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

机译:使用发表后三周内可获得的数据预测两年内临床文章的引文计数:回顾性队列研究

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摘要

>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.
机译:>目的,通过使用外部来源和在线文章评级服务发布的三周内的数据,确定通过关键评估基本标准的临床文章是否可以预测两年的引用次数。>设计回顾性队列研究。>设置加拿大在线评分服务。>参与者 2005年1月至2005年6月出版的105种期刊中的1274篇文章随机分为60:40的比例>主要结果指标,由McMaster在线证据系统定期收集的20篇文章和期刊功能(包括临床相关性和新闻价值)与两年引用次数进行比较。 >结果推导分析表明,回归方程占变异的60%(R 2 = 0.60,95%置信区间0.538至0.629)。应用于验证数据集的模型给出了相似的预测(R 2 = 0.56,0.476至0.596,收缩率0.04;收缩率衡量了导出的方程与验证数据集数据匹配的程度)。预测上半部和前三分之一的被引文章的敏感性为83%和61%,特异性为72%和82%。通过在许多数据库中建立索引,可以预测较高的引用率;作者数量;摘要期刊的摘要;临床相关性评分;被引用参考文献的数量; >结论可以使用发布后三周内的数据可靠地预测两年内的引文计数。

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