[X] Close
You are about to erase all the values you have customized, search history, page format, etc.
Click here to RESET all values       Click here to GO BACK without resetting any value
Item 1 of about 1
1. Shaikh N, Badgett RG, Pi M, Wilczynski NL, McKibbon KA, Ketchum AM, Haynes RB: Development and validation of filters for the retrieval of studies of clinical examination from Medline. J Med Internet Res; 2011 Oct 19;13(4):e82
PDF icon [Fulltext service] Download fulltext PDF of this article and others, as many as you want.

  • [Source] The source of this record is MEDLINE®, a database of the U.S. National Library of Medicine.
  • [Title] Development and validation of filters for the retrieval of studies of clinical examination from Medline.
  • BACKGROUND: Efficiently finding clinical examination studies--studies that quantify the value of symptoms and signs in the diagnosis of disease-is becoming increasingly difficult.
  • Filters developed to retrieve studies of diagnosis from Medline lack specificity because they also retrieve large numbers of studies on the diagnostic value of imaging and laboratory tests.
  • OBJECTIVE: The objective was to develop filters for retrieving clinical examination studies from Medline.
  • METHODS: We developed filters in a training dataset and validated them in a testing database.
  • We created the training database by hand searching 161 journals (n = 52,636 studies).
  • We evaluated the recall and precision of 65 candidate single-term filters in identifying studies that reported the sensitivity and specificity of symptoms or signs in the training database.
  • To identify best combinations of these search terms, we used recursive partitioning.
  • The best-performing filters in the training database as well as 13 previously developed filters were evaluated in a testing database (n = 431,120 studies).
  • We also examined the impact of examining reference lists of included articles on recall.
  • RESULTS: In the training database, the single-term filters with the highest recall (95%) and the highest precision (8.4%) were diagnosis[subheading] and "medical history taking"[MeSH], respectively.
  • The multiple-term filter developed using recursive partitioning (the RP filter) had a recall of 100% and a precision of 89% in the training database.
  • In the testing database, the Haynes-2004-Sensitive filter (recall 98%, precision 0.13%) and the RP filter (recall 89%, precision 0.52%) showed the best performance.
  • The recall of these two filters increased to 99% and 94% respectively with review of the reference lists of the included articles.
  • CONCLUSIONS: Recursive partitioning appears to be a useful method of developing search filters.
  • The empirical search filters proposed here can assist in the retrieval of clinical examination studies from Medline; however, because of the low precision of the search strategies, retrieving relevant studies remains challenging.
  • Improving precision may require systematic changes in the tagging of articles by the National Library of Medicine.
  • [MeSH-major] Diagnosis. MEDLINE
  • [MeSH-minor] Databases, Factual. Diagnostic Techniques and Procedures. Humans

  • [Email] Email this result item
    Email the results to the following email address:   [X] Close
  • [Cites] J Clin Epidemiol. 2000 Jan;53(1):65-9 [10693905.001]
  • [Cites] J Am Med Inform Assoc. 2002 Nov-Dec;9(6):653-8 [12386115.001]
  • [Cites] Health Info Libr J. 2003 Sep;20(3):150-9 [12919278.001]
  • [Cites] BMC Med Res Methodol. 2002 Jul 3;2:9 [12097142.001]
  • [Cites] AMIA Annu Symp Proc. 2003;:728-32 [14728269.001]
  • [Cites] BMJ. 2004 May 1;328(7447):1040 [15073027.001]
  • [Cites] Br Med J. 1975 May 31;2(5969):486-9 [1148666.001]
  • [Cites] Am J Dis Child. 1977 May;131(5):514-7 [855837.001]
  • [Cites] Br Med J. 1979 Jul 7;2(6181):21-4 [466256.001]
  • [Cites] J Chronic Dis. 1984;37(9-10):721-31 [6501544.001]
  • [Cites] West J Med. 1992 Feb;156(2):163-5 [1536065.001]
  • [Cites] J Am Med Inform Assoc. 1994 Nov-Dec;1(6):447-58 [7850570.001]
  • [Cites] JAMA. 1997 Feb 19;277(7):572-4 [9032165.001]
  • [Cites] Fam Pract. 1997 Jun;14(3):204-8 [9201493.001]
  • [Cites] ACP J Club. 2005 Jan-Feb;142(1):A8-9 [15656539.001]
  • [Cites] BMJ. 2005 May 21;330(7501):1179 [15894554.001]
  • [Cites] Health Info Libr J. 2005 Jun;22(2):81-2 [15910578.001]
  • [Cites] J Clin Epidemiol. 2006 Mar;59(3):234-40 [16488353.001]
  • [Cites] J Clin Epidemiol. 2007 Jan;60(1):29-33 [17161751.001]
  • [Cites] BMC Med Inform Decis Mak. 2007;7:16 [17573961.001]
  • [Cites] J Gen Intern Med. 2008 Jun;23(6):768-74 [18347878.001]
  • [Cites] Genome Inform. 2007;18:267-76 [18546494.001]
  • [Cites] Ann Intern Med. 2008 Dec 16;149(12):889-97 [19075208.001]
  • [ErratumIn] J Med Internet Res. 2012;14(4):e108 [22864147.001]
  • (PMID = 22011384.001).
  • [ISSN] 1438-8871
  • [Journal-full-title] Journal of medical Internet research
  • [ISO-abbreviation] J. Med. Internet Res.
  • [Language] eng
  • [Publication-type] Evaluation Studies; Journal Article; Validation Studies
  • [Publication-country] Canada
  • [Other-IDs] NLM/ PMC3222198
  •  go-up   go-down


Advertisement





Advertisement