Curti Stefania, Gori Davide, Di Gregori Valentina, Farioli Andrea, Baldasseroni Alberto, Fantini Maria Pia, Christiani David C, Violante Francesco S, Mattioli Stefano
Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.
Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.
BMJ Open. 2016 Dec 21;6(12):e013092. doi: 10.1136/bmjopen-2016-013092.
Several PubMed search filters have been developed in contexts other than environmental. We aimed at identifying efficient PubMed search filters for the study of environmental determinants of diseases related to outdoor air pollution.
We compiled a list of Medical Subject Headings (MeSH) and non-MeSH terms seeming pertinent to outdoor air pollutants exposure as determinants of diseases in the general population. We estimated proportions of potentially pertinent articles to formulate two filters (one 'more specific', one 'more sensitive'). Their overall performance was evaluated as compared with our gold standard derived from systematic reviews on diseases potentially related to outdoor air pollution. We tested these filters in the study of three diseases potentially associated with outdoor air pollution and calculated the number of needed to read (NNR) abstracts to identify one potentially pertinent article in the context of these diseases. Last searches were run in January 2016.
The 'more specific' filter was based on the combination of terms that yielded a threshold of potentially pertinent articles ≥40%. The 'more sensitive' filter was based on the combination of all search terms under study. When compared with the gold standard, the 'more specific' filter reported the highest specificity (67.4%; with a sensitivity of 82.5%), while the 'more sensitive' one reported the highest sensitivity (98.5%; with a specificity of 47.9%). The NNR to find one potentially pertinent article was 1.9 for the 'more specific' filter and 3.3 for the 'more sensitive' one.
The proposed search filters could help healthcare professionals investigate environmental determinants of medical conditions that could be potentially related to outdoor air pollution.
除环境领域外，已在其他背景下开发了几种PubMed搜索过滤器。我们旨在确定用于研究与室外空气污染相关疾病的环境决定因素的有效PubMed搜索过滤器。
我们编制了一份医学主题词表（MeSH）和非MeSH术语列表，这些术语似乎与室外空气污染物暴露作为一般人群疾病的决定因素相关。我们估计了潜在相关文章的比例，以制定两个过滤器（一个“更具体”，一个“更敏感”）。与我们从关于可能与室外空气污染相关疾病的系统评价中得出的金标准相比，评估了它们的整体性能。我们在三种可能与室外空气污染相关的疾病研究中测试了这些过滤器，并计算了在这些疾病背景下识别一篇潜在相关文章所需阅读的摘要数量（NNR）。最后一次搜索于2016年1月进行。
“更具体”的过滤器基于产生潜在相关文章阈值≥40%的术语组合。“更敏感”的过滤器基于所研究的所有搜索词的组合。与金标准相比，“更具体”的过滤器具有最高的特异性（67.4%；敏感性为82.5%），而“更敏感”的过滤器具有最高的敏感性（98.5%；特异性为47.9%）。“更具体”的过滤器找到一篇潜在相关文章的NNR为1.9，“更敏感”的过滤器为3.3。
所提出的搜索过滤器可帮助医疗保健专业人员调查可能与室外空气污染相关的医疗状况的环境决定因素。
