• 1. Guangdong Provincial Hospital of Chinese Medicine, Guangdong Provincial Academy of Chinese Medical Sciences, the Second Clinical School of Guangzhou University of Chinese Medicine, Guangzhou 510120, P. R. China;
  • 2. State Key Laboratory of Dampness Syndrome of Chinese Medicine (the Second Affiliated Hospital of Guangzhou University of Chinese Medicine), Guangzhou 510120, P. R. China;
NI Xiaojia, Email: grace1984325@126.com
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Objective To evaluate the methodological quality of cross-sectional surveys about Chinese medicine syndrome in a population at potential risk of cerebrovascular diseases. Methods  The CNKI, WanFang Data, CBM and PubMed databases were electronically searched to collect cross-sectional surveys about Chinese medicine syndromes in a population at potential risk of cerebrovascular diseases from inception to December, 2022. The methodological quality was assessed using the JBI scale. Results  A total of 105 studies were included. The average reporting rate of JBI was 52.06%, and the items with the highest scores included "sufficient coverage of the identified sample in data analysis" (100%), "description of study subjects and setting" (92.38%), and "using valid methods for the identification of the condition" (86.67%). Items with the lowest scores included "adequate sample size" (13.33%), "adequate response rate or low response rate managed appropriately" (14.29%), and "study participants recruited in an appropriate way" (20.95%). Subgroup analysis suggested that type of publication and number of implementation centers were potential factors influencing methodology quality (P<0.05). Conclusion  The methods essential to a cross-sectional survey such as sampling, sample size calculation and handling with the response rate, and the syndrome diagnosis scales specific to Chinese medicine require further improvement.

Citation: SU Qing, XU Yao, MO Ruibi, CHEN Yifan, CAI Yefeng, NI Xiaojia. The methodological assessment of cross-sectional surveys about Chinese medicine syndrome in a population at potential risk of cerebrovascular diseases. Chinese Journal of Evidence-Based Medicine, 2023, 23(10): 1204-1211. doi: 10.7507/1672-2531.202303149 Copy

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