Evidence map›Paper›PMID 38591943›Full record

ArticleTranslational vision science & technology2024

Quantitative Assessment of Fundus Tessellated Density in Highly Myopic Glaucoma Using Deep Learning.

Xiaohong Chen, Xuhao Chen, Jianqi Chen, Zhidong Li, Shaofen Huang, Xinyue Shen, Yue Xiao, Zhenquan Wu, Yingting Zhu, Lin Lu and 1 more

Open access · goldAbstract read
In one paragraph

Article in Translational vision science & technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
4.8field-weighted citation impact, top 5% of its field
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, 9 citations in OpenAlex.

  1. Observational
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  4. 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

11 authors at 1 institution in 1 country.

Xiaohong ChenState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, World Health Organization Collaborating Center for Eye Care and Vision, Guangzhou, China.
Xuhao ChenState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, World Health Organization Collaborating Center for Eye Care and Vision, Guangzhou, China.
Jianqi ChenState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, World Health Organization Collaborating Center for Eye Care and Vision, Guangzhou, China.
Zhidong LiState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, World Health Organization Collaborating Center for Eye Care and Vision, Guangzhou, China.
Shaofen HuangState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, World Health Organization Collaborating Center for Eye Care and Vision, Guangzhou, China.
Xinyue ShenState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, World Health Organization Collaborating Center for Eye Care and Vision, Guangzhou, China.
Yue XiaoState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, World Health Organization Collaborating Center for Eye Care and Vision, Guangzhou, China.
Zhenquan WuShenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, China.
Yingting ZhuState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, World Health Organization Collaborating Center for Eye Care and Vision, Guangzhou, China.
Lin LuState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, World Health Organization Collaborating Center for Eye Care and Vision, Guangzhou, China.
Yehong ZhuoState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, World Health Organization Collaborating Center for Eye Care and Vision, Guangzhou, China.
Jinan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To characterize the fundus tessellated density (FTD) in highly myopic glaucoma (HMG) and high myopia (HM) for discovering early signs and diagnostic markers. Methods: This retrospective cross-sectional study included hospital in-patients with HM (133 eyes) and HMG (73 eyes) with an axial length ≥26 mm at Zhongshan Ophthalmic Center. Using deep learning, FTD was quantified as the average exposed choroid area per unit area on fundus photographs in the global, macular, and disc regions. FTD-associated factors were assessed using partial correlation. Diagnostic efficacy was analyzed using the area under the curve (AUC). Results: HMG patients had lower global (0.20 ± 0.12 versus 0.36 ± 0.09) and macular FTD (0.25 ± 0.14 vs. 0.40 ± 0.09) but larger disc FTD (0.24 ± 0.11 vs. 0.19 ± 0.07) than HM patients in the tessellated fundus (all P < 0.001). In the macular region, nasal FTD was lowest in the HM (0.26 ± 0.13) but highest in the HMG (0.32 ± 0.13) compared with the superior, inferior, and temporal subregions (all P < 0.05). A fundus with a macular region nasal/temporal (NT) FTD ratio > 0.96 (AUC = 0.909) was 15.7 times more indicative of HMG than HM. A higher macular region NT ratio with a lower horizontal parapapillary atrophy/disc ratio indicated a higher possibility of HMG than HM (AUC = 0.932). Conclusions: FTD differs in degree and distribution between HMG and HM. A higher macular NT alone or with a lower horizontal parapapillary atrophy/disc ratio may help differentiate HMG. Translational Relevance: Deep learning-based FTD measurement could potentially assist glaucoma diagnosis in HM.

Indexed as

Deep LearningGlaucomaMyopiaAtrophyChoroidCross-Sectional StudiesHumansRetrospective Studies

Identifiers

PMID38591943
PMCPMC11008756
OpenAlexW4394604970

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.