In one paragraphObservational study in Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie, 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 itWhat 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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
15 authors.
Jingting LuoBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, No 1 Dongjiaominxiang Alley, Dongcheng District, Beijing, 100730, China.ORCID http://orcid.org/0000-0002-8415-7595 Shiyi YinBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, No 1 Dongjiaominxiang Alley, Dongcheng District, Beijing, 100730, China.ORCID http://orcid.org/0000-0001-9119-0302 Haihan ZhangBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, No 1 Dongjiaominxiang Alley, Dongcheng District, Beijing, 100730, China.ORCID http://orcid.org/0009-0006-9193-1063 Hanqing ZhaoBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, No 1 Dongjiaominxiang Alley, Dongcheng District, Beijing, 100730, China.
Jinlu ZhangChigenovo Corporation Limited, Beijing, 102206, China.
Jieqiong ChenDepartment of Ophthalmology, Shanghai General Hospital (Shanghai First People's Hospital), Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID http://orcid.org/0000-0003-1673-6517 Haowen LiBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, No 1 Dongjiaominxiang Alley, Dongcheng District, Beijing, 100730, China.
Manisha BhariBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, No 1 Dongjiaominxiang Alley, Dongcheng District, Beijing, 100730, China.ORCID http://orcid.org/0000-0003-4446-1979 Chuqiao LiangBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, No 1 Dongjiaominxiang Alley, Dongcheng District, Beijing, 100730, China.ORCID http://orcid.org/0000-0003-4733-7957 Jingyuan ZhuBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, No 1 Dongjiaominxiang Alley, Dongcheng District, Beijing, 100730, China.ORCID http://orcid.org/0000-0003-4545-7760 Wenbin WeiBeijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, No 1 Dongjiaominxiang Alley, Dongcheng District, Beijing, 100730, China. weiwenbintr@163.com.ORCID http://orcid.org/0000-0003-2386-0989 Funding
Beijing Science and Technology Planning Project Z201100005520045Capital Health Research and Development of Special Fund 2024-1-2052Capital Medical University Scientific Research Cultivation Fund 2025: PYZ24115National Natural Science Foundation of China 82141128National Natural Science Foundation of China 82220108017Sanming Project of Medicine in Shenzen Municipality SZSM202311018The Fund for Beijing Science & Technology Development of Traditional Chinese Medicine BJZYQN-2023-25
6 · The paper itselfAbstract
purposeVisual functional testing methods are limited and cannot be well applied in all kinds of ocular diseases, especially those with low-vision. To determine whether full-field stimulus threshold (FST) is an effective method in evaluating Bietti crystalline dystrophy (BCD), with the capability in replacing other traditional visual functional methods, we designed the study.
methodsThis study was a prospective cross-sectional observational study, conducted from September 2022 to March 2023. It was a sub-study of Beijing Tongren Eye Disease Clinical Database Biobank. The study was conducted in Beijing Tongren Hospital, Capital Medical University. BCD patients who were diagnosed based on clinical features, validated by whole-exome sequencing were included. The normal volunteers were included as control group. All BCD patients underwent comprehensive evaluations, including FST, best-corrected visual acuity (BCVA), color vision, microperimetry, full-field electroretinography (ffERG), optical coherence tomography (OCT), multimodal imaging system and 4 self-reported questionnaires. The normal control group subjects only conducted FST examination. The correlation between FST and BCVA, and the differences of FST values between disease severity groups, were evaluated. The BCVA logistic regression model, FST model and hybrid model's performance (area under the curve [AUC]) were tested in predicting disease severity.
results43 BCD patients (40.60 ± 8.57 years, 22 female [51%]) and 36 normal volunteers (38.56 ± 12.42 years, 21 female [58%]) were included. FST showed a moderate correlation with BCVA scores. Stage 2 group exhibited notably lower FST values than the stage 3 group, while the severely diminished group showed remarkable lower FST values than the extinguished group. The hybrid model showed better performance (AUC = 0.9221 and 0.9496) than FST model (AUC = 0.9026 and 0.9429), better than BCVA model (AUC = 0.8549 and 0.8487) in predicting disease severity.
conclusionsThe FST serves as a useful indicator for evaluating visual function and predicting the severity of disease in patients with BCD. The clinical implementation of FST value will serve as an important assay in various ocular diseases, necessitating further validation studies prior to its application.
Indexed as
Corneal Dystrophies, HereditaryRetinal DiseasesVisual AcuityVisual FieldsAdultCross-Sectional StudiesElectroretinographyFemaleHumansMaleMiddle AgedProspective StudiesTomography, Optical CoherenceVisual Field TestsBietti crystalline dystrophyFull-field stimulus thresholdInherited retinal diseasesVisual function
Identifiers
PMID41258201
PMCPMC12966260
What Socratic holds
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LicenceCC BY-NC-ND
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