Prediction of citation counts for clinical articles at two years using data available within three weeks of publication: retrospective cohort study

Objective To determine if citation counts at two years could be predicted for clinical articles that pass basic criteria for critical appraisal using data within three weeks of publication from external sources and an online article rating service.Design Retrospective cohort study.Setting Online rat...

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Veröffentlicht in:BMJ 2008-03, Vol.336 (7645), p.655-657
Hauptverfasser: Lokker, Cynthia, McKibbon, K Ann, McKinlay, R James, Wilczynski, Nancy L, Haynes, R Brian
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container_end_page 657
container_issue 7645
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container_title BMJ
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creator Lokker, Cynthia
McKibbon, K Ann
McKinlay, R James
Wilczynski, Nancy L
Haynes, R Brian
description Objective To determine if citation counts at two years could be predicted for clinical articles that pass basic criteria for critical appraisal using data within three weeks of publication from external sources and an online article rating service.Design Retrospective cohort study.Setting Online rating service, Canada.Participants 1274 articles from 105 journals published from January to June 2005, randomly divided into a 60:40 split to provide derivation and validation datasets.Main outcome measures 20 article and journal features, including ratings of clinical relevance and newsworthiness, routinely collected by the McMaster online rating of evidence system, compared with citation counts at two years.Results The derivation analysis showed that the regression equation accounted for 60% of the variation (R2=0.60, 95% confidence interval 0.538 to 0.629). This model applied to the validation dataset gave a similar prediction (R2=0.56, 0.476 to 0.596, shrinkage 0.04; shrinkage measures how well the derived equation matches data from the validation dataset). Cited articles in the top half and top third were predicted with 83% and 61% sensitivity and 72% and 82% specificity. Higher citations were predicted by indexing in numerous databases; number of authors; abstraction in synoptic journals; clinical relevance scores; number of cited references; and original, multicentred, and therapy articles from journals with a greater proportion of articles abstracted.Conclusion Citation counts can be reliably predicted at two years using data within three weeks of publication.
doi_str_mv 10.1136/bmj.39482.526713.BE
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This model applied to the validation dataset gave a similar prediction (R2=0.56, 0.476 to 0.596, shrinkage 0.04; shrinkage measures how well the derived equation matches data from the validation dataset). Cited articles in the top half and top third were predicted with 83% and 61% sensitivity and 72% and 82% specificity. Higher citations were predicted by indexing in numerous databases; number of authors; abstraction in synoptic journals; clinical relevance scores; number of cited references; and original, multicentred, and therapy articles from journals with a greater proportion of articles abstracted.Conclusion Citation counts can be reliably predicted at two years using data within three weeks of publication.</description><edition>International edition</edition><identifier>ISSN: 0959-8138</identifier><identifier>ISSN: 0959-8146</identifier><identifier>ISSN: 0959-535X</identifier><identifier>EISSN: 1468-5833</identifier><identifier>EISSN: 1756-1833</identifier><identifier>DOI: 10.1136/bmj.39482.526713.BE</identifier><identifier>PMID: 18292132</identifier><identifier>CODEN: BMJOAE</identifier><language>eng</language><publisher>London: British Medical Journal Publishing Group</publisher><subject>Abstracting ; Authorship ; Bibliographic citations ; Bibliometrics ; Biological and medical sciences ; Citation analysis ; Citation indexes ; Clinical outcomes ; Clinical trials ; Cohort Studies ; Confidence interval ; Datasets ; Evidence based medicine ; General aspects ; Health care ; Medical journals ; Medical practice ; Medical sciences ; Miscellaneous ; Modeling ; Online databases ; Periodical indexing ; Periodicals as Topic - statistics &amp; numerical data ; Predictions ; Public health. 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Hygiene-occupational medicine ; Publication Bias ; Regression analysis ; Research methods ; Retrospective Studies ; Time Factors</subject><ispartof>BMJ, 2008-03, Vol.336 (7645), p.655-657</ispartof><rights>BMJ Publishing Group Ltd 2008</rights><rights>Copyright 2008 BMJ Publishing Group Ltd.