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Evidence-based research methods to evaluate the clinical curative effects of traditional Mongolian medicine — Gurigumu formulae for liver diseases as an example

Yibo Liu, Baochang Zhou, Haiqi Fu and 3 more

Pharmacological Research - Modern Chinese Medicine · 2022

doi:10.1016/j.prmcm.2022.100070 (opens in a new tab)

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Abstract

Objective: We introduced meta-analysis and trial sequential analysis (TSA) into the evidence-based evaluation of the efficacy of the Mongolian medicine formula Gurigumu for liver diseases as an evidence-based medicine approach to identify the problems in the modernization process of Mongolian medicine. Methods: Randomized controlled trials of Gurigumu formulae for liver diseases were collected from several bibliographic databases by combining subject words and free words. The Cochrane Collaboration Network Bias Risk Assessment Tool was used to evaluate the quality of the studies included in the analysis. RevMan software (version 5.3) was used to evaluate the total effective rate; other outcome indicators including alanine aminotransferase (ALT), aspartate aminotransferase (AST), total cholesterol (TC), and triglyceride (TG) levels underwent meta-analysis and subgroup analysis before and after treatment. TSA was used for the sequential analysis of total efficiency to verify the stability of the results. Results: Fifteen randomized controlled trials involving 1188 patients were included in the analysis. The results of the meta-analysis showed that the Gurigumu formulae had potential effects for liver disease in the total effective rate, ALT, AST, TG, and TC. Further, the total effective rate was were found to be stable via TSA verification. Conclusion: This study determined the potential impact of Gurigumu formulae on liver diseases. Through the process of evidence-based research, key problems in the experimental design of Mongolian medicine and in the clinical methods were identified. The results introduce a new direction for the construction and improvement of a modern Mongolian medical system.

Abstract licence: CC BY-NC-ND

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