From abstract to impact in cardiovascular research: factors predicting publication and citation

Eur Heart J. 2012 Dec;33(24):3034-45. doi: 10.1093/eurheartj/ehs113. Epub 2012 Jun 5.

Abstract

Aims: Through a 4-year follow-up of the abstracts submitted to the European Society of Cardiology Congress in 2006, we aimed at identifying factors predicting high-quality research, appraising the quality of the peer review and editorial processes, and thereby revealing potential ways to improve future research, peer review, and editorial work. METHODS AND RESULTS All abstracts submitted in 2006 were assessed for acceptance, presentation format, and average reviewer rating. Accepted and rejected studies were followed for 4 years. Multivariate regression analyses of a representative selection of 10% of all abstracts (n= 1002) were performed to identify factors predicting acceptance, subsequent publication, and citation. A total of 10 020 abstracts were submitted, 3104 (31%) were accepted for poster, and 701 (7%) for oral presentation. At Congress level, basic research, a patient number ≥ 100, and prospective study design were identified as independent predictors of acceptance. These factors differed from those predicting full-text publication, which included academic affiliation. The single parameter predicting frequent citation was study design with randomized controlled trials reaching the highest citation rates. The publication rate of accepted studies was 38%, whereas only 24% of rejected studies were published. Among published studies, those accepted at the Congress received higher citation rates than rejected ones.

Conclusions: Research of high quality was determined by study design and largely identified at Congress level through blinded peer review. The scientometric follow-up revealed a marked disparity between predictors of full-text publication and those predicting citation or acceptance at the Congress.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomedical Research / standards*
  • Biomedical Research / statistics & numerical data
  • Cardiology / standards*
  • Editorial Policies
  • Female
  • Humans
  • Journal Impact Factor
  • Male
  • Peer Review
  • Publishing / standards*
  • Publishing / statistics & numerical data
  • Randomized Controlled Trials as Topic / statistics & numerical data
  • Regression Analysis
  • Sex Factors