Fake Science: More Common Than You Think

Yet again the edifices of peer review were shaken by recent retractions in The New England Journal of Medicine and Cochrane Reviews. The article (and another “expression of concern publication”) retracted in the NEJM was authored by a Brigham and Women’s Hospital researcher (an institution of which I am a graduate), Dr. Piero Anversa, who has been implicated in the fraudulent publication of as many as 31 cardiac stem cell articles. Meanwhile, under seeming political pressures from a group of patient activists that decried an analysis entitled: “Exercise as treatment for patients with chronic fatigue syndrome,” deeming it a personal affront to their suffering, the editors of the prestigious Cochrane Reviews decided to withdraw it. The scientist who did the actual review for the journal lodged a bitter complaint about this “editorial” decision; it is hard to miss the irony here of Cochrane Reviews being a supposed impartial arbitrator of medical scientific quality that drives clinical decision-making. Fraudulent scientific results, politics trumping science, what is a reader to believe?

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Towards a Cureus Data Repository

*Co-authored by John R. Adler & Achim Schweikard

Most scientific articles come with some form of data. For Cureus, our data includes medical images, graphics, drawings and tables. Access to such data enables a reader to verify the content and credibility of an article while also better understanding it. Many types of data, provided they are findable via search, can have value to readers independent of the article with which it was originally connected; medical imagery and genetic sequencing information being cases in point. For example, with modern methods of machine learning requiring large data sets for training, journals are a logical repository for such information. Therefore a peer-reviewed article that provides access to data will oftentimes prove much more valuable than that same article without data. Especially for internet-based media with access to large amounts of digital storage space, data sharing between authors and readers would and should become a standard. As an example, instead of showing data for a single representative case in an article, which is typical for traditional journals, we could make data for all cases in this article available to readers. Readers could then download such enhanced data sets directly in electronic format.

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