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【原创】第29届Cochrane-Systle Systematic Review全程报道
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小弟有幸获得丁香园循证版提供的免费名额,代表丁香园循证版参加SRS举办的第29届Cochrane-Systle Systematic Review培训班,现发占位贴,持续报道培训内容!(报告人:@zl在路上)
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zl在路上 edited on
AM.主讲:夏君,Clive E Adams主题:何为循证,如何制作Protocol和Cochrane SR?围绕上述主题,夏君老师就循证的产生,Cocharne Collaboration的发展及SR的制作做了简要的概述,此部分均是基础的知识讲解,但是有一点夏君老师尤为强调:作为一个系统评价者,应该如何选用数据处理软件?夏老师认为作为一个普通的系统评价制作者,RevMan已经较为全面了,尽管诸如SPSS、SAS和Stata等高级统计学软件的数据处理功能都极为强大,然而作者本身对软件的运行程序和过程,尤其是录入数据的处理判断不佳,可能造成一定行错误。Clive 教授就SR的制作中的问题做了详细讲解,其中较为重要的是如何处理缺失数据,如何进行亚组分析和如何撰写SR的method部分。Clive就missing data处理的重要性用一个例子做了阐释:纳入100个患者,干预组和对照组随机纳入50人,干预组为new drug,对照组为old treatment,研究结束时干预组脱落1人(死亡),对照组无缺损。如果作者不告知干预组缺失者是死亡,作者就会认为脱落率很低,结果很可信,这样的结果是会误导临床实践的,必须严格处理missing data。关于亚组分析,必须注意不要data-driving,在制作SR之前应该实现明确Subgroup analysis的原因。关于撰写SR的method section,可以参考协作组或者以成熟的撰写template,但必须在ackonwledge section部分致谢。 PM.主讲:李博主题:如何实现循证检索,如何筛选、纳入文献及RevMan实战研究。循证包括用证和创证,因此如何实现循证检索就涉及用证和创证检索。李博老师就循证检索常用的database进行了详细深入的介绍,并重点强调了PubMed、Medline和Ovid的区别和联系。并以自身的Cochrane Registration Title作为示例进行了细节解说。此部分的重点内容在于Cochrane Handbook为循证检索制定的专业检索式,并选取志愿者现场演示。 系统综述是团队协作,文献筛选一般为三人合作,并可依据Kappa一致性系数加以判定。在本部分的讲解中,李博老师重点强调了文献纳入与排除应严格基于inclusion and exclusion criteria,不应随心所欲。纳入标准:宁可错杀一千,不可随意降低质量!RevMan软件实战演示,园子里已有大量讲解,在此就不做详细报道。首先就未能及时更新报告内容致歉,小弟现将余下培训内容更新如下: AM.主讲:夏君(Jun Xia)主题:偏倚风险评估偏倚风险评估是阐述结果,并评价结果及所得结论可信度的基础,为便于学员全面的理解偏倚风险评估的各环节所涉及的具体评估条目,夏君老师以巧克力是否能够预防瞌睡为例,做了一个现场RCT。通过该RCT,从随机(随机抽样和随机分组)、分配隐藏(保护前面的随机及为盲法实施垫底基础)、盲法、选择性报告结局,不完全数据、及其他可能影响结局指标评价而又未能包括在前述的评估条目中的可能偏倚均作了详细而幽默的解释。其中分配隐藏是最容易混淆的概念,一般均认为allocation concealment是不必要的,认为其与blinding并无区别,通过夏君老师的RCT,这些迷惑均得到了解释,最重要的一点就在于allocation concealment是保护前面的随机及为盲法实施垫底基础。此外,夏老师还揭示了为何按顺序或者生日单双号分组不是随机,按顺序分组不能均衡各组种混杂因素,会造成系统误差,而生日单双号则破坏了随机的不可预测性。 PM.主讲:Clive E Admas主题:数据提取数据提取是系统综述中极为重要的一环,适宜的数据是合并出可靠结果集得出结论的关键。Clive教授就Binary 和Continuous 数据如何提取和转换进行了讲授,并以Cochrane SR的数据提取方式和Cochrane Schizophrenia Group的数据提取表格为模板,step-by-step的讲授了数据提取应注意的每一个环节。最重要的一句话:Once random will analysis。 AM.主讲:郭秀花主题:临床研究设计及异质性分析与处理异质性包括三个方面:临床异质性、方法学异质性和统计学异质性。其中临床和方法学异质性又是造成异质性的主要来源。为便于透彻的理解异质性的分析与处理,郭教授就临床研究设计进行了详细的概述,主要涉及RCT的三要素(随机、对照与重复)。其中交叉设计和析因设计也有一定涉及,并对析因设计的因素和水平加以了阐述。此外对SR中常用的效应统计量的概念及计算式均深入的加以了讲解。郭教授阐述了综述、SR和Meta-analysis之间的区别与联系,而后对异质性的分析和处理做了系统的讲解和实战演示。小弟总结如下:异质性分析包括异质性检验和异质性处理,异质性检验又可分为图示法和数值法,检验了异质性,重点在于对异质性的处理——分析异质性的来源,而不是随便的使用随机效应模型。 PM.
