Evidence map›Paper›PMID 41983121›Full record

ArticleFrontiers in immunology2026

Endometrial immune dysregulation shapes CD8

Shan Jiang, Yeqing Fu, Xiufeng Lin, Qingni Li, Zhibin Huang, Cong Zhou, Yecheng Zou, Yutong Li

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
–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

8 authors.

Shan JiangReproductive Center, Boai Hospital of Zhongshan, Zhongshan, Guangdong, China.
Yeqing FuReproductive Center, Boai Hospital of Zhongshan, Zhongshan, Guangdong, China.
Xiufeng LinReproductive Center, Boai Hospital of Zhongshan, Zhongshan, Guangdong, China.
Qingni LiReproductive Center, Boai Hospital of Zhongshan, Zhongshan, Guangdong, China.
Zhibin HuangReproductive Center, Boai Hospital of Zhongshan, Zhongshan, Guangdong, China.
Cong ZhouThe First School of Clinical Medicine, Guangdong Medical University, Zhanjiang, Guangdong, China.
Yecheng ZouReproductive Center, Boai Hospital of Zhongshan, Zhongshan, Guangdong, China.
Yutong LiThe First School of Clinical Medicine, Guangdong Medical University, Zhanjiang, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The recurrent implantation failure (RIF) remains a major clinical challenge in assisted reproduction. While endometrial immune dysregulation is implicated, its specific role and interaction with clinical factors are poorly defined. The lack of integrated, multimodal predictive models that combine clinical history with immune profiling limits personalized management. Methods: This study conducted a retrospective cohort study of 110 RIF patients, collecting comprehensive clinical and immune parameters. Traditional statistics and machine learning were employed to identify key predictors and build predictive models. Model interpretability was assessed using SHAP analysis, and causal pathways were explored Results: Previous implantation failure number was the strongest negative predictor (aOR = 0.74, 95% CI 0.60-0.91, Conclusion: This integrated clinical-immune signature underscores the pivotal, threshold-dependent role of endometrial CD8

Indexed as

CD8-Positive T-LymphocytesEmbryo ImplantationEndometriumAdultFemaleHumansMachine LearningPredictive Learning ModelsPregnancyRetrospective StudiesTreatment FailureCD8+ T cellsimmune disorderimplantation failure numbermachine learningpredictive modelingrecurrent implantation failure

Identifiers

PMID41983121
PMCPMC13070820

What OpenQuestion holds

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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.