Quality Evaluation of Animal Experimental Studies on Prevention and Treatment of Atherosclerosis byTraditional Chinese Medicine Compound Formula:Literatures during 2017—2022
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Quality Evaluation of Animal Experimental Studies on Prevention and Treatment of Atherosclerosis byTraditional Chinese Medicine Compound Formula:Literatures during 2017—2022
Journal of Traditional Chinese MedicineVol. 64, Issue 9, Pages: 901-908(2023)
LI Ruoqi, ZHENG Danping, LI Yingying, et al. Quality Evaluation of Animal Experimental Studies on Prevention and Treatment of Atherosclerosis byTraditional Chinese Medicine Compound Formula:Literatures during 2017—2022[J]. Journal of Traditional Chinese Medicine, 2023, 64(9): 901-908.
LI Ruoqi, ZHENG Danping, LI Yingying, et al. Quality Evaluation of Animal Experimental Studies on Prevention and Treatment of Atherosclerosis byTraditional Chinese Medicine Compound Formula:Literatures during 2017—2022[J]. Journal of Traditional Chinese Medicine, 2023, 64(9): 901-908.DOI: 10.13288/j.11-2166/r.2023.09.008.
Quality Evaluation of Animal Experimental Studies on Prevention and Treatment of Atherosclerosis byTraditional Chinese Medicine Compound Formula:Literatures during 2017—2022
计算机检索中国知网(CNKI)、万方数据知识服务平台(WF)、维普中文期刊服务平台(VIP)、中国生物医学文献数据库(SinoMed)、PubMed、Web of science、Cochrane library和Embase数据库,收集2017年1月1日至2022年9月20日发表的中药复方防治AS动物实验文献,基于SYRCLE偏倚风险评估工具和ARRIVE 指南对纳入的文献进行评分并计算各条目“低风险”符合率。
To explore the methods that can improve the quality of animal experiments on the prevention and treatment of atherosclerosis by traditional Chinese medicine (TCM) compound formula, by evaluating the methodological quality and reporting quality, and by analyzing the risk of bias in the experimental process and the inadequacy reporting of the researches.
Methods
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CNKI,WanFang,VIP,SinoMed,PubMed,Web of science, Cochrane library and Embase databases were searched to collect animal experimental literature on the prevention and treatment of atherosclerosis by TCM compounds published between January 1st, 2017 and September 20th, 2022. The included literature was scored based on the SYRCLE bias risk assessment tool and ARRIVE 2019 guidelines, and the coincidence rate of “low risk” for each item was calculated.
Results
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A total of 343 studies out of the initially screened 7921 studies were included, involving 301 in Chinese and 42 in English. The score of SYRCLE tool was 13.26±1.26,and the “low-risk” coincidence rate was 35.74%. The score of the ARRIVE guideline wass 24.39±1.65,and the “low-risk” coincidence rate was 42.22% of the essential items, while those were 9.41±2.34 and 20.10% of the recommended items. According to the SYRCLE's tool,245 studies (71.43%) did not provide details for sequence allocation reported no effective interventions in terms of selection bias,implementation bias,and measurement bias. Only five studies (1.46%) described baseline characteristics,and two studies (0.58%) reported the implementation of blinding in the outcome evaluation. None of the studies reported method of sample size determination,designation of primary outcome measure,and registration protocol in the ARRIVE guidelines. Only 49 studies (14.29%) identified animals not included in the analysis,and 54 studies (15.74%) provided details of the statistical method. Additional information on experimental animals was provided in 33 studies (9.62%).
Conclusion
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There are many problems in the methodological quality and reporting quality of animal experiments on the prevention and treatment of atherosclerosis by TCM compound formulas in literatures published during 2017—2022,especially in the implementation of the randomization and blinding during the experiments,and the adequate reporting of the experimental data report completeness.Therefore, it is recommended to design and report a study with reference to the evaluation tools, so as to improve the credibility and reproducibility of experimental studies.
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references
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Quality Evaluation of Animal Experimental Studies on Prevention and Treatment of Atherosclerosis by Traditional Chinese Medicine Compound Formula:Literatures during 2017 — 2022
LI Ruoqi 1 , ZHENG Danping 2 , LI Yingying 1 , TANG Danli 1 , SUI Yu 1
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