Evidence map›Paper›PMID 40610592›Full record

ArticleNPJ digital medicine2025

A three-tier AI solution for equitable glaucoma diagnosis across China's hierarchical healthcare system.

Yi Zhou, Haitao Nie, Xinyu Gong, Minhui Dai, Zhaohong Guo, Xiaoling Deng, Mengyang Li, Yong Liu, Lingyu Sun, Xiangyi Tang and 9 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. 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

19 authors.

Yi Zhou *Eye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China.
Haitao Nie *School of Automation, Central South University, Changsha, Hunan, China.
Xinyu GongSchool of Automation, Central South University, Changsha, Hunan, China.
Minhui DaiEye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China.
Zhaohong GuoDepartment of Ophthalmology, Yiyang Central Hospital, Yiyang, Hunan, China.
Xiaoling DengDepartment of Ophthalmology, Taojiang County People's Hospital, Taojiang, Hunan, China.
Mengyang LiSchool of Automation, Central South University, Changsha, Hunan, China.
Yong LiuDepartment of Ophthalmology, Taojiang County People's Hospital, Taojiang, Hunan, China.
Lingyu SunEye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China.
Xiangyi TangEye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China.
Ling ZhouEye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China.
Zhiyao TangEye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China.
Ziqing XiaSchool of Automation, Central South University, Changsha, Hunan, China.
Lemeng FengEye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China.
Wulong ZhangEye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China.
Qingqing YiDepartment of Ophthalmology, Yiyang Central Hospital, Yiyang, Hunan, China.
Xiaobo XiaEye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China. xbxia21@csu.edu.cn.
Bin XieSchool of Automation, Central South University, Changsha, Hunan, China. xiebin@csu.edu.cn.
Weitao SongEye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China. wtsong1980@csu.edu.cn.ORCID http://orcid.org/0000-0001-6320-3209

Funding

National Natural Science Foundation of China (National Science Foundation of China) 81974132
6 · The paper itself

Abstract

Artificial intelligence (AI) offers a solution to glaucoma care inequities driven by uneven resource distribution, but its real-world implementation remains limited. Here, we introduce Multi-Glau, an three-tier AI system tailored to China's hierarchical healthcare system to promote health equity in glaucoma care, even in settings with limited equipment. The system comprises three modules: (1) a screening module for primary hospitals that eliminates reliance on imaging; (2) a pre-diagnosis module for handling incomplete data in secondary hospitals, and (3) a definitive diagnosis module for the precise diagnosis of glaucoma severity in tertiary hospitals. Multi-Glau achieved high performance (AUC: 0.9254 for screening, 0.8650 for pre-diagnosis, and 0.9516 for definitive diagnosis), with its generalizability confirmed through multicenter validation. Multi-Glau outperformed state-of-the-art models, particularly in handling missing data and providing precise glaucoma severity diagnosis, while improving ophthalmologists' performance. These results demonstrate Multi-Glau's potential to bridge diagnostic gaps across hospital tiers and enhance equitable healthcare access.

Identifiers

PMID40610592
PMCPMC12226717

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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.