0408 PubMed search strings for the study of putative environmental determinants of disease
本研究开发了两种PubMed检索策略（高特异性和高敏感性），用于查找环境污染与疾病（如自身免疫病、猝死、先天性心脏缺陷）关联的文献，并评估了找到一篇相关文章需要阅读的摘要数量。
<h3>Objectives</h3> Several optimised search strategies have been developed in Medicine, and more recently in Occupational Medicine. Aim of this study is to identify efficient PubMed search strategies for the study of putative environmental determinants of a disease. <h3>Method</h3> We compiled a list of search terms (either Medical Subjects Heading [MeSH] or non-MeSH) seeming pertinent to exposure to pollutants as determinants of diseases in general population. We estimated proportions of potentially pertinent articles to formulate two search strategies (one “more specific”, one “more sensitive”). We applied these strategies to retrieve information on the putative environmental determinants of three diseases: autoimmune disease, sudden death and congenital heart defects. We evaluated the number of needed to read (NNR) abstracts to identify one potentially pertinent article in the context of these pathologies. <h3>Results</h3> The “more specific” search string was based on the combination of terms that yielded the highest proportion (≥ 40%) of potentially pertinent abstracts, including the MeSH terms <i>‘air pollutants’,</i> ‘<i>air pollution’, ‘disorders of environmental origin’, ‘environmental exposure’</i> and ‘<i>particulate matter’</i>. The “more sensitive” string was based on use of broader search fields and additional coverage provided by other search terms under study. Using the “more specific” string, the NNR to find one potentially pertinent article were: 2.7 for autoimmune disease; 3.2 for sudden death; 1.1 for congenital heart defects. Using the sensitive strategy, the NNR were 4.0, 6.1 and 3.4, respectively. <h3>Conclusions</h3> The proposed strings could help health care professionals investigate environmental determinants of medical conditions that could be related to pollution.