Unsatisfied methodological qualities assessment of systematic reviews/Meta-analyses on Chinese medicine for stroke and their risk factors
Journal Title: Medical Data Mining - Year 2021, Vol 4, Issue 1
Abstract
Background: Stroke is not only high in morbidity and mortality but also poses a great burden of disease and it is also the most reported disease in Chinese medicine systematic reviews. Therefore, the quality of such evidence couldn’t be ignored. This study aims to use a measurement tool to assess systematic reviews (AMSTAR) to assess the methodological qualities of SR/Meta-analyses of Chinese medicine on stroke. Methods: Systematic searching of seven electronic databases and PROSPERO registration platform was carried out. Two researchers separately selected studies, extracted bibliographical characteristics and scored every included study independently after training. Total score and the proportion of each item completion were explored in different subgroup comparisons. Spearman rank correlation and multivariable logistic regression were used to measure the association between bibliographical characteristics and total score or each item. Results: Total average score of AMSTAR 1.0 checklists of 234 systematic reviews/Meta-analyses was 4.47 (95% CI 4.27–4.68) and the qualities were unsatisfied especially in terms of priori setting (2.14%), grey literature inclusion (5.13%), providing a list of excluded studies (2.14%) and conflict of interest (0.00%). No improvement was found in 3 years even after the publication of AMSTAR. Chinese or non-registered systematic reviews/Meta-analyses showed even worse methodological qualities (P < 0.01). Positive correlation was found between individual items and number of pages, number of authors, research questions, languages or Meta-analyse separately (P < 0.05). Conclusion: The methodological qualities of systematic reviews/Meta-analyses of Chinese medicine on stroke are poor especially Chinese studies，non-registered studies, brief studies and studies without Meta-analyse or cooperation. There is no obvious improvement over these years even after the publication of AMSTAR tool, so it is urgent to promote the use of AMSTAR or develop other efficient methods to control the quantity and monitor the quality in future.
Authors and Affiliations
Jia- Ying Wang 1* , Nan Li2 , Jun- Feng Wang3 , Ming- Hui Wang4
Keywords
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- EP ID EP693185
- DOI 10.12032/MDM2021033001
- Views 112
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