Evidence mapPaperPMID 42367768Full record

ReviewFrontiers in immunology2026

Autoimmune gastritis: a comprehensive review of pathophysiology, risk stratification, and management.

Minxiao Feng, Wenting Xu, Haiyan Zhu

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 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. Review
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

3 authors.

Minxiao Feng *Department of Gastroenterology, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Jiangsu, China.
Wenting Xu *Department of Reproduction, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Jiangsu, China.
Haiyan ZhuDepartment of Gastroenterology, The Third Affiliated Hospital of Zhejiang Chinese Medical University, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autoimmune gastritis (AIG) is a chronic, organ-specific autoimmune disease characterized by the immune-mediated destruction of gastric parietal cells, leading to impaired acid secretion, vitamin B12 deficiency, and an increased risk of gastric malignancies. The diagnosis of AIG relies on endoscopic findings combined with serological markers and histopathological confirmation. This review synthesizes current knowledge on the pathophysiology, diagnosis, and management of AIG, with a special focus on familial aggregation, polyglandular autoimmunity, and emerging therapeutic strategies. We discuss the diagnostic challenges posed by serological variability, the complex interplay with Helicobacter pylori infection, and the diagnostic pitfalls of macrocytic anemia. Furthermore, we explore precision risk stratification models for gastric neuroendocrine tumors (gNETs) and gastric adenocarcinoma, emphasizing the roles of endoscopic surveillance and molecular biomarkers. Finally, we review emerging therapeutic options, including novel immunomodulators and microbiome-targeted interventions. This review provides a comprehensive framework for clinicians to navigate the complexities of AIG, from early diagnosis to long-term management, with the goal of improving patient outcomes and mitigating the risk of malignant transformation.

Indexed as

Autoimmune DiseasesGastritisAnimalsDisease ManagementGenetic Predisposition to DiseaseHelicobacter InfectionsHumansRisk Assessmentautoimmune gastritisfamilial aggregationgastric neuroendocrine tumorsgenetic susceptibilityrisk stratificationthyroid autoimmunity

Identifiers

PMID42367768
PMCPMC13303924

What Socratic holds

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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.