Palliative and Supportive Services, Flinders University, GPO Box 2100, Adelaide 5001, Australia.
BMC Med Res Methodol. 2013 Jul 2;13:86. doi: 10.1186/1471-2288-13-86.
BACKGROUND: PubMed translations of OvidSP Medline search filters offer searchers improved ease of access. They may also facilitate access to PubMed's unique content, including citations for the most recently published biomedical evidence. Retrieving this content requires a search strategy comprising natural language terms ('textwords'), rather than Medical Subject Headings (MeSH). We describe a reproducible methodology that uses a validated PubMed search filter translation to create a textword-only strategy to extend retrieval to PubMed's unique heart failure literature. METHODS: We translated an OvidSP Medline heart failure search filter for PubMed and established version equivalence in terms of indexed literature retrieval. The PubMed version was then run within PubMed to identify citations retrieved by the filter's MeSH terms (Heart failure, Left ventricular dysfunction, and Cardiomyopathy). It was then rerun with the same MeSH terms restricted to searching on title and abstract fields (i.e. as 'textwords'). Citations retrieved by the MeSH search but not the textword search were isolated. Frequency analysis of their titles/abstracts identified natural language alternatives for those MeSH terms that performed less effectively as textwords. These terms were tested in combination to determine the best performing search string for reclaiming this 'lost set'. This string, restricted to searching on PubMed's unique content, was then combined with the validated PubMed translation to extend the filter's performance in this database. RESULTS: The PubMed heart failure filter retrieved 6829 citations. Of these, 834 (12%) failed to be retrieved when MeSH terms were converted to textwords. Frequency analysis of the 834 citations identified five high frequency natural language alternatives that could improve retrieval of this set (cardiac failure, cardiac resynchronization, left ventricular systolic dysfunction, left ventricular diastolic dysfunction, and LV dysfunction). Together these terms reclaimed 157/834 (18.8%) of lost citations. CONCLUSIONS: MeSH terms facilitate precise searching in PubMed's indexed subset. They may, however, work less effectively as search terms prior to subject indexing. A validated PubMed search filter can be used to develop a supplementary textword-only search strategy to extend retrieval to PubMed's unique content. A PubMed heart failure search filter is available on the CareSearch website (http://www.caresearch.com.au) providing access to both indexed and non-indexed heart failure evidence.
背景:PubMed 对 OvidSP Medline 搜索过滤器的翻译为搜索者提供了更便捷的访问方式。它们还可以方便地获取 PubMed 独特的内容,包括最近发表的生物医学证据的引文。检索此内容需要一个包含自然语言术语(“文本词”)的搜索策略,而不是医学主题词(MeSH)。我们描述了一种可重现的方法,该方法使用经过验证的 PubMed 搜索过滤器翻译来创建仅使用文本词的策略,以扩展对 PubMed 独特的心力衰竭文献的检索。
方法:我们翻译了一个用于 PubMed 的 OvidSP Medline 心力衰竭搜索过滤器,并根据索引文献检索建立了版本等效性。然后在 PubMed 中运行 PubMed 版本,以识别过滤器的 MeSH 术语(心力衰竭、左心室功能障碍和心肌病)检索到的引文。然后,将其重新运行,将相同的 MeSH 术语限制在标题和摘要字段上(即作为“文本词”)进行搜索。从 MeSH 搜索中检索到但不在文本词搜索中检索到的引文被隔离。对其标题/摘要进行频率分析,确定那些作为文本词表现不佳的 MeSH 术语的自然语言替代词。然后将这些术语组合在一起,以确定用于检索此“丢失集”的最佳搜索字符串。将此字符串限制在 PubMed 的独特内容上进行搜索,然后将其与经过验证的 PubMed 翻译相结合,以扩展该过滤器在该数据库中的性能。
结果:PubMed 心力衰竭过滤器检索到 6829 条引文。其中,834 条(12%)在将 MeSH 术语转换为文本词时无法检索到。对 834 条引文的频率分析确定了五个高频自然语言替代词,可以提高该集合的检索效果(心力衰竭、心脏再同步、左心室收缩功能障碍、左心室舒张功能障碍和 LV 功能障碍)。这些术语一起重新检索到 157/834(18.8%)丢失的引文。
结论:MeSH 术语可在 PubMed 的索引子集中进行精确搜索。然而,在主题索引之前,它们可能作为搜索词的效果较差。可以使用经过验证的 PubMed 搜索过滤器来开发补充的仅使用文本词的搜索策略,以扩展对 PubMed 独特内容的检索。可以在 CareSearch 网站(http://www.caresearch.com.au)上访问经过验证的 PubMed 心力衰竭搜索过滤器,提供对已索引和未索引心力衰竭证据的访问。
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