SynthesisMedicine2021
Xuesaitong injection treating acute myocardial infarction: A systematic review and meta-analysis.
Synthesis in Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 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
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- Comparative effectiveness and safety of four traditional Chinese medicine injections with invigorating blood circulation, equivalent effect of anticoagulation or antiplatelet in acute myocardial infarction: a Bayesian network meta-analysis.Frontiers in pharmacology · 2024Pooled it
- Research progress on the mechanism of panax notoginseng saponin in the treatment of atherosclerosis.Frontiers in cardiovascular medicine · 2026Review
- Pharmacological properties and mechanisms of Notoginsenoside R1 in ischemia-reperfusion injury.Chinese journal of traumatology = Zhonghua chuang shang za zhi · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAlthough the incidence of acute myocardial infarction (AMI) is decreasing, the mortality in AMI patients remains substantial. Traditional Chinese medicine has shown its role in the prevention and management of AMI. The purpose of this study is to evaluate the clinical efficacy of Xuesaitong injection (XST) for the treatment of AMI by a meta-analysis.
methodsA literature search was performed in 5 medical databases up to June 1, 2020. Randomized controlled trials involving XST combined with conventional treatment versus conventional treatment were included. A meta-analysis of clinical efficacy, left ventricular function and other objective parameters was performed to evaluate the effects of XST on AMI.
resultsFive randomized controlled trials involving 539 participants were eventually included. Meta-analysis showed that the combination of XST and conventional treatment could achieve significantly better effect on improving clinical efficacy (risk ratio: 1.09 [1.01, 1.17]; P = .04), left ventricular ejection fraction (mean difference [MD]: 3.18 [1.69, 4.67]; P < .0001), hypersensitive C-reactive protein (MD: -2.58 [-5.04, -0.12]; P = .04), interleukin 6 (MD: -26.00 [-38.85, -13.16]; P < .0001), cardiac troponin T (MD: -15.85 [-18.09, -13.61]; P < .00001) and creatine kinase myocardial isoenzyme (MD: -73.06 [-79.74, -66.37]; P < .00001).
conclusionXST combined with conventional treatment can achieve better efficacy on clinical performance and some of the AMI related parameters. However the interpretation of the results should be cautious, due to the relatively low quality of included trials. More rigorously designed, large-scaled, randomized controlled trials are warranted to support its clinical use in the future.
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.