Identification of risk conditions for the development of adrenal disorders: how optimized PubMed search strategies makes
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ENDOCRINE METHODS AND TECHNIQUES
Identification of risk conditions for the development of adrenal disorders: how optimized PubMed search strategies makes the difference Federica Guaraldi • Mirko Parasiliti-Caprino • Riccardo Goggi • Guglielmo Beccuti • Silvia Grottoli • Emanuela Arvat • Lucia Ghizzoni Ezio Ghigo • Roberta Giordano • Davide Gori
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Received: 20 March 2014 / Accepted: 8 May 2014 Springer Science+Business Media New York 2014
Abstract The exponential growth of scientific literature available through electronic databases (namely PubMed) has increased the chance of finding interesting articles. At the same time, search has become more complicated, time consuming, and at risk of missing important information. Therefore, optimized strategies have to be adopted to maximize searching impact. The aim of this study was to formulate efficient strings to search PubMed for etiologic associations between adrenal disorders (ADs) and other conditions. A comprehensive list of terms identifying endogenous conditions primarily affecting adrenals was compiled. An ad hoc analysis was performed to find the best way to express each term in order to find the highest number of potentially pertinent articles in PubMed. A
Electronic supplementary material The online version of this article (doi:10.1007/s12020-014-0295-x) contains supplementary material, which is available to authorized users. F. Guaraldi (&) M. Parasiliti-Caprino G. Beccuti S. Grottoli L. Ghizzoni E. Ghigo R. Giordano Division of Endocrinology, Diabetology and Metabolism, Department of Medical Sciences, University of Turin, Corso Dogliotti, 14, 10126 Turin, Italy e-mail: [email protected] R. Goggi D. Gori Department of Biomedical and Neuromotor Sciences, School of Hygiene and Preventive Medicine, University of Bologna, Bologna, Italy E. Arvat Division of Endocrine Oncology, Department of Oncology, University of Turin, Turin, Italy R. Giordano Department of Clinical and Biological Sciences, University of Turin, Turin, Italy
predefined number of retrieved abstracts were read to assess their association with ADs’ etiology. A more sensitive (providing the largest literature coverage) and a more specific (including only those terms retrieving [40 % of potentially pertinent articles) string were formulated. Various researches were performed to assess strings’ ability to identify articles of interest in comparison with non-optimized literature searches. We formulated optimized, ready applicable tools for the identification of the literature assessing etiologic associations in the field of ADs using PubMed, and demonstrated the advantages deriving from their application. Detailed description of the methodological process is also provided, so that this work can easily be translated to other fields of practice. Keywords Search string Adrenal diseases Adrenal disorders Congenital adrenal disorders Adrenal genetic diseases
Introduction PubMed (http://www.ncbi.nlm.nih.gov/pubmed/) represents the reference scientific electronic databas
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