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Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement

Overview of attention for article published in BMC Medicine, January 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

news
2 news outlets
blogs
3 blogs
twitter
31 X users
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2 patents
facebook
2 Facebook pages
googleplus
2 Google+ users

Citations

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1130 Dimensions

Readers on

mendeley
790 Mendeley
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1 CiteULike
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Title
Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement
Published in
BMC Medicine, January 2015
DOI 10.1186/s12916-014-0241-z
Pubmed ID
Authors

Gary S Collins, Johannes B Reitsma, Douglas G Altman, Karel GM Moons

Abstract

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).Editors' note: In order to encourage dissemination of the TRIPOD Statement, this article is freely accessible on the Annals of Internal Medicine Web site (www.annals.org) and will be also published in BJOG, British Journal of Cancer, British Journal of Surgery, BMC Medicine, British Medical Journal, Circulation, Diabetic Medicine, European Journal of Clinical Investigation, European Urology, and Journal of Clinical Epidemiology. The authors jointly hold the copyright of this article. An accompanying Explanation and Elaboration article is freely available only on www.annals.org; Annals of Internal Medicine holds copyright for that article.

X Demographics

X Demographics

The data shown below were collected from the profiles of 31 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 790 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Spain 1 <1%
France 1 <1%
Belgium 1 <1%
Unknown 786 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 111 14%
Researcher 107 14%
Student > Master 71 9%
Other 67 8%
Student > Bachelor 58 7%
Other 133 17%
Unknown 243 31%
Readers by discipline Count As %
Medicine and Dentistry 238 30%
Computer Science 40 5%
Nursing and Health Professions 35 4%
Biochemistry, Genetics and Molecular Biology 33 4%
Engineering 30 4%
Other 129 16%
Unknown 285 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 56. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 December 2023.
All research outputs
#777,463
of 25,753,578 outputs
Outputs from BMC Medicine
#544
of 4,086 outputs
Outputs of similar age
#9,699
of 360,983 outputs
Outputs of similar age from BMC Medicine
#11
of 62 outputs
Altmetric has tracked 25,753,578 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,086 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 45.9. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 360,983 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.