Evidence map›Paper›PMID 35251707›Full record

ArticleJournal of ophthalmology2022

Choroidal Vascularity Index Assessment: A Potential Noninvasive Technique for Diagnosing Diabetic Nephropathy.

Xue Han, Nan-Nan Du, Shuang Li, Zong-Li Diao, Li Fu, Wen-Hu Liu

Abstract read
In one paragraph

Article in Journal of ophthalmology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Three-Dimensional Choroidal Vessels Assessment in Diabetic Retinopathy.Investigative ophthalmology & visual science · 2025
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  2. Review
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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

6 authors.

Xue HanDepartment of Nephrology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0002-9793-9270
Nan-Nan DuDepartment of Nephrology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0002-8998-6026
Shuang LiDepartmentof Ophthalmology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0002-1084-8887
Zong-Li DiaoDepartment of Nephrology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0002-5019-9009
Li FuInternational Medical Center, Beijing Friendship Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0002-2095-8131
Wen-Hu LiuDepartment of Nephrology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0002-6532-4394

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsThis study aimed to compare the accuracy of the choroidal vascularity index (CVI) and diabetic retinopathy (DR) in the diagnosis of diabetic nephropathy (DN).

methodsWe performed a cross-sectional study of 117 patients with proteinuria and diabetes mellitus (DM) in which 45 patients were diagnosed with DN by renal pathology. Demographic information, clinical features, and laboratory data were collected. A total of 234 eyes underwent evaluation of DR and the CVI using enhanced depth imaging-optical coherence tomography scans. We analyzed the association between the CVI and DN and compared the CVI and DR for diagnosing DN using area under receiver operating characteristic curves (AUROCs).

resultsThe severe nonproliferative DR and proliferative DR groups showed a lower CVI than the no DR and mild/moderate nonproliferative DR groups (

conclusionThe CVI might be a reliable noninvasive technique for predicting the pathological stage of DN and is superior to DR in diagnosing DN.

Identifiers

PMID35251707
PMCPMC8894076

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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.