Biomedical literature has enormously grown in the last decades and become broadly available through online databases. Ad-hoc search methods, created on the basis of research field and goals, are required to enhance the quality of searching. Aim of this study was to formulate efficient, evidence-based PubMed search strategies to retrieve articles assessing etiologic associations between a condition of interest and hypothalamic-pituitary disorders (HPD). Based on expert knowledge, 17 MeSH (Medical Subjects Headings) and 79 free terms related to HPD were identified to search PubMed. Using random samples of abstracts retrieved by each term, we estimated the proportion of articles containing pertinent information and formulated two strings (one more specific, one more sensitive) for the detection of articles focusing on the etiology of HPD, that were then applied to retrieve articles identifying possible etiologic associations between HPD and three diseases (malaria, LHON and celiac disease) considered not associated to HPD, and define the number of abstracts needed to read (NNR) to find one potentially pertinent article. We propose two strings: one sensitive string derived from the combination of articles providing the largest literature coverage in the field and one specific including combined terms retrieving ≥40% of potentially pertinent articles. NNR were 2.1 and 1.6 for malaria, 3.36 and 2.29 for celiac disease, 2.8 and 2.2 for LHON, respectively. For the first time, two reliable, readily applicable strings are proposed for the retrieval of medical literature assessing putative etiologic associations between HPD and other medical conditions of interest.

Guaraldi F., Grottoli S., Arvat E., Mattioli S., Ghigo E., Gori D. (2013). PubMed Search strategies for the identification of etiologic associations between hypothalamic-pituitary disorders and other medical conditions. PITUITARY, 16(4), 471-482 [10.1007/s11102-012-0443-3].

PubMed Search strategies for the identification of etiologic associations between hypothalamic-pituitary disorders and other medical conditions

MATTIOLI, STEFANO;GORI, DAVIDE
2013

Abstract

Biomedical literature has enormously grown in the last decades and become broadly available through online databases. Ad-hoc search methods, created on the basis of research field and goals, are required to enhance the quality of searching. Aim of this study was to formulate efficient, evidence-based PubMed search strategies to retrieve articles assessing etiologic associations between a condition of interest and hypothalamic-pituitary disorders (HPD). Based on expert knowledge, 17 MeSH (Medical Subjects Headings) and 79 free terms related to HPD were identified to search PubMed. Using random samples of abstracts retrieved by each term, we estimated the proportion of articles containing pertinent information and formulated two strings (one more specific, one more sensitive) for the detection of articles focusing on the etiology of HPD, that were then applied to retrieve articles identifying possible etiologic associations between HPD and three diseases (malaria, LHON and celiac disease) considered not associated to HPD, and define the number of abstracts needed to read (NNR) to find one potentially pertinent article. We propose two strings: one sensitive string derived from the combination of articles providing the largest literature coverage in the field and one specific including combined terms retrieving ≥40% of potentially pertinent articles. NNR were 2.1 and 1.6 for malaria, 3.36 and 2.29 for celiac disease, 2.8 and 2.2 for LHON, respectively. For the first time, two reliable, readily applicable strings are proposed for the retrieval of medical literature assessing putative etiologic associations between HPD and other medical conditions of interest.
2013
Guaraldi F., Grottoli S., Arvat E., Mattioli S., Ghigo E., Gori D. (2013). PubMed Search strategies for the identification of etiologic associations between hypothalamic-pituitary disorders and other medical conditions. PITUITARY, 16(4), 471-482 [10.1007/s11102-012-0443-3].
Guaraldi F.; Grottoli S.; Arvat E.; Mattioli S.; Ghigo E.; Gori D.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/131337
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