Evidence map›Paper›PMID 39930419›Full record

ArticleBMC ophthalmology2025

Utilizing fundus images captured by two ultra-wide field imaging systems to measure diagnostic indicators and assess the grade of diabetic retinopathy.

Yaoyao Sun, Xiuju Chen, Zongming Song, Tingting Liu, Ye Tao, Tinglan Lai, Yanru Chen, Minghan Li, Jinfeng Qu, Xiaoxin Li

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC ophthalmology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

10 authors.

Yaoyao SunDepartment of Ophthalmology, Peking University People's Hospital, Beijing, China.
Xiuju ChenXiamen Eye Center of Xiamen University, Xiamen, China.
Zongming SongHenan Provincial People's Hospital, Zhengzhou, China.
Tingting LiuEye Institute of Shandong First Medical University, Eye Hospital of Shandong, Medical University (Shandong Eye Hospital), Jinan, China.
Ye TaoDepartment of Ophthalmology, Peking University People's Hospital, Beijing, China.
Tinglan LaiXiamen Eye Center of Xiamen University, Xiamen, China.
Yanru ChenXiamen Eye Center of Xiamen University, Xiamen, China.
Minghan LiXiamen Eye Center of Xiamen University, Xiamen, China.
Jinfeng QuDepartment of Ophthalmology, Peking University People's Hospital, Beijing, China. drbari@163.com.
Xiaoxin LiDepartment of Ophthalmology, Peking University People's Hospital, Beijing, China. drlixiaoxin@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study compared the effectiveness of different ultrawide field fundus imaging systems (Clarus™ 500 and Optos

methodsThis was a prospective, multicentre study. Retinal photographs were captured at four eye centres utilizing both the Clarus™ 500 and Optos

resultsA total of 113 patients, 201 eyes and 402 images were included in this study. 39 images were excluded due to the poor image quality and 363 images were finally analyzed. The Clarus™ imaging system demonstrated better image quality than the Optos

conclusionClarus

Indexed as

Diabetic RetinopathyDiagnostic Techniques, OphthalmologicalPhotographyRetinaAdultAgedFemaleFundus OculiHumansMaleMiddle AgedProspective StudiesSeverity of Illness IndexChinese clinical diagnosis and treatment guidelines for diabetic retinopathyDiabetic retinopathyEarly treatment of diabetic retinopathy study diabetic retinopathy severityInternational clinical diabetic retinopathy severityUltra-wide-field retinal imaging systems

Identifiers

PMID39930419
PMCPMC11812173

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.