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在EMBASE中检测临床合理的预后研究的最佳搜索策略:一项分析性调查。

Optimal search strategies for detecting clinically sound prognostic studies in EMBASE: an analytic survey.

作者信息

Wilczynski Nancy L, Haynes R Brian

机构信息

Health Information Research Unit, Department of Clinical Epidemiology and Biostatistics, McMaster University, Room 2C10b, 1200 Main Street West, Hamilton, Ontario, L8N 3Z5, Canada.

出版信息

J Am Med Inform Assoc. 2005 Jul-Aug;12(4):481-5. doi: 10.1197/jamia.M1752. Epub 2005 Mar 31.

Abstract

BACKGROUND

Clinical end users of EMBASE have a difficult time retrieving articles that are both scientifically sound and directly relevant to clinical practice. Search filters have been developed to assist end users in increasing the success of their searches. Many filters have been developed for the literature on therapy and reviews for use in MEDLINE, but little has been done for use in EMBASE with no filter development for studies of prognosis. The objective of this study was to determine how well various methodologic textwords, index terms, and their Boolean combinations retrieve methodologically sound literature on the prognosis of health disorders in EMBASE.

METHODS

An analytic survey was conducted, comparing hand searches of 55 journals with retrievals from EMBASE for 4,843 candidate search terms and 8,919 combinations. All articles were rated using purpose and quality indicators, and clinically relevant prognostic articles were categorized as "pass" or "fail" according to explicit criteria for scientific merit. Candidate search strategies were run in EMBASE, the retrievals being compared with the hand search data. The sensitivity, specificity, precision, and accuracy of the search strategies were calculated.

RESULTS

Of the 1,064 articles about prognosis, 148 (13.9%) met basic criteria for scientific merit. Combinations of search terms reached peak sensitivities of 98.7% with specificity at 50.6%. Compared with best single terms, best multiple terms increased sensitivity for sound studies by 12.2% (absolute increase), while decreasing specificity (absolute decrease 5.1%) when sensitivity was maximized. Combinations of search terms reached peak specificities of 93.4% with sensitivity at 50.7%. Compared with best single terms, best multiple terms increased specificity for sound studies by 7.1% (absolute increase), while decreasing sensitivity (absolute decrease 8.8%) when specificity was maximized.

CONCLUSION

Empirically derived search strategies combining indexing terms and textwords can achieve high sensitivity or specificity for retrieving sound prognostic studies from EMBASE.

摘要

背景

EMBASE的临床终端用户在检索既科学合理又与临床实践直接相关的文章时面临困难。已开发出搜索过滤器以帮助终端用户提高搜索成功率。已为MEDLINE上的治疗文献和综述开发了许多过滤器,但在EMBASE中使用的却很少,且尚未针对预后研究开发过滤器。本研究的目的是确定各种方法学文本词、索引词及其布尔组合在EMBASE中检索有关健康障碍预后的方法学合理文献的效果如何。

方法

进行了一项分析性调查,将55种期刊的手工检索结果与从EMBASE中检索4843个候选搜索词和8919种组合的结果进行比较。所有文章均使用目的和质量指标进行评分,临床相关的预后文章根据明确的科学价值标准分为“通过”或“未通过”。在EMBASE中运行候选搜索策略,将检索结果与手工检索数据进行比较。计算搜索策略的敏感性、特异性、精确性和准确性。

结果

在1064篇关于预后的文章中,148篇(13.9%)符合科学价值的基本标准。搜索词组合的敏感性峰值达到98.7%,特异性为50.6%。与最佳单个词相比,最佳多个词在声音研究中的敏感性提高了12.2%(绝对增加),而在敏感性最大化时特异性降低(绝对降低5.1%)。搜索词组合的特异性峰值达到93.4%,敏感性为50.7%。与最佳单个词相比,最佳多个词在声音研究中的特异性提高了7.1%(绝对增加),而在特异性最大化时敏感性降低(绝对降低8.8%)。

结论

结合索引词和文本词的经验性搜索策略在从EMBASE中检索合理的预后研究时可实现高敏感性或特异性。

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