Development and introduction of online evidence-based medicine research helper_Chinese Journal of Evidence-Based Medicine

Authors：

HUANG Qiao ^1,2,3 , WANG Yu ^1,2,3 , MA Wenhao ³ , WANG Yongbo ^1,2,3 , LI Xuhui ^1,2,3 , ZENG Xiantao ^1,2,3,4 ,  JIN Yinghui ^1,2,3

1. Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, P. R. China;
2. Center for Evidence-Based and Translational Medicine, Wuhan University, Wuhan 430071, P. R. China;
3. Department of Evidence-Based Medicine and Clinical Epidemiology, The Second Clinical College, Wuhan University, Wuhan 430071, P. R. China;
4. Urology Institute, Wuhan University, Wuhan 430071, P. R. China;

Corresponding author：

JIN Yinghui, Email: jinyinghui0301@163.com

Keywords：

Evidence-based medicine; Online tool; Effect measure conversion; Research registration; Database; Quality evaluation; Reporting guideline

DOI：

10.7507/1672-2531.202208041

Video：

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Based on previous evidence-based researches and teaching experience, our team conducted literature and book review, and summarized 4 requirements, 1) effect measure calculation and conversion, 2) registration of evidence-based research, 3) evidence-based research database and 4) quality evaluation tools and reporting guidelines. We developed an online platform of evidence-based medicine research helper using the front-end and back-end technology, which can be accessed using www.ebm-helper.cn. Currently, the online tool has included 46 scenarios for effect measure calculation and conversion, introduction of 7 evidence-based research registration platforms, 26 commonly used databases for evidence-based research and 29 quality evaluation tools and reporting guidelines. This online tool can help researchers to solve specific problems encountered in different stages of evidence-based medicine research. Promoting the application of this platform in evidence-based medicine will help researchers to use the tool scientifically and improve research efficiency.

Citation： HUANG Qiao, WANG Yu, MA Wenhao, WANG Yongbo, LI Xuhui, ZENG Xiantao, JIN Yinghui. Development and introduction of online evidence-based medicine research helper. Chinese Journal of Evidence-Based Medicine, 2022, 22(12): 1483-1488. doi: 10.7507/1672-2531.202208041 Copy

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8.	Newcombe RG. Two-sided confidence intervals for the single proportion: comparison of seven methods. Stat Med, 1998, 17(8): 857-872.
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13.	曾宪涛. 再谈循证医学. 武警医学, 2016, 27(7): 649-654.

1. 李幼平, 李静, 孙鑫, 等. 循证医学在中国的起源与发展: 献给中国循证医学20周年. 中国循证医学杂志, 2016, 16(1): 2-6.
2. 黄桥, 邝心颖, 童铁军, 等. 基于中位数为效应量的Meta分析及R实现. 医学新知, 2020, 30(4): 265-271.
3. 罗德惠, 万翔, 刘际明, 等. 如何实现从样本量、中位数、极值或四分位数到均数与标准差的转换. 中国循证医学杂志, 2017, 17(11): 1350-1356.
4. McGrath S, Zhao X, Steele R, et al. Estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis. Stat Methods Med Res, 2020, 29(9): 2520-2537.
5. Cai S, Zhou J, Pan J. Estimating the sample mean and standard deviation from order statistics and sample size in meta-analysis. Stat Methods Med Res, 2021, 30(12): 2701-2719.
6. Altman DG, Bland JM. How to obtain the confidence interval from a P value. BMJ, 2011, 343: d2090.
7. Lakens D. Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Front Psychol, 2013, 4: 863.
8. Newcombe RG. Two-sided confidence intervals for the single proportion: comparison of seven methods. Stat Med, 1998, 17(8): 857-872.
9. Liu N, Zhou Y, Lee JJ. IPDfromKM: reconstruct individual patient data from published Kaplan-Meier survival curves. BMC Med Res Methodol, 2021, 21(1): 111.
10. 方程, 邓巍, 樊景春, 等. 系统评价与Meta分析的注册平台简介. 同济大学学报(医学版), 2019, 40(3): 380-387.
11. 李柄辉, 訾豪, 李路遥, 等. 医学领域一次研究和二次研究的方法学质量(偏倚风险)评价工具. 医学新知, 2021, 31(1): 51-58.
12. 陈耀龙. 医学研究报告规范的发展与简介. 兰州大学学报(医学版), 2022, 48(1): 1-4.
13. 曾宪涛. 再谈循证医学. 武警医学, 2016, 27(7): 649-654.

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