title: [Limiting a Medline/PubMed query to the "best" articles using the JCR relative impact factor].
abstract: BACKGROUND
  Medline/PubMed is the most frequently used medical bibliographic research database. The aim of this study was to propose a new generic method to limit any Medline/PubMed query based on the relative impact factor and the A & B categories of the SIGAPS score.
  
  
  METHODS
  The entire PubMed corpus was used for the feasibility study, then ten frequent diseases in terms of PubMed indexing and the citations of four Nobel prize winners. The relative impact factor (RIF) was calculated by medical specialty defined in Journal Citation Reports. The two queries, which included all the journals in category A (or A OR B), were added to any Medline/PubMed query as a central point of the feasibility study.
  
  
  RESULTS
  Limitation using the SIGAPS category A was larger than the when using the Core Clinical Journals (CCJ): 15.65% of PubMed corpus vs 8.64% for CCJ. The response time of this limit applied to the entire PubMed corpus was less than two seconds. For five diseases out of ten, limiting the citations with the RIF was more effective than with the CCJ. For the four Nobel prize winners, limiting the citations with the RIF was more effective than the CCJ.
  
  
  CONCLUSIONS
  The feasibility study to apply a new filter based on the relative impact factor on any Medline/PubMed query was positive.
authors.affiliation: DIH, HEGP, & Inserm UMR_S 872 eq22, faculté de médecine, université Paris-Descartes, Sorbonne-Paris-Cité, AP-HP, Paris, France.
authors.forename: P
authors.initials: P
authors.lastname: Avillach
authors.affiliation: CISMeF ; SIBM, & TIBS, LITIS EA 4108, France & LIMICS, Inserm U1142, université de Rouen, CHU de Rouen, cour Leschevin, porte 21, 3(e) étage, 1, rue de Germont, 76031 Rouen cedex, France.
authors.forename: G
authors.initials: G
authors.lastname: Kerdelhué
authors.affiliation: Université de Lille II, CHRU de Lille & CERIM, Lille, France.
authors.forename: P
authors.initials: P
authors.lastname: Devos
authors.affiliation: EAM 4128 : santé, individu et société, université Claude-Bernard Lyon 1, Lyon, France.
authors.forename: H
authors.initials: H
authors.lastname: Maisonneuve
authors.affiliation: CISMeF ; SIBM, & TIBS, LITIS EA 4108, France & LIMICS, Inserm U1142, université de Rouen, CHU de Rouen, cour Leschevin, porte 21, 3(e) étage, 1, rue de Germont, 76031 Rouen cedex, France. Electronic address: Stefan.Darmoni@chu-rouen.fr.
authors.forename: S J
authors.initials: SJ
authors.lastname: Darmoni
mesh_terms: D015982:Bias; D005240:Feasibility Studies; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods* / Q000592:standards* / Q000706:statistics & numerical data; D055811:Journal Impact Factor; D016239:MEDLINE / Q000706:statistics & numerical data*; D039781:PubMed / Q000706:statistics & numerical data*; D015983:Selection Bias; D012693:Serial Publications / Q000592:standards* / Q000600:supply & distribution
keywords: Base documentaire; Bibliographic research database; Facteur d’impact; Impact factor; Medline/PubMed; SIGAPS score; Score SIGAPS