Agoritsas Thomas, Merglen Arnaud, Courvoisier Delphine S, Combescure Christophe, Garin Nicolas, Perrier Arnaud, Perneger Thomas V
Division of Clinical Epidemiology, University Hospitals of Geneva, Geneva, Switzerland.
J Med Internet Res. 2012 Jun 12;14(3):e85. doi: 10.2196/jmir.2021.
Clinicians perform searches in PubMed daily, but retrieving relevant studies is challenging due to the rapid expansion of medical knowledge. Little is known about the performance of search strategies when they are applied to answer specific clinical questions.
To compare the performance of 15 PubMed search strategies in retrieving relevant clinical trials on therapeutic interventions.
We used Cochrane systematic reviews to identify relevant trials for 30 clinical questions. Search terms were extracted from the abstract using a predefined procedure based on the population, interventions, comparison, outcomes (PICO) framework and combined into queries. We tested 15 search strategies that varied in their query (PIC or PICO), use of PubMed's Clinical Queries therapeutic filters (broad or narrow), search limits, and PubMed links to related articles. We assessed sensitivity (recall) and positive predictive value (precision) of each strategy on the first 2 PubMed pages (40 articles) and on the complete search output.
The performance of the search strategies varied widely according to the clinical question. Unfiltered searches and those using the broad filter of Clinical Queries produced large outputs and retrieved few relevant articles within the first 2 pages, resulting in a median sensitivity of only 10%-25%. In contrast, all searches using the narrow filter performed significantly better, with a median sensitivity of about 50% (all P < .001 compared with unfiltered queries) and positive predictive values of 20%-30% (P < .001 compared with unfiltered queries). This benefit was consistent for most clinical questions. Searches based on related articles retrieved about a third of the relevant studies.
The Clinical Queries narrow filter, along with well-formulated queries based on the PICO framework, provided the greatest aid in retrieving relevant clinical trials within the 2 first PubMed pages. These results can help clinicians apply effective strategies to answer their questions at the point of care.
临床医生每天都会在PubMed中进行检索，但由于医学知识的快速增长，检索相关研究具有挑战性。对于将检索策略应用于回答特定临床问题时的表现，人们了解甚少。
比较15种PubMed检索策略在检索治疗性干预相关临床试验方面的表现。
我们使用Cochrane系统评价来识别针对30个临床问题的相关试验。检索词是根据人群、干预措施、对照、结局（PICO）框架，通过预定义程序从摘要中提取的，并组合成查询式。我们测试了15种检索策略，这些策略在查询式（PIC或PICO）、是否使用PubMed临床查询治疗性过滤器（宽泛或狭窄）、检索限制以及PubMed与相关文章的链接方面存在差异。我们在前两页PubMed（40篇文章）以及完整检索结果中评估了每种策略的敏感性（召回率）和阳性预测值（精确率）。
检索策略的表现因临床问题而异。未过滤的检索以及使用临床查询宽泛过滤器的检索产生了大量结果，在前两页中检索到的相关文章很少，导致中位敏感性仅为10% - 25%。相比之下，所有使用狭窄过滤器的检索表现明显更好，中位敏感性约为50%（与未过滤的查询相比，所有P < 0.001），阳性预测值为20% - 30%（与未过滤的查询相比，P < 0.001）。这种优势在大多数临床问题中都是一致的。基于相关文章的检索检索到了约三分之一的相关研究。
临床查询狭窄过滤器以及基于PICO框架精心制定的查询式，在PubMed的前两页中检索相关临床试验方面提供了最大帮助。这些结果可以帮助临床医生应用有效的策略在医疗点回答他们的问题。
