ArticleSystematic reviews2025
An evidence mapping study based on systematic reviews of traditional Chinese medicine (TCM) for diabetic retinopathy.
Article in Systematic reviews, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled 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.
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.
Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- An evidence mapping study based on systematic reviews of traditional Chinese medicine for hyperuricemia.Frontiers in nutrition · 2026Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDiabetic retinopathy (DR) is a leading cause of vision impairment and blindness among individuals with diabetes. Traditional Chinese medicine (TCM) has been explored as an alternative treatment for DR, but the quality of evidence remains uncertain. A comprehensive evidence mapping study is necessary to synthesize existing SRs, identify gaps in the literature, and highlight areas requiring further research.
objectiveThis study aims to evaluate the reporting and methodological quality of SRs on TCM for DR and to assess the effectiveness of TCM interventions using an evidence-mapping approach.
methodsA comprehensive search of major biomedical databases to identify relevant SRs published up to November 2023. The reporting quality of the included SRs was assessed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, while the methodological quality was evaluated using the Assessment of Multiple Systematic Reviews 2 (AMSTAR 2) tool.
resultsA total of 51 SRs involving 131,084 participants were included in the analysis. Evidence mapping indicated that TCM is relatively effective in treating DR. However, the methodological quality and reporting standards of these SRs were generally suboptimal. According to the AMSTAR 2 assessment, only one SR (2%) was rated as high quality, 29 SRs (56.9%) were of moderate quality, 20 SRs (39.2%) were of low quality, and one SR (2%) was of critically low quality. While all studies adequately reported the PICO components, risk of bias assessment, and statistical methods, none provided information on funding sources. Furthermore, only one study (2%) included a list of excluded studies with reasons, and eight SRs (15.7%) documented pre-specified protocols. Common reporting deficiencies included incomplete protocol and registration details, unclear review rationales, and insufficient presentation of relevant outcome data.
conclusionThis evidence mapping study highlights the potential benefits of TCM for treating DR while identifying significant gaps in the existing literature. Although TCM interventions show potential benefits for treating DR, the overall quality of SRs is suboptimal. Future research should focus on addressing these gaps, particularly in areas such as funding disclosure and methodological rigor, to enhance the reliability of evidence on TCM interventions for DR.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.