Shenzhen, China.
Zuying XiongDivision of Renal Medicine, Peking University Shenzhen Hospital, Peking University, Shenzhen, China.
Zibo XiongDivision of Renal Medicine, Peking University Shenzhen Hospital, Peking University, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The diagnosis and management of relapsing peritoneal dialysis-associated peritonitis (PDAP) remains a clinical challenge. This study aimed to identify biomarkers associated with relapsing PDAP and discuss potential mechanisms. Methods: 31 PDAP patients treated in 2023 were prospectively enrolled, including 23 cured patients and 8 with relapsing PDAP. Peritoneal dialysate samples were collected for conventional bacterial culture, 16S rDNA sequencing, and proteomic analysis. Results: The positivity rate for conventional culture was 64.5%, while that for 16S rDNA sequencing was 67.8%; combining both methods increased the detection rate to 83.9%. Microbiome analysis revealed that PDAP relapse may stem not only from exogenous pathogens but also from gut-derived bacterial translocation due to impaired local immunity. Proteomic profiling revealed that compared with the Cured group, the Relapse group showed downregulated levels of CCL28, CD40, and uPA, and upregulated NRTN. Bioinformatic analysis revealed dysregulation in pathways related to inflammation, fibrinolysis, and immune clearance, thus linking relapsing PDAP to a disturbed peritoneal immune microenvironment. Conclusion: Relapsing PDAP is linked to peritoneal immune dysregulation, and 16S rDNA sequencing represents a complementary diagnostic tool. These findings may guide precise management and improve patient outcomes.

Indexed as

Peritoneal DialysisPeritonitisAdultAgedBiomarkersFemaleHumansMaleMiddle AgedProspective StudiesProteomicsRecurrenceRNA, Ribosomal, 16SBiomarkersRNA, Ribosomal, 16Simmune dysfunctioninflammationperitoneal dialysisperitonitisrelapsing

Identifiers

PMID42490785
PMCPMC13375459

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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.