</rights><rights>2008 INIST-CNRS</rights><rights>Copyright: 2008 (c) BMJ Publishing Group Ltd 2008</rights><rights>Copyright BMJ Publishing Group Mar 22, 2008</rights><rights>BMJ Publishing Group Ltd 2008 2008 BMJ Publishing Group Ltd</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-b734t-91b10a843798c496ce439557f07c1285cdbc315054f44aa798d68eb34030c5c33</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttp://bmj.com/content/336/7645/655.full.pdf$$EPDF$$P50$$Gbmj$$H</linktopdf><linktohtml>$$Uhttp://bmj.com/content/336/7645/655.full$$EHTML$$P50$$Gbmj$$H</linktohtml><link.rule.ids>114,115,230,314,776,780,799,881,3183,23550,27901,27902,30976,30977,57992,58225,77569,77600</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=20182038$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/18292132$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lokker, Cynthia</creatorcontrib><creatorcontrib>McKibbon, K Ann</creatorcontrib><creatorcontrib>McKinlay, R James</creatorcontrib><creatorcontrib>Wilczynski, Nancy L</creatorcontrib><creatorcontrib>Haynes, R Brian</creatorcontrib><title>Prediction of citation counts for clinical articles at two years using data available within three weeks of publication: retrospective cohort study</title><title>BMJ</title><addtitle>BMJ</addtitle><description>Objective To determine if citation counts at two years could be predicted for clinical articles that pass basic criteria for critical appraisal using data within three weeks of publication from external sources and an online article rating service.Design Retrospective cohort study.Setting Online rating service, Canada.Participants 1274 articles from 105 journals published from January to June 2005, randomly divided into a 60:40 split to provide derivation and validation datasets.Main outcome measures 20 article and journal features, including ratings of clinical relevance and newsworthiness, routinely collected by the McMaster online rating of evidence system, compared with citation counts at two years.Results The derivation analysis showed that the regression equation accounted for 60% of the variation (R2=0.60, 95% confidence interval 0.538 to 0.629). This model applied to the validation dataset gave a similar prediction (R2=0.56, 0.476 to 0.596, shrinkage 0.04; shrinkage measures how well the derived equation matches data from the validation dataset). Cited articles in the top half and top third were predicted with 83% and 61% sensitivity and 72% and 82% specificity. Higher citations were predicted by indexing in numerous databases; number of authors; abstraction in synoptic journals; clinical relevance scores; number of cited references; and original, multicentred, and therapy articles from journals with a greater proportion of articles abstracted.Conclusion Citation counts can be reliably predicted at two years using data within three weeks of publication.</description><subject>Abstracting</subject><subject>Authorship</subject><subject>Bibliographic citations</subject><subject>Bibliometrics</subject><subject>Biological and medical sciences</subject><subject>Citation analysis</subject><subject>Citation indexes</subject><subject>Clinical outcomes</subject><subject>Clinical trials</subject><subject>Cohort Studies</subject><subject>Confidence interval</subject><subject>Datasets</subject><subject>Evidence based medicine</subject><subject>General aspects</subject><subject>Health care</subject><subject>Medical journals</subject><subject>Medical practice</subject><subject>Medical sciences</subject><subject>Miscellaneous</subject><subject>Modeling</subject><subject>Online databases</subject><subject>Periodical indexing</subject><subject>Periodicals as Topic - statistics &amp; numerical data</subject><subject>Predictions</subject><subject>Public health. 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This model applied to the validation dataset gave a similar prediction (R2=0.56, 0.476 to 0.596, shrinkage 0.04; shrinkage measures how well the derived equation matches data from the validation dataset). Cited articles in the top half and top third were predicted with 83% and 61% sensitivity and 72% and 82% specificity. Higher citations were predicted by indexing in numerous databases; number of authors; abstraction in synoptic journals; clinical relevance scores; number of cited references; and original, multicentred, and therapy articles from journals with a greater proportion of articles abstracted.Conclusion Citation counts can be reliably predicted at two years using data within three weeks of publication.</abstract><cop>London</cop><pub>British Medical Journal Publishing Group</pub><pmid>18292132</pmid><doi>10.1136/bmj.39482.526713.BE</doi><tpages>3</tpages><edition>International edition</edition><oa>free_for_read</oa></addata></record>
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source Applied Social Sciences Index & Abstracts (ASSIA); Jstor Complete Legacy; MEDLINE; BMJ Journals - NESLi2; Alma/SFX Local Collection
subjects Abstracting
Authorship
Bibliographic citations
Bibliometrics
Biological and medical sciences
Citation analysis
Citation indexes
Clinical outcomes
Clinical trials
Cohort Studies
Confidence interval
Datasets
Evidence based medicine
General aspects
Health care
Medical journals
Medical practice
Medical sciences
Miscellaneous
Modeling
Online databases
Periodical indexing
Periodicals as Topic - statistics & numerical data
Predictions
Public health. Hygiene
Public health. Hygiene-occupational medicine
Publication Bias
Regression analysis
Research methods
Retrospective Studies
Time Factors
title Prediction of citation counts for clinical articles at two years using data available within three weeks of publication: retrospective cohort study
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