York Health Economics Consortium, Enterprise House, Innovation Way, University of York, York, UK.
Metaxis Ltd, Curbridge, UK.
Health Info Libr J. 2019 Mar;36(1):73-90. doi: 10.1111/hir.12251. Epub 2019 Feb 8.
Evidence synthesis reviews in health care rely on the efficient identification of research evidence, particularly evidence from randomised controlled trials (RCTs). There are no recently validated filters to identify RCTs in the Cumulative Index to Nursing and Allied Health Literature (CINAHL Plus).
To develop, test and validate a search filter to identify reports of RCTs from CINAHL Plus.
Nine sets of relevant and irrelevant records were identified to develop and test search filters iteratively. Two sets were used to validate the sensitivity and precision of the filters. The performance of two previously published filters and the filter built into EBSCOhost was evaluated.
We present a validated filter which offers sensitivity of 0.88 (95% CI: 0.77-0.95) and precision of 0.36 (95% CI: 0.31-0.41). This is comparable to the sensitivity of published filters, but has much better precision.
A sensitive and precise filter, developed using records selected based on title and abstract information, is available for identifying reports of RCTs in the CINAHL Plus database via EBSCOhost. Using this filter is likely to reduce the number of results needing to be screened to a quarter of those retrieved by other published filters.
医疗保健中的证据综合评价依赖于对研究证据的高效识别，特别是随机对照试验（RCT）的证据。在《护理与联合健康文献累积索引》（CINAHL Plus）中，尚无最近经过验证的筛选器来识别 RCT。
开发、测试和验证一种用于从 CINAHL Plus 中识别 RCT 报告的搜索筛选器。
确定了九组相关和不相关的记录，以迭代方式开发和测试搜索筛选器。其中两组用于验证筛选器的灵敏度和精度。评估了两个先前发表的筛选器和 EBSCOhost 内置筛选器的性能。
我们提出了一个经过验证的筛选器，其灵敏度为 0.88（95%置信区间：0.77-0.95），精度为 0.36（95%置信区间：0.31-0.41）。这与已发表的筛选器的灵敏度相当，但精度更高。
一种基于标题和摘要信息选择记录开发的灵敏且精确的筛选器，可通过 EBSCOhost 在 CINAHL Plus 数据库中识别 RCT 报告。使用该筛选器可能会将需要筛选的结果数量减少到其他已发表筛选器检索到的结果的四分之一。