主讲:刘雅莉,赵赛主题:结果解释及结论总结与RevMan软件的系统实战演练下午的培训分为两个环节,第一环节是中国中医科学院刘雅莉博士(兰州大学循证医学中心硕导,师从杨克虎教授)就SR的结果解释及结论总结做系统解析。刘雅莉老师首先对前两天的内容加以了概括性回顾,而后通过Cochrane SR和general SR两方面对如何解释结果和得出结论做了讲解。此环节重点在于GRADE证据分级及推荐系统的引入。刘老师就RCT设计的5个降级因素(研究局限性、不精确性、间接比较、不一致性和可能的发表偏倚)及观察性研究的三个升级因素(大的效应量、剂量反应及可能降低效应量的混在因素存在)该如何评价做了阐述。第二个环节有SRS学术主管赵赛老师主讲。赵老师通过自身在Cochrane注册及发表SR的经验及对RevMan软件的理解,step-by-step的为学员们演示了RevMan文献、数据录入及分析的详细内容。通过三天的系统培训,小弟在循证方面的理解和功底有了大步提升。再次,再次感谢丁香园、循证版、各位版主及战友,感谢这次难能可贵的机会,小弟定将再接再厉,为循证出一份力!
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zl在路上 edited on
你这也太超前了吧
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楼上XD,不好意思,插入一下。我也来说说体会,昨天讲课的李老师、仇老师、周老师等水平确实很高,有时候一句话就能解决很多困扰很久的问题。做系统评价或分析最难的我觉得一个是选题,另一个就是制定检索策略。比如课堂上讲讲的这个例子的检索:Insecticide-treat vsnon-insecticide-treated bed net for preventing malaria检索过程:“malaria” search1 malaria*2 plasmodium*3 “blackwater fever”4 “marsh fever” 5 “Malaria”[mesh]6 1 or 2 or 3 or or 5 “bed-net”search7 nets*or bednet*or bed-net*or curtain* or “mosquitonet” or insecticide-treated or”insecticide treated”8 Exp”Bedding and Linens”[mesh]9”Mosquito control”[mesh]10 7 or 8 or 9 这里有点不明白,主题词检索“Bedding and Linens”用不用exp检索,结果差别太大了。Search &Bedding and Linens&[Mesh]
17:45:13Search (bedding and linens[MeSH Terms])
17:43:51Search (exp[bedding and linens])
17:42:57既然pubmed 的主题检索是自动扩展的,那为什么差别这样大?要是想查“全”,是不是所有主题检索都要用exp,为什么有时候用有时候不用?
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doctor02 edited on
丁香园助理版主
doctor02 楼上XD,不好意思,插入一下。我也来说说体会,昨天讲课的李老师、仇老师、周老师等水平确实很高,有时候一句话就能解决很多困扰很久的问题。做系统评价或分析最难的我觉得一个是选题,另一个就是制定检索策略。比如课堂上讲讲的这个例子的检索:Insecticide-treat vsnon-insecticide-treated bed net for preventing malaria检索过程:“malaria” search1 malaria*2 plasmodium*3 “blackwater fever”4 “marsh fever” 5 “Malaria”[mesh]6 1 or 2 or 3 or or 5 “bed-net”search7 nets*or bednet*or bed-net*or curtain* or “mosquitonet” or insecticide-treated or”insecticide treated”8 Exp”Bedding and Linens”[mesh]9”Mosquito control”[mesh]10 7 or 8 or 9 这里有点不明白,主题词检索“Bedding and Linens”用不用exp检索,结果差别太大了。Search &Bedding and Linens&[Mesh]
17:45:13Search (bedding and linens[MeSH Terms])
17:43:51Search (exp[bedding and linens])
17:42:57[img]data:image/base64,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[/img]既然pubmed 的主题检索是自动扩展的,那为什么差别这样大?要是想查“全”,是不是所有主题检索都要用exp,为什么有时候用有时候不用? 我也在上海听课呢,你的检索是错的,具体问题见下一帖子哈,这个引用起,写起来麻烦,欢迎讨论哈
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你的理解:pubmed是会默认拓展的,这是正确的呢,而且其会将自由词自动对应到主题词进行检索呢。具体如你的例子:当我们输入 malaria那么其检索结果如下:检索的具体过程呢,是在这里的,如下所示:你的第三个检索是错的,你输入时候是:(exp [bedding and linens])你注意哈下图:有个 Unknownfield was ignored: [bedding and linens]. 这个你要注意哈嘛,直接把你的[beddingand linens]忽略了呢,也就是只检索了exp,这个就搞笑了呢。再看看具体的检索过程:这就证明真的不对呢。楼主掌握住pubmed的数据库特征,也注意哈自查,不要忽视细节哟。加油!欢迎讨论。不知道解决你的问题没有,如果没有,可以现场讨论。我是丁香园上海班这次的免费名额获得者
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确实是的,小细节很重要。请教个问题,检索策略怎么是“bed-net”和“malaria”两个检索咧?“bed-net”下检索的“bedding and linens”是同义词?exp?
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sanerboy 确实是的,小细节很重要。请教个问题,检索策略怎么是“bed-net”和“malaria”两个检索咧? ...那个exp是多余的,有时间给你细讲
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我也想请教个问题,检索策略怎么是“bed-net”和“malaria”两个检索?“bed-net”下检索的“bedding and linens”是同义词?exp?
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&bed-net&and &malaria&分别代表PICO中的&I& and &P&,故在检索中将两者用AND进行合并检索; “bedding and linens&是&bed-net&的Mesh词 (小弟将其理解为数据库中所有bed-net近义词的代表词),不知能否回答楼上的问题。
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有课件吗?能分享一下吗?
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有课件吗?
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