ZHANG Wei,MA Lin,DENG Hongyong.Evidence evaluation tool for clinical randomized controlled trials of traditional Chinese medicine based on GRADE System[J].Shanghai Journal of Traditional Chinese Medicine,2022,56(04):6-13.
ZHANG Wei,MA Lin,DENG Hongyong.Evidence evaluation tool for clinical randomized controlled trials of traditional Chinese medicine based on GRADE System[J].Shanghai Journal of Traditional Chinese Medicine,2022,56(04):6-13. DOI: 10.16305/j.1007-1334.2022.2111011.
Evidence evaluation tool for clinical randomized controlled trials of traditional Chinese medicine based on GRADE System
Objective,2,The GRADE system was revised to retain its scientific nature, reflect the characteristics of traditional Chinese medicine (TCM) and improve its practicality.,Methods,2,The initial revised entries of the modified Delphi expert questionnaire were formulated on the basis of literature research, and two rounds of expert surveys were conducted. An expert consensus meeting was held to form an evaluation tool.,Results,2,A total of 27 experts participated in the two rounds of questionnaire surveys on the initial revised entries and provided expert opinions, and 5 experts participated in the expert consensus meeting, who facilitated the formation of ,Evidence⁃Evaluation Tool of Clinical Evidence of Traditional Chinese Medicine Clinical Randomized Controlled Trials Based on GRADE System. ,The evaluation tool simplifies the GRADE system and adapts to the TCM clinical application, and it contains 9 revised items involving high-quality evidence sources, evidence downgrading factors and upgrading factors.,Conclusion,2,After revision, the GRADE system can better embody the theoretical and clinical characteristics of TCM and becomes more adaptable so that it can improve the application quality of GRADE system in the evaluation of TCM clinical evidence.
关键词
中医药学GRADE体系临床疗效评价随机对照试验循证医学专家共识
Keywords
traditional Chinese medicineGRADE systemclinical effect evaluationrandomized controlled trialsevidence-based medicineexpert consensus
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