Evidence map›Paper›PMID 32049817›Full record

SynthesisMedicine2020

Traditional chinese medicine for diabetic retinopathy: A systematic review and meta-analysis.

Bing Pang, Qing-Wei Li, Ya-Li Qin, Guang-Tong Dong, Shuo Feng, Jia Wang, Xiao-Lin Tong, Qing Ni

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 pooled it
–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

20 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. International Diagnostic Guidelines for Blood-Stasis Syndrome.Chinese journal of integrative medicine · 2022
    Article
  17. Article
  18. A Network Pharmacology to Explore the Mechanism ofEvidence-based complementary and alternative medicine : eCAM · 2020
    Article
  19. Article
  20. 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

8 authors.

Bing Pang
Qing-Wei LiFrom Department of Endocrinology, Guang' anmen Hospital of China Academy of Chinese Medical Sciences, Beijing.
Ya-Li QinZhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou.
Guang-Tong DongFrom Department of Endocrinology, Guang' anmen Hospital of China Academy of Chinese Medical Sciences, Beijing.
Shuo FengBeijing Chinese Medicine Hospital, Capital Medical University.
Jia WangGeneral Department, Guang' anmen Hospital of China Academy of Chinese Medical Sciences, Beijing, China.
Xiao-Lin TongFrom Department of Endocrinology, Guang' anmen Hospital of China Academy of Chinese Medical Sciences, Beijing.
Qing NiFrom Department of Endocrinology, Guang' anmen Hospital of China Academy of Chinese Medical Sciences, Beijing.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTraditional Chinese medicine (TCM) has been used to treat diabetic complications including diabetic retinopathy for many years.

objectivesThis review was performed to systematically assess the efficacy and safety of TCM for treating non- proliferative diabetic retinopathy (NPDR).

methodsRetrieval from 7 electronic databases was conducted to determine eligible trials published until March 1, 2018. Randomized controlled trials of NPDR that comparing compound Chinese medicine containing the therapeutic method of activating blood and remove stasis versus controls were included for analysis. Primary outcomes were progression of retinopathy. Secondary outcomes included visual acuity, mean defect of visual field, micro-aneurysms, hemorrhage areas, exudates, capillary nonperfusion areas, hemorheological indicators, oscillatory potentials (Ops), glycated haemoglobin (HbA1c), and adverse events. Data extraction and quality assessment were performed. Results expressing as risk ratios (RRs) or mean differences (MD) were analyzed with a fixed- or random- effect model. I statistics were used to assess heterogeneity.

resultsA total of 33 trials and 3373 participants were included. Findings revealed that no included studies reported the progression of retinopathy. Compared with conventional medicine, TCM was significantly better at improving visual acuity (MD, -0.10; 95% confidence interval [CI] -0.16 to -0.05) and Ops (MD, -4.68, 95% CI -8.51 to -0.85), and reducing the mean defect of visual field (MD, -1.43; 95%CI, -2.17 to -0.68), micro-aneurysms (MD, -4.51; 95% CI, -6.23 to -2.79), hemorrhage areas (MD, -0.62; 95% CI, -1.06 to -0.19), plasma viscosity (MD, -0.10; 95% CI, -0.20 to 0.00), and HbA1c (MD, -0.22; 95% CI, -0.42 to -0.03). Compared with placebo, TCM was also associated with a decline in the number of microaneurysms (MD, -4.35; 95% CI, -6.25 to -2.45), exudates (MD, -0.17; 95% CI -0.31 to -0.03), capillary nonperfusion areas (MD, -0.18; 95% CI, -0.31 to -0.04), and HbA1c (MD, -0.88; 95% CI, -1.44 to -0.32). Compared with blank groups, TCM was superior at decreasing the mean defect of visual field (MD, -0.87; 95% CI -0.95 to -0.79) and the numbers of micro-aneurysms (MD, -3.35; 95% CI, -4.73 to -1.97). Adverse events were also assessed.

conclusionActivating blood compound Chinese herbal medicine could help to improve visual acuity, micro-aneurysms and HbA1c. Further trials are needed to provide more reliable evidence.

Indexed as

AdultAgedDiabetic RetinopathyDisease ProgressionFemaleHumansMaleMedicine, Chinese TraditionalMiddle AgedRandomized Controlled Trials as TopicTreatment OutcomeVisual Acuity

Identifiers

PMID32049817
PMCPMC7035093

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